diff --git a/_solved/00-jupyter_introduction.ipynb b/_solved/00-jupyter_introduction.ipynb index ddd9e39..aa12d3f 100644 --- a/_solved/00-jupyter_introduction.ipynb +++ b/_solved/00-jupyter_introduction.ipynb @@ -2,19 +2,11 @@ "cells": [ { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "

Jupyter notebook INTRODUCTION

\n", "\n", - "\n", - "> *DS Data manipulation, analysis and visualisation in Python* \n", - "> *December, 2019*\n", - "\n", - "> *© 2016, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", + "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" ] @@ -22,15 +14,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -53,11 +37,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "
To run a cell: push the start triangle in the menu or type **SHIFT + ENTER/RETURN**\n", "![](../img/shiftenter.jpg)" @@ -72,22 +52,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "We will work in **Jupyter notebooks** during this course. A notebook is a collection of `cells`, that can contain different content:" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Code" ] @@ -95,15 +67,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -121,15 +85,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -153,33 +109,21 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Markdown" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "Text cells, using Markdown syntax. With the syntax, you can make text **bold** or *italic*, amongst many other things..." ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "* list\n", "* with\n", @@ -193,24 +137,16 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "Mathematical formulas can also be incorporated (LaTeX it is...)\n", "$$\\frac{dBZV}{dt}=BZV_{in} - k_1 .BZV$$\n", - "$$\\frac{dOZ}{dt}=k_2 .(OZ_{sat}-OZ) - k_1 .BZV$$\n" + "$$\\frac{dOZ}{dt}=k_2 .(OZ_{sat}-OZ) - k_1 .BZV$$" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "Or tables:\n", "\n", @@ -233,22 +169,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "Code can also be incorporated, but than just to illustrate:" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "```python\n", "BOT = 12\n", @@ -258,11 +186,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "See also: https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet" ] @@ -276,11 +200,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "You can also use HTML commands, just check this cell:\n", "

html-adapted titel with <h3>

\n", @@ -289,11 +209,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "## Headings of different sizes: section\n", "### subsection\n", @@ -302,44 +218,28 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Raw Text" ] }, { "cell_type": "raw", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "Cfr. any text editor" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "# Notebook handling ESSENTIALS" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Completion: TAB\n", "![](../img/tabbutton.jpg)" @@ -347,11 +247,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "* The **TAB** button is essential: It provides you all **possible actions** you can do after loading in a library *AND* it is used for **automatic autocompletion**:" ] @@ -359,15 +255,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -388,15 +276,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "my_very_long_variable_name = 3" @@ -404,22 +284,14 @@ }, { "cell_type": "raw", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "my_ + TAB" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Help: SHIFT + TAB\n", "![](../img/shift-tab.png)" @@ -427,27 +299,15 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ - "* The **SHIFT-TAB** combination is ultra essential to get information/help about the current operation " + "* The **SHIFT-TAB** combination is ultra essential to get information/help about the current operation" ] }, { "cell_type": "code", "execution_count": 6, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -467,15 +327,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -496,15 +348,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -533,11 +377,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "
\n", " EXERCISE: What happens if you put two question marks behind the command?\n", @@ -547,15 +387,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -589,16 +421,12 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## *edit* mode to *command* mode\n", "\n", - "* *edit* mode means you're editing a cell, i.e. with your cursor inside a cell to type content --> green colored side\n", - "* *command* mode means you're NOT editing(!), i.e. NOT with your cursor inside a cell to type content --> blue colored side\n", + "* *edit* mode means you're editing a cell, i.e. with your cursor inside a cell to type content\n", + "* *command* mode means you're NOT editing(!), i.e. NOT with your cursor inside a cell to type content\n", "\n", "To start editing, click inside a cell or \n", "\"Key\n", @@ -609,11 +437,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## new cell A-bove\n", "\"Key\n", @@ -623,11 +447,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## new cell B-elow\n", "\"Key\n", @@ -637,44 +457,28 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## CTRL + SHIFT + C" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "Just do it!" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Trouble..." ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "
\n", " NOTE: When you're stuck, or things do crash: \n", @@ -687,11 +491,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "* **Stackoverflow** is really, really, really nice!\n", "\n", @@ -700,22 +500,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "* Google search is with you!" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "
**REMEMBER**: To run a cell: push the start triangle in the menu or type **SHIFT + ENTER**\n", "![](../img/shiftenter.jpg)" @@ -723,22 +515,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "# some MAGIC..." ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## `%psearch`" ] @@ -746,15 +530,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -779,11 +555,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## `%%timeit`" ] @@ -791,15 +563,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -820,15 +584,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "import numpy as np" @@ -837,15 +593,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -893,11 +641,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "## `%lsmagic`" ] @@ -905,15 +649,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -1068,11 +804,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "# Let's get started!" ] @@ -1080,15 +812,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "from IPython.display import FileLink, FileLinks" @@ -1097,15 +821,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -1141,11 +857,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "The follow-up notebooks provide additional background (largely adopted from the [scientific python notes](http://www.scipy-lectures.org/), which you can explore on your own to get more background on the Python syntax if specific elements would not be clear. \n", "\n", @@ -1154,8 +866,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1169,7 +884,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/_solved/case1_bike_count.ipynb b/_solved/case1_bike_count.ipynb index f97ef1c..1d09350 100644 --- a/_solved/case1_bike_count.ipynb +++ b/_solved/case1_bike_count.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Bike count data

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -93,7 +90,9 @@ "cell_type": "code", "execution_count": 2, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -104,11 +103,10 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -200,11 +198,10 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -296,11 +293,10 @@ "cell_type": "code", "execution_count": 5, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -322,11 +318,10 @@ "cell_type": "code", "execution_count": 6, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -392,11 +387,10 @@ "cell_type": "code", "execution_count": 7, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -424,7 +418,9 @@ "cell_type": "code", "execution_count": 8, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -435,7 +431,9 @@ "cell_type": "code", "execution_count": 9, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -446,7 +444,9 @@ "cell_type": "code", "execution_count": 10, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -458,10 +458,7 @@ "cell_type": "code", "execution_count": 11, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -548,10 +545,7 @@ "cell_type": "code", "execution_count": 12, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -611,10 +605,7 @@ "cell_type": "code", "execution_count": 14, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -640,10 +631,7 @@ "cell_type": "code", "execution_count": 15, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -699,7 +687,9 @@ "cell_type": "code", "execution_count": 16, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -732,10 +722,7 @@ "cell_type": "code", "execution_count": 17, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -891,10 +878,7 @@ "cell_type": "code", "execution_count": 20, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -934,10 +918,7 @@ "cell_type": "code", "execution_count": 21, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -997,10 +978,7 @@ "cell_type": "code", "execution_count": 22, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -1122,11 +1100,10 @@ "cell_type": "code", "execution_count": 23, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1177,7 +1154,9 @@ "cell_type": "code", "execution_count": 24, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1206,11 +1185,10 @@ "cell_type": "code", "execution_count": 25, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1353,11 +1331,10 @@ "cell_type": "code", "execution_count": 26, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1399,11 +1376,10 @@ "cell_type": "code", "execution_count": 27, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1444,11 +1420,10 @@ "cell_type": "code", "execution_count": 28, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1501,7 +1476,9 @@ "cell_type": "code", "execution_count": 29, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1512,7 +1489,9 @@ "cell_type": "code", "execution_count": 30, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1523,11 +1502,10 @@ "cell_type": "code", "execution_count": 31, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1549,8 +1527,9 @@ "cell_type": "code", "execution_count": 32, "metadata": { - "clear_cell": true, - "tags": [] + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1614,11 +1593,10 @@ "cell_type": "code", "execution_count": 33, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1668,7 +1646,9 @@ "cell_type": "code", "execution_count": 34, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1679,11 +1659,10 @@ "cell_type": "code", "execution_count": 35, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1763,11 +1742,10 @@ "cell_type": "code", "execution_count": 36, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1825,7 +1803,9 @@ "cell_type": "code", "execution_count": 37, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1845,11 +1825,10 @@ "cell_type": "code", "execution_count": 38, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1881,11 +1860,10 @@ "cell_type": "code", "execution_count": 39, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1924,11 +1902,10 @@ "cell_type": "code", "execution_count": 40, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1999,10 +1976,7 @@ "cell_type": "code", "execution_count": 44, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -2041,10 +2015,7 @@ "cell_type": "code", "execution_count": 79, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -2108,10 +2079,7 @@ "cell_type": "code", "execution_count": 65, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -2150,8 +2118,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2165,7 +2136,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.8.12" }, "nav_menu": {}, "toc": { diff --git a/_solved/case2_observations.ipynb b/_solved/case2_observations.ipynb new file mode 100644 index 0000000..9ed5094 --- /dev/null +++ b/_solved/case2_observations.ipynb @@ -0,0 +1,4375 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

CASE - Observation data

\n", + "\n", + "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", + "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "plt.style.use('seaborn-whitegrid')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Observation data of species (when and where is a given species observed) is typical in biodiversity studies. Large international initiatives support the collection of this data by volunteers, e.g. [iNaturalist](https://www.inaturalist.org/). Thanks to initiatives like [GBIF](https://www.gbif.org/), a lot of these data is also openly available. \n", + "\n", + "In this example, data originates from a [study](http://esapubs.org/archive/ecol/E090/118/metadata.htm) of a Chihuahuan desert ecosystem near Portal, Arizona. It is a long-term observation study in 24 different plots (each plot identified with a `verbatimLocality` identifier) and defines, apart from the species, location and date of the observations, also the sex and the weight (if available).\n", + "\n", + "The data consists of two data sets:\n", + "\n", + "1. `observations.csv` the individual observations.\n", + "2. `species_names.csv` the overview list of the species names.\n", + "\n", + "Let's start with the observations data!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Reading in the observations data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Read in the `data/observations.csv` file with Pandas and assign the resulting DataFrame to a variable with the name `observations`.\n", + "- Make sure the 'occurrenceID' column is used as the index of the resulting DataFrame while reading in the data set.\n", + "- Inspect the first five rows of the DataFrame and the data types of each of the data columns.\n", + "\n", + "
Hints\n", + " \n", + "- All read functions in Pandas start with `pd.read_...`.\n", + "- Setting a column as index can be done with an argument of the `read_csv` function To check the documentation of a function, use the keystroke combination of SHIFT + TAB when the cursor is on the function.\n", + "- Remember `.head()` and `.info()`?\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "observations = pd.read_csv(\"data/observations.csv\", index_col=\"occurrenceID\")" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyear
occurrenceID
12MNaN-109.08197531.938887NaN1671977
23MNaN-109.08120831.938896NaN1671977
32FNaN-109.08197531.9388872439521.01671977
47MNaN-109.08281631.9381132439521.01671977
53MNaN-109.08120831.9388962439521.01671977
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" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude \\\n", + "occurrenceID \n", + "1 2 M NaN -109.081975 \n", + "2 3 M NaN -109.081208 \n", + "3 2 F NaN -109.081975 \n", + "4 7 M NaN -109.082816 \n", + "5 3 M NaN -109.081208 \n", + "\n", + " decimalLatitude species_ID day month year \n", + "occurrenceID \n", + "1 31.938887 NaN 16 7 1977 \n", + "2 31.938896 NaN 16 7 1977 \n", + "3 31.938887 2439521.0 16 7 1977 \n", + "4 31.938113 2439521.0 16 7 1977 \n", + "5 31.938896 2439521.0 16 7 1977 " + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observations.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Int64Index: 35550 entries, 1 to 35550\n", + "Data columns (total 9 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 verbatimLocality 35550 non-null int64 \n", + " 1 verbatimSex 33042 non-null object \n", + " 2 weight 32283 non-null float64\n", + " 3 decimalLongitude 35550 non-null float64\n", + " 4 decimalLatitude 35550 non-null float64\n", + " 5 species_ID 33448 non-null float64\n", + " 6 day 35550 non-null int64 \n", + " 7 month 35550 non-null int64 \n", + " 8 year 35550 non-null int64 \n", + "dtypes: float64(4), int64(4), object(1)\n", + "memory usage: 2.7+ MB\n" + ] + } + ], + "source": [ + "observations.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Create a new column with the name `eventDate` which contains datetime-aware information of each observation. To do so, combine the columns `day`, `month` and `year` into a datetime-aware data type by using the `pd.to_datetime` function from Pandas (check the help of that function to see how multiple columns with the year, month and day can be converted).\n", + "\n", + "
Hints\n", + "\n", + "- `pd.to_datetime` can automatically combine the information from multiple columns. To select multiple columns, use a list of column names, e.g. `df[[\"my_col1\", \"my_col2\"]]`\n", + "- To create a new column, assign the result to new name, e.g. `df[\"my_new_col\"] = df[\"my_col\"] + 1`\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyeareventDate
occurrenceID
12MNaN-109.08197531.938887NaN16719771977-07-16
23MNaN-109.08120831.938896NaN16719771977-07-16
32FNaN-109.08197531.9388872439521.016719771977-07-16
47MNaN-109.08281631.9381132439521.016719771977-07-16
53MNaN-109.08120831.9388962439521.016719771977-07-16
.................................
3554615NaNNaN-109.08103631.9370592437568.0311220022002-12-31
3554715NaNNaN-109.08103631.9370592437568.0311220022002-12-31
3554810F14.0-109.08009131.9380172437874.0311220022002-12-31
355497M51.0-109.08281631.9381132439541.0311220022002-12-31
355505NaNNaN-109.07960231.938970NaN311220022002-12-31
\n", + "

35550 rows × 10 columns

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" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude \\\n", + "occurrenceID \n", + "1 2 M NaN -109.081975 \n", + "2 3 M NaN -109.081208 \n", + "3 2 F NaN -109.081975 \n", + "4 7 M NaN -109.082816 \n", + "5 3 M NaN -109.081208 \n", + "... ... ... ... ... \n", + "35546 15 NaN NaN -109.081036 \n", + "35547 15 NaN NaN -109.081036 \n", + "35548 10 F 14.0 -109.080091 \n", + "35549 7 M 51.0 -109.082816 \n", + "35550 5 NaN NaN -109.079602 \n", + "\n", + " decimalLatitude species_ID day month year eventDate \n", + "occurrenceID \n", + "1 31.938887 NaN 16 7 1977 1977-07-16 \n", + "2 31.938896 NaN 16 7 1977 1977-07-16 \n", + "3 31.938887 2439521.0 16 7 1977 1977-07-16 \n", + "4 31.938113 2439521.0 16 7 1977 1977-07-16 \n", + "5 31.938896 2439521.0 16 7 1977 1977-07-16 \n", + "... ... ... ... ... ... ... \n", + "35546 31.937059 2437568.0 31 12 2002 2002-12-31 \n", + "35547 31.937059 2437568.0 31 12 2002 2002-12-31 \n", + "35548 31.938017 2437874.0 31 12 2002 2002-12-31 \n", + "35549 31.938113 2439541.0 31 12 2002 2002-12-31 \n", + "35550 31.938970 NaN 31 12 2002 2002-12-31 \n", + "\n", + "[35550 rows x 10 columns]" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observations[\"eventDate\"] = pd.to_datetime(observations[[\"year\", \"month\", \"day\"]])\n", + "observations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "For convenience when this dataset will be combined with other datasets, add a new column, `datasetName`, to the survey data set with `\"Ecological Archives E090-118-D1.\"` as value for each of the individual records (static value for the entire data set)\n", + "\n", + "
Hints\n", + "\n", + "- When a column does not exist, a new `df[\"a_new_column\"]` can be created by assigning a value to it.\n", + "- Pandas will automatically broadcast a single string value to each of the rows in the DataFrame.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "observations[\"datasetName\"] = \"Ecological Archives E090-118-D1.\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Cleaning the `verbatimSex` column" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['M', 'F', nan, 'R', 'P', 'Z'], dtype=object)" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observations[\"verbatimSex\"].unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For the further analysis (and the species concerned in this specific data set), the `sex` information should be either `male` or `female`. We want to create a new column, named `sex` and convert the current values to the corresponding sex, taking into account the following mapping:\n", + "* `M` -> `male`\n", + "* `F` -> `female`\n", + "* `R` -> `male`\n", + "* `P` -> `female`\n", + "* `Z` -> nan" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Express the mapping of the values (e.g. `M` -> `male`) into a Python dictionary object with the variable name `sex_dict`. `Z` values correspond to _Not a Number_, which can be defined as `np.nan`. \n", + "- Use the `sex_dict` dictionary to replace the values in the `verbatimSex` column to the new values and save the mapped values in a new column 'sex' of the DataFrame.\n", + "- Check the conversion by printing the unique values within the new column `sex`.\n", + "\n", + "
Hints\n", + " \n", + "- A dictionary is a Python standard library data structure, see https://docs.python.org/3/tutorial/datastructures.html#dictionaries - no Pandas magic involved when you need a key/value mapping.\n", + "- When you need to replace values, look for the Pandas method `replace`. \n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "sex_dict = {\"M\": \"male\",\n", + " \"F\": \"female\",\n", + " \"R\": \"male\",\n", + " \"P\": \"female\",\n", + " \"Z\": np.nan}" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "observations['sex'] = observations['verbatimSex'].replace(sex_dict)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['male', 'female', nan], dtype=object)" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observations[\"sex\"].unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Tackle missing values (NaN) and duplicate values" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "See [pandas_08_missing_values.ipynb](pandas_08_missing_values.ipynb) for an overview of functionality to work with missing values." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "How many records in the data set have no information about the `species`? Use the `isna()` method to find out.\n", + "\n", + "
Hints\n", + "\n", + "- Do NOT use `survey_data_processed['species'] == np.nan`, but use the available method `isna()` to check if a value is NaN\n", + "- The result of an (element-wise) condition returns a set of True/False values, corresponding to 1/0 values. The amount of True values is equal to the sum.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "2102" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observations['species_ID'].isna().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "How many duplicate records are present in the dataset? Use the method `duplicated()` to check if a row is a duplicate.\n", + "\n", + "
Hints\n", + " \n", + "- The result of an (element-wise) condition returns a set of True/False values, corresponding to 1/0 values. The amount of True values is equal to the sum.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1579" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observations.duplicated().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Select all duplicate data by filtering the `observations` data and assign the result to a new variable `duplicate_observations`. The `duplicated()` method provides a `keep` argument define which duplicates (if any) to mark.\n", + "- Sort the `duplicate_observations` data on both the columns `eventDate` and `verbatimLocality` and show the first 9 records.\n", + "\n", + "
Hints\n", + "\n", + "- Check the documentation of the `duplicated` method to find out which value the argument `keep` requires to select all duplicate data.\n", + "- `sort_values()` can work with a single columns name as well as a list of names.\n", + "\n", + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyeareventDatedatasetNamesex
occurrenceID
53MNaN-109.08120831.9388962439521.016719771977-07-16Ecological Archives E090-118-D1.male
143MNaN-109.08120831.9388962439521.016719771977-07-16Ecological Archives E090-118-D1.male
47MNaN-109.08281631.9381132439521.016719771977-07-16Ecological Archives E090-118-D1.male
137MNaN-109.08281631.9381132439521.016719771977-07-16Ecological Archives E090-118-D1.male
3411FNaN-109.07930731.9380562439521.017719771977-07-17Ecological Archives E090-118-D1.female
3811FNaN-109.07930731.9380562439521.017719771977-07-17Ecological Archives E090-118-D1.female
4011FNaN-109.07930731.9380562439521.017719771977-07-17Ecological Archives E090-118-D1.female
2715MNaN-109.08103631.9370592439521.017719771977-07-17Ecological Archives E090-118-D1.male
2815MNaN-109.08103631.9370592439521.017719771977-07-17Ecological Archives E090-118-D1.male
\n", + "
" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude \\\n", + "occurrenceID \n", + "5 3 M NaN -109.081208 \n", + "14 3 M NaN -109.081208 \n", + "4 7 M NaN -109.082816 \n", + "13 7 M NaN -109.082816 \n", + "34 11 F NaN -109.079307 \n", + "38 11 F NaN -109.079307 \n", + "40 11 F NaN -109.079307 \n", + "27 15 M NaN -109.081036 \n", + "28 15 M NaN -109.081036 \n", + "\n", + " decimalLatitude species_ID day month year eventDate \\\n", + "occurrenceID \n", + "5 31.938896 2439521.0 16 7 1977 1977-07-16 \n", + "14 31.938896 2439521.0 16 7 1977 1977-07-16 \n", + "4 31.938113 2439521.0 16 7 1977 1977-07-16 \n", + "13 31.938113 2439521.0 16 7 1977 1977-07-16 \n", + "34 31.938056 2439521.0 17 7 1977 1977-07-17 \n", + "38 31.938056 2439521.0 17 7 1977 1977-07-17 \n", + "40 31.938056 2439521.0 17 7 1977 1977-07-17 \n", + "27 31.937059 2439521.0 17 7 1977 1977-07-17 \n", + "28 31.937059 2439521.0 17 7 1977 1977-07-17 \n", + "\n", + " datasetName sex \n", + "occurrenceID \n", + "5 Ecological Archives E090-118-D1. male \n", + "14 Ecological Archives E090-118-D1. male \n", + "4 Ecological Archives E090-118-D1. male \n", + "13 Ecological Archives E090-118-D1. male \n", + "34 Ecological Archives E090-118-D1. female \n", + "38 Ecological Archives E090-118-D1. female \n", + "40 Ecological Archives E090-118-D1. female \n", + "27 Ecological Archives E090-118-D1. male \n", + "28 Ecological Archives E090-118-D1. male " + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "duplicate_observations = observations[observations.duplicated(keep=False)]\n", + "duplicate_observations.sort_values([\"eventDate\", \"verbatimLocality\"]).head(9)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Exclude the duplicate values (i.e. keep the first occurrence while removing the other ones) from the `observations` data set and save the result as `observations_unique`. Use the `drop duplicates()` method from Pandas.\n", + "- How many observations are still left in the data set? \n", + "\n", + "
Hints\n", + "\n", + "- `keep=First` is the default option for `drop_duplicates`\n", + "- The number of rows in a DataFrame is equal to the `len`gth\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "observations_unique = observations.drop_duplicates()" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "33971" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(observations_unique)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Use the `dropna()` method to find out: \n", + "\n", + "- For how many observations (rows) we have all the information available (i.e. no NaN values in any of the columns)? \n", + "- For how many observations (rows) we do have the `species_ID` data available ? \n", + "- Remove the data without `species_ID` data from the observations and assign the result to a new variable `observations_with_ID`\n", + "\n", + "
Hints\n", + "\n", + "- `dropna` by default removes by default all rows for which _any_ of the columns contains a `NaN` value.\n", + "- To specify which specific columns to check, use the `subset` argument\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "29777" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(observations_unique.dropna())" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "31876" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(observations_unique.dropna(subset=['species_ID']))" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyeareventDatedatasetNamesex
occurrenceID
32FNaN-109.08197531.9388872439521.016719771977-07-16Ecological Archives E090-118-D1.female
47MNaN-109.08281631.9381132439521.016719771977-07-16Ecological Archives E090-118-D1.male
53MNaN-109.08120831.9388962439521.016719771977-07-16Ecological Archives E090-118-D1.male
61MNaN-109.08282931.9388512439566.016719771977-07-16Ecological Archives E090-118-D1.male
72FNaN-109.08197531.9388872437981.016719771977-07-16Ecological Archives E090-118-D1.female
\n", + "
" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude \\\n", + "occurrenceID \n", + "3 2 F NaN -109.081975 \n", + "4 7 M NaN -109.082816 \n", + "5 3 M NaN -109.081208 \n", + "6 1 M NaN -109.082829 \n", + "7 2 F NaN -109.081975 \n", + "\n", + " decimalLatitude species_ID day month year eventDate \\\n", + "occurrenceID \n", + "3 31.938887 2439521.0 16 7 1977 1977-07-16 \n", + "4 31.938113 2439521.0 16 7 1977 1977-07-16 \n", + "5 31.938896 2439521.0 16 7 1977 1977-07-16 \n", + "6 31.938851 2439566.0 16 7 1977 1977-07-16 \n", + "7 31.938887 2437981.0 16 7 1977 1977-07-16 \n", + "\n", + " datasetName sex \n", + "occurrenceID \n", + "3 Ecological Archives E090-118-D1. female \n", + "4 Ecological Archives E090-118-D1. male \n", + "5 Ecological Archives E090-118-D1. male \n", + "6 Ecological Archives E090-118-D1. male \n", + "7 Ecological Archives E090-118-D1. female " + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observations_with_ID = observations_unique.dropna(subset=['species_ID'])\n", + "observations_with_ID.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Filter the `observations` data and select only those records that do not have a `species_ID` while having information on the `sex`. Store the result as variable `not_identified`.\n", + "\n", + "
Hints\n", + "\n", + "- To combine logical operators element-wise in Pandas, use the `&` operator.\n", + "- Pandas provides both a `isna()` and a `notna()` method to check the existence of `NaN` values.\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "mask = observations['species_ID'].isna() & observations['sex'].notna()\n", + "not_identified = observations[mask]" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyeareventDatedatasetNamesex
occurrenceID
12MNaN-109.08197531.938887NaN16719771977-07-16Ecological Archives E090-118-D1.male
23MNaN-109.08120831.938896NaN16719771977-07-16Ecological Archives E090-118-D1.male
2315FNaN-109.08103631.937059NaN17719771977-07-17Ecological Archives E090-118-D1.female
3917MNaN-109.07941531.937117NaN17719771977-07-17Ecological Archives E090-118-D1.male
713F22.0-109.08120831.938896NaN19819771977-08-19Ecological Archives E090-118-D1.female
\n", + "
" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude \\\n", + "occurrenceID \n", + "1 2 M NaN -109.081975 \n", + "2 3 M NaN -109.081208 \n", + "23 15 F NaN -109.081036 \n", + "39 17 M NaN -109.079415 \n", + "71 3 F 22.0 -109.081208 \n", + "\n", + " decimalLatitude species_ID day month year eventDate \\\n", + "occurrenceID \n", + "1 31.938887 NaN 16 7 1977 1977-07-16 \n", + "2 31.938896 NaN 16 7 1977 1977-07-16 \n", + "23 31.937059 NaN 17 7 1977 1977-07-17 \n", + "39 31.937117 NaN 17 7 1977 1977-07-17 \n", + "71 31.938896 NaN 19 8 1977 1977-08-19 \n", + "\n", + " datasetName sex \n", + "occurrenceID \n", + "1 Ecological Archives E090-118-D1. male \n", + "2 Ecological Archives E090-118-D1. male \n", + "23 Ecological Archives E090-118-D1. female \n", + "39 Ecological Archives E090-118-D1. male \n", + "71 Ecological Archives E090-118-D1. female " + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "not_identified.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Adding the names of the observed species" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [], + "source": [ + "# Recap from previous exercises - remove duplicates and observations without species information\n", + "observations_unique_ = observations.drop_duplicates()\n", + "observations_data = observations_unique_.dropna(subset=['species_ID'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the data set `observations`, the column `specied_ID` provides only an identifier instead of the full name. The name information is provided in a separate file `species_names.csv`:" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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nameclasskingdomorderphylumscientificNameIDtaxa
0Dipodomys merriamiMammaliaAnimaliaRodentiaChordataDipodomys merriami Mearns, 18902439521Rodent
1Perognathus flavusMammaliaAnimaliaRodentiaChordataPerognathus flavus Baird, 18552439566Rodent
2Peromyscus eremicusMammaliaAnimaliaRodentiaChordataPeromyscus eremicus (Baird, 1857)2437981Rodent
3Sigmodon hispidusMammaliaAnimaliaRodentiaChordataSigmodon hispidus Say & Ord, 18252438147Rodent
4Dipodomys spectabilisMammaliaAnimaliaRodentiaChordataDipodomys spectabilis Merriam, 18902439531Rodent
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" + ], + "text/plain": [ + " name class kingdom order phylum \\\n", + "0 Dipodomys merriami Mammalia Animalia Rodentia Chordata \n", + "1 Perognathus flavus Mammalia Animalia Rodentia Chordata \n", + "2 Peromyscus eremicus Mammalia Animalia Rodentia Chordata \n", + "3 Sigmodon hispidus Mammalia Animalia Rodentia Chordata \n", + "4 Dipodomys spectabilis Mammalia Animalia Rodentia Chordata \n", + "\n", + " scientificName ID taxa \n", + "0 Dipodomys merriami Mearns, 1890 2439521 Rodent \n", + "1 Perognathus flavus Baird, 1855 2439566 Rodent \n", + "2 Peromyscus eremicus (Baird, 1857) 2437981 Rodent \n", + "3 Sigmodon hispidus Say & Ord, 1825 2438147 Rodent \n", + "4 Dipodomys spectabilis Merriam, 1890 2439531 Rodent " + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "species_names = pd.read_csv(\"data/species_names.csv\")\n", + "species_names.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The species names contains for each identifier in the `ID` column the scientific name of a species. The `species_names` data set contains in total 38 different scientific names:" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(38, 8)" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "species_names.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For further analysis, let's combine both in a single DataFrame in the following exercise." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Combine the DataFrames `observations` and `species_names` by adding the corresponding species name information (name, class, kingdom,..) to the individual observations using the `pd.merge()` function. Assign the output to a new variable `survey_data`.\n", + "\n", + "
Hints\n", + "\n", + "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", + "- Take into account that our key-column is different for `observations` and `species_names`, respectively `specied_ID` and `ID`. The `pd.merge()` function has `left_on` and `right_on` keywords to specify the name of the column in the left and right `DataFrame` to merge on.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyeareventDatedatasetNamesexnameclasskingdomorderphylumscientificNameIDtaxa
02FNaN-109.08197531.9388872439521.016719771977-07-16Ecological Archives E090-118-D1.femaleDipodomys merriamiMammaliaAnimaliaRodentiaChordataDipodomys merriami Mearns, 18902439521Rodent
17MNaN-109.08281631.9381132439521.016719771977-07-16Ecological Archives E090-118-D1.maleDipodomys merriamiMammaliaAnimaliaRodentiaChordataDipodomys merriami Mearns, 18902439521Rodent
23MNaN-109.08120831.9388962439521.016719771977-07-16Ecological Archives E090-118-D1.maleDipodomys merriamiMammaliaAnimaliaRodentiaChordataDipodomys merriami Mearns, 18902439521Rodent
31MNaN-109.08282931.9388512439566.016719771977-07-16Ecological Archives E090-118-D1.malePerognathus flavusMammaliaAnimaliaRodentiaChordataPerognathus flavus Baird, 18552439566Rodent
42FNaN-109.08197531.9388872437981.016719771977-07-16Ecological Archives E090-118-D1.femalePeromyscus eremicusMammaliaAnimaliaRodentiaChordataPeromyscus eremicus (Baird, 1857)2437981Rodent
...............................................................
3187115F29.0-109.08103631.9370592439581.0311220022002-12-31Ecological Archives E090-118-D1.femaleChaetodipus baileyiMammaliaAnimaliaRodentiaChordataChaetodipus baileyi (Merriam, 1894)2439581Rodent
3187215F34.0-109.08103631.9370592439581.0311220022002-12-31Ecological Archives E090-118-D1.femaleChaetodipus baileyiMammaliaAnimaliaRodentiaChordataChaetodipus baileyi (Merriam, 1894)2439581Rodent
3187315NaNNaN-109.08103631.9370592437568.0311220022002-12-31Ecological Archives E090-118-D1.NaNAmmospermophilus harrisiMammaliaAnimaliaRodentiaChordataAmmospermophilus harrisii (Audubon & Bachman, ...2437568Rodent-not censused
3187410F14.0-109.08009131.9380172437874.0311220022002-12-31Ecological Archives E090-118-D1.femaleReithrodontomys megalotisMammaliaAnimaliaRodentiaChordataReithrodontomys megalotis (Baird, 1857)2437874Rodent
318757M51.0-109.08281631.9381132439541.0311220022002-12-31Ecological Archives E090-118-D1.maleDipodomys ordiiMammaliaAnimaliaRodentiaChordataDipodomys ordii Woodhouse, 18532439541Rodent
\n", + "

31876 rows × 20 columns

\n", + "
" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude \\\n", + "0 2 F NaN -109.081975 \n", + "1 7 M NaN -109.082816 \n", + "2 3 M NaN -109.081208 \n", + "3 1 M NaN -109.082829 \n", + "4 2 F NaN -109.081975 \n", + "... ... ... ... ... \n", + "31871 15 F 29.0 -109.081036 \n", + "31872 15 F 34.0 -109.081036 \n", + "31873 15 NaN NaN -109.081036 \n", + "31874 10 F 14.0 -109.080091 \n", + "31875 7 M 51.0 -109.082816 \n", + "\n", + " decimalLatitude species_ID day month year eventDate \\\n", + "0 31.938887 2439521.0 16 7 1977 1977-07-16 \n", + "1 31.938113 2439521.0 16 7 1977 1977-07-16 \n", + "2 31.938896 2439521.0 16 7 1977 1977-07-16 \n", + "3 31.938851 2439566.0 16 7 1977 1977-07-16 \n", + "4 31.938887 2437981.0 16 7 1977 1977-07-16 \n", + "... ... ... ... ... ... ... \n", + "31871 31.937059 2439581.0 31 12 2002 2002-12-31 \n", + "31872 31.937059 2439581.0 31 12 2002 2002-12-31 \n", + "31873 31.937059 2437568.0 31 12 2002 2002-12-31 \n", + "31874 31.938017 2437874.0 31 12 2002 2002-12-31 \n", + "31875 31.938113 2439541.0 31 12 2002 2002-12-31 \n", + "\n", + " datasetName sex name \\\n", + "0 Ecological Archives E090-118-D1. female Dipodomys merriami \n", + "1 Ecological Archives E090-118-D1. male Dipodomys merriami \n", + "2 Ecological Archives E090-118-D1. male Dipodomys merriami \n", + "3 Ecological Archives E090-118-D1. male Perognathus flavus \n", + "4 Ecological Archives E090-118-D1. female Peromyscus eremicus \n", + "... ... ... ... \n", + "31871 Ecological Archives E090-118-D1. female Chaetodipus baileyi \n", + "31872 Ecological Archives E090-118-D1. female Chaetodipus baileyi \n", + "31873 Ecological Archives E090-118-D1. NaN Ammospermophilus harrisi \n", + "31874 Ecological Archives E090-118-D1. female Reithrodontomys megalotis \n", + "31875 Ecological Archives E090-118-D1. male Dipodomys ordii \n", + "\n", + " class kingdom order phylum \\\n", + "0 Mammalia Animalia Rodentia Chordata \n", + "1 Mammalia Animalia Rodentia Chordata \n", + "2 Mammalia Animalia Rodentia Chordata \n", + "3 Mammalia Animalia Rodentia Chordata \n", + "4 Mammalia Animalia Rodentia Chordata \n", + "... ... ... ... ... \n", + "31871 Mammalia Animalia Rodentia Chordata \n", + "31872 Mammalia Animalia Rodentia Chordata \n", + "31873 Mammalia Animalia Rodentia Chordata \n", + "31874 Mammalia Animalia Rodentia Chordata \n", + "31875 Mammalia Animalia Rodentia Chordata \n", + "\n", + " scientificName ID \\\n", + "0 Dipodomys merriami Mearns, 1890 2439521 \n", + "1 Dipodomys merriami Mearns, 1890 2439521 \n", + "2 Dipodomys merriami Mearns, 1890 2439521 \n", + "3 Perognathus flavus Baird, 1855 2439566 \n", + "4 Peromyscus eremicus (Baird, 1857) 2437981 \n", + "... ... ... \n", + "31871 Chaetodipus baileyi (Merriam, 1894) 2439581 \n", + "31872 Chaetodipus baileyi (Merriam, 1894) 2439581 \n", + "31873 Ammospermophilus harrisii (Audubon & Bachman, ... 2437568 \n", + "31874 Reithrodontomys megalotis (Baird, 1857) 2437874 \n", + "31875 Dipodomys ordii Woodhouse, 1853 2439541 \n", + "\n", + " taxa \n", + "0 Rodent \n", + "1 Rodent \n", + "2 Rodent \n", + "3 Rodent \n", + "4 Rodent \n", + "... ... \n", + "31871 Rodent \n", + "31872 Rodent \n", + "31873 Rodent-not censused \n", + "31874 Rodent \n", + "31875 Rodent \n", + "\n", + "[31876 rows x 20 columns]" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "survey_data = pd.merge(observations_data, species_names, how=\"left\",\n", + " left_on=\"species_ID\", right_on=\"ID\")\n", + "survey_data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Select subsets according to taxa of species" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Rodent 30869\n", + "Rodent-not censused 595\n", + "Bird 344\n", + "Rabbit 59\n", + "Reptile 9\n", + "Name: taxa, dtype: int64" + ] + }, + "execution_count": 96, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "survey_data['taxa'].value_counts()\n", + "#survey_data.groupby('taxa').size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Select the observations for which the `taxa` is equal to 'Rabbit', 'Bird' or 'Reptile'. Assign the result to a variable `non_rodent_species`. Use the `isin` method for the selection.\n", + "\n", + "
Hints\n", + "\n", + "- You do not have to combine three different conditions, but use the `isin` operator with a list of names.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "non_rodent_species = survey_data[survey_data['taxa'].isin(['Rabbit', 'Bird', 'Reptile'])]" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "412" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(non_rodent_species)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Select the observations for which the `name` starts with the characters 'r' (make sure it does not matter if a capital character is used in the 'taxa' name). Call the resulting variable `r_species`.\n", + "\n", + "
Hints\n", + "\n", + "- Remember the `.str.` construction to provide all kind of string functionalities? You can combine multiple of these after each other.\n", + "- If the presence of capital letters should not matter, make everything lowercase first before comparing (`.lower()`) \n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "r_species = survey_data[survey_data['name'].str.lower().str.startswith('r')]" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "2568" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(r_species)" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Reithrodontomys megalotis 2485\n", + "Reithrodontomys fulvescens 75\n", + "Reithrodontomys montanus 8\n", + "Name: name, dtype: int64" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "r_species[\"name\"].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Select the observations that are not Birds. Call the resulting variable non_bird_species.\n", + "\n", + "
Hints\n", + "\n", + "- Logical operators like `==`, `!=`, `>`,... can still be used.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "non_bird_species = survey_data[survey_data['taxa'] != 'Bird']" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "31532" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(non_bird_species)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Select the __Bird__ (taxa is Bird) observations from 1985-01 till 1989-12 usint the `eventDate` column. Call the resulting variable `birds_85_89`.\n", + "\n", + "
Hints\n", + "\n", + "- No hints, you can do this! (with the help of some `<=` and `&`, and don't forget the put brackets around each comparison that you combine)\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyeareventDatedatasetNamesexnameclasskingdomorderphylumscientificNameIDtaxa
869514NaNNaN-109.08182731.9370542491757.019119851985-01-19Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
872410NaNNaN-109.08009131.9380172491757.020119851985-01-20Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
87579NaNNaN-109.08090331.9378592491757.020119851985-01-20Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
879912NaNNaN-109.07851931.9382032491757.016219851985-02-16Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
928722NaNNaN-109.07860231.9364415231474.015619851985-06-15Ecological Archives E090-118-D1.NaNCampylorhynchus brunneicapillusAvesAnimaliaPasseriformesChordataCampylorhynchus brunneicapillus (Lafresnaye, 1...5231474Bird
\n", + "
" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude decimalLatitude \\\n", + "8695 14 NaN NaN -109.081827 31.937054 \n", + "8724 10 NaN NaN -109.080091 31.938017 \n", + "8757 9 NaN NaN -109.080903 31.937859 \n", + "8799 12 NaN NaN -109.078519 31.938203 \n", + "9287 22 NaN NaN -109.078602 31.936441 \n", + "\n", + " species_ID day month year eventDate \\\n", + "8695 2491757.0 19 1 1985 1985-01-19 \n", + "8724 2491757.0 20 1 1985 1985-01-20 \n", + "8757 2491757.0 20 1 1985 1985-01-20 \n", + "8799 2491757.0 16 2 1985 1985-02-16 \n", + "9287 5231474.0 15 6 1985 1985-06-15 \n", + "\n", + " datasetName sex name \\\n", + "8695 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "8724 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "8757 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "8799 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "9287 Ecological Archives E090-118-D1. NaN Campylorhynchus brunneicapillus \n", + "\n", + " class kingdom order phylum \\\n", + "8695 Aves Animalia Passeriformes Chordata \n", + "8724 Aves Animalia Passeriformes Chordata \n", + "8757 Aves Animalia Passeriformes Chordata \n", + "8799 Aves Animalia Passeriformes Chordata \n", + "9287 Aves Animalia Passeriformes Chordata \n", + "\n", + " scientificName ID taxa \n", + "8695 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "8724 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "8757 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "8799 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "9287 Campylorhynchus brunneicapillus (Lafresnaye, 1... 5231474 Bird " + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "birds_85_89 = survey_data[(survey_data[\"eventDate\"] >= \"1985-01-01\")\n", + " & (survey_data[\"eventDate\"] <= \"1989-12-31 23:59\")\n", + " & (survey_data['taxa'] == 'Bird')]\n", + "birds_85_89.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexweightdecimalLongitudedecimalLatitudespecies_IDdaymonthyeareventDatedatasetNamesexnameclasskingdomorderphylumscientificNameIDtaxa
869514NaNNaN-109.08182731.9370542491757.019119851985-01-19Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
872410NaNNaN-109.08009131.9380172491757.020119851985-01-20Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
87579NaNNaN-109.08090331.9378592491757.020119851985-01-20Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
879912NaNNaN-109.07851931.9382032491757.016219851985-02-16Ecological Archives E090-118-D1.NaNAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)2491757Bird
928722NaNNaN-109.07860231.9364415231474.015619851985-06-15Ecological Archives E090-118-D1.NaNCampylorhynchus brunneicapillusAvesAnimaliaPasseriformesChordataCampylorhynchus brunneicapillus (Lafresnaye, 1...5231474Bird
\n", + "
" + ], + "text/plain": [ + " verbatimLocality verbatimSex weight decimalLongitude decimalLatitude \\\n", + "8695 14 NaN NaN -109.081827 31.937054 \n", + "8724 10 NaN NaN -109.080091 31.938017 \n", + "8757 9 NaN NaN -109.080903 31.937859 \n", + "8799 12 NaN NaN -109.078519 31.938203 \n", + "9287 22 NaN NaN -109.078602 31.936441 \n", + "\n", + " species_ID day month year eventDate \\\n", + "8695 2491757.0 19 1 1985 1985-01-19 \n", + "8724 2491757.0 20 1 1985 1985-01-20 \n", + "8757 2491757.0 20 1 1985 1985-01-20 \n", + "8799 2491757.0 16 2 1985 1985-02-16 \n", + "9287 5231474.0 15 6 1985 1985-06-15 \n", + "\n", + " datasetName sex name \\\n", + "8695 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "8724 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "8757 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "8799 Ecological Archives E090-118-D1. NaN Amphispiza bilineata \n", + "9287 Ecological Archives E090-118-D1. NaN Campylorhynchus brunneicapillus \n", + "\n", + " class kingdom order phylum \\\n", + "8695 Aves Animalia Passeriformes Chordata \n", + "8724 Aves Animalia Passeriformes Chordata \n", + "8757 Aves Animalia Passeriformes Chordata \n", + "8799 Aves Animalia Passeriformes Chordata \n", + "9287 Aves Animalia Passeriformes Chordata \n", + "\n", + " scientificName ID taxa \n", + "8695 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "8724 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "8757 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "8799 Amphispiza bilineata (Cassin, 1850) 2491757 Bird \n", + "9287 Campylorhynchus brunneicapillus (Lafresnaye, 1... 5231474 Bird " + ] + }, + "execution_count": 105, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# alternative solution\n", + "birds_85_89 = survey_data[(survey_data[\"eventDate\"].dt.year >= 1985)\n", + " & (survey_data[\"eventDate\"].dt.year <= 1989) \n", + " & (survey_data['taxa'] == 'Bird')]\n", + "birds_85_89.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Drop the observations for which no `weight` information is available.\n", + "- On the filtered data, compare the median weight for each of the species (use the `name` column)\n", + "- Sort the output from high to low median weight (i.e. descending)\n", + " \n", + "__Note__ You can do this all in a single line statement, but don't have to do it as such!\n", + "\n", + "
Hints \n", + "\n", + "- You will need `dropna`, `groupby`, `median` and `sort_values`.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "name\n", + "Dipodomys spectabilis 124.0\n", + "Spermophilus spilosoma 93.5\n", + "Sigmodon hispidus 72.0\n", + "Sigmodon fulviventer 50.0\n", + "Dipodomys ordii 50.0\n", + "Sigmodon ochrognathus 49.0\n", + "Dipodomys merriami 44.0\n", + "Perognathus hispidus 32.0\n", + "Onychomys leucogaster 32.0\n", + "Chaetodipus baileyi 31.0\n", + "Onychomys torridus 24.0\n", + "Peromyscus eremicus 22.0\n", + "Peromyscus maniculatus 22.0\n", + "Peromyscus leucopus 20.0\n", + "Chaetodipus intermedius 19.5\n", + "Chaetodipus penicillatus 17.0\n", + "Reithrodontomys fulvescens 13.0\n", + "Reithrodontomys montanus 10.5\n", + "Reithrodontomys megalotis 10.0\n", + "Perognathus flavus 8.0\n", + "Baiomys taylori 8.0\n", + "Name: weight, dtype: float64" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Multiple lines\n", + "obs_with_weight = survey_data.dropna(subset=[\"weight\"])\n", + "median_weight = obs_with_weight.groupby(['name'])[\"weight\"].median()\n", + "median_weight.sort_values(ascending=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "name\n", + "Dipodomys spectabilis 124.0\n", + "Spermophilus spilosoma 93.5\n", + "Sigmodon hispidus 72.0\n", + "Sigmodon fulviventer 50.0\n", + "Dipodomys ordii 50.0\n", + "Sigmodon ochrognathus 49.0\n", + "Dipodomys merriami 44.0\n", + "Perognathus hispidus 32.0\n", + "Onychomys leucogaster 32.0\n", + "Chaetodipus baileyi 31.0\n", + "Onychomys torridus 24.0\n", + "Peromyscus eremicus 22.0\n", + "Peromyscus maniculatus 22.0\n", + "Peromyscus leucopus 20.0\n", + "Chaetodipus intermedius 19.5\n", + "Chaetodipus penicillatus 17.0\n", + "Reithrodontomys fulvescens 13.0\n", + "Reithrodontomys montanus 10.5\n", + "Reithrodontomys megalotis 10.0\n", + "Perognathus flavus 8.0\n", + "Baiomys taylori 8.0\n", + "Name: weight, dtype: float64" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Single line statement\n", + "survey_data.dropna(subset=[\"weight\"]).groupby(['name'])[\"weight\"].median().sort_values(ascending=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Species abundance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Which 8 species (use the `name` column to identify the different species) have been observed most over the entire data set?\n", + "\n", + "
Hints\n", + "\n", + "- Pandas provide a function to combine sorting and showing the first n records, see [here](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.nlargest.html)...\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "name\n", + "Dipodomys merriami 10025\n", + "Dipodomys ordii 2966\n", + "Chaetodipus penicillatus 2928\n", + "Chaetodipus baileyi 2696\n", + "Reithrodontomys megalotis 2485\n", + "Dipodomys spectabilis 2481\n", + "Onychomys torridus 2220\n", + "Perognathus flavus 1475\n", + "dtype: int64" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "survey_data.groupby(\"name\").size().nlargest(8)" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Dipodomys merriami 10025\n", + "Dipodomys ordii 2966\n", + "Chaetodipus penicillatus 2928\n", + "Chaetodipus baileyi 2696\n", + "Reithrodontomys megalotis 2485\n", + "Dipodomys spectabilis 2481\n", + "Onychomys torridus 2220\n", + "Perognathus flavus 1475\n", + "Name: name, dtype: int64" + ] + }, + "execution_count": 109, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "survey_data['name'].value_counts()[:8]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- What is the number of different species in each of the `verbatimLocality` plots? Use the `nunique` method. Assign the output to a new variable `n_species_per_plot`.\n", + "- Define a Matplotlib `Figure` (`fig`) and `Axes` (`ax`) to prepare a plot. Make an horizontal bar chart using Pandas `plot` function linked to the just created Matplotlib `ax`. Each bar represents the `species per plot/verbatimLocality`. Change the y-label to 'Plot number'.\n", + "\n", + "
Hints\n", + "\n", + "- _...in each of the..._ should provide a hint to use `groupby` for this exercise. The `nunique` is the aggregation function for each of the groups.\n", + "- `fig, ax = plt.subplots()` prepares a Matplotlib Figure and Axes.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "n_species_per_plot = survey_data.groupby([\"verbatimLocality\"])[\"name\"].nunique()" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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VqxQAUGUBh/yBAwfOGdanP9gEAAhfAbfJtG7dWl9++WXF919//XXFVT0AILxVeiV/8803V8QYzJ8/X7Vq1ZLL5VJZWZni4+M1YsQIO+sEAFRDpUN+/fr1dtYBALBAwHvyq1ev1htvvKHDhw/L5/NVvL5w4cKAJz87oOyLL76Q1+uV2+1WdHS0pk6dqksuueTiOgAAVCrgkPd6vUpPT1ejRo2qdGJ/AWXz58+X1+vVFVdcoZkzZ+q1117TwIEDzzmWFEpT0auZLrxXp2yPDicBh3yrVq30m9/8RrVq1arSiU8FlM2ZM6fitRkzZkiSfD6fCgsLlZSUVMVyAQBVEXDId+7cWd26ddNVV12lqKioitcD3a5xu91yu889/UcffaRJkybp6quv1p133lmNkgEAFyrgkM/OztbUqVODlv/epUsXde7cWdOmTdPs2bP93q4BYKZIfkLW2ICyVq1aqX379n6vyqvqvffeU48ePeRyudSzZ09lZWVd9DkBRI5IjnsI97iKageUlZeX67bbblPLli3PuF0zffr0KheRlZWlyy+/XK1atdKmTZvUvHnzKp8DAHDhAg75Bx98sFon9hdQNnHiRE2YMEFRUVHyeDzyer3VOjcA4MIEHPIbN270+3r79u3Pe1xlAWVLly4NWJRTtlmF+69/wUSvZnJSr5Eq4JCPjY2t+PqXX37R559/rvj4eEuLAgAER8Ah369fvzO+HzBgADtiACBCBBzy27ZtO+P7oqIi7dixw7KCAADBE3DIT5gwoeJrl8ulevXqafTo0ZYWBQAIjoBD/nyf7gQACG8Bh/xLL73k9wO3161bF/DkZ6dQ7t69W6NGjdLx48fldruD+iQtAOBcAYf8u+++q9WrV1/Qh3efzl8K5Ysvvqj7779fvXv31quvvqr58+dr+PDh5xxLCqWp6NVMpFCGs4Af/5eQkFCtSINTKZSNGzeueG38+PHq2bOnpJNbMw8cOFDl8wIALlzA6X3ixAnddtttuv7666sUa+AvhfLUbwPl5eVasmSJBg8eXJ2aAQAXKOCQT0tLC+qC5eXlGj58uG6++eYzbuUAMF8kpjieYmwKZaD4gqoaNWqUmjVrpieffDKo5wUQ/iI5AiHcIxwqS6EMeE8+mFasWKGaNWvq6aeftnNZAHCsgFfyP//8sy699NIzXvvuu++UkJBw3uP8pVDu27dPtWrVUv/+/SWd/KNuenr6Occ65S/w4X5lEEz0aiYn9RqpKh3y+/fv1759+zR69GhNmTJFPp9PknT06FH98Y9/VF5e3nlPXFkKJQDAPpUO+e3bt+v111/X999/f8bVdo0aNXTHHXfYURsA4CJVOuRvvPFG3XjjjbrjjjvUsWNHHTx4UFFRUapXr56d9QEALkLAe/I+n089e/aU2+3WiRMnVKNGDf35z39WUlKSHfUBAC5CwCGflZWlRYsWVTy5unv3bg0dOlRLliyxvDgAwMUJuIWyZs2aZ0QTNGnSpFoxBwAA+wWc1pdffrkmTJig9u3by+fzaf369bryyisv6ORnp1BKJ6OLp0yZoo0bN6pu3bp+jyOgzFT0aqbI7NUpW7UDDvmMjAz985//VH5+vlwul9q1a6fevXsHPLG/FMo333xTe/fuPeM3AwCAdSod8h9++GHF17GxsercuXPF9x9//LG6du163hOfSqGcM2dOxWvdu3dXvXr19NZbb11MzQCAC1TpkH/33XfPe2CgIe8vhZLtlwBgr0qH/OTJk3Xs2DEVFRWpSZMmqlHD1pgbALBUVRMljUuhXLVqlZ5//nk1btxYxcXFmjp1qhITE+2sDQAsU9XMnXDP6akshbLSIT937ly98cYbiomJ0U8//aT09HTNnTvXsgIBAMFX6ZCvWbOmYmJiJJ3cRnn06NEqndhfCmXHjh31r3/9S0VFRXrsscfUtm1bv5/x6pStTeF+ZRBM9GomJ/UaqSod8i6X67zfB1JZCuUf/vCHKp0HAFB9lQ75goIC3XvvvZJO5tfs2LFD9957r3w+n1wul3Jzc20rEgBQPZUOefayA0Dkq3TIX3bZZXbWAQCwAJvfAcBglg75LVu2qHv37lq8eLGkkzHF/fv3V2pqqp555hkdO3bMyuUBwPEsywz2F1A2Y8YMpaamqlevXvJ6vcrNzVVqauo5x5JCaSp6NdOF9+qU7dHhxLIr+VMBZacnTm7YsEHJycmSpOTkZK1bt86q5QEAsvBK3l9AWWlpqaKjoyVJcXFxKioqsmp5AIAsHPL+nP5Alc/ns3NpAGEgEgO+TjEuoMwKtWvXVllZmTwejwoLC/nwEMBhIjkCIdwjHCoLKLN1C2XHjh2Vl5cnSVq5cuUZH0QCAAg+y67k/QWUTZs2TSNHjlROTo6aNm2qu+66y6rlAQCSXL4wuzmen5+vpKSkUJdhi3D/9S+Y6NVM9Bo+KpudPPEKAAZjyAOAwRjyAGAwhjwAGIwhDwAGs/VhqBMnTmj8+PHaunWratasqfT0dCUkJJzzcwSUmYpezURAWTiz9Up+9erVOnz4sJYuXapJkybJ6/XauTwAOI6tQ/77779XYmKiJOnKK6/Url27VF5ebmcJAOAotg75Fi1a6OOPP1Z5ebm2b9+uH3/8UcXFxXaWAACOYus9+a5du+rzzz9Xv379dN111+nqq68mjRJwkEhMcTyFFMoL9Oyzz1Z83b17dzVs2NDuEgCESDjHAgQSCbEG/th6u2bz5s0aNWqUJOmjjz7S9ddfrxo12MUJAFax9Uq+RYsW8vl8SklJUf369ZWZmen355yyzSrcrwyCiV7N5KReI5WtQ75GjRqaMmWKnUsCgKNxrwQADMaQBwCDMeQBwGAMeQAwmK1/eD1y5IhGjBihgwcP6pdfftHgwYP5MG8AsJCtQ/6NN95Q8+bNNXToUBUWFuqhhx7Su+++e87PkUJpKnoNd07Zvuwktt6uiY2N1YEDByRJhw4dUmxsrJ3LA4Dj2Holf/vtt2v58uXq0aOHDh06pOzsbDuXBwDHsXXI/+Mf/1DTpk31yiuvaPPmzRozZoxef/11O0sAcB5VDeCK1NCu6ojUXm0d8p9//rk6deokSWrZsqUKCwt1/Phxud2256QB8KOqEQVOijUI917DIqCsWbNm2rRpkyRp586dqlu3LgMeACxk64RNSUnR6NGjlZaWpuPHjys9Pd3O5QHAcWwd8nXr1tX06dMD/pxTtnGF+69/wUSvQGjwxCsAGIwhDwAGY8gDgMEY8gBgMIY8ABjM1t01y5Yt04oVKyq+Lygo0BdffGFnCQDgKLYO+fvuu0/33XefJGnjxo165513/P4cKZSmotdQcMqWZPgXsts1L730kgYNGhSq5QHAEUIy5L/88ks1adJEcXFxoVgeABwjJMExubm56tOnTyiWBhzHyuTESE1mrI5I7TUkQ37Dhg0aO3ZsKJYGHMfKiAUnRTiEe69hkUIpSYWFhapbt66io6PtXhoAHMf2K/mioiJdcskl5/0Zp+wGCPcrg2CiVyA0bL+Sb926tebOnWv3sgDgSDzxCgAGY8gDgMEY8gBgMIY8ABiMIQ8ABrN9C+WKFSs0d+5cud1uPfPMM+rates5P0NAmano1UwX3qtTtkeHE1uv5IuLi/XSSy9pyZIlmjVrllatWmXn8gDgOLZeya9bt04dOnRQvXr1VK9ePWVkZNi5PAA4jq1X8j/99JN8Pp+GDBmi1NRUrVu3zs7lAcBxbL8nX1hYqJkzZ2rXrl168MEH9cEHH8jlctldBoAQiMQUx1NIobwADRs21A033CC3260rr7xSdevW1f79+9WwYUM7ywAQIpGc6RPumURhkULZqVMnrV+/XidOnND+/ftVUlKi2NhYO0sAAEex9Uo+Pj5ePXv21EMPPaTS0lKNHTtWNWqc+/8Zp2yzCvcrg2CiVzM5qddIZfs9+b59+6pv3752LwsAjsQTrwBgMIY8ABiMIQ8ABmPIA4DBbP3Da0FBgQYNGqRmzZpJklq0aKFx48bZWQIAOIqtQ76kpEQ9e/bUmDFjzvtzpFCail7NZF2vTtlObSVbb9ccOXLEzuUAwPFsHfIlJSXKz8/Xo48+qn79+mn9+vV2Lg8AjmPr7ZqWLVtq8ODBSk5O1o4dO/T73/9eK1euVHR0tJ1lAIgQ4RQIRkDZBUhISFBCQoIkqXnz5mrUqJEKCwt1xRVX2FkGgAgRTpEJ4R7hEBYBZbm5uVq4cKEkqaioSPv27VN8fLydJQCAo9h6Jd+jRw8NGzZMeXl5OnbsmNLT07lVAwAWsnXIx8TEaM6cOQF/zinbpsL9179golczOanXSMUTrwBgMIY8ABiMIQ8ABmPIA4DBGPIAYDDbP/5POvnk2O23367Bgwfr7rvvPuffCSgzFb2GglN2q8G/kFzJv/zyy2rQoEEolgYAR7F9yH/33Xfatm2bbrnlFruXBgDHsX3IZ2ZmauTIkXYvCwCOZOs9+TfffFNt27YlkAywkZXJiZGazFgdkdqrrUN+zZo1+vHHH7VmzRr9/PPPio6O1qWXXqqOHTvaWQbgKFbGDjgp1iDce60shdLWIf/iiy9WfJ2VlaXLLruMAQ8AFgrJFspAnLLlK9yvDIKJXoHQCNmQf+qpp0K1NAA4Bk+8AoDBGPIAYDCGPAAYjCEPAAaz9Q+vpaWlGjlypPbt26ejR49q0KBB+t3vfmdnCQDgKLYO+Q8++ECtW7fWY489pp07d+rhhx/2O+RJoTQVvZqJXoPBqq3jtg753r17V3y9e/duxcfH27k8ADhOSPbJ9+3bVz///LNmzZoViuUBwDFCMuSXLl2qb775Rn/605+0YsUKuVyuUJQBAGHDqvAzW4d8QUGBGjZsqCZNmqhVq1YqLy/X/v371bBhQzvLAICwc7FRGJUFlNm6hfKzzz7TvHnzJEl79+5VSUmJYmNj7SwBABzF1iHft29f7d+/X6mpqXr88cf13HPPqUYNtuoDgFVsvV3j8Xj0l7/8JeDPkUJpHno1E72GPy6jAcBgDHkAMBhDHgAMxpAHAIMx5AHAYLY/8er1epWfn6/jx4/riSee0K233mp3CQDgGLYO+fXr12vr1q3KyclRcXGx+vTp43fIk0JpKno1U+QlMzqJrUO+Xbt2SkxMlCTFxMSotLRU5eXlioqKsrMMAHAMW+/JR0VFqU6dOpKkZcuWqUuXLgx4ALBQSFIoV61apdzc3IocGwDwx6pkxuooKysLq3oulO1Dfu3atZo1a5bmzp2r+vXr2708gAgSTjEC4R5rUFkKpa1D/vDhw/J6vVqwYIEaNGhg59IA4Ei2Dvm3335bxcXFGjJkSMVrmZmZatq06Rk/55S/qIf7lUEw0auZnNRrpLJ1yKekpCglJcXOJQHA0XjiFQAMxpAHAIMx5AHAYAx5ADAYQx4ADBaSJ163bNmiQYMGacCAAUpLSzvn3wkoMxW9muadh64OdQkIwPYr+ZKSEmVkZKhDhw52Lw0AjmP7kI+OjtacOXPUuHFju5cGAMex/XaN2+2W2x2Su0QA4DhMWwDVFqnJjNURqb0y5AFUm8fjcUx2Tbjn9FSWQskWSgAwmO1X8gUFBcrMzNTOnTvldruVl5enrKysM6KHSaE0D72aKRJvXziN7UO+devWWrRokd3LAoAjcbsGAAzm8vl8vlAXcbrK/ngAADi/pKSkc14LuyEPAAgebtcAgMEY8gBgsLB6GOr555/Xpk2b5HK5NHr0aCUmJoa6JEsUFBRo0KBBatasmSSpRYsWGjduXIirCq6zk0Z3796t4cOHq7y8XHFxcZo6daqio6NDXWZQnN1rRkaGvvjiC9WtW1eS9Mgjj+iWW24JbZFB4vV6lZ+fr+PHj+uJJ55QmzZtjH1fz+51w4YNEfm+hs2Q37hxo3744Qfl5ORo27ZtGjVqlJYtWxbqsixRUlKinj17asyYMaEuxRL+kkZnzJih1NRU9erVS16vV7m5uUpNTQ1hlcHhr9eSkhJNmjTJuL3y69ev19atW5WTk6Pi4mL16dNHHTp0MPJ9razXSHxfw+Z2zbp169S9e3dJ0jXXXKNDhw7pv//9b4irssaRI0dCXYKl/CWNbtiwQcnJyZKk5ORkrVu3LlTlBZW/Xk19f9u1a6fp06dLkmJiYlRaWmrs++qv10OHDoW4quoJmyG/d+9excbGVnzfsGFDFRUVhbAi65SUlCg/P1+PPvqo+vXrp/Xr14e6pKByu93yeDxnvFZaWlrxa3xcXJwx762/Xo8cOaKZM2eqf//+GjZsmA4cOBCa4oIsKipKderUkSQtW7ZMXbp0MfZ99ddrWVlZRL6vYTPkz97J6fP55HK5QlSNtVq2bKnBgwdr7ty5mjhxokaOHKljx46FuixLnf5emr5rt2/fvho2bJgWLVqkhIQEZWVlhbqkoFq1apVyc3P13HPPGf++nt5rpL6vYTPk4+PjtXfv3orv9+zZo0aNGoWwIuskJCRU/IrbvHlzNWrUSIWFhSGuylq1a9dWWVmZJKmwsNDoD43p0aOHmjdvXvH1t99+G+KKgmft2rWaNWuW5syZo/r16xv9vp7da6S+r2Ez5H/7298qLy9PkvT111+rcePGqlevXoirskZubq4WLlwoSSoqKtK+ffsUHx8f4qqs1bFjx4r3d+XKlercuXOIK7LOwIEDtWvXLkkn/xZx7bXXhrii4Dh8+LC8Xq+ys7MrAgVNfV/99Rqp72tYPfE6bdo0ffbZZ3K5XBo/frxatmwZ6pIscfDgQQ0bNkwlJSU6duyYnnzySXXt2jXUZQXN2Umj8fHxmjZtmkaOHKmjR4+qadOmmjx5smrWrBnqUi+av14feOABvfLKK6pTp45q166tyZMnq2HDhqEu9aLl5OQoKyur4mpWkqZMmaKxY8ca97766/Wee+7RokWLIu59DashDwAIrrC5XQMACD6GPAAYjCEPAAZjyAOAwRjyAGAwhjwAGIwhDwAGY8gDgMH+P2orFT5XJMZ/AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(6, 6))\n", + "n_species_per_plot.plot(kind=\"barh\", ax=ax)\n", + "ax.set_ylabel(\"Plot number\");" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "# Alternative option to calculate the species per plot:\n", + "# inspired on the pivot table we already had:\n", + "# species_per_plot = survey_data.reset_index().pivot_table(\n", + "# index=\"name\", columns=\"verbatimLocality\", values=\"ID\", aggfunc='count')\n", + "# n_species_per_plot = species_per_plot.count()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- What is the number of plots (`verbatimLocality`) each of the species have been observed in? Assign the output to a new variable `n_plots_per_species`. Sort the counts from low to high.\n", + "- Make an horizontal bar chart using Pandas `plot` function to show the number of plots each of the species was found (using the `n_plots_per_species` variable). \n", + "\n", + "
Hints\n", + "\n", + "- Use the previous exercise to solve this one.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_plots_per_species = survey_data.groupby([\"name\"])[\"verbatimLocality\"].nunique().sort_values()\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 8))\n", + "n_plots_per_species.plot(kind=\"barh\", ax=ax)\n", + "ax.set_xlabel(\"Number of plots\");\n", + "ax.set_ylabel(\"\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Starting from the `survey_data`, calculate the amount of males and females present in each of the plots (`verbatimLocality`). The result should return the counts for each of the combinations of `sex` and `verbatimLocality`. Assign to a new variable `n_plot_sex` and ensure the counts are in a column named \"count\".\n", + "- Use a `pivot_table` to convert the `n_plot_sex` DataFrame to a new DataFrame with the `verbatimLocality` as index and `male`/`female` as column names. Assign to a new variable `pivoted`.\n", + "\n", + "
Hints\n", + "\n", + "- _...for each of the combinations..._ `groupby` can also be used with multiple columns at the same time.\n", + "- If a `groupby` operation gives a Series as result, you can give that Series a name with the `.rename(..)` method.\n", + "- `reset_index()` is useful function to convert multiple indices into columns again.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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sexverbatimLocalitycount
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" + ], + "text/plain": [ + " sex verbatimLocality count\n", + "0 female 1 792\n", + "1 female 2 838\n", + "2 female 3 809\n", + "3 female 4 825\n", + "4 female 5 494" + ] + }, + "execution_count": 114, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "n_plot_sex = survey_data.groupby([\"sex\", \"verbatimLocality\"]).size().rename(\"count\").reset_index()\n", + "n_plot_sex.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "sex female male\n", + "verbatimLocality \n", + "1 792 1027\n", + "2 838 1017\n", + "3 809 742\n", + "4 825 972\n", + "5 494 552" + ] + }, + "execution_count": 115, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pivoted = n_plot_sex.pivot_table(columns=\"sex\", index=\"verbatimLocality\", values=\"count\")\n", + "pivoted.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As such, we can use the variable `pivoted` to plot the result:" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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JkiQBFmNJkiQJsBhLkiRJgBf4OKolpF9U9sLhWypuIJIkSccBjxhLkiRJWIwlSZIkwGIsSZIkAc4x1nHEOdvSHn4WJKl0HjGWJEmSsBhLkiRJgMVYkiRJAizGkiRJEmAxliRJkgCLsSRJkgRYjCVJkiTAYixJkiQBFmNJkiQJsBhLkiRJgJeEViXTePCbZS5bFVuBA5EkScccjxhLkiRJWIwlSZIkwGIsSZIkAc4xliTpuHaw72a81bNJBY5EOvI8YixJkiRhMZYkSZIAi7EkSZIEWIwlSZIkwC/fSZLCwIvrSKoMPGIsSZIkYTGWJEmSAIuxJEmSBDjHWJIk6ZjlBVrCy2IsSZJUCSWkX1T2wuFbKm4gxxCnUkiSJElYjCVJkiTAYixJkiQBFmNJkiQJsBhLkiRJgMVYkiRJAizGkiRJEnAY5zGeM2cOzz77LFFRUfTr148zzzyTgQMHUlxcTHx8PGPHjiUmJoY5c+YwdepUqlSpQkpKCl26dAnn+CVJkqSwKFcxzsvLY9KkScyaNYuCggLS0tJ4++236d69O506dWLMmDFkZGSQnJzMpEmTyMjIIDo6muTkZNq3b0+NGjXCvBmSJEnS4SnXVIqFCxfSqlUrTjjhBOrWrcuIESNYvHgxSUlJACQlJbFw4UKWLFlCYmIicXFxxMbG0rJlS7KyssK6AZIkSVI4lOuI8Y8//khJSQl3330369ev56677qKwsJCYmBgA4uPjyc3NZcOGDdSqVSv0vDp16pCbmxuekUuSJElhVO45xjk5OTzxxBOsXbuWm2++mYiIiNCykpKSff7c+/69H7e37Ozs8g6lQtZnXvjzioqKKnw7ylKZt8/3SnhVhtczoYLzDqYyvF8q8/uzsr+WlT3vYPzsla5cxbh27do0b96cqKgoTjnlFKpXr05kZCRFRUXExsaSk5ND3bp1qVevHgsWLAg9b/369TRr1qzUdSYklLWr/rY8QzzI+n6NeeHNK1t2dnYA663M2+d7JbyO39czmLyjZ/uCeb9UdF5Fvp5lZ8XGxlaC17Ky5/nZO1SZmZllLivXHOM2bdqwaNEidu/ezaZNmygoKKB169bMnTsXgHnz5tG2bVuaNm3K0qVLyc/PZ/v27WRlZdGyZcvyREqSJEmBKtcR43r16tGhQwd69uxJYWEhw4YNIzExkUGDBpGenk79+vVJTk4mOjqa/v3706tXLyIiIujduzdxcXHh3gZJ0n4aD36zzGWrYitwIJJ0DCn3HONu3brRrVu3fe6bMmXKAY/r2LEjHTt2LG+MJEmSVCHKXYwlSVLllpB+UdkLh2+puIFIFcRLQkuSJElYjCVJkiTAYixJkiQBFmNJkiQJ8Mt3kiTpOOWXC7U/jxhLkiRJWIwlSZIkwKkUOoL8FZYkSTqaWIwlSZLC5GCXY3+rZ5MKHInKw6kUkiRJEh4xliRJRwmn2OlI84ixJEmShMVYkiRJApxKIUmSKrGDfRluVWwFDkTHBI8YS5IkSViMJUmSJMBiLEmSJAEWY0mSJAmwGEuSJEmAxViSJEkCLMaSJEkSYDGWJEmSAIuxJEmSBFiMJUmSJMBLQitgXopTkrQ3fy7oaOYRY0mSJAmLsSRJkgRYjCVJkiTAYixJkiQBFmNJkiQJsBhLkiRJgMVYkiRJAizGkiRJEmAxliRJkgCLsSRJkgRYjCVJkiTAYixJkiQBFmNJkiQJsBhLkiRJAEQd6QFIkiRJhyoh/aKyFw7fUq51WowlScecxoPfLHPZWz2bVOBIJFUmTqWQJEmSsBhLkiRJgMVYkiRJAizGkiRJEuCX7yRJkipEEGdRUHgdVjEuKiriqquuonfv3rRq1YqBAwdSXFxMfHw8Y8eOJSYmhjlz5jB16lSqVKlCSkoKXbp0CdfYJUmSVIkd7Aw0q2LDn3dYUymefPJJatSoAcDEiRPp3r0706dPp0GDBmRkZFBQUMCkSZN44YUXmDZtGs8++yybN28Ow7AlSZKk8Cp3MV65ciUrVqzg0ksvBWDx4sUkJSUBkJSUxMKFC1myZAmJiYnExcURGxtLy5YtycrKCsvAJUmSpHAqdzEePXo0gwcPDv29sLCQmJgYAOLj48nNzWXDhg3UqlUr9Jg6deqQm5t7GMOVJEmSglGuOcavvvoqzZo1o2HDhqH7IiIiQrdLSkr2+XPv+/d+3N6ys7PLM5QyhXt95pl3qIqKiip8O0rjaxleleH1rOx5Ff1+OV7fn5XhvWJeeFWGz0K5ivGCBQtYvXo1CxYs4KeffiImJoaqVatSVFREbGwsOTk51K1bl3r16rFgwYLQ89avX0+zZs1KXWdCQkIZad+WZ4gHWd+vMc+88MjOzg7zen0tw6uyv57Hb15sbGwg78OyHPvvz6Pn3868YyGvbMfKZyEzM7PMZeUqxo899ljodlpaGg0aNOCzzz5j7ty5/OlPf2LevHm0bduWpk2bMmzYMPLz84mMjCQrK4uhQ4eWJ1KSJEkKVNjOY3zXXXcxaNAg0tPTqV+/PsnJyURHR9O/f3969epFREQEvXv3Ji4uLlyRkiRJUtgcdjG+6667QrenTJlywPKOHTvSsWPHw42RJEmSAuUloSVJkiQsxpIkSRJgMZYkSZIAi7EkSZIEhPGsFJIkHQ0S0i8qe+HwLRU3EEnHHI8YS5IkSViMJUmSJMBiLEmSJAEWY0mSJAmwGEuSJEmAxViSJEkCLMaSJEkSYDGWJEmSAIuxJEmSBFiMJUmSJMBiLEmSJAEWY0mSJAmwGEuSJEmAxViSJEkCLMaSJEkSAFFHegDSsazx4DfLXPZWzyYVOBJJknS4PGIsSZIkYTGWJEmSAIuxJEmSBFiMJUmSJMBiLEmSJAEWY0mSJAmwGEuSJEmA5zGWApOQflHZC4dvqbiBSJKk38QjxpIkSRIWY0mSJAmwGEuSJEmAxViSJEkCLMaSJEkSYDGWJEmSAE/XJknSYfHUjFLl4RFjSZIkCYuxJEmSBFiMJUmSJMBiLEmSJAEWY0mSJAmwGEuSJEmAxViSJEkCLMaSJEkSYDGWJEmSAIuxJEmSBFiMJUmSJMBiLEmSJAEQVd4njhkzhszMTHbt2sXtt99OYmIiAwcOpLi4mPj4eMaOHUtMTAxz5sxh6tSpVKlShZSUFLp06RLO8UuSFLjGg98sc9mq2AociKRAlasYL1q0iG+++Yb09HTy8vK47rrraNWqFd27d6dTp06MGTOGjIwMkpOTmTRpEhkZGURHR5OcnEz79u2pUaNGmDdDkiRJOjzlmkrxxz/+kccffxyAk046icLCQhYvXkxSUhIASUlJLFy4kCVLlpCYmEhcXByxsbG0bNmSrKys8I1ekiRJCpNyFePIyEiqVasGwMyZM2nXrh2FhYXExMQAEB8fT25uLhs2bKBWrVqh59WpU4fc3NwwDFuSJEkKr3LPMQaYP38+GRkZPP/883To0CF0f0lJyT5/7n1/REREqevKzs4+nKEEvj7zzDtW8yrDthUVFVX4dpSlMrye5pl3rGWZd2zkVYZ9dbmL8QcffMBTTz3Fs88+S1xcHFWrVqWoqIjY2FhycnKoW7cu9erVY8GCBaHnrF+/nmbNmpW6voSEhDKSvi3X+Mpe368xz7yjNa8yb9vBZWdnB7Deyv56mmfe0Zhl3rGfdxDDTzrIsi3lXGn4ty8zM7PMZeWaSrF161bGjBnD5MmTQ1+ka926NXPnzgVg3rx5tG3blqZNm7J06VLy8/PZvn07WVlZtGzZsjyRkiRJUqDKdcT4n//8J3l5edx9992h+x599FGGDRtGeno69evXJzk5mejoaPr370+vXr2IiIigd+/exMXFhWvskiRJUtiUqxinpKSQkpJywP1Tpkw54L6OHTvSsWPH8sRIkiRJFcYr30mSJElYjCVJkiTAYixJkiQBFmNJkiQJsBhLkiRJgMVYkiRJAg7zktCSJEk6fjQe/GaZy1bFVuBAAuIRY0mSJAmLsSRJkgRYjCVJkiTAYixJkiQBfvlO0lHiYF/oeKtnkwociSTpeOURY0mSJAmPGEs6BiSkX1T2wuFbKm4gkqRKzSPGkiRJEhZjSZIkCbAYS5IkSYDFWJIkSQIsxpIkSRJgMZYkSZIAi7EkSZIEWIwlSZIkwGIsSZIkARZjSZIkCbAYS5IkSYDFWJIkSQIsxpIkSRJgMZYkSZIAi7EkSZIEWIwlSZIkwGIsSZIkARZjSZIkCbAYS5IkSYDFWJIkSQIsxpIkSRJgMZYkSZIAi7EkSZIEWIwlSZIkwGIsSZIkARZjSZIkCbAYS5IkSYDFWJIkSQIsxpIkSRJgMZYkSZIAi7EkSZIEWIwlSZIkwGIsSZIkARBVESEjR45kyZIlREREMHToUM4777yKiJUkSZJ+s8CL8f/7f/+P77//nvT0dFasWMGQIUOYOXNm0LGSJEnSIQl8KsXChQtp3749AKeffjr5+fls27Yt6FhJkiTpkARejDds2EDNmjVDf69duza5ublBx0qSJEmHJKKkpKQkyIBhw4Zx6aWXho4a33jjjYwaNYrGjRuHHpOZmRnkECRJkqSQFi1alHp/4HOM69Wrx4YNG0J/X79+PXXq1NnnMWUNTpIkSaoogU+luPjii5k7dy4AX331FXXr1uWEE04IOlaSJEk6JIEfMT7//PM555xz6NatGxERETz44INBR0qSJEmHrEIu8DFgwABefvll/u///o+zzjorLOv8+uuvad++Pf/7v/8blvX9mjFjxpCSksJ///d/M2/evMByCgsL6devHz169KBr16689957gWXtraioiKSkJGbPnh1ozrJly2jXrh2pqamkpqYyYsSIQPMA5syZw7XXXsv111/P+++/H2jWzJkzQ9uWmppK8+bNA83bvn07ffr0ITU1lW7duvHBBx8Emrd7927uv/9+unXrRmpqKitXrgwkZ//P97p160hNTaV79+7069ePHTt2BJoHMG3aNM455xy2b98e1qzS8tatW8ctt9xCjx49uOWWW8L+BeX98z777DNuvPFGUlNT6dWrF5s2bQo07xcffPABf/jDH8KaVVreiBEjuP7660OfwwULFgSat3PnTvr370+XLl3o2bMnW7ZsCTSvb9++oW275ppruP/++wPN++STT0Lvl9tvvz2s27d/1sqVK7npppvo0aMHw4YNY9euXWHLggN/lge9bymtOwS5bylt+4Lct+yfF/S+pawuFs59S4Vc4CPcCgoKGDFiBK1ataqQvEWLFvHNN9+Qnp5OXl4e1113HVdeeWUgWe+99x7nnnsut956K2vWrOEvf/kLl112WSBZe3vyySepUaNG4DkFBQV06NCB++67L/AsgLy8PCZNmsSsWbMoKCggLS2NSy65JLC8rl270rVrV2DPObzfeuutwLIAXnnlFU499VT69+9PTk4OPXv25O233w4s791332Xr1q28/PLL/PDDDzzyyCNMnjw5rBmlfb4nTpxI9+7d6dSpE2PGjCEjI4Pu3bsHlvfqq6+yYcMG6tatG5aMX8t77LHHuOGGG+jcuTMvvfQSU6ZMYeDAgYHlTZkyhTFjxtCwYUOeeOIJZsyYwd/+9rfA8gB+/vlnnn76aeLj48OSc7C8goICHnnkERISEsKaVVbejBkzqFmzJuPHjyc9PZ1PP/2UpKSkwPImTpwYuj1kyJDQPieovFGjRjFu3DiaNGnCU089RXp6OrfddlsgWePGjeO2227jkksuYdKkSbz11ltcc801h50Fpf8sb9WqVWD7ltLyCgoKAtu3lJZ34YUXBrZvKS3vvPPOC2zfUlYXC/e+5Zi8JHRMTAzPPPNMIG+s0vzxj3/k8ccfB+Ckk06isLCQ4uLiQLI6d+7MrbfeCuw5ilSvXr1Acva2cuVKVqxYwaWXXhp4VhD/Qz6YhQsX0qpVK0444QTq1q1bIUeofzFp0iTuvPPOQDNq1qzJ5s2bAcjPz9/n1IhBWLVqVejKlaeccgpr164N+2ehtM/34sWLQ0UjKSmJhQsXBprXvn177rnnHiIiIsKWc7C8Bx98kA4dOgD7/psGlTdx4kQaNmxISUkJOTk5/O53vws0D+Cpp56ie/fuxMTEhC2rrLwg9zOl5b333ntce+21AKSkpIStFJeV94tvv/2WrVu3hvVqsqXl7f2e3LJlS9j2M6Vlff/996Htadu2LR999FFYsqD0n+VB7ltKy0tKSgps31JaXpD7ltLy/v73vwe2bymri4V733JMFuOoqChiY2MrLC8yMpJq1aoBe35V3q5dOyIjIwPN7NatGwMGDGDo0KGB5gCMHj2awYMHB54De44QZGZm8te//pWbbrqJRYsWBZr3448/UlJSwt1330337t3DutM7mC+++IKTTz457EfH9nfVVVexdu1arrjiCnr06MGgQYMCzTvzzDP58MMPKS4u5ttvv2X16tXk5eWFNaO0z3dhYWFopxcfHx/WXweWlhfkF4RLy6tWrRqRkZEUFxczffr0sB0hKysP4N///jcdO3Zkw4YNoVIXVN53333H8uXL6dSpU9hyDpa3fft2nnjiCVJTUxkwYEBYy0BpeWvWrOGTTz6hV69e3HPPPYHn/eLFF1+kR48eYcsqK2/IkCH07t2bDh06kJmZyXXXXRdY1plnnhma8vbBBx/sc1arw1Xaz/Ig9y2l5cXFxYVt/b8lL8h9S1ndKKh9S2l5P/zwQ9j3LcdkMT5S5s+fT0ZGBg888EDgWS+//DJPPvkk9957L0GeavrVV1+lWbNmNGzYMLCMvZ111ln07t2bZ599locffpjBgweHfU7X/nJychg3bhyPPvooQ4YMCfT1/EVGRkbYfngczGuvvUb9+vV55513mDp1auBHxC+55BISExO56aabmDp1Kk2aNKmQ13PvoysVkXckFBcXM3DgQC666KIKmSbWrl073n77bZo0acLTTz8daNaoUaMYMmRIoBl7++XAwrRp0zjttNNIS0sLNK+kpISTTz6Z5557jjPOOCPs04tKs2PHDjIzM7nooosCz3r44Yd54oknmDt3Li1atGD69OmBZQ0aNIi33nqLm2++mZKSkkA+73v/LK+IfUtFdofS8oLet+yfF/S+Ze+8IPYtFuPf6IMPPuCpp57imWeeCfR/fMuWLWPdunUAJCQkUFxcHPbJ63tbsGAB7777LjfccAMzZ87kH//4Bx9//HFgeaeddlro11annnoqderUIScnJ7C82rVr07x5c6KiojjllFOoXr16oK/nLxYvXhz4F+8AsrKyaNOmDbDnPx05OTlh/7LK/u655x5efvllHnroIfLz86ldu3ageQBVq1alqKgI2PMfnYqaRlWRhgwZQqNGjejTp0/gWe+88w6w5z8cvxwFDEpOTg7ffvstAwYM4IYbbmD9+vVhP8q5vyuuuIJTTz01dPs///lPoHl16tShZcuWALRp04YVK1YEmgd7vhAXzikUB/Of//wndL2B1q1bs2zZssCyTj75ZCZPnsyLL75I06ZNadCgQVjXv//P8qD3LRXVHQ6WF+S+Zf+8oPcte+cVFBQEsm+xGP8GW7duZcyYMUyePDnwL6h9+umnPP/888Cey2kXFBQEOm/0scceY9asWcyYMYOuXbty55130rp168DyMjIyePHFFwHIzc1l48aNgc6jbtOmDYsWLWL37t1s2rQp8NcT9uxcq1evHva5lKVp1KgRS5YsAfb8Ord69epERQX3ndrly5eH/nf+73//m7PPPpsqVYLfjbRu3Tp0PvR58+bRtm3bwDMr0pw5c4iOjqZv374VkpeWlkZ2djYAS5YsCZXIINSrV4/58+czY8YMZsyYQd26dQM/m9Df/vY31q5dC+z5T+oZZ5wRaF67du1CZ4T58ssvA309f7F06dKwneXp19SpUydU9pcuXUqjRo0Cy5o4cWLoLCKzZ8/m8ssvD9u6S/tZHuS+pSK7Q1l5Qe5bSssLct+yf15Q+5bALwkdhGXLljF69GjWrFlDVFQU9erVIy0tLbA3Xnp6Omlpafv8A48ePZr69euHPauoqIj77ruPdevWUVRURJ8+fcK6YziYtLQ0GjRowPXXXx9YxpYtWxgwYAAFBQXs2LGDPn36BHqWCNgzLeXNN9+ksLCQO+64I6xfjCnNsmXLeOyxx3j22WcDzYE9cymHDh3Kxo0b2bVrF/369Qv01/C7d+9m6NChfPfdd8TFxTF69OiwHzEu7fM9btw4Bg8ezM8//0z9+vUZNWoU0dHRgeW1bt2ajz/+mM8//5zExESaNWsWtm9yl5a3ceNG/uu//is0t/m0005j+PDhgeXde++9jBw5ksjISGJjYxkzZkzY/h1/bf98+eWX869//SssWWXl3XjjjTz33HNUq1aNqlWrMmrUqEC3b9y4cYwePZrc3FxiYmIYPXr0AVd4DWdeWloaaWlptGjRgs6dO4cl52B599xzD2PGjCE6OpqTTjqJkSNHcuKJJwaSNWDAAEaMGEF0dDQXXnghd9999+Fv1P+vtJ/ljz76KMOGDQtk31Ja3oUXXsjixYsD2beUlrd27VpOPPHEQPYtpeX17duX8ePHB7Jv+bUuFq59yzFZjCVJkqRwcyqFJEmShMVYkiRJAizGkiRJEmAxliRJkgCLsSRJkgRYjCUpUGlpab/53Jrbtm3jww8/BODpp5/ms88++03Pu/zyy9m+fXu5x1iaX8adnZ3NxIkTAXj33XcDv1KlJB1JwV0JQJJ0SL788ks++ugj2rRpw2233XakhwPsuQJnQkICAC+88AIXXXRRhVy8RpKOBIuxJP1GycnJ/OMf/6B+/fqsWbOG3r17c/bZZ7N69Wp27dpF3759adWqFampqaGrrdWsWZOlS5dyxx13sHr1agYOHEi7du14/vnnmTt3Lrt37+aSSy6hT58+/M///A/btm2jcePGfPbZZ3To0IG8vDw++eQT8vLy+Oabb7jnnnt44403WLlyJePGjaNp06aljnXr1q0MHjyY/Px8du3axbBhwzjnnHN49dVXmTZtGlWqVOHPf/4znTt3LnUsv1i8eDEvvfQSl19+OZ9//jm33noriYmJnH766XTt2hWAzp0789JLLwV+VUlJCppTKSTpN2rfvj3vvfcesGdawRVXXEF8fDzTpk1j0qRJjBw5MvTYM844gwceeACAjRs38uSTTzJhwgQee+yx0GOmT5/OjBkzmD17Ntu2baNXr1507tyZlJSUfXJXrVrFk08+ye23387kyZOZNGkSt912G2+88UaZY506dSpNmzZl2rRpDB06lFGjRrFt2zYmTZrESy+9xHPPPcfrr79e5lj2l5ycTHx8PM888wxdunThrbfeAmDFihU0bNjQUiypUvCIsST9RldeeSWjR4/mpptu4t133yU6OpqffvqJrKwsAH7++efQHNzzzjsv9LwLLrgAgDPPPJN169YBEBsbS48ePYiKiiIvL4/NmzeXmXvuuecSERFBfHw8f/jDH4iMjKROnTqh3NIsW7aMO+64A4DExES+++47vv32W0477TRiY2OJjY3lySefPOSxwJ7Sn5+fz8aNG3n33Xe55pprDv7CSdIxwmIsSb/RmWeeyfr161m3bh1bt27l/PPPJzk5mauvvvqAx0ZHR4duR0RE7LNszZo1vPDCC7zyyitUr1691OfvLSoqqtTbJSUlZT4nIiLigOVVqlRh9+7dhzWWX1x99dW88847LFy4MFSwJelY51QKSToEl1xyCX//+99JSkqiadOmzJ8/H9gzXWLChAmlPiczMxOA5cuX06BBA/Ly8qhVqxbVq1fnyy+/ZM2aNezcuZMqVaqE7awPiYmJLF68GIDPP/+cM844gyZNmvDdd9+xfft2fv75Z/785z+XOZbSREREhMZ3zTXXMHv2bOLj46latWpYxixJR5pHjCXpEFx55ZV069aN119/nUaNGrFo0SK6detGcXHxPl9a21vt2rVDX7677777SEhIoHr16nTr1o0WLVrQrVs3HnroIYYOHcq4ceOoX7/+IY/r1ltvJTIyEthzNPfmm29m6NCh3HzzzZSUlPDAAw9QrVo1+vbty1/+8hdKSkro2bNnmWNp0aLFARkXXHABqampvPjii9SuXZtq1ar95iPMknQsiCg52O/iJEkqxaZNm/jrX/9KRkYGVar4y0dJlYN7M0nSIZk/fz633HIL9957r6VYUqXiEWNJkiQJjxhLkiRJgMVYkiRJAizGkiRJEmAxliRJkgCLsSRJkgRYjCVJkiQA/j+CzQr1/+3JTQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pivoted.plot(kind='bar', figsize=(12, 6), rot=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Recreate the previous plot with the `catplot` function from the Seaborn library directly starting from survey_data. \n", + "\n", + "
Hints\n", + "\n", + "- Check the `kind` argument of the `catplot` function to find out how to use counts to define the bars instead of a `y` value.\n", + "- To link a column to different colors, use the `hue` argument\n", + "\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 117, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.catplot(data=survey_data, x=\"verbatimLocality\", \n", + " hue=\"sex\", kind=\"count\", height=3, aspect=3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Create a table, called `heatmap_prep`, based on the `survey_data` DataFrame with the row index the individual years, in the column the months of the year (1-> 12) and as values of the table, the counts for each of these year/month combinations.\n", + "- Using the seaborn documentation, make a heatmap starting from the `heatmap_prep` variable.\n", + "\n", + "
Hints\n", + "\n", + "- A `pivot_table` has an `aggfunc` parameter by which the aggregation of the cells combined into the year/month element are combined (e.g. mean, max, count,...). \n", + "- You can use the `ID` to count the number of observations.\n", + "- seaborn has an `heatmap` function which requires a short-form DataFrame, comparable to giving each element in a table a color value.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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0oyMiIiJeWYJ8ObJPZ3ScTifJyckUFRUBUFdXx4IFC8jIyGDVqlV0dnYCsG7dOtLS0khNTaWwsND9+bfeeouEhAR2797ty5giIiLihVpAeNHS0oLdbichIcF9LS8vj6ysLKZNm0ZBQQFlZWWMGzeOmpoaiouL6e7u5sc//jFz5syhtbWVZ555hh/84Ae+iigiIiIDnM9mdMLDwyksLCQmJsZ97dChQ8TFxQGQmJhIdXU1UVFRtLe309HRQXt7OyEhIURGRhIdHc3jjz/O4MGDfRVRREREziLYZ3R8VuhYrVYiIiJOuxYbG0tlZSUAVVVVuFwubDYbs2bNYvr06UyfPp20tDQGDx5MZGQkoaGB2TdKREREgoNfd13l5ORQVlbGwoULMQwDwzA4fPgwO3fuZNeuXezcuZPi4mKamgKvsaKIiMg3UYil/1/+5NddVzabDYfDAfTM6DQ0NLB//34mTZpEZGQkAOPGjcPpdJ62tkdERETkn+HXGZ38/HwqKioAKC0tZcaMGYwePZra2lq6u7s5deoUTqeTUaNG+TOWiIiIeGHxwf/8yWczOrW1teTm5lJfX4/VaqW8vJzs7GzsdjsOh4P4+HiSkpIAmDp1Kunp6RiGwbx58xg5ciQVFRWsX7+ejz76iPfee49NmzaxYcMGX8UVERGRXgT3KTpgMQzDMDvEP6vrz0+ZHcFDoHYvNz790OwIHj6/a4nZETwEYvdyy4XDzI7gobvhb2ZH6FUgdi8PRIHYvdxo/cLsCB4sAdq93HLJFX693/Zhl/b7mLNcn/b7mN7oZGQRERHxSr2uRERERAJUcD+6Kn/G7AieOtrMTtC77gD8bb5wqNkJPFjCB5kdwUMgTunT1mp2gt51tJudwINldKzZETx0rHvY7AgewlJ/ZnYED6E/vdPsCAFhR3T/P7r610Y9uhIREZEAEBLky5H16EpEREQGLM3oiIiIiFfBPZ+jGR0REREZwHxa6DidTpKTkykqKgKgrq6OBQsWkJGRwapVq+js7ARg3bp1pKWlkZqaSmFhIQCdnZ3k5OSQnp7Oz372M95++21fRhUREZFeWCz9//InnxU6LS0t2O3203pW5eXlkZWVRVFRETabjbKyMpxOJzU1NRQXF7NlyxZKS0tpbGzkD3/4A5GRkWzevJnf/OY3PPxw4O0SEBERGegsPnh509bWxsyZMyktLeXIkSNkZmaSnp7O3XffTUdHBwDbtm1j7ty53HzzzZSUlJw1v88KnfDwcAoLC4mJiXFfO3ToEHFxcQAkJiZSXV1NVFQU7e3tdHR00N7eTkhICJGRkdxwww2sWLECgKFDh3LixAlfRRUREZEA8MQTTzBkyBCgpz9meno6mzdvZsSIEZSUlNDS0kJBQQHPPvssmzZt4umnnz5rfeCzQsdqtRIREXHatdjYWCorK4Ge7uUulwubzcasWbOYPn0606dPJy0tjcGDBxMWFsagQT1nmmzcuJGf/OQnvooqIiIiXvirqWddXR0ffvihuw9mTU0NM2fOBGDmzJm88cYb7Nu3j4kTJxIVFUVERASTJ09m7969Z8zv18XIOTk5lJWVsXDhQgzDwDAMDh8+zM6dO9m1axc7d+6kuLiYpqYm92eef/553nvvPZYsCby+SCIiItI/cnNzWb58ufvHra2thIeHAxAdHU1jYyMul4uhQ//nsNlhw4bR2Nh4xnH9ur3cZrPhcDiAnhmdhoYG9u/fz6RJk4iMjARg3LhxOJ1OEhISeOGFF/jLX/7Cf/zHfxAWFubPqCIiIgKE+GHx8Msvv8yVV17JqFGj3NcsX1m1/GUTh683czAM47T39cavhU5+fj5xcXEkJSVRWlrK7NmzGTZsGBs3bqS7u5uuri6cTiejRo3i8OHDFBcXU1RU5H6EJSIiIgNPRUUFhw8fpqKign/84x+Eh4cTGRlJW1sbERERHD16lJiYGIYPH05FRYX7cw0NDVx55ZVnHNtnhU5tbS25ubnU19djtVopLy8nOzsbu92Ow+EgPj7e/Rxu6tSppKenYxgG8+bNY+TIkfzf//t/OXHiBFlZWe4x169f757GEhEREd/zx27wRx55xP3Pjz32GCNGjOCdd96hvLyc2bNns2PHDhITE5k0aRKrVq3i5MmThIaGsnfvXh544IEzjq2mnv1NTT37Tk09+0RNPc+Bmnr2iZp69o2aevZ4bfjIfh/zmqN/9/pzXxY611xzDTk5ObS3t3PppZfy0EMPERYWxvbt21m/fj0Wi4WMjAxuuOGGM95LLSBEREQkYPzyl790//Mzz3hOaMyaNYtZs2b1eTwVOiIiIuKVt+3gwUK9rkRERGTACu4ZHaPb7ASehg43O0Hvjh01O4GnAFx7YoQF3mJ3yyWXmx3Bg+X8C8yO0LsAXKNjnGw6+5v8LHzpSrMjeOruMjuBh+7a/zQ7Qq9CJlzr1/v5uzdVfwvuQkdERER8Ktgf/QR7fhERERGvNKMjIiIiXgX5kyvN6IiIiMjA5dNCx+l0kpycTFFREdDTmXTBggVkZGSwatUqOjs7AVi3bh1paWmkpqZSWFgIQFNTE7/4xS/IzMwkLS2Nffv2+TKqiIiI9MJisfT7y598Vui0tLRgt9tJSEhwX8vLyyMrK4uioiJsNhtlZWU4nU5qamooLi5my5YtlJaW0tjYyLZt25g9ezabNm3ivvvu49FHH/VVVBEREfHC4oOXP/ms0AkPD6ewsJCYmBj3tUOHDhEXFwdAYmIi1dXVREVF0d7eTkdHB+3t7YSEhBAZGcmtt97KT3/6UwCOHDnC8OEBum1bREREApbPFiNbrVas1tOHj42NpbKykjlz5lBVVYXL5cJmszFr1iymT59OV1cXS5YsYfDgwQA0Njbyf/7P/6G5uZmNGzf6KqqIiIh4ocXI5yAnJ4eysjIWLlyIYRgYhsHhw4fZuXMnu3btYufOnRQXF9PU1HPAVnR0NC+++CIrVqxgxYoV/owqIiIiA4Bft5fbbDYcDgcAVVVVNDQ0sH//fiZNmkRkZCQA48aNw+l0Ehoayrhx47jwwguZNm0a999/vz+jioiICPh98XB/8+uMTn5+PhUVFQCUlpYyY8YMRo8eTW1tLd3d3Zw6dQqn08moUaPYsWMHL730EgDvv/8+NpvNn1FFRERkAPDZjE5tbS25ubnU19djtVopLy8nOzsbu92Ow+EgPj6epKQkAKZOnUp6ejqGYTBv3jxGjhzJ4sWLWb58OTt37qSjo4M1a9b4KqqIiIh4ERLcEzpYDMMwzA7xz+ravt7sCJ6iLjI7Qe8CsamnNczsBJ4uGGp2Ag+WIdFmR/Cgpp59F4hNPQkNwH/3ArCpJ4MizU7QK3839fzrqMv7fcwrD3/S72N6o5ORRUREZMBSrysRERHxKsjXImtGR0RERAauoJ7RCZ11m9kRPBgf7jE7Qu+u+J7ZCTwF4F8Turc+ZnYEDyG//J3ZETx0/3e12RF6ZQnANXKWQFznYXSbncCD5fJJZkfwYPyjzuwIASEAv6rPSVAXOiIiIuJbOkdHREREJEBpRkdERES8CvIJHc3oiIiIyMDl00LH6XSSnJxMUVERAHV1dSxYsICMjAxWrVpFZ2cnAOvWrSMtLY3U1FQKCwtPG8PlcnHVVVdRU1Pjy6giIiLSC4vF0u8vf/JZodPS0oLdbichIcF9LS8vj6ysLIqKirDZbJSVleF0OqmpqaG4uJgtW7ZQWlpKY2Oj+zNr165l1KhRvoopIiIiZ2Cx9P/Ln3xW6ISHh1NYWEhMTIz72qFDh4iLiwMgMTGR6upqoqKiaG9vp6Ojg/b2dkJCQtydzN944w3OP/98YmNjfRVTREREBjCfFTpWq5WIiIjTrsXGxlJZWQlAVVUVLpcLm83GrFmzmD59OtOnTyctLY3BgwfT0dFBQUEB9957r68iioiIyFmEWCz9/vJrfn/eLCcnh7KyMhYuXIhhGBiGweHDh9m5cye7du1i586dFBcX09TUxFNPPcXNN9/MBRcEaPNAERERCXh+3V5us9lwOBxAz4xOQ0MD+/fvZ9KkSe7HVePGjcPpdPLaa6/R3d3N888/z9/+9jfeffddHn30Ub797W/7M7KIiMg3WrBvL/droZOfn09cXBxJSUmUlpYye/Zshg0bxsaNG+nu7qarqwun08moUaMoLi52f2758uXceOONKnJERETknPis0KmtrSU3N5f6+nqsVivl5eVkZ2djt9txOBzEx8eTlJQEwNSpU0lPT8cwDObNm8fIkSN9FUtERETOQbC3gLAYhmGYHWIgCdimnlFDzU7gKQD/5QnEpp6haurZZ4HY1JPuLrMTeFJTzz4J1Kaelku+5df7fTD+in4f89sHP+z3Mb3RycgiIiIyYKnXlYiIiHgV7I+ugrrQ6X7zj2ZH8DRkmNkJemX5rPHsb/Kz7m3PmR3BQ0j6r8yO4MH4+0GzI3iwDB5idoTg0d5qdgIPRluz2RE8GG+XmR3BU4Cu7PD3o6tgF9SFjoiIiPhWkE/oqNARERER74L90ZUWI4uIiMiApRkdERER8SrIJ3R8O6PjdDpJTk6mqKgIgLq6OhYsWEBGRgarVq2is7MTgHXr1pGWlkZqaiqFhYUAlJeXc91115GZmUlmZiZPPPGEL6OKiIjIAOSzGZ2WlhbsdjsJCQnua3l5eWRlZTFt2jQKCgooKytj3Lhx1NTUUFxcTHd3Nz/+8Y+ZM2cOLS0tLFiwgEWLFvkqooiIiJyFv7uN9zefzeiEh4dTWFhITEyM+9qhQ4eIi4sDIDExkerqaqKiomhvb6ejo4P29nZCQkKIjIykuTnwtj+KiIh801gs/f/yJ58VOlarlYiIiNOuxcbGUllZCfR0L3e5XNhsNmbNmsX06dOZPn06aWlpDB48mJaWFnbu3MnPf/5zbr31Vg4eDLyzRERERCSw+XUxck5ODmvWrKG0tJSrr74awzA4fPgwO3fuZNeuXXR2dpKWlsb111/PD3/4Q+Li4vjhD3/I22+/zbJly/jjHwPwgEAREZEBLNi3l/u10LHZbDgcDqBnRqehoYH9+/czadIkIiMjARg3bhxOp/O0tT2TJ0/m2LFjdHV1ERoa6s/IIiIiEsT8eo5Ofn4+FRUVAJSWljJjxgxGjx5NbW0t3d3dnDp1CqfTyahRoygoKKC8vBzo2b01dOhQFTkiIiJ+FuxrdHw2o1NbW0tubi719fVYrVbKy8vJzs7GbrfjcDiIj48nKSkJgKlTp5Keno5hGMybN4+RI0cye/ZsVqxYwaZNm+js7OQ3v/mNr6KKiIjIAGUxjADtWtYHaurZd5aQwJsNU1PPPuruNjuBp+4usxP0LhDXErR+YXYCD4HY1JOONrMTeArQ/zyGXHW9X+9X/73x/T7miHf8t8FIJyOLiIiIV5aQAPwLxDlQrysREREZsDSjIyIiIl4F4hPhcxHUa3Sk77rfqzI7ggdL1FCzI3gKxHUC50WZncBTAK47AeCCi81O4Kmr0+wEngLwv1xG0xGzI3iwDIo0O0KvLN/6vl/vd2Tyd/p9TNvbB/p9TG80oyMiIiJeBXuvKxU6IiIi4lWQ1zlajCwiIiIDl2Z0RERExKtg73Xl0xkdp9NJcnIyRUVFANTV1bFgwQIyMjJYtWoVnZ09i/TWrVtHWloaqampFBYWuj+/fv16Zs+ezdy5c9m/f78vo4qIiMgA5LMZnZaWFux2+2nNOfPy8sjKymLatGkUFBRQVlbGuHHjqKmpobi4mO7ubn784x8zZ84cTpw4wZ///GdefPFF3n//fV599VUmTpzoq7giIiLSiyCf0PHdjE54eDiFhYXExMS4rx06dIi4uDgAEhMTqa6uJioqivb2djo6OmhvbyckJITIyEh2795NSkoKVquV7373u/zqVwF4NL+IiMgAZ7FY+v3lTz4rdKxWKxEREaddi42NpbKyEoCqqipcLhc2m41Zs2Yxffp0pk+fTlpaGoMHD6a+vp5jx46xZMkSbrnlFg4e9F9fDBERERkY/LrrKicnh7KyMhYuXIhhGBiGweHDh9m5cye7du1i586dFBcX09TUhGEYtLa28vjjj/PLX/6SlStX+jOqiIiI0PPoqr9f/uTXXVc2mw2HwwH0zOg0NDSwf/9+Jk2aRGRkzwmU48aNw+l0MmzYMMaOHYvFYmHy5MnU19f7M6qIiIgMAH6d0cnPz6eiogKA0tJSZsyYwejRo6mtraW7u5tTp07hdDoZNWoU1157LVVVPW0L6urqsNls/owqIiIiBP8aHZ/N6NTW1pKbm0t9fT1Wq5Xy8nKys7Ox2+04HA7i4+NJSkoCYOrUqaSnp2MYBvPmzWPkyJGMHDmSqqoqMjMz6ejoYPXq1b6KKiIiIl5YgvxoYTX1/IZQU88+UlPPvlFTz75TU88+UVPPvvN3U88Tif1/tMuQKv+djaeTkUVERMQrnYwsIiIiEqA0oyMiIiLehQT3jE5QFzpG49/MjuDpVKvZCXplNBw2O4KH7i0OsyN4CPlJqtkRPFgu/xezI3jo3rbR7Ai9uyrR7AQeLOcPMTuCB6P5hNkRPB0JvO/zkJvvMzuC9IOgLnRERETEx4J8jY4KHREREfFKi5FFREREApRmdERERMQ7LUb2zul0snjxYhYtWkRGRgZ1dXWsXr0ai8XC5Zdfzpo1a7Baraxbt46amhoMwyA5OZnbb7+dJ554gtdffx2A7u5uXC4X5eXlvowrIiIiA4zPCp2WlhbsdjsJCQnua3l5eWRlZTFt2jQKCgooKytj3Lhx1NTUUFxcTHd3Nz/+8Y+ZM2cOd955J3feeScAL730Ek1NTb6KKiIiIt5ojU7vwsPDKSwsJCYmxn3t0KFDxMXFAZCYmEh1dTVRUVG0t7fT0dFBe3s7ISEh7k7mAJ2dnWzZsoWMjAxfRRUREREvLCGWfn/5k88KHavVSkRExGnXYmNjqaysBKCqqgqXy4XNZmPWrFlMnz6d6dOnk5aWxuDBg92f2bFjB9dcc43HWCIiIiJn49ddVzk5OZSVlbFw4UIMw8AwDA4fPszOnTvZtWsXO3fupLi4+LTHVC+++CI33XSTP2OKiIjIlyyW/n/5kV93XdlsNhyOntNwq6qqaGhoYP/+/UyaNMn9uGrcuHE4nU4SEhJoaWnh6NGjjBw50p8xRUREZIDw64xOfn4+FRUVAJSWljJjxgxGjx5NbW0t3d3dnDp1CqfTyahRowA4ePAgY8aM8WdEERER+YpgX6Pjsxmd2tpacnNzqa+vx2q1Ul5eTnZ2Nna7HYfDQXx8PElJSQBMnTqV9PR0DMNg3rx57hmcxsZGhg4d6quIIiIicjZBvuvKYhiGYXaIf5aaevZd9/t7zI7gwXj1FbMjeFBTz77p3pJvdoTeqalnn6ipZ9+EqqknAF/8OL7fxxz855p+H9MbnYwsIiIi3vnhUVNrayvLly+nqamJ9vZ2Fi9ezPjx47n//vvp6uoiOjqa3/72t4SHh7Nt2zY2btxISEgIqampzJs374xjq9ARERERU+3evZsJEyZw++23U19fz89//nO+//3vk56eTkpKCmvXrqWkpIQ5c+ZQUFBASUkJYWFhzJkzh+TkZIYMGeJ17KAudLr3V5kdwdPnn5mdoHcXBt5ap9BF95odwVPk4LO/x99OBt6p4CGpi82O0Lvmk2Yn8BQVeP/uWU61mx3BgxFxvtkRPHS//pLZEXoVMuVGv97PH93Lr7/+evc/HzlyhOHDh1NTU8Ovf/1rAGbOnMmzzz7LmDFjmDhxIlFRUQBMnjyZvXv3MmPGDK9jB3WhIyIiIgNHWloa//jHP3jyySe59dZbCQ8PByA6OprGxkZcLtdpm5SGDRtGY2PjGcdUoSMiIiLe+XE7eHFxMQcOHGDZsmWnzSR9uW/q6/unDMM464yTX8/RERERkSDjh5ORa2trOXLkCADf+c536OrqIjIykra2NgCOHj1KTEwMw4cPx+VyuT/X0NBAdHT0GeOr0BERERFTvf3222zYsAEAl8tFS0sLU6ZMoby8HOjpe5mYmMikSZPYv38/J0+epLm5mb179zJ58uQzjq1HVyIiIuKVxQ9TImlpaaxcuZL09HTa2tpYvXo1EyZMICcnh61bt3LppZcyZ84cwsLCWLp0KbfddhsWi4UlS5a4FyZ7ze/LAwOdTieLFy9m0aJFZGRkUFdXx+rVq7FYLFx++eWsWbMGq9XKunXrqKmpwTAMkpOTuf322zl69CgPPPAAHR0ddHd3s2LFCiZMmHDa+F1/ed5X0f952nXVZyEjv212BE+BuOuqOQD/TA2+0OwEvdOuq74JxF1XRw+ZHcFTR5vZCXrl711XLXOn9vuY571Y3e9jeuOzOq2lpQW73U5CQoL7Wl5eHllZWRQVFWGz2SgrK8PpdFJTU0NxcTFbtmyhtLSUxsZGnn32Wa677jo2bdrE0qVLWbduna+iioiIiDdB3r3cZ4VOeHg4hYWFxMTEuK8dOnSIuLg4ABITE6muriYqKor29nY6Ojpob28nJCSEyMhILrroIk6cOAHAyZMnueiii3wVVURERLxQU09vA1utWK2nDx8bG0tlZSVz5syhqqoKl8uFzWZj1qxZTJ8+na6uLpYsWcLgwYNZtGgR8+bN4+WXX+aLL75gy5YtvooqIiIiA5Rfd13l5ORQVlbGwoULMQwDwzA4fPgwO3fuZNeuXezcuZPi4mKampp4+umnSUlJYfv27djtdnJzc/0ZVURERECPrs6FzWbD4XDw3HPPMWnSJEaMGMH+/fuZNGkSkZGRREVFMW7cOJxOJ3v37iUxsacT8dSpU6mtrfVnVBERERkA/Fro5OfnU1FRAUBpaSkzZsxg9OjR1NbW0t3dzalTp3A6nYwaNYrLLruMffv2AfDuu+9y2WWX+TOqiIiIQM/JyP398iOfrdGpra0lNzeX+vp6rFYr5eXlZGdnY7fbcTgcxMfHk5SUBPTM2KSnp2MYBvPmzWPkyJHccccdrFy5ku3btwOwcuVKX0UVERERL/zR1NOXfHqOjq/pHJ1zoHN0+kbn6PSNztHpO52j0yc6R6fv/H2OTlt6Ur+PGbG5ot/H9EYnI4uIiIh3fn7U1N/U60pEREQGrOCe0WltNjuBp1MdZifoXQBW5Mbxo2ZH8NTeYnYCT52B92fK+GuV2RF6FfqzpWZH8GAc/cjsCJ4C8ZFMAH53Gh2B94jPFEG+RkczOiIiIjJgBfeMjoiIiPhUsO+6UqEjIiIi3gXg0odzoUdXIiIiMmD5tNBxOp0kJydTVFQEQF1dHQsWLCAjI4NVq1bR2dkJwLp160hLSyM1NZXCwkIAWlpa+NWvfkV6ejq33XYbjY2NvowqIiIivbBYLP3+8iefFTotLS3Y7XYSEhLc1/Ly8sjKyqKoqAibzUZZWRlOp5OamhqKi4vZsmULpaWlNDY28vvf/55Ro0axefNm7rzzTvLz830VVURERAYonxU64eHhFBYWEhMT47526NAh4uLiAEhMTKS6upqoqCja29vp6Oigvb2dkJAQIiMj+eSTT9zvnTx5Mnv27PFVVBEREfEmyHtd+azQsVqtREREnHYtNjaWyspKAKqqqnC5XNhsNmbNmsX06dOZPn06aWlpDB48+LT3vvXWW3z66ae+iioiIiLeWCz9//KjsxY6//3f/91vN8vJyaGsrIyFCxdiGAaGYXD48GF27tzJrl272LlzJ8XFxTQ1NTFv3jzCwsKYP38+1dXVDB0agP1iREREJKCddXv5ww8/zIYNG7Ba//c70W02Gw6HA+iZ0WloaGD//v1MmjSJyMhIAMaNG4fT6SQhIYFf//rXADQ3N/Pqq6/+r+8vIiIi58YS5NvLz1q9nHfeefzrv/4r48ePJywszH390UcfPeeb5efnExcXR1JSEqWlpcyePZthw4axceNGuru76erqwul0MmrUKCorK3nnnXe455572LZtG4mJied8PxEREflmO2uh8/Of/9zjmsvlOuvAtbW15ObmUl9fj9Vqpby8nOzsbOx2Ow6Hg/j4eJKSkgCYOnUq6enpGIbBvHnzGDlyJMOGDeP5559n/vz5xMTE8NBDD537/zsRERH53wnyk5EthmEYZ3pDZ2cnr732GidOnADg1KlTOBwOdu3a5Y98Z9T156fMjuCpNQCbQgLE2MxO4MESGWV2BE/nBWCmQGzq+f5fzY7QKzX17KMvTpidwIPRcNjsCB6M9lazI/QqNCnNr/c7def1/T5m2BOv9PuY3px1Rueee+7h/PPP56233mLGjBnU1NRw1113+SObiIiIyP/KWXddffbZZ+Tm5jJy5Ej+7d/+jc2bN7u3fYuIiMjANuBPRj516hT19fWEhoby8ccfEx4ezscff+yPbCIiIiL/K2d9dHX33Xezf/9+Fi9ezO23384XX3zBggUL/JHt7N6vNTuBB8u0H5sdoXeBuJgsPOLs7/EzywUXmx3BkzXs7O/xM0vMaLMj9Mr41Gl2BE9hgffnnEGRZifwYLnkMrMjePr8uNkJAsNA317+Za+qzs7OgFiALCIiItJXZ310VVNTww033MBPfvIToKfTeFVVlc+DiYiISAAY6C0g8vPz2bhxI9HR0QAsXLiQxx9/3OfBREREJAAM9EInNDSUiy66yL1K+uKLL/b7imkRERGRf8ZZC51Ro0bx6KOPcvz4cV555RXuvfdevv3tb/dpcKfTSXJyMkVFRQDU1dWxYMECMjIyWLVqFZ2dnQAUFxczd+5c0tLSKC8vB3p2ey1dupT58+eTkZHB4cOBd5iUiIjIgDfQZ3T++7//m/DwcCZMmMBf//pXZs6cyZo1a846cEtLC3a73b2YGSAvL4+srCyKioqw2WyUlZXR1NTEhg0b2Lx5Mxs3buSZZ56hra2NP/3pT1xwwQVs2bKF22+/nd/97nf/q/+jIiIi8s1z1kLnySef5MILL6SpqYmPPvqItrY2WlrO3uYgPDycwsJCYmJi3NcOHTpEXFwcAImJiVRXV1NfX8/YsWMZNGgQgwYNYvz48ezbt4833niD6667DoBrrrmGPXv2/LP/H0VEROSfFRLS/y9/xj/bG4YPH056ejpPPfUUd999N1u3biU5OZkVK1bQ0NDg9XNWq5WIiNPPj4iNjXWfqlxVVYXL5WL06NE4nU6OHTtGc3Mz77zzDk1NTbhcLoYOHQr0rBMKCQmhoyPwev6IiIgMaEH+6Oqs5+gcPnyYV155hZ07d3LJJZdw++23M336dPbs2cOvfvUriouL+3yznJwc1qxZQ2lpKVdffTWGYTBkyBCWLVvG4sWLiY6O5oorrsAwDL7ea9QwDC2CFhERkXNy1kJn6dKlzJ49m6effpohQ4a4r//whz9k6tSp53Qzm82Gw+EAemZ0vpwRSklJISUlBYD77ruPESNGMHz4cBobGxk/fjynTp3CMAzCwgLvhFgREZEBLcgnGc766Or3v/89CxYsOK3I+dIvf/nLc7pZfn4+FRUVAJSWljJjxgw6OzvJzMykvb2dxsZGDhw4wIQJE5g6dSrbt28HYPfu3cTHx5/TvURERETOOqPzz6qtrSU3N5f6+nqsVivl5eVkZ2djt9txOBzEx8eTlJQEwKxZs0hNTSUiIoIHH3wQq9XK9ddfz+uvv878+fMJDw/n4Ycf9lVUERER8SbIZ3QsxtcXwwSRrv/7K7MjeFBTz3MQiE09LxxmdgRPAdjUM2AF4tdZIDb1bG82O4GnU+1mJ/BgBGhTz5C46X69X+f9P+v3Ma1rf9/vY3rj3z1eIiIiIn7ks0dXIiIiMgAE4hOBc6AZHRERERmwgnpGxzJzttkRPHUH4BoBgLBwsxN4sFw03OwInvx8YmfQCsD1FAC0fmF2Ak/nDzE7gae2s59u72/dB94yO4KnAPzeBMDPa3Q0oyMiIiISoIJ6RkdERER8LMhndFToiIiIiHdB/kg/uNOLiIiInIFPCx2n00lycjJFRUUA1NXVsWDBAjIyMli1ahWdnZ0AFBcXM3fuXNLS0igvL3d//q233iIhIYHdu3f7MqaIiIh4E+Tdy31W6LS0tGC320lISHBfy8vLIysri6KiImw2G2VlZTQ1NbFhwwY2b97Mxo0beeaZZ2hra+Nvf/sbzzzzDD/4wQ98FVFEREQGOJ8VOuHh4RQWFhITE+O+dujQIeLi4gBITEykurqa+vp6xo4dy6BBgxg0aBDjx49n3759REdH8/jjjzN48GBfRRQREZGz0YxO76xWKxERp/d4iY2NpbKyEoCqqipcLhejR4/G6XRy7Ngxmpubeeedd2hqaiIyMpLQ0FBfxRMREZG+CPJCx6+7rnJyclizZg2lpaVcffXVGIbBkCFDWLZsGYsXLyY6OporrriCIO4zKiIiIgHEr4WOzWbD4XAAPTM6DQ0NAKSkpJCSkgLAfffdx4gRI/wZS0RERLywaHt53+Xn51NRUQFAaWkpM2bMoLOzk8zMTNrb22lsbOTAgQNMmDDBn7FERERkgPLZjE5tbS25ubnU19djtVopLy8nOzsbu92Ow+EgPj6epKQkAGbNmkVqaioRERE8+OCDWK1WKioqWL9+PR999BHvvfcemzZtYsOGDb6KKyIiIr0J8pORLUYQL4jp3veq2RE8qalnn6mpZxBTU8++C8imns1mJ/Cgpp59FzrrNr/er+v/+3m/jxm62n8TF/pWFxERkQFLva5ERETEuyB/dBXUhY7lgovNjuDBaD5pdoTeWcPMTuApAP/lMf7+gdkRPIRcdb3ZETx07XrO7Ai9CvlOvNkRPJ1qMzuBp/CIs7/Hz0J/eqfZETx9dtTsBNIPgrrQERERER8L8rWLwZ1eRERE5Aw0oyMiIiLeBeAyg3OhQkdERES8C/JCR4+uREREZMDyaaHjdDpJTk6mqKgIgLq6OhYsWEBGRgarVq2is7MTgOLiYubOnUtaWhrl5eUAdHZ2kpOTQ3p6Oj/72c94++23fRlVREREehPk3ct9Vui0tLRgt9tJSEhwX8vLyyMrK4uioiJsNhtlZWU0NTWxYcMGNm/ezMaNG3nmmWdoa2vjD3/4A5GRkWzevJnf/OY3PPzww76KKiIiIgOUzwqd8PBwCgsLiYmJcV87dOgQcXFxACQmJlJdXU19fT1jx45l0KBBDBo0iPHjx7Nv3z5uuOEGVqxYAcDQoUM5ceKEr6KKiIiINyEh/f/yZ3xfDWy1WomIOP1QqtjYWCorKwGoqqrC5XIxevRonE4nx44do7m5mXfeeYempibCwsIYNGgQABs3buQnP/mJr6KKiIiIN0H+6Mqvu65ycnJYs2YNpaWlXH311RiGwZAhQ1i2bBmLFy8mOjqaK664gq/2GX3++ed57733ePLJJ/0ZVURERAYAvxY6NpsNh8MB9MzoNDQ0AJCSkkJKSgoA9913HyNGjADghRde4C9/+Qv/8R//QVhYALYwEBERGei0vbzv8vPzqaioAKC0tJQZM2bQ2dlJZmYm7e3tNDY2cuDAASZMmMDhw4cpLi7m8ccfdz/CEhERETkXPpvRqa2tJTc3l/r6eqxWK+Xl5WRnZ2O323E4HMTHx5OUlATArFmzSE1NJSIiggcffBCr1coLL7zAiRMnyMrKco+5fv16wsPDfRVZREREvi7Ie11ZjK8uiAkyxsd/NTuCB3Uv77uA7D5f/6HZETyoe3nfqXt5H4UE3qH4ltHfNTuCp0DtXn7hcL/ermvd3f0+Zui9j/b7mN4Ed5kmIiIicgaBV9aLiIhI4AjyxchBXehYLow5+5v8zHLBMLMj9Mpo/cLsCB4sg843O4IHyxXfMzuCB+PoR2ZH8BAyKcnsCL2yBOJagsgosxN4sgTgr1PT381O4CkAH/HJudPvooiIiHgX5DM6AVjWi4iIiPQPzeiIiIiId4H4SPgcqNARERER7/Toyjun00lycjJFRUUA1NXVsWDBAjIyMli1ahWdnZ0AFBcXM3fuXNLS0igvLwegqamJX/ziF2RmZpKWlsa+fft8GVVEREQGIJ/N6LS0tGC320lISHBfy8vLIysri2nTplFQUEBZWRlTpkxhw4YN/PGPfwTglltuYdq0aWzbto3Zs2fz05/+lLfeeotHH32UDRs2+CquiIiI9MZPMzpr165lz549dHZ2cscddzBx4kTuv/9+urq6iI6O5re//S3h4eFs27aNjRs3EhISQmpqKvPmzTvjuD4rdMLDwyksLKSwsNB97dChQ8TFxQGQmJjI5s2bueyyyxg7dqy7n9X48ePZt28ft956q/tzR44cYfhw/54EKSIiIv7x5ptv8sEHH7B161aOHz/OjTfeSEJCAunp6aSkpLB27VpKSkqYM2cOBQUFlJSUEBYWxpw5c0hOTmbIkCFex/bZoyur1UpERMRp12JjY6msrAR6upe7XC5Gjx6N0+nk2LFjNDc3884779DU1ARAY2Mjc+fO5YknnuCee+7xVVQRERHxxhLS/6+vueqqq3j00Z62EBdeeCGtra3U1NQwc+ZMAGbOnMkbb7zBvn37mDhxIlFRUURERDB58mT27t17xvh+XUqdk5NDWVkZCxcuxDAMDMNgyJAhLFu2jMWLF7N8+XKuuOIKvmy/FR0dzYsvvsiKFStYsWKFP6OKiIgIQIil/19fExoaynnnnQfACy+8wLXXXktra6u7kXd0dDSNjY24XC6GDh3q/tywYcNobGw8c/x+/KU4K5vNhsPh4LnnnmPSpEmMGDECgJSUFIqLi3nssccwDIMRI0bw1ltv8dlnnwEwbdo03nvvPX9GFRERET/btWsXJSUlrF69GstX1gZ9OQHy9T7khmGc9r7e+LXQyc/Pp6KiAoDS0lJmzJhBZ2cnmZmZtLe309jYyIEDB5gwYQI7duzgpZdeAuD999/HZrP5M6qIiIiAXx5dQc+SlieffJLCwkKioqKIjIykra0NgKNHjxITE8Pw4cNxuVzuzzQ0NBAdHX3G+D5bjFxbW0tubi719fVYrVbKy8vJzs7GbrfjcDiIj48nKSkJgFmzZpGamkpERAQPPvggVqvV/Shr586ddHR0sGbNGl9FFRERERN9/vnnrF27lmeffda9sHjKlCmUl5cze/ZsduzYQWJiIpMmTWLVqlWcPHmS0NBQ9u7dywMPPHDGsS3G1+eBgsmxT81O4MnoNjtBrwKyqWcgNjsMwBNAjY5WsyN4CtBmhwHZ1DMQG2gGYqbuTrMTeArQP+dcdIlfb9f11Mp+HzM06zen/Xjr1q089thjjBkzxn3t4YcfZtWqVbS3t3PppZfy0EMPERYWxvbt21m/fj0Wi4WMjAxuuOGGM95LhU5/U6HTZyp0+kaFTt+p0OmjQMykQqfv/F3oPP1v/T5m6C/s/T6mNwH4p11ERESkfwRouSoiIiIBIch7XQV3oTP0UrMTeDA+/qvZEXplGRp4u9aMtmazI3iwDDrf7AgeLOddaHYET4H4mCFQBeDiAONUu9kRPFisYWZH8BSgSxHk3AR3oSMiIiK+FYhrus5BcKcXEREROQPN6IiIiIh3WqMjIiIiA1YgHttwDnya3ul0kpycTFFREQB1dXUsWLCAjIwMVq1aRWdnz4LG4uJi5s6dS1paGuXl5aeN4XK5uOqqq6ipqfFlVBERERmAfFbotLS0YLfbSUhIcF/Ly8sjKyuLoqIibDYbZWVlNDU1sWHDBjZv3szGjRt55pln3L0tANauXcuoUaN8FVNERETOxGLp/5cf+azQCQ8Pp7CwkJiYGPe1Q4cOERcXB0BiYiLV1dXU19czduxYBg0axKBBgxg/fjz79u0D4I033uD8888nNjbWVzFFRERkAPNZoWO1WomIiDjtWmxsLJWVlUBPl1KXy8Xo0aNxOp0cO3aM5uZm3nnnHZqamujo6KCgoIB7773XVxFFRETkbPzUvdxX/LoYOScnhzVr1lBaWsrVV1+NYRgMGTKEZcuWsXjxYqKjo7niiiswDIOnnnqKm2++mQsuuMCfEUVEROSrQrTrqs9sNhsOhwPomdFpaGgAICUlhZSUFADuu+8+RowYwaZNm+ju7ub555/nb3/7G++++y6PPvoo3/72t/0ZWURERIKYXwud/Px84uLiSEpKorS0lNmzZ9PZ2cmtt97K008/zcmTJzlw4AATJkyguLjY/bnly5dz4403qsgRERHxtyA/GdlnhU5tbS25ubnU19djtVopLy8nOzsbu92Ow+EgPj6epKQkAGbNmkVqaioRERE8+OCDWK063kdERET+9yyGYQRgy7ngpaaefaemnn0UGoCFv5p69l0AfsOqqWcfBep/Hv3c0Lpry9p+HzN0/v39PqY3AfgNKiIiIgEjyB9dBXd6ERERkTMI7hmdzxrMTuDBEnWx2RF613nK7AQejE8/MjuCB8v3ks2O4KH7zT+aHcGDZehwsyP0ymj93OwIHozGerMjeLKGm53AQ2hSmtkRPHQVLDM7Qq9Cl/zWvzcM8u3lmtERERGRASu4Z3RERETEt/zcm6q/qdARERER77QYWURERCQwaUZHREREvNNiZO+cTifJyckUFRUBUFdXx4IFC8jIyGDVqlV0dvYcOlZcXMzcuXNJS0ujvLwcgPLycq677joyMzPJzMzkiSee8GVUERERGYB8NqPT0tKC3W4nISHBfS0vL4+srCymTZtGQUEBZWVlTJkyhQ0bNvDHP/Zsob3llluYNm0aLS0tLFiwgEWLFvkqooiIiJyN1uj0Ljw8nMLCQmJiYtzXDh06RFxcHACJiYlUV1dTX1/P2LFjGTRoEIMGDWL8+PHs27eP5ubAaw8gIiIiwcVnhY7VaiUiIuK0a7GxsVRWVgJQVVWFy+Vi9OjROJ1Ojh07RnNzM++88w5NTU20tLSwc+dOfv7zn3Prrbdy8OBBX0UVERERbyyW/n/5kV8XI+fk5LBmzRpKS0u5+uqrMQyDIUOGsGzZMhYvXkx0dDRXXHEFhmHwwx/+kLi4OH74wx/y9ttvs2zZMvfjLREREfGTIH905ddCx2az4XA4gJ4ZnYaGnhYOKSkppKSkAHDfffcxYsQI9yMugMmTJ3Ps2DG6uroIDQ31Z2QREREJYn4t0/Lz86moqACgtLSUGTNm0NnZSWZmJu3t7TQ2NnLgwAEmTJhAQUGBeweW0+lk6NChKnJERET8LcTS/y8/8tmMTm1tLbm5udTX12O1WikvLyc7Oxu73Y7D4SA+Pp6kpCQAZs2aRWpqKhERETz44INYrVZmz57NihUr2LRpE52dnfzmN7/xVVQREREZoCyGYRhmh/inBWD3ck61m52gdwHYq6T7b4G3wDxE3cv7RN3L+07dy/tG3cv7zt/dy7v+5Oj3MUN/cke/j+mNTkYWERER7wLwL8rnIriXUouIiIicQVDP6HR/sMfsCB6Mz4+bHaF33V1mJ/C077/MTuChOwB7uhgnm8yO4CFQH11ZIqPMjuDBCAm8TRSWiPPNjuCh+93dZkfwYLl6utkRAkNIcM+JBHd6ERERkTMI6hkdERER8bEgX6OjQkdERES8C/KTkYM7vYiIiMgZ+LTQcTqdJCcnU1RUBEBdXR0LFiwgIyODVatW0dnZCUBxcTFz584lLS3NfRoywPr165k9ezZz585l//79vowqIiIivVFTz961tLRgt9tJSEhwX8vLyyMrK4tp06ZRUFBAWVkZU6ZMYcOGDe6GnbfccgvTpk3j8OHD/PnPf+bFF1/k/fff59VXX2XixIm+iisiIiIDkM8KnfDwcAoLCyksLHRfO3TokLtZZ2JiIps3b+ayyy5j7NixDBo0CIDx48ezb98+9u3bR0pKClarle9+97t897vf9VVUERER8Ubby3tntVqJiIg47VpsbCyVlZVAT/dyl8vF6NGjcTqdHDt2jObmZt555x2ampqor6/n2LFjLFmyhFtuuYWDBwOvXYCIiIgENr+WaTk5OZSVlbFw4UIMw8AwDIYMGcKyZctYvHgxy5cv54orrnD/XGtrK48//ji//OUvWblypT+jioiICGiNzrmw2Ww4HD3Nwaqqqmho6GnKmZKSQkpKCgD33XcfI0aMYNiwYYwdOxaLxcLkyZOprw/AxngiIiIDnbaX911+fj4VFRUAlJaWMmPGDDo7O8nMzKS9vZ3GxkYOHDjAhAkTuPbaa6mqqgJ6dmvZbDZ/RhUREZEBwGczOrW1teTm5lJfX4/VaqW8vJzs7GzsdjsOh4P4+HiSkpIAmDVrFqmpqURERPDggw9itVq58sorqaqqIjMzk46ODlavXu2rqCIiIuJNkJ+MbDEMwzA7xD+r++0ysyN4UFPPcxCATT0tM2ebHcGDcfSw2RE8hFz+L2ZHCBrdf//A7AgeLOddYHYET+cNNjuBp/ZWsxP0KuSq6/16v67dm/t9zNDp6f0+pjdqASEiIiLeBfkaHRU6IiIi4l1IcD+6Cu4yTUREROQMgnpGJ2RyitkRPHStXWx2hN61Bt6zZuPzz82O4MF44RmzI3gwGpvMjuBhyVPVZkfo1ZPGSbMjeHr3dbMTeDACce3JZy6zE3iwXDLa7AiBIcgfXQV3ehEREZEzCOoZHREREfGxIN9erkJHREREvNOjKxEREZHA5NMZHafTyeLFi1m0aBEZGRnU1dWxevVqLBYLl19+OWvWrMFqtVJcXMwLL7xAWFgYt956Kz/60Y944okneP31nkV83d3duFwuysvLfRlXREREvsaiR1e9a2lpwW63k5CQ4L6Wl5dHVlYW06ZNo6CggLKyMqZMmcKGDRv44x//CMAtt9zCtGnTuPPOO7nzzjsBeOmll2hqCrydJyIiIhLYfPboKjw8nMLCQmJiYtzXDh06RFxcHACJiYlUV1dTX1/P2LFjGTRoEIMGDWL8+PHs27fP/ZnOzk62bNlCRkaGr6KKiIiIN5aQ/n/5kc/uZrVaiYiIOO1abGwslZWVAFRVVeFyuRg9ejROp5Njx47R3NzMO++8c9rszY4dO7jmmms8xhIRERE5G7+WVTk5OZSVlbFw4UIMw8AwDIYMGcKyZctYvHgxy5cv54orruCrfUZffPFFbrrpJn/GFBERkS8F+YyOX7eX22w2HA4H0DOj09DQAEBKSgopKT2nHN93332MGDEC6Fnnc/ToUUaOHOnPmCIiIvIl9brqu/z8fCoqKgAoLS1lxowZdHZ2kpmZSXt7O42NjRw4cIAJEyYAcPDgQcaMGePPiCIiIjKA+GxGp7a2ltzcXOrr67FarZSXl5OdnY3dbsfhcBAfH09SUhIAs2bNIjU1lYiICB588EGs1p5YjY2NDB061FcRRURE5GyC/MBAi/HVBTHyv6amnn0XiE09CcBF74HY1POXaurZZ10lj5gdwdP5g81O4Ckk1OwEHgK1qWfIpJl+vV/3f73S72OGXHV9v4/pjVpAiIiIiHc6MFBEREQGrCB/dBXc6UVERETOIKjX6BiNfzM7Qi8C85ez++BbZkfwEJp4s9kRPHT+W6bZETxYZqSYHcFTV6fZCXrXecrsBJ6sYWYn8BRxntkJPFgio8yO4MFyQWBuhrF8+yq/3q97745+HzPk+//a72N6vZff7iQiIiLiZ1qjIyIiIt4F+RodFToiIiLinU5GFhEREQlMPi10nE4nycnJFBUVAVBXV8eCBQvIyMhg1apVdHb2LGgsLi5m7ty5pKWlUV5eDsDRo0e57bbbyMzMZMGCBdTW1voyqoiIiPQmyJt6+uxuLS0t2O12EhIS3Nfy8vLIysqiqKgIm81GWVkZTU1NbNiwgc2bN7Nx40aeeeYZ2traePbZZ7nuuuvYtGkTS5cuZd26db6KKiIiIgOUzwqd8PBwCgsLiYmJcV87dOgQcXFxACQmJlJdXU19fT1jx45l0KBBDBo0iPHjx7Nv3z4uuugiTpw4AcDJkye56KKLfBVVREREvLFY+v/lRz5bjGy1Wt3NOb8UGxtLZWUlc+bMoaqqCpfLxejRo3E6nRw7doxBgwbxzjvvcPXVV7No0SLmzZvHyy+/zBdffMGWLVt8FVVEREQGKL8+KMvJyaGsrIyFCxdiGAaGYTBkyBC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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "heatmap_prep = survey_data.pivot_table(index='year', columns='month', \n", + " values=\"ID\", aggfunc='count')\n", + "fig, ax = plt.subplots(figsize=(10, 8))\n", + "ax = sns.heatmap(heatmap_prep, cmap='Reds')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Remark that we started from a `tidy` data format (also called *long* format) and converted to *short* format with in the row index the years, in the column the months and the counts for each of these year/month combinations as values." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Make a summary table with the number of records of each of the species in each of the plots (called `verbatimLocality`)? Each of the species `name`s is a row index and each of the `verbatimLocality` plots is a column name.\n", + "- Use the Seaborn documentation to make a heatmap.\n", + "\n", + "
Hints\n", + "\n", + "- Make sure to pass the correct columns to respectively the `index`, `columns`, `values` and `aggfunc` parameters of the `pivot_table` function. You can use the `ID` to count the number of observations for each name/locality combination (when counting rows, the exact column doesn't matter).\n", + "\n", + "
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Calamospiza melanocorysNaN1.01.0NaNNaNNaNNaN1.01.02.0...1.0NaNNaN1.0NaNNaN1.0NaN1.0NaN
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" + ], + "text/plain": [ + "verbatimLocality 1 2 3 4 5 6 7 8 9 \\\n", + "name \n", + "Ammodramus savannarum NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", + "Ammospermophilus harrisi 5.0 6.0 2.0 2.0 3.0 6.0 21.0 10.0 14.0 \n", + "Amphispiza bilineata 5.0 10.0 10.0 3.0 2.0 14.0 18.0 6.0 8.0 \n", + "Baiomys taylori 1.0 1.0 18.0 NaN 4.0 NaN NaN NaN NaN \n", + "Calamospiza melanocorys NaN 1.0 1.0 NaN NaN NaN NaN 1.0 1.0 \n", + "\n", + "verbatimLocality 10 ... 15 16 17 18 19 20 21 \\\n", + "name ... \n", + "Ammodramus savannarum NaN ... NaN NaN NaN NaN 1.0 NaN NaN \n", + "Ammospermophilus harrisi 1.0 ... 70.0 8.0 27.0 12.0 9.0 28.0 16.0 \n", + "Amphispiza bilineata 6.0 ... 8.0 8.0 3.0 8.0 11.0 22.0 6.0 \n", + "Baiomys taylori NaN ... NaN NaN NaN 2.0 15.0 1.0 3.0 \n", + "Calamospiza melanocorys 2.0 ... 1.0 NaN NaN 1.0 NaN NaN 1.0 \n", + "\n", + "verbatimLocality 22 23 24 \n", + "name \n", + "Ammodramus savannarum NaN NaN NaN \n", + "Ammospermophilus harrisi 4.0 19.0 17.0 \n", + "Amphispiza bilineata 10.0 14.0 14.0 \n", + "Baiomys taylori NaN NaN NaN \n", + "Calamospiza melanocorys NaN 1.0 NaN \n", + "\n", + "[5 rows x 24 columns]" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "species_per_plot = survey_data.reset_index().pivot_table(index=\"name\", \n", + " columns=\"verbatimLocality\", \n", + " values=\"ID\", \n", + " aggfunc='count')\n", + "species_per_plot.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,8))\n", + "sns.heatmap(species_per_plot, ax=ax, cmap='Greens')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Make a plot visualizing the evolution of the number of observations for each of the individual __years__ (i.e. annual counts) using the `resample` method.\n", + "\n", + "
Hints\n", + "\n", + "- You want to `resample` the data using the `eventDate` column to create annual counts. If the index is not a datetime-index, you can use the `on=` keyword to specify which datetime column to use.\n", + "- `resample` needs an aggregation function on how to combine the values within a single 'group' (in this case data within a year). In this example, we want to know the `size` of each group, i.e. the number of records within each year.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "survey_data.resample('A', on='eventDate').size().plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (OPTIONAL SECTION) Evolution of species during monitoring period" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "*In this section, all plots can be made with the embedded Pandas plot function, unless specificly asked*" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Plot using Pandas `plot` function the number of records for `Dipodomys merriami` for each month of the year (January (1) -> December (12)), aggregated over all years.\n", + "\n", + "
Hints\n", + "\n", + "- _...for each month of..._ requires `groupby`. \n", + "- `resample` is not useful here, as we do not want to change the time-interval, but look at month of the year (over all years)\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "merriami = survey_data[survey_data[\"name\"] == \"Dipodomys merriami\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Month of the year')" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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L5eXlIS4uDmPGjMGwYcMQExOj13mIiOj96HwnP2fOHFSvXh1t2rSBIAi4ePEiYmJi9BoB2KRJE0ycOBFdu3bF3bt3MWrUKJw4cULvmbFERB/KXCZRmc1kqEePHmHp0qXaz318fDB8+HC9FnNxcYGLiwsAoEGDBqhZsybS0tJQr149vc5HRPShzGVbZ7OZDFVUVIS0tDTt548ePUJxcbFeRezduxfbtm0DAKSnp+Pp06dwcHDQ61xERKSbznfy06dPx8iRI6FUKlFSUgKlUon58+frtVj37t3xj3/8A8ePH0dhYSFCQkJ4qYaIyIgUQll7CZfh2bNnUCgUqFatmlELiouLM9jdPB8bOU8IYu/sXW6McbmmrOws9538rFmz3nnCxYsXV7wqIiIyqnJD/q+//sLz58/h5eWFzp07o3LlymLWRUREBlBuyEdFReH+/fs4fPgwVq1ahdq1a8Pb2xtffPEFbGxsxKyRiIj09M67a5ycnDB+/Hjs3bsX06ZNQ2JiInr16oVx48aJVR8REVWAzrtrBEFATEwMDh06hNjYWHh5eaFnz55i1EZERBVUbshfu3YNhw4dwoULF9CiRQv07NkT3333HdRqnb8XiIjITJSb2IMHD4aTkxNatGgBQRBw9OhRHD16VPt13l1DRGT+yg15Tn4iIvr4lRvydevWFbOOUjgZSq7YuzzJq3exJ1Pp3LvGGAoKCtC1a1dERUWZYnkiItkwScivXbsWn3zyiSmWJiKSFdFDPjExEQkJCejSpYvYSxMRyY7oIR8WFoagoCCxlyUikiVRb3rfv38/WrVqxSEhRCRbr6ZBmc1kKEM6c+YMHjx4gDNnzuDRo0ewtLRE7dq14enpKWYZREQm82p7YbEmQ4ka8itWrNB+vGrVKtStW5cBT0RkRCa5u4aIiMRhso1oJk+eXO7XxH5YwFxwSg57lxs59y4WvpMnIpIwhjwRkYQx5ImIJIwhT0QkYQx5IiIJY8gTEUkYQ56ISMIY8kREEmaWU7k5GUqu2Ls8sXfAeA+Bihry+fn5CAoKwtOnT/HixQtMmDABX3zxhZglEBHJiqghf/r0abi6uuLrr79GcnIyvvrqK4Y8EZERiRryvXv31n6cmpoKBwcHMZcnIpIdk1yTHzJkCB49eoR169aZYnkiItkwScjv2rUL8fHx+Oc//4kDBw5AoVCYogwiIrNhrClRoob89evXYWdnhzp16qBp06bQaDTIyMiAnZ2dmGUQEZmdim65XN5kKFHvk7906RI2b94MAHjy5Any8vJga2srZglERLIiasgPGTIEGRkZGDp0KL755ht8++23UCr5PBYRkbGIernGysoKy5YtE3NJIiJZM8snXjn+T37YO3uXG7F657USIiIJY8gTEUkYQ56ISMIY8kREEsaQJyKSMIY8EZGEMeSJiCSMIU9EJGGiPwwVHh6OuLg4FBcXY+zYsejRo8dbr+H4P7li7/Jk2N7l+jBleUQN+ZiYGNy+fRu7d+9GZmYm+vfvX2bIExGRYYga8u3atUOLFi0AANWrV0d+fj40Gg1UKpWYZRARyYao1+RVKhWqVKkCANizZw86derEgCciMiKTbFB28uRJ7N27V7u3PBGRoRhrwpKhFRQUiFKr6CF/7tw5rFu3Dhs3bkTVqlXFXp6IJO5j2dXS0LtQljcZStSQz8nJQXh4OH766Sd88sknYi5NRCRLoob8kSNHkJmZiWnTpmmPhYWFwdHRUcwyiIhkQ9SQ9/Pzg5+fn5hLEhHJGidDmRFOyWHvciPn3sXCbQ2IiCSMIU9EJGEMeSIiCWPIExFJGEOeiEjCGPJERBLGkCcikjCGPBGRhJnlw1CcDCVX7F3K5PqQo6mZ5J38rVu30K1bN2zfvt0UyxMRyYboIZ+Xl4fQ0FB4eHiIvTQRkeyIHvKWlpbYsGEDatWqJfbSRESyI/o1ebVaDbXaLP8UQERGVNYUJLGmI5kjyU6GIiJ5Kmu3STnvQinWZCjeQklEJGEMeSIiCRP9cs3169cRFhaG5ORkqNVqHD9+HKtWreLMVyIiIxA95F1dXREZGfnO18j1oQlen2TvRIbGyzVERBLGkCcikjCGPBGRhCkEQRBMXcTryrvXk4iI3s3d3f2tY2YX8kREZDi8XENEJGEMeSIiCTOrvWsWLVqEq1evQqFQYPbs2WjRooWpSzK48PBwxMXFobi4GGPHjoWbmxtmzpwJjUYDe3t7LF26FJaWljhw4AC2bt0KpVIJPz8/DBw40NSlG0RBQQF8fHwwceJEeHh4yKb3AwcOYOPGjVCr1Zg6dSoaNWoki95zc3MRGBiIZ8+eoaioCBMnTkTDhg0l3futW7cwYcIEjBw5Ev7+/khNTX3vfouKihAUFISUlBSoVCosXrwY9erVq1hBgpmIjY0VvvnmG0EQBOH27dvCwIEDTVyR4UVHRwtjxowRBEEQMjIyhM6dOwtBQUHCkSNHBEEQhLCwMGHHjh1Cbm6u0KNHDyE7O1vIz88XvL29hczMTBNWbjjff/+9MGDAAGHfvn2y6T0jI0Po0aOHkJOTI6SlpQnBwcGy6T0yMlKIiIgQBEEQHj16JHh7e0u699zcXMHf318IDg4WIiMjBUEQPqjfqKgoISQkRBAEQThz5owwderUCtdkNpdroqOj0a1bNwBAw4YNkZ2djefPn5u4KsNq164dVq5cCQCoXr068vPzERsbi65duwIAunbtiujoaFy9ehVubm6oWrUqrKys0LZtW1y+fNmUpRtEYmIiEhIS0KVLFwCQTe/R0dHw8PCAjY0NatWqhdDQUNn0bmtri6ysLABAdnY2bG1tJd17WfMyPqTf6OhodO/eHQDg5eVlkLsNzSbknzx5AltbW+3ndnZ2SE9PN2FFhqdSqVClShUAwJ49e9CpUyfk5+fD0tISAGBvb4/09HQ8efIENWrU0H5fzZo1JfGzCAsLQ1BQkPZzufT+8OFDCIKAadOmYejQoYiOjpZN7z4+PkhJSUH37t3h7++PwMBASfeuVqthZWVV6tiH9Pv6cZVKBaVSicLCworVVKHvNiDhjTs5BUGAQqEwUTXGdfLkSezduxebN2+Gt7e39virn4EUfxb79+9Hq1atSl1ffL0nKfcOAGlpaVi9ejVSUlIwfPhw2fT+888/w9HREZs2bcLNmzcxZ84c2fT+yof0a4yfg9m8k3dwcMCTJ0+0nz9+/Bg1a9Y0YUXGce7cOaxbtw4bNmxA1apVUblyZRQUFAB4GQS1atUq82dhb29vqpIN4syZMzh16hQGDx6MPXv24IcffpBN73Z2dmjdujXUajWcnJxgbW0tm94vX74MLy8vAECTJk2QlpYmm95f+ZB+HRwctP+CKSoqgiAIsLCwqND6ZhPyHTp0wPHjxwEAN27cQK1atWBjY2PiqgwrJycH4eHhWL9+vXZrZU9PT23fJ06cQMeOHdGyZUv88ccfyM7ORm5uLi5fvoy2bduasPKKW7FiBfbt24d///vfGDRoECZMmCCb3r28vBATE4OSkhJkZGQgLy9PNr07Ozvj6tWrAIDk5GRYW1vLpvdXPqTfDh064NixYwCA06dPo3379hVe36yeeI2IiMClS5egUCgwb948NGnSxNQlGdTu3buxatUqNGjQQHtsyZIlCA4OxosXL+Do6IjFixfDwsICx44dw6ZNm6BQKODv748+ffqYsHLDWrVqFerWrQsvLy8EBgbKovddu3bh8OHDyM/Px/jx4+Hm5iaL3nNzczF79mw8ffoUxcXFmDp1KlxcXCTb+5vzMhwcHBAREYGgoKD36lej0SA4OBhJSUmwtLTEkiVLUKdOnQrVZFYhT0REhmU2l2uIiMjwGPJERBLGkCcikjCGPBGRhDHkiYgkjCFPH42HDx9iwIABRjl3RkYGfHx8sGzZMqOcn8hUGPJEeLl5mrOzM2bMmGHqUogMivfJk1FFRUUhLi4OGRkZuHv3LkaPHo1Bgwbhb3/7Gw4ePAhra2uEhYXhs88+AwD8/vvvyMzMxO3btzF9+nQcOnQIiYmJiIiIgJ2dHSZMmIDmzZvjzp07aNy4MebPn4+0tDQEBwejsLAQKpUKCxYsgKOjI3r06IFmzZqhQ4cOGDRokLamI0eO4KeffoJKpULz5s0RHByMAQMGICUlBYMGDSoV9LGxsVi+fLn2wZbFixdDoVAgKCgIycnJqFSpEsLDw1GjRo23jv3222+4ffs2AgMDkZubC19fX/zyyy/o0aMHOnXqBDs7O9y7dw8WFhbIysrCihUrMHfuXDx48ADFxcWYMmUKPDw8EBAQAE9PT8TExCAzMxPr1q2Do6MjFi5ciGvXrkGpVOK7775Do0aNsHz5cly6dAkajQb+/v748ssvcf78eaxYsQJWVlaws7NDREREhR+Vp4+H2WxQRtJ169Yt7Nq1C0lJSfj73/9eKnDflJSUhJ07d2LPnj1Yv3499u/fj6ioKBw6dAgjRoxAYmIi1q9fj9q1a2PgwIH466+/sHXrVowaNQqenp44e/YsfvjhByxYsAAPHjzAmjVrtL9AgJdPYC5fvhz79++HtbU1xo0bh5iYGAQGBmLHjh1vvZOfN28etmzZgjp16mD+/Pk4ePAgSkpKULNmTSxbtgyHDx/GqVOnYGFh8daxN3cjfKW4uBidOnVCp06dEBQUhOrVqyM0NBT79++Hvb09Fi1ahIyMDIwYMQIHDx4EANjY2GDr1q2IiIjAiRMn0KhRI6SmpmL37t34/fffceTIEWRnZyM5ORk7duxAYWEh+vfvj27dumH79u0ICgpC27ZtceLECWRlZUlmXxjSjSFPRteqVSuoVCrUrl0bOTk573ytq6srFAoF7O3t0bhxY6hUKtSsWVO7t7iTk5P2MW83NzfcvXsXV65cwd27d7F27VpoNBrtVq2VK1cuFfDAy18izs7OsLa2BgC0adMG8fHxaNas2Vu1ZGVlQaFQaNd7ted3cXExPDw8ALzcShcAQkJC3joWFRVVbp+vTz179fGVK1cQFxen7fXFixfabWZf7eNSu3ZtZGVl4c8//0SbNm0AvJxT0K5dO/z444+4evUqAgICAAAlJSVIT09Hz549MW/ePPj6+sLHx4cBLzMMeTI6tfrd/5sVFRWV+drXP351VfHNbVcVCgUsLCywcuXKUoMaAJR5SeLN7VzftZXrm68tKSmBQqGASqVCSUlJqdeWdez18xYXF5db26uPLSwsMG7cOHz55Zdv1aJSqUrVXNZ6lpaWGDhwIMaOHVvqeL169dCxY0ecPHkS48ePx8qVK+Hi4lJmzyQ9/MMrmYSNjQ3S09Oh0Wi0uxS+j/v37+Px48cQBAF//PEHXFxc0LJlS5w8eRLAyylMry5xlKV+/fq4d++edurYxYsX4erqWuZrq1evDoVCgZSUlFKvdXNzQ0xMDICXOwWuW7euzGM2NjZ4/PgxALzXhJ/X+3j69Cm+//77cl/r5uaG2NhYAC93bf3uu+/QokULnD59GiUlJXjx4gVCQ0MBAGvWrIFarYafnx969+6NxMREnbWQdPCdPJmEv78/xo0bhwYNGqBhw4bv/X1NmjTB8uXLkZCQgNatW6Nhw4aYNGkSZs+ejcOHD0OhUGDx4sXlfn+VKlUwc+ZMjBkzBkqlEu7u7mjbtq02MN8UGhqKGTNmQK1W4//+7//g4+ODkpISXLhwAf7+/lCpVAgPD4etre1bx6ytrbF27VoEBASgc+fOOoc/9OrVCzExMRgyZAg0Gg0mTZpU7mvbtWuHU6dOYejQoQBe/u2gcePGaN++Pfz8/CAIgvZrjo6OGDVqFKpVq4Zq1aph1KhRun7MJCG8u4aISMJ4uYaISMIY8kREEsaQJyKSMIY8EZGEMeSJiCSMIU9EJGEMeSIiCWPIExFJ2P8DS1h1y9NgLLYAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "merriami.groupby(merriami['eventDate'].dt.month).size().plot(kind=\"barh\", ax=ax)\n", + "ax.set_xlabel(\"number of occurrences\")\n", + "ax.set_ylabel(\"Month of the year\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Plot, for the species 'Dipodomys merriami', 'Dipodomys ordii', 'Reithrodontomys megalotis' and 'Chaetodipus baileyi', the monthly number of records as a function of time for the whole monitoring period. Plot each of the individual species in a separate subplot and provide them all with the same y-axis scale\n", + "\n", + "
Hints\n", + "\n", + "- `isin` is useful to select from within a list of elements.\n", + "- `groupby` AND `resample` need to be combined. We do want to change the time-interval to represent data as a function of time (`resample`) and we want to do this _for each name/species_ (`groupby`). The order matters!\n", + "- `unstack` is a Pandas function a bit similar to `pivot`. Check the [unstack documentation](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.unstack.html) as it might be helpful for this exercise.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "subsetspecies = survey_data[survey_data[\"name\"].isin(['Dipodomys merriami', 'Dipodomys ordii',\n", + " 'Reithrodontomys megalotis', 'Chaetodipus baileyi'])]" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "month_evolution = subsetspecies.groupby(\"name\").resample('M', on='eventDate').size()" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "species_evolution = month_evolution.unstack(level=0)\n", + "axs = species_evolution.plot(subplots=True, figsize=(14, 8), sharey=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Recreate the same plot as in the previous exercise using Seaborn `relplot` functon with the `month_evolution` variable.\n", + "\n", + "
Hints\n", + "\n", + "- We want to have the `counts` as a function of `eventDate`, so link these columns to y and x respectively.\n", + "- To create subplots in Seaborn, the usage of _facetting_ (splitting data sets to multiple facets) is used by linking a column name to the `row`/`col` parameter. \n", + "- Using `height` and `widht`, the figure size can be optimized.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "# Given as solution..\n", + "subsetspecies = survey_data[survey_data[\"name\"].isin(['Dipodomys merriami', 'Dipodomys ordii',\n", + " 'Reithrodontomys megalotis', 'Chaetodipus baileyi'])]\n", + "month_evolution = subsetspecies.groupby(\"name\").resample('M', on='eventDate').size().rename(\"counts\")\n", + "month_evolution = month_evolution.reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.relplot(data=month_evolution, x='eventDate', y=\"counts\", \n", + " row=\"name\", kind=\"line\", hue=\"name\", height=2, aspect=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Plot the annual amount of occurrences for each of the 'taxa' as a function of time using Seaborn. Plot each taxa in a separate subplot and do not share the y-axis among the facets.\n", + "\n", + "
Hints\n", + "\n", + "- Combine `resample` and `groupby`!\n", + "- Check out the previous exercise for the plot function.\n", + "- Pass the `sharey=False` to the `facet_kws` argument as a dictionary.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "year_evolution = survey_data.groupby(\"taxa\").resample('A', on='eventDate').size()\n", + "year_evolution.name = \"counts\"\n", + "year_evolution = year_evolution.reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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taxaeventDatecounts
0Bird1980-12-3117
1Bird1981-12-318
2Bird1982-12-3131
3Bird1983-12-3131
4Bird1984-12-3116
\n", + "
" + ], + "text/plain": [ + " taxa eventDate counts\n", + "0 Bird 1980-12-31 17\n", + "1 Bird 1981-12-31 8\n", + "2 Bird 1982-12-31 31\n", + "3 Bird 1983-12-31 31\n", + "4 Bird 1984-12-31 16" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "year_evolution.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.relplot(data=year_evolution, x='eventDate', y=\"counts\", \n", + " col=\"taxa\", col_wrap=2, kind=\"line\", height=2, aspect=5, \n", + " facet_kws={\"sharey\": False})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "The observations where taken by volunteers. You wonder on which day of the week the most observations where done. Calculate for each day of the week (`weekday`) the number of observations and make a barplot.\n", + "\n", + "
Hints\n", + "\n", + "- Did you know the Python standard Library has a module `calendar` which contains names of week days, month names,...?\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": { + "collapsed": false, + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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r1o2YmBj27dtHaGgo//Ef/0GVKlUICQnh7Nmz7N+/H4vFQrdu3ZgwYQI7d+5k7dq1NGzYEMMwaNKkCTdu3GDatGncvHmT3Nxcpk+fjtVqZffu3SxevBiA9957j+7du9OjRw+79ysi4qgeGUb9+/fHarU+dJ+9XbhwgdWrV1O7dm26du1KVlbWQ49NTk4mJiaGmjVr8s477/DNN9/g7OzMli1bMAyDpUuXsmPHDqpVq2ZbnsvIyGDYsGH07NmT2NhY1qxZw4cffsi8efPIy8vDzc2N48ePP3CpUkRESs4jwyg0NBSAmJgYunXrds++3bt326+q/+Pn54eXlxcAderUITs7+6HH1q9fn5o1awIQFBTE66+/TnBwMAMGDMBqteLh4UHt2rWBO/fauzvmqlWrWLduHfn5+VSpUgVnZ2e6du3KoUOH8PLyom3btiW6JFkRJScnm11CicrNza1wPT2KI/XrSL1C+er3kWGUmJhIUlISn3zyCWlpabbt+fn5bNiwgeDgYLsW99NzVoZh2B59Dtzz6HNXV1fb69mzZ5OSksKePXsICQlh/fr1WCyWe8YB+Pjjj/H29mbx4sUkJSWxaNEiAF5++WXWrFlDvXr17N5jRdCsWTOzSyhRycnJFa6nR3Gkfh2pVyh7/cbHxz903yPvTefl5UWVKlUoKCjAarXa/rt58yYLFiwo8UKLw8PDg4yMDODBjd24cYMVK1bQuHFjQkNDqVGjBhaLhezsbLKysigoKCAhIQEAq9WKn58fAAcOHKCgoAC48z/X9PR0EhMTadeuXSl1JiLiuB45M3rqqacYNGgQXbp0wc3NjezsbNuswiwDBw7kt7/9Lfv27Xtg4nt6emK1Whk6dChVqlShdevW1KhRg9DQUEJCQqhXrx5NmjSxjRUeHs7evXsZNWoUu3fvZseOHQwZMoROnTqRk5Nzz0xMRETsw8koRrpMnz6dQ4cOUbduXeBfy2Xbt2+3e4FmMAyD119/ndmzZ9OgQYP79sfHx7M6bbUJlZVNFe3edGVtacPeHKlfR+oVyl6/8fHxBAQEPHBfse5Nd/r0aQ4dOuQQs4S7f9/00ksvPTCIRESk5BUrjPz9/bFardSqVcve9ZjO19fXLnd9EBGRhytWGKWmptKzZ08aNGiAs7NzhV+mK46KtjT1KGVtqi8iFU+xwsisK+dERMQxFOux49WrV2fXrl1s3LiRevXqkZqaStWqVe1dm4iIOIhihVFERATVqlUjKSkJgGvXrjFt2jS7FiYiIo6jWGGUk5PDq6++arvLQd++fcnNzbVrYSIi4jiKFUZFRUX87//+r+3S7q+//pqioiK7FiYiIo6jWBcwzJgxgxkzZnDq1Ck6d+5M06ZNmTNnjr1rExERB1GsMPr2229ZtGiR7Q4MIiIiJalYYWS1Wpk4cSKVK1emd+/eBAUF4ePjY+/aRETEQRTrnFFoaCg7duzg/fffx8XFhRkzZvDKK6/YuzYREXEQxQojuPNohoSEBI4fP05GRob+Il9EREpMsZbpxo4dS0ZGBl26dGHUqFG0bt3a3nWJiIgDKdbMqFu3bri4uHDw4EFat27N0qVLOXz4sL1rExERB1GsMNq/fz8ff/yx7Wq6MWPGsGLFCrsWJiIijqNYYeTi4kLNmjVtf/Rau3Zth3i2kYiIlI5inTPy9fVl2bJlWK1WvvjiC/bv3297dLeIiMiTKlYYzZ07l127dhEQEMDx48fp0aMHffr0sXdtZdr4XePNLqF0nXuyjzvS859E5OcrVhhZLBYGDhzIwIED7V2PiIg4oGL/nZGIiIi9KIxERMR0dgmj4OBgUlNTbe/79OnDoUOHbO8nTZrEN99888gxcnJy6N69e4nXFhUVxfLly0t8XBEReXx2CaMOHTpw9OhR4M5TYXNzc/nb3/5m25+YmEibNm3s8dUiIlIOFesChp+rQ4cOxMTEMGTIEBISEhgwYADx8fEApKSk4OvryzfffMP69etxcXGhefPmREREcOPGDSZPngxAy5YtbeP16tWLESNGEBMTQ35+Phs2bMDd3Z3p06eTmppKYWEhU6ZM4cUXX+TPf/4zUVFRuLq64u/vz8yZM4mNjWXevHn4+vpStWpV6tevT2FhIeHh4aSnp3Pz5k0mT56Mn58fM2bMYPPmzQCsWrUKT09PxowZY4+fSURE/o9dZkbt27e3hc+xY8fo2LEjt2/fts2QWrRowUcffcQnn3xCVFQU//jHP4iPj2fnzp00adKEDRs20LRpU9t4t2/f5he/+AWbN2/G19eXb7/9ll27duHl5cWmTZtYuXIl8+bNA2DdunUsX76cLVu20Lx5c3Jzc3n//fdZvHgxH330EVarFYDr16/TuXNnoqKiWLZsGcuXL6dx48bk5eVx5coVAA4dOkTfvn3t8ROJiMiP2GVmVKNGDdzd3UlPT+fkyZNMnTqVli1bcuLECY4dO8azzz5LWloab7zxBgDZ2dmkpaWRkpJCu3btgDuB9mNt27YFwMfHh+zsbE6cOEF8fDwJCQkA5OXlkZ+fT3BwMJMmTWLAgAEEBwdTuXJlLl++jL+/PwDt2rUjLy+PatWqkZSUxNatW7FYLGRmZgIwYMAA9uzZQ79+/fD09KROnTr2+IkcTnJystklFFtubm65qvdJOVK/jtQrlK9+7RJGcGep7vDhwzg5OVG5cmXbH8wmJSUxatQo4uLiWLdu3T2fSUhIwGK5M1krKiq6Z5+zs7PttWEYuLq6MmHCBIKDg+85bvz48fTv3599+/YxduxYoqKibGPe/SzA7t27uX79Op9++imZmZkMHToUuHPxxeTJk3F3d79vbHl85emRI8nJyeWq3iflSP06Uq9Q9vq9u2L2IHa7tLtDhw5s3bqV559/HoCAgAC++uor6tati7+/PykpKfzwww8A/P73vyc9PZ1GjRpx6tQpAOLi4h45fqtWrThw4AAAP/zwAx988AFFRUUsXboULy8vXn/9dZ5//nnS0tLw9vbm/PnzGIZhu7DCarXi6+uLxWJh//795OfnA1CrVi2qV6/Ozp076dWrlz1+GhER+Qm7hVH79u05ffo0AQEBwJ2bq2ZmZtK+fXvc3d159913efPNNxk5ciSZmZnUrVuXl19+mRMnTjB27Fi+//77R47fp08fPDw8GDlyJBMmTCAgIACLxYKHhwcjRoxg7NixODk50axZM6ZOnUpYWBgTJkywPS69d+/eHDx4kLFjx+Lu7o6Pjw8rV64EICgoCG9vbzw9Pe3184iIyI84GXfXrcQmPDycQYMG8cILLzxwf3x8PKvTVpdyVeVbebo3XVlb2rA3R+rXkXqFstdvfHy8bYLyU7oDw4/k5eUxfPhwPD09HxpEIiJS8ux2AUN5VKlSJbZt22Z2GSIiDkdh9JjK07LTkyprU30RqXi0TCciIqZTGImIiOkURiIiYjqFkYiImE5hJCIiplMYiYiI6RRGIiJiOoWRiIiYTmEkIiKmUxiJiIjpFEYiImI6hZGIiJhOYSQiIqZTGImIiOkURiIiYjo9z+gxjd813uwSSte5//8hjvSMJxEpWZoZiYiI6RRGIiJiOoWRiIiYrsydM1qwYAGnT58mIyODW7du4efnR/Xq1VmxYkWJjH/mzBnmzp3Lpk2bSmQ8ERF5cmUujCIiIgCIjo7m7NmzhIeHm1yRiIjYW7lYpouIiCAmJgaAmJgYW2Bt3ryZkSNH8uqrr7J+/XoAvvvuO0aMGMHo0aN54403yMrK4sqVK4wYMYJx48bx2Wef2cZdv349I0aMYNiwYaxYsYLbt2/Tq1cvcnJyADh27BihoaGl3K2IiOMpF2H0IKmpqezdu5ctW7awefNm/vrXv5KWlkZ0dDSvvPIKmzZtYty4cWRkZPDJJ5/Qt29f1q5di5eX1z3jfPrpp2zbto3o6Ghu3bpFz549OXjwIAAHDx4kODjYjPZERBxKmVumK66kpCQuXrzImDFjAMjJyeHy5cv06NGDWbNmceHCBfr27Uvjxo1JSUnhpZdeAqBDhw4cPnwYgMqVKxMSEoKLiwtWq5XMzExefvllPvzwQ/r378/Ro0cJCwszrcfyJjk52ewSSkRubm6F6aU4HKlfR+oVyle/5SKMnJycbK8LCwsBcHV1pWvXrsyZM+e+47dv325bznv77bcxDAOL5c4ksKioCIDLly+zceNG/vSnP+Hh4WGbATVt2pSrV6+SmJhIkyZNqFSpkr3bqzCaNWtmdgklIjk5ucL0UhyO1K8j9Qplr9/4+PiH7isXy3QeHh5kZGQA/2rml7/8JXFxcdy6dQvDMPjd735Hbm4uUVFRZGZmMmDAAMaOHUtycjKNGjXi1KlTAMTFxQFgtVqpVasWHh4enD59msuXL1NQUABAnz59mDNnDv379zehWxERx1MuZkYDBw7kt7/9Lfv27bOl/NNPP82YMWMYNWoUzs7O9OzZk8qVK+Pn50dYWBhVq1bFzc2N+fPnk5eXx9SpU9m/fz/PPvsscOdf8R4eHowcOZKAgABGjhzJ7Nmz2bhxI3379mX9+vV06NDBzLZFRBxGmQ2jwYMH2163aNGCffv23XfMqFGjGDVq1D3bAgMDCQwMvO/YH19Fd9e6dese+N3//d//zfDhw3F2dv65ZYuIyGMos2FklsjISFJTU1m5cqXZpYiIOAyF0U/87ne/M7sEERGHozB6TI70uISydkWOiFQ85eJqOhERqdgURiIiYjqFkYiImE5hJCIiplMYiYiI6RRGIiJiOoWRiIiYTmEkIiKmUxiJiIjpFEYiImI6hZGIiJhOYSQiIqZTGImIiOkURiIiYjqFkYiImE7PM3pM43eNN7uE0nXO7ALu5UjPkxJxBJoZiYiI6RRGIiJiOoWRiIiYrkyH0aVLl2jatCknTpy4Z/vgwYOJiIh47HEXLlxIdHT0E1YnIiIlpUyHEUD9+vXZvXu37f3FixfJzs42sSIRESlpZf5qulatWnHkyBFu376Ns7Mzf/nLX+jUqRO5ubnExcWxdOlSXFxc8Pb2Zv78+ezevZv4+HiuXbvG999/zxtvvMGwYcPYuXMna9eupWHDhhiGQZMmTbhx4wbTpk3j5s2b5ObmMn36dKxWK7t372bx4sUAvPfee3Tv3p0ePXqY/EuIiFRcZX5m5OrqSqtWrYiLiwPgyy+/pEuXLgDMnDmTpUuXEhUVRfXq1dm1axcAZ86cYcWKFaxcuZKoqCgMw2Dp0qVs3LiRDz74gIsXLwKQkZHBsGHD2LRpE7/5zW9Ys2YNnTt3JjExkby8PAzD4Pjx4/zqV78yp3kREQdR5mdGAC+99BK7d+/Gy8sLb29vqlSpQmZmJk5OTjz11FMAtG3bloSEBJ577jmef/55nJ2d8fHxITs7G6vVioeHB7Vr1wagTZs2ANSpU4dVq1axbt068vPzqVKlCs7OznTt2pVDhw7h5eVF27ZtcXNzM613ebDk5GS7jZ2bm2vX8csaR+rXkXqF8tVvuQijjh07MmfOHLy8vAgKCgLAyckJwzBsxxQVFeHk5ASAi8v9bVks/5oE3v3cxx9/jLe3N4sXLyYpKYlFixYB8PLLL7NmzRrq1atHcHCw3fqSx9esWTO7jZ2cnGzX8csaR+rXkXqFstdvfHz8Q/eV+WU6uLNU165dO3bs2EH37t0BqF69Ok5OTqSlpQFw9OhRmjdv/sDP16hRg+zsbLKysigoKCAhIQEAq9WKn58fAAcOHKCgoAC48z+69PR0EhMTadeunb3bExFxeOUijODOUt1zzz1H1apVbdvmzp3LtGnTGD16NAUFBfTr1++Bn7VYLISGhhISEsKUKVNo0qQJAAMHDmTDhg3827/9Gy1btiQjI4MdO3YA0KlTJ5o3b26bbYmIiP04GT9e6xLgzjLe66+/zuzZs2nQoMF9++Pj41mdttqEyuQue96brqwtbdibI/XrSL1C2es3Pj6egICAB+4rNzOj0nLp0iWGDBlCx44dHxhEIiJS8srFBQylydfXV3dnEBEpZZoZiYiI6TQzekyO9DydsrbuLCIVj2ZGIiJiOoWRiIiYTmEkIiKmUxiJiIjpFEYiImI6hZGIiJhOtwN6DI+686yIiDzcw24HpDASERHTaZlORERMpzASERHT6XZAP9O8efM4efIkTk5OvPvuu7Rs2dLskh7bokWLiI+Pp7CwkPHjx9OiRQvefvttbt++jZeXF4sXL8bNzY3PP/+cjz/+GIvFwogRIxg6dCgFBQVERESQlpaGs7Mz8+fPp379+ma39P+Vm5tLv379mDRpEi+++GKF7vfzzz9n7dq1uLi4EBYWxrPPPlth+83JySE8PJzr169TUFDApEmTeOaZZypcv2fOnOHXv/41r732GiEhIfzjH/944h7//ve/M2vWLACaNm3K7NmzzWnOkGKLi4sz3nrrLcMwDOPs2bPG0KFDTa7o8cXGxhrjxo0zDMMwrl27ZnTp0sWIiIgwvvjiC8MwDGPhwoXG5s2bjZycHKN3795GVlaWcevWLSMoKMiwWq1GdHS0MWvWLMMwDOOrr74ywsLCzGrlZ/nggw+MwYMHGzt27KjQ/V67ds3o3bu3kZ2dbaSnpxuRkZEVut9NmzYZS5YsMQzDMK5cuWIEBQVVuH5zcnKMkJAQIzIy0ti0aZNhGEaJ9BgSEmKcPHnSMAzDmDJlivHVV1+VfnOGYWiZ7meIjY2lZ8+eADzzzDNkZWVx48YNk6t6PO3atWPZsmXAnUe437p1i7i4OHr06AFAjx49iI2N5eTJk7Ro0YKqVatSuXJl2rZtS0JCArGxsfTq1QuAzp07l4srDFNSUjh37hxdu3YFqND9xsbG8uKLL+Lp6UndunWZO3duhe63Zs2aZGZmApCVlUXNmjUrXL9ubm6sWbOGunXr2rY9aY/5+flcvnzZtsJzdwwzKIx+hqtXr1KzZk3b+9q1a5ORkWFiRY/P2dmZKlWqAPDZZ58RGBjIrVu3cHNzA8DLy4uMjAyuXr1KrVq1bJ+rU6fOfdudnZ2xWCzk5+eXfiM/w8KFC4mIiLC9r8j9Xrp0CcMwmDp1Kq+++iqxsbEVut9+/fqRlpZGr169CAkJITw8vML16+LiQuXKle/Z9qQ9Xr16lWrVqtmOvTuGGXTO6GcwfnIVvGEYODk5mVRNyThw4ADbt29n/fr1BAUF2bbf7fVhPZe33+LPf/4zzz///D3nAX5cb0XrFyA9PZ0VK1aQlpbGmDFjKnS/O3fu5Omnn2bdunX8/e9/57333qvQ/d71pD0+aJtZNDP6Gby9vbl69art/T//+U/q1KljYkVP5vDhw/zXf/0Xa9asoWrVqri7u5Obmwvc+R9Z3bp1H9izl5cX3t7etn9BFRQUYBgGrq6upvRRHF999RVffvklw4cP57PPPmPVqlUVut/atWvTunVrXFxc8PPzw8PDo0L3m5CQQOfOnQHw9/cnPT29Qvd715P2WLduXdvy5o/HMIPC6Gfo1KkT+/btA+C7776jbt26eHp6mlzV48nOzmbRokX84Q9/oEaNGgB07NjR1t9f//pXfvWrX9GqVSuSkpLIysoiJyeHhIQE2rZtS6dOndi7dy8AMTExdOjQwaxWiuXDDz9kx44dbNu2jWHDhvHrX/+6QvfbuXNnvv32W4qKirh27Ro3b96s0P02aNCAkydPAnD58mU8PDwqdL93PWmPrq6u/OIXv+DYsWP3jGEG3YHhZ1qyZAnHjh3DycmJmTNn4u/vb3ZJj2Xr1q0sX76cRo0a2bYtWLCAyMhI8vLyePrpp5k/fz6urq7s3buXdevW4eTkREhICAMGDOD27dtERkZy4cIF3NzcWLBgAU899ZSJHRXf8uXLqVevHp07dyY8PLzC9vvHP/6Rv/zlL9y6dYuJEyfSokWLCttvTk4O7777Lj/88AOFhYWEhYXRuHHjCtXvqVOnWLhwIZcvX8bFxQVvb2+WLFlCRETEE/V47tw5ZsyYQVFREa1ateKdd94xpT+FkYiImE7LdCIiYjqFkYiImE5hJCIiplMYiYiI6RRGIiJiOoWRiIiYTmEkIiKmUxiJiIjp/h/a4bqM/7b6VwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "survey_data.groupby(survey_data[\"eventDate\"].dt.weekday).size().plot(kind='barh', color='#66b266', ax=ax)\n", + "\n", + "import calendar\n", + "xticks = ax.set_yticklabels(calendar.day_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nice work!" + ] + } + ], + "metadata": { + "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "nav_menu": {}, + "toc": { + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 6, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": true + }, + "toc-autonumbering": false, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/_solved/case2_observations_analysis.ipynb b/_solved/case2_observations_analysis.ipynb index 1ea0d33..d0c0d41 100644 --- a/_solved/case2_observations_analysis.ipynb +++ b/_solved/case2_observations_analysis.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Observation data - analysis

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -62,7 +59,9 @@ "cell_type": "code", "execution_count": 2, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -74,7 +73,9 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -311,7 +312,9 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -387,7 +390,9 @@ "cell_type": "code", "execution_count": 5, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -426,7 +431,9 @@ "cell_type": "code", "execution_count": 6, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -452,7 +459,7 @@ "\n", "**EXERCISE**\n", "\n", - "- Select all duplicate data by filtering the `observations` data and assign the result to a new variable `duplicate_observations`. The `duplicated()` method provides an `keep` argument define which duplicates (if any) to mark.\n", + "- Select all duplicate data by filtering the `observations` data and assign the result to a new variable `duplicate_observations`. The `duplicated()` method provides a `keep` argument define which duplicates (if any) to mark.\n", "- Sort the `duplicate_observations` data on both the columns `eventDate` and `verbatimLocality` and show the first 9 records.\n", "\n", "
Hints\n", @@ -467,7 +474,9 @@ "cell_type": "code", "execution_count": 7, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -832,7 +841,9 @@ "cell_type": "code", "execution_count": 8, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -843,7 +854,9 @@ "cell_type": "code", "execution_count": 9, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -886,7 +899,9 @@ "cell_type": "code", "execution_count": 10, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -926,7 +941,9 @@ "cell_type": "code", "execution_count": 11, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1246,9 +1263,245 @@ "cell_type": "code", "execution_count": 15, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexwgtdatasetNamesexeventDatedecimalLongitudedecimalLatitudegenusspeciestaxanameclasskingdomorderphylumscientificNamestatususageKey
occurrenceID
78011NaNNaNEcological Archives E090-118-D1.NaN1978-04-09-109.07930731.938056SylvilagusauduboniiRabbitSylvilagus auduboniiMammaliaAnimaliaLagomorphaChordataSylvilagus audubonii (Baird, 1858)ACCEPTED2436910.0
8141NaNNaNEcological Archives E090-118-D1.NaN1978-04-10-109.08282931.938851SylvilagusauduboniiRabbitSylvilagus auduboniiMammaliaAnimaliaLagomorphaChordataSylvilagus audubonii (Baird, 1858)ACCEPTED2436910.0
31278NaNNaNEcological Archives E090-118-D1.NaN1980-07-21-109.08168031.937884AmphispizabilineataBirdAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)ACCEPTED2491757.0
314724NaNNaNEcological Archives E090-118-D1.NaN1980-07-21-109.07773631.938560AmphispizabilineataBirdAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)ACCEPTED2491757.0
315319NaNNaNEcological Archives E090-118-D1.NaN1980-07-21-109.07791231.937438AmphispizabilineataBirdAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)ACCEPTED2491757.0
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" + ], + "text/plain": [ + " verbatimLocality verbatimSex wgt \\\n", + "occurrenceID \n", + "780 11 NaN NaN \n", + "814 1 NaN NaN \n", + "3127 8 NaN NaN \n", + "3147 24 NaN NaN \n", + "3153 19 NaN NaN \n", + "\n", + " datasetName sex eventDate \\\n", + "occurrenceID \n", + "780 Ecological Archives E090-118-D1. NaN 1978-04-09 \n", + "814 Ecological Archives E090-118-D1. NaN 1978-04-10 \n", + "3127 Ecological Archives E090-118-D1. NaN 1980-07-21 \n", + "3147 Ecological Archives E090-118-D1. NaN 1980-07-21 \n", + "3153 Ecological Archives E090-118-D1. NaN 1980-07-21 \n", + "\n", + " decimalLongitude decimalLatitude genus species \\\n", + "occurrenceID \n", + "780 -109.079307 31.938056 Sylvilagus audubonii \n", + "814 -109.082829 31.938851 Sylvilagus audubonii \n", + "3127 -109.081680 31.937884 Amphispiza bilineata \n", + "3147 -109.077736 31.938560 Amphispiza bilineata \n", + "3153 -109.077912 31.937438 Amphispiza bilineata \n", + "\n", + " taxa name class kingdom order \\\n", + "occurrenceID \n", + "780 Rabbit Sylvilagus audubonii Mammalia Animalia Lagomorpha \n", + "814 Rabbit Sylvilagus audubonii Mammalia Animalia Lagomorpha \n", + "3127 Bird Amphispiza bilineata Aves Animalia Passeriformes \n", + "3147 Bird Amphispiza bilineata Aves Animalia Passeriformes \n", + "3153 Bird Amphispiza bilineata Aves Animalia Passeriformes \n", + "\n", + " phylum scientificName status \\\n", + "occurrenceID \n", + "780 Chordata Sylvilagus audubonii (Baird, 1858) ACCEPTED \n", + "814 Chordata Sylvilagus audubonii (Baird, 1858) ACCEPTED \n", + "3127 Chordata Amphispiza bilineata (Cassin, 1850) ACCEPTED \n", + "3147 Chordata Amphispiza bilineata (Cassin, 1850) ACCEPTED \n", + "3153 Chordata Amphispiza bilineata (Cassin, 1850) ACCEPTED \n", + "\n", + " usageKey \n", + "occurrenceID \n", + "780 2436910.0 \n", + "814 2436910.0 \n", + "3127 2491757.0 \n", + "3147 2491757.0 \n", + "3153 2491757.0 " + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "non_rodent_species = survey_data[survey_data['taxa'].isin(['Rabbit', 'Bird', 'Reptile'])]\n", "non_rodent_species.head()" @@ -1262,43 +1515,279 @@ { "data": { "text/plain": [ - "427" + "427" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(non_rodent_species)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Select the observations for which the `name` starts with the characters 'r' (make sure it does not matter if a capital character is used in the 'taxa' name). Call the resulting variable `r_species`.\n", + "\n", + "
Hints\n", + "\n", + "- Remember the `.str.` construction to provide all kind of string functionalities? You can combine multiple of these after each other.\n", + "- If the presence of capital letters should not matter, make everything lowercase first before comparing (`.lower()`)\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexwgtdatasetNamesexeventDatedecimalLongitudedecimalLatitudegenusspeciestaxanameclasskingdomorderphylumscientificNamestatususageKey
occurrenceID
31219M13.0Ecological Archives E090-118-D1.male1977-10-17-109.07791231.937438ReithrodontomysmegalotisRodentReithrodontomys megalotisMammaliaAnimaliaRodentiaChordataReithrodontomys megalotis (Baird, 1857)ACCEPTED2437874.0
39817F7.0Ecological Archives E090-118-D1.female1977-11-13-109.07941531.937117ReithrodontomysmegalotisRodentReithrodontomys megalotisMammaliaAnimaliaRodentiaChordataReithrodontomys megalotis (Baird, 1857)ACCEPTED2437874.0
69617NaNNaNEcological Archives E090-118-D1.NaN1978-03-12-109.07941531.937117ReithrodontomysmegalotisRodentReithrodontomys megalotisMammaliaAnimaliaRodentiaChordataReithrodontomys megalotis (Baird, 1857)ACCEPTED2437874.0
147919M8.0Ecological Archives E090-118-D1.male1978-12-02-109.07791231.937438ReithrodontomysmegalotisRodentReithrodontomys megalotisMammaliaAnimaliaRodentiaChordataReithrodontomys megalotis (Baird, 1857)ACCEPTED2437874.0
149521F7.0Ecological Archives E090-118-D1.female1978-12-02-109.07939831.936448ReithrodontomysmegalotisRodentReithrodontomys megalotisMammaliaAnimaliaRodentiaChordataReithrodontomys megalotis (Baird, 1857)ACCEPTED2437874.0
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\n", - "\n", - "**EXERCISE**\n", - "\n", - "Select the observations for which the `name` starts with the characters 'r' (make sure it does not matter if a capital character is used in the 'taxa' name). Call the resulting variable `r_species`.\n", - "\n", - "
Hints\n", - "\n", - "- Remember the `.str.` construction to provide all kind of string functionalities? You can combine multiple of these after each other.\n", - "- If the presence of capital letters should not matter, make everything lowercase first before comparing (`.lower()`)\n", - "\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "clear_cell": true - }, - "outputs": [], "source": [ "r_species = survey_data[survey_data['name'].str.lower().str.startswith('r')]\n", "r_species.head()" @@ -1370,9 +1859,237 @@ "cell_type": "code", "execution_count": 20, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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verbatimLocalityverbatimSexwgtdatasetNamesexeventDatedecimalLongitudedecimalLatitudegenusspeciestaxanameclasskingdomorderphylumscientificNamestatususageKey
occurrenceID
32FNaNEcological Archives E090-118-D1.female1977-07-16-109.08197531.938887DipodomysmerriamiRodentDipodomys merriamiMammaliaAnimaliaRodentiaChordataDipodomys merriami Mearns, 1890ACCEPTED2439521.0
47MNaNEcological Archives E090-118-D1.male1977-07-16-109.08281631.938113DipodomysmerriamiRodentDipodomys merriamiMammaliaAnimaliaRodentiaChordataDipodomys merriami Mearns, 1890ACCEPTED2439521.0
53MNaNEcological Archives E090-118-D1.male1977-07-16-109.08120831.938896DipodomysmerriamiRodentDipodomys merriamiMammaliaAnimaliaRodentiaChordataDipodomys merriami Mearns, 1890ACCEPTED2439521.0
61MNaNEcological Archives E090-118-D1.male1977-07-16-109.08282931.938851PerognathusflavusRodentPerognathus flavusMammaliaAnimaliaRodentiaChordataPerognathus flavus Baird, 1855ACCEPTED2439566.0
72FNaNEcological Archives E090-118-D1.female1977-07-16-109.08197531.938887PeromyscuseremicusRodentPeromyscus eremicusMammaliaAnimaliaRodentiaChordataPeromyscus eremicus (Baird, 1857)ACCEPTED2437981.0
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" + ], + "text/plain": [ + " verbatimLocality verbatimSex wgt \\\n", + "occurrenceID \n", + "3 2 F NaN \n", + "4 7 M NaN \n", + "5 3 M NaN \n", + "6 1 M NaN \n", + "7 2 F NaN \n", + "\n", + " datasetName sex eventDate \\\n", + "occurrenceID \n", + "3 Ecological Archives E090-118-D1. female 1977-07-16 \n", + "4 Ecological Archives E090-118-D1. male 1977-07-16 \n", + "5 Ecological Archives E090-118-D1. male 1977-07-16 \n", + "6 Ecological Archives E090-118-D1. male 1977-07-16 \n", + "7 Ecological Archives E090-118-D1. female 1977-07-16 \n", + "\n", + " decimalLongitude decimalLatitude genus species \\\n", + "occurrenceID \n", + "3 -109.081975 31.938887 Dipodomys merriami \n", + "4 -109.082816 31.938113 Dipodomys merriami \n", + "5 -109.081208 31.938896 Dipodomys merriami \n", + "6 -109.082829 31.938851 Perognathus flavus \n", + "7 -109.081975 31.938887 Peromyscus eremicus \n", + "\n", + " taxa name class kingdom order \\\n", + "occurrenceID \n", + "3 Rodent Dipodomys merriami Mammalia Animalia Rodentia \n", + "4 Rodent Dipodomys merriami Mammalia Animalia Rodentia \n", + "5 Rodent Dipodomys merriami Mammalia Animalia Rodentia \n", + "6 Rodent Perognathus flavus Mammalia Animalia Rodentia \n", + "7 Rodent Peromyscus eremicus Mammalia Animalia Rodentia \n", + "\n", + " phylum scientificName status usageKey \n", + "occurrenceID \n", + "3 Chordata Dipodomys merriami Mearns, 1890 ACCEPTED 2439521.0 \n", + "4 Chordata Dipodomys merriami Mearns, 1890 ACCEPTED 2439521.0 \n", + "5 Chordata Dipodomys merriami Mearns, 1890 ACCEPTED 2439521.0 \n", + "6 Chordata Perognathus flavus Baird, 1855 ACCEPTED 2439566.0 \n", + "7 Chordata Peromyscus eremicus (Baird, 1857) ACCEPTED 2437981.0 " + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "non_bird_species = survey_data[survey_data['taxa'] != 'Bird']\n", "non_bird_species.head()" @@ -1420,7 +2137,9 @@ "cell_type": "code", "execution_count": 22, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1683,7 +2402,9 @@ "cell_type": "code", "execution_count": 23, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1961,7 +2682,9 @@ "cell_type": "code", "execution_count": 24, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2011,7 +2734,9 @@ "cell_type": "code", "execution_count": 25, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2088,7 +2813,9 @@ "cell_type": "code", "execution_count": 26, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2119,7 +2846,9 @@ "cell_type": "code", "execution_count": 27, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2168,7 +2897,9 @@ "cell_type": "code", "execution_count": 28, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2183,7 +2914,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -2228,12 +2959,14 @@ "cell_type": "code", "execution_count": 29, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "image/png": 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279+Pq6sr06ZNY/jw4ezatQtnZ2dOnz6NgYEBn376KUlJSSiVygr3kJuby7p16/juu+9Yv349MTExJCQksHHjRhwcHCoNnwWwtbVl9uzZpKSkkJGRwbZt29DR0eHQoUMAXLp0qUJAbb9+/cjNzWXQoEF07NgRR0dHZs6ciY+PDyNGjCApKUmdX5cQQgihFlJJoIZJTU2lfv365T6rLEg2OTkZZ2dnACwsLNDX1yczMxN9fX1Vhlr79u0BSE5OxsHBAQ0NDbS1tWnbti3JyckAtGzZEngYgFu22mZoaEhBQQGvvfYaenp6JCUlsXPnTlatWoWxsTFXrlxh0qRJaGlpMXHixAr3UPZo1sDAADs7OzQ0NDAyMiI/P7/K8FkAGxsbVRtWVlYVSjPVq1evyoDaR0N97ezsVH8uC/UVQgghXiZSSaAGUSqVxMbGsmLFCjIyMlSfVxYkm52dzfHjx2nZsiVpaWnk5ORgbGzMvXv3yMzMxNTUlDNnzlC/fn3s7OyIi4tj9OjRFBYWcurUKYYMGQJUHWpbxs3NjfDwcCwsLDA1NeW3337D3NycdevWcerUKZYtW8amTZvKnVNdm1WFz+7btw+F4n+bex/9c5mqAmqf5D6qIkG16iPb59VPxlj9ZIzVS8a35pEJ2v935MgRvLy8UCgUFBcX4+3tja2tbbkJWmVBsh07diQgIIC9e/eSl5dHcHAwWlpaLFy4kLFjx2JkZISW1sNh7t27N0ePHmXYsGEUFhbi6OioWnF6nH79+hEcHMzSpUsBaN68OT4+PmzYsAGFQsGHH374VPdbVfjsk6gqoFYIIYQQz4YE1T6FFxkk++DBA0aMGEFsbGylq1ovMwmqVS/5zVj9ZIzVT8ZYvWR81U+Cav+BTp48iZubG5MmTfrHTc6EEEIIUdEr8Yjz7wTRPqqq1bMnDaL9qzp06PDU9TP/qqioKEaMGFHlz728vAgKClJtAADKjWHZKuPThtpKUK0QQoiaSIJq1UyCaJ9MeHh4tRO0ylQ2hn831FYIIYR4lb0yE7RH/ROCaC9fvszMmTPR0tJCU1OTJUuWcOXKFSIiIlAoFGRkZDBs2DCGDx/OhQsXmD9/PgDGxsYsWLAAPT095s+fz+nTpyksLMTb25uLFy9y9+5dgoKC8PX1ZdasWdy7d4+srCxcXV3x9PQEYOXKlWRlZaGjo8OSJUu4ePGiagzLlK20ZWdns3jxYrS0tDA0NCQ0NBR9ff3n9VULIYQQL6VXcoIGL38Q7eHDh2nVqhX+/v4cP36cu3fvqu5h+/btlJSU4OzsjKOjI4GBgSxYsIAmTZoQGxvL2rVrad26NVlZWWzdupWMjAyioqLw8fEhKiqKoKAg/vjjDwYOHMiAAQNIS0vDy8tLNUEbMGAAAwcO5Ouvv2b16tX06dOnynHet28f/fv3Z+zYsezfv5+cnByZoAkhhHhpSFDtc/ayB9EOHTqUNWvWMG7cOAwMDPDx8VH1pSxY1t7enmvXrpGcnMzcuXMBKCwsxMbGhsuXL9OuXTvgYfBs2fllzMzM2LBhAz/88AP6+vrlwmgdHByAh+/GHTx4sNpx/uCDD4iIiGDUqFFYWFjQpk2bao8XQgghahIJqn2O/glBtPHx8XTs2JHJkyeza9cu1q5dyzvvvMO5c+coLi6moKCApKQkGjdujI2NDYsXL8bS0pITJ06QkZGBlpYWe/bsAeDevXtMnTqVL7/8krLUlXXr1tGuXTs8PT05cuRIuYnYmTNnsLCw4Pjx49jb21d7Xzt37mTIkCH4+fmxevVqYmJiKt2QIUG16iPb59VPxlj9ZIzVS8a35nllJmj/tCDa1q1bM336dMLCwlAoFMycOROlUklRURHjx48nOzubiRMnYmpqSlBQEH5+fhQXFwMQEhKCtbU1v/32Gx4eHhQXF6vat7Ozw9fXl6FDhxIUFMTOnTsxNjZGU1OTgoIC4OFjyw0bNqCnp8fixYs5f/58lff1r3/9C39/f+rUqYO2tjbBwcFP+I0JIYQQry4Jqn3Eyx5Em5CQUOFl/ZeBBNWql/xmrH4yxuonY6xeMr7qJ0G1LyEJohVCCCHEo16ZR5xPomz17Pr16yxZsoTs7GwKCwtp3rw5vr6+z2T3YWWrdM8qiLZz58507ty52mNSU1M5f/58tTsvq3Lo0CFu3rzJsGHDyn3u5ubGsmXLsLKyeuo2hRBCCFGRTND+JC8vj0mTJjF//nzatm0LwLfffsvHH3/8j3iR/ciRI1y6dOkvTdB69uyphh49JJUEhBBC1ERSSaCG+Omnn+jUqZNqcgYwZMgQoqOjuX79Ol988QU6OjrcuHGD9PR0Fi1aRFZWFjExMaxcuRIAd3d3Vq5cycGDB4mOjqakpIS+ffvi7e1NQUEBH3/8MampqRgbG7Ny5UoePHhQaRius7MzDg4OJCYmYmNjQ926dTl+/Dg6OjpERkbi5eXFvHnzsLe35+DBg/z0008MGjSoymDY4uJiIiMjycvLo3379jRo0IB58+ahqamJrq4u8+bNo6SkhIkTJ2JsbEzPnj05dOgQJiYm5OTkMHDgQK5evYqvry/Lly/n559/pn79+mRlZQEQFhaGmZkZHh4eJCcnExQUxKZNm1i+fDlHjhyhpKSEgQMHMnr06Of+vQohhBAvE5mg/cn169dp1KhRhc+trKxITU0FwNLSkuDgYGJiYtiyZQtz585l/vz53L17l4yMDExMTNDU1GTNmjXs2LEDHR0dFi1aRG5uLvfv38fHxwcrKyu8vLw4d+4c33//faVhuLm5uQwaNIiOHTvi6OjIzJkz8fHxYcSIESQlJeHq6sq3337LjBkz2LZtG++//z67du2qMhhWU1OTCRMmcOnSJfr27YuLiwshISG0aNGCffv2sWjRImbMmEFGRgbbtm1DR0eHQ4cO4ezsTP/+/YmLiwMgMTGRY8eOsXXrVu7fv8+AAQOqHdPt27cTFRWFhYWFqg0hhBDiZSBBtTWEhYUFp0+frvD5lStXVIW/y3Zh1K9fn5MnT6KhocHbb7/Nrl27SElJYejQoVy/fh17e3tq1aoFQEBAAABGRkaqd7XMzMx48OBBlWG4gCqmw9DQUFWg3NDQkPz8fJycnBgyZAhjx47l1q1btGrVCisrqycOhk1PT1fdS6dOnfj000+Bh5PRsrBbABsbm3LnJSUl0bp1axQKBfr6+jRt2rTaMV22bBnLli3j9u3b9OjRo9pjhRBCiJpEgmpriL59+xIREcHp06dVk5vY2FhMTU157bXXgMpDZ9999118fX158OABH3/8MTk5OVy6dImCggJ0dHT46KOPmDVrVqXn2tnZVRqGW9W1ytSuXZvOnTsTEhLC4MGDgccHwyoUCkpKSgAwNzfn/PnzNG/enGPHjmFtba065lF/7oONjQ0bN26kpKSEvLw8kpKSANDV1VXlypWV0SooKGDPnj0sW7aM0tJSBg4cyMCBA2nYsGG5Nv8J7/fVVLJ9Xv1kjNVPxli9ZHxrHpmg/Ymenh4REREsWLCA7OxsiouLadasGcuWLav2PAsLC/T09GjXrh1aWlqYmpoyfvx4RowYgYaGBr1798bCwqLSc99///1Kw3CfhJubGx4eHgQFBQGPD4Zt2rQp4eHhtGrVivnz5zNv3jxKS0vR1NRkwYIFT3TNFi1a4OjoyNChQzE3N6du3boAvPXWW0ydOpVjx47RunVr4GH4r5GREYMHD8bIyIju3burViKFEEIIUTkJqn2GyiZaZfU8n4fTp08TFRXFkiVLnts1nzUJqlUv+c1Y/WSM1U/GWL1kfNXvaYNqZQXtGcjLy8PT05MePXo818lZVFQU27ZtU+0eFUIIIcQ/g0zQnoFatWq9kN2JI0aMYMSIEc/9ukIIIYRQr1dmgpaQkMDUqVNp0qQJAPn5+Tg7O+Pl5fWCe/byiIuLw8jIiL59+z7ztiWoVgghRE0kQbXPQZcuXVSFxAsKCnB0dGTw4MEYGhq+4J69HFxcXF50F4QQQohXwis1QXuUUqlEoVCgqanJhQsXmD9/PgDGxsYsWLCAs2fPEhoaira2Nm5ubtSrV4/PPvsMXV1d1THnzp0jMjISbW1tbt26hbu7O0eOHOH8+fOMHDmSrl27Mn36dLZu3QrA1KlTee+994iPj6+QrP/7778TEhJCaWkpFhYWhIaGMn78eIKCgrCzsyM6Oprbt28zYcIEpkyZglKpJC8vj+nTp1eov/npp59y7NgxSktLGT16NG+99RZeXl6qigCRkZEEBQVx9epVSkpKmDp1Kp07d35s5YKIiAjMzMwYNmwY8+fP5/Tp0xQWFuLt7Y2BgQGbN29WTYDLao7+8MMPrFmzBi0tLRo2bMiSJUukILwQQoiXhgTVPgdHjhzBy8sLDQ0NtLW1CQwMRE9Pj8DAQBYsWECTJk2IjY1l7dq1dOvWjfz8fGJjYyktLaVv375ER0djYWHBhg0bCA8Pp1evXty6dYvt27fzxx9/MGXKFH788UfS0tKYPHkynp6e1KpVi6SkJMzMzEhJSaFNmzZ4e3tXSNYPDAxk+fLl2NnZ8fXXX5OcnFzpPVy7do3bt2+zfv167ty5w5UrV8r9/ODBg6SkpLB582by8/Nxc3Oje/fuAKqKAN988w0mJiYsWLCArKwsRowYwXfffffYygVl4uPjycrKYuvWrWRkZBAVFUW3bt0q7e+uXbsYPXo0AwcOZPv27SiVSlmxFEII8dKQoNrn4NFHnI9KTk5m7ty5ABQWFqqS88v+NysrC319fVWOWadOnVi2bBm9evXC3t4ebW1tDAwMaNSokSr3Kz8/HwBXV1fi4uKwtLTk7bffBipP1r9z546qUsDw4cMr9LEsDcXe3p7hw4czbdo0ioqKKrxDl5iYyB9//KH6vKioSFWiqux+EhMTOXHihKpiQlFRkaqeZnWVC8pcvnyZdu3aAVCvXj18fHxISEiotL8zZ85k9erVREdHY2trS79+/SrcmxBCCCHKe6UmaFWxsbFh8eLFWFpacuLECVUaftmjOBMTE5RKJenp6Zibm3P06FFV6n51Sf8Ajo6OrFu3DmNjY1asWFFlsr65uTlXrlzB2tqayMhIbGxs0NHRISMjAzs7O86ePYuFhQUXLlwgNzeXyMhI0tPTcXd3p3fv3qrr2dra0rlzZ1Xh81WrVqlKS5X11dbWlvr16/PBBx+Ql5dHeHg4RkZGT3Q/Zefv2bMHgHv37jF16lS8vb1V43bjxg3u3r0LwJYtW/D29qZu3brMmTOHH3/8kSFDhlRoUyoJqI/kG6mfjLH6yRirl4xvzSMTNCAoKAg/Pz+Ki4sBCAkJIT09XfVzDQ0N5s+fj7e3NxoaGhgZGbFw4UIuXrz42LZ1dXXp1KkTmZmZqvJNlSXrz507l4CAABQKBfXq1WP06NHo6OgQHBxMgwYNMDc3B8Da2povvviC7du3o62tzUcffVTuen369OHo0aN4enpy//59+vXrpyqWXsbd3Z3Zs2czYsQIlEolnp6eT/VeWN++ffntt9/w8PCguLiYDz/8kNatW2NgYICrqyt2dnaqSWGbNm0YM2YMxsbG6Onp0atXrye+jhBCCPGqkkoCz0FQUBBvvvkmXbt2fdFdqZGkkoB6yW/G6idjrH4yxuol46t+T1tJQLbTqdl7771HXl6eTM6EEEII8cRq1CPOP4fJ5ubmYmVlRWhoKDo6OpWeExISwpgxY6hTpw4///wzzs7O+Pv74+TkRM+ePf9Wf9zc3Fi2bJnqcd2TioqKUiX8r1u37m/1oSaJi4vj0qVL+Pr6Vvrz7Oxs1XcQGRlJly5daNOmzRO1LUG1QgghaqIX9Y50jVtB69KlC5s2bWLTpk3ExcWhra3N/v37qzx+1qxZWFpacuHChWqPe57Cw8NfdBdeiEe/gwkTJjzx5EwIIYQQ5dWoFbQ/KygoID09XbXDsKoA1qCgICIiIjh//jxbtmwBHu4eXLt2LUqlkqCgIExNTZk4cSLGxsb07NmT7t27M2/ePDQ1NdHV1WXevHlYWlqyfPlyfv75Z+rXr6+KnsjJyWH69OkolUqKi4uZMmUKXbt2xdnZmddff50LFy6goaHBqlWriIqK4u7duwQFBTFr1iwCAgK4fv06xcXFjBkzBicnJ7y8vGjWrBkXL16kTp06ODg48Msvv5CTk8O6desIDg7G2dmZXr16kZyczOLFi5k5cyYzZ85ES0sLTU1NlixZoor9AAgLC+Pq1atkZWVx9+5dPD09+eGHH7h8+TKLFy+mXbt2bNq0iV27dqGhoYGTkxMjR47k6tWr+Pv7q4Jkb9y4waZNm4iKiuKHH36gqKgIAwMDwsLCyn0369at47vvvkNLSwsHBwemT59e7js4deoUTk5OvPbaa9X2WwghhBAV1bgJWlmY7J07d1AoFLi5udG1a9dqA1gBPvjgAzZv3sywYcM4deoUrVq1YtKkScTFxREXF8e4cePIyMhg27Zt6Ojo4OLiQkhICC1atGDfvn0sWrSIyZMnc+zYMbZu3cr9+/cZMGAA8HBFrFu3bowaNYq0tDQ8PDzYt28fubm5DBw4kMDAQD7++GMOHTrExIkTiYqKIigoiKioKExMTFi6dClKpRIXFxe6dOkCPNzdOHv2bMaOHUutWrX46quv8PPz49ixY7i6uhIdHU2vXr3YunUrQ4cO5fDhw7Rq1Qp/f3+OHz/O3bt3K0x0atWqxZdffklkZCQHDx4kIiKCbdu28d1336Gvr8/u3bv55ptv0NDQYPTo0fz73//m008/5YMPPuCNN94gJiaGGzduUFJSQnZ2NuvXr0ehUDB27FjOnDmjus6FCxf4/vvv2bx5M1paWnh7e3PgwIEK3wHwRP0WQgghaiqpJPD/lYXJZmVl8d5776ne/6ougLUyZYGrZmZm5OXlAWBlZaV6ly09PV21m6JTp058+umnJCUl0bp1axQKBfr6+jRt2hR4GGTr7OwMgIWFBfr6+mRmZgLQsmVLABo0aFAuzLXsvLKEfX19fezs7Lh+/Xq5/hkaGqreuSsLhO3bty8hISHcuXOHX3/9lWnTplFSUsKaNWsYN24cBgYG+Pj4VLjnsr4YGBio2iwLzU1MTCQ1NZXRo0cDcPfuXa5du0ZycjLt27cHoGPHjuzcuROFQoG2tjbTpk2jTp063Lp1i6KiItV1Ll26RNu2bdHW1gbAwcGBixcv0rZt2wp9Gjp06GP7LYQQQtRUUkngT8pWnkaOHMn27durDWCFh6GyJSUlqr9XFrj6aNaXubk558+fp3nz5hw7dgxra2tsbGzYuHEjJSUl5OXlqcob2dnZcfz4cVq2bElaWho5OTmqTLPKrlOWXFJ2Xv/+/VEqlSQmJj7RhgMNDQ2cnZ0JCQmhe/fuaGtrs3v3bjp27MjkyZPZtWsXa9euZeHChRXOq4qtrS1NmjRh7dq1aGhosH79epo2bUrTpk05deoUb7zxBr///jsA58+fZ9++fcTGxvLgwQNcXFx4NI3F1taWr776iqKiIjQ1NTl27BjvvPNOhe8AHpaFely/QYJq1Um2z6ufjLH6yRirl4xvzVNjJ2gATZo0wcvLi/nz57NixYpqA1gbNWpEYmIi69evf6K258+fz7x58ygtLUVTU5MFCxbw2muv4ejoyNChQzE3N6du3brAwx2GAQEB7N27l7y8PIKDg9HSqnro7Ozs8PX1ZcGCBQQGBuLh4UF+fj6TJ09Wtfk4Li4u9OrVi//85z8AtG7dmunTpxMWFoZCoWDmzJlP1E6Z5s2b07VrVzw8PCgoKKBNmzZYWFjg6+tLQEAA69atw8DAAC0tLRo3bkzt2rVxcXFBR0eHevXqlQvubdasGW+99RYeHh6UlJTQsWNH+vXrR3p6eoXv4O/2WwghhHgVSVBtDZWWlsaMGTPYsGGDWq+zY8cO2rZtS+PGjYmNjeXkyZOVrnCpkwTVqpf8Zqx+MsbqJ2OsXjK+6ve0QbU1egXtVbV3714+//xzQkJC1H6tBg0a4OPjQ+3atVEoFCxYsEDt1xRCCCFE9WpcDtpfcfHiRSZMmICXlxfvvvsuK1eupLS0lISEhL/9UnpqaupT5au5ubmRkpJCXFwc8fHxf+mab775Jjt37lRLjlhkZCSnT59W/b1Tp07ExcXx9ddfM378eA4fPkxKSgpubm7Aw9qef9788Kgff/yRtLS0Z95PIYQQ4lX20q+g5eTkMG3aNMLCwrC2tlbllG3evBlbW9u/3f6RI0e4dOkSffr0earzXFxc/va11WHChAlV/qys8kJKSsoTt7dx40aCgoL+dnSGVBIQQghRE72oTWwv/QQtPj6ezp07Y21tDYCmpiaLFy9GW1ubU6dOcfXqVcaNG0dmZia9e/fG29ubo0eP8vnnnwMPc0kWL16MjY1NhSDX4cOHExkZSV5eHu3bt6dBgwZPHG4bFhaGmZkZtra2REREoFAoyMjIYNiwYQwfPlwVsGtnZ0d0dDS3b99mwoQJTJkyBaVSSV5eHtOnT6dz586qe01ISKi0rQsXLjB//nwAjI2NWbBgAWfPnmXNmjVoa2uTkpKCk5MTEydOVJXBev3115k5cyapqakUFhYSGBjI5cuXuXTpEu7u7hXGOTExkUWLFlFSUkJOTg6zZ88mJyeHc+fO4efnx9KlS/Hz8yMmJgb4X5mstLQ0Fi9ejJaWFoaGhoSGhpbb3CGEEEKIil76CVp6ejqvvfZauc/09PRUf87Pz2fVqlUUFxfTq1cvvL29uXjxIkuXLsXCwoKIiAj27NlD//79Kw1ynTBhApcuXaJv375PFW77qLS0NLZv305JSQnOzs44OjpWei/Xrl3j9u3brF+/njt37nDlypUnaiswMJAFCxbQpEkTYmNjWbt2Ld26dSM1NZUdO3ZQUFBAjx49mDhxoqqdzZs307BhQ5YvX05iYiKHDx/G0NCwynFOSkrCz8+PZs2asXPnTuLi4pg/fz4tWrQgKChIlYn2Z/v27aN///6MHTuW/fv3k5OTIxM0IYQQLw0Jqv2LLC0tOXv2bLnPrl+/zq1btwCwt7dXhdOWRWNYWFgQEhJCnTp1SEtLo0OHDlUGuT7qacJtH9W+fXtVH+zt7Su0W7aR1t7enuHDhzNt2jSKiopUobyPays5OZm5c+cCUFhYiI2NDQBNmzZFS0sLLS0tatWqVa6dS5cuqR5pluWhxcXFVT7IPMyNW7VqFbVq1SI3N/exk6yye/rggw+IiIhg1KhRWFhYSH1OIYQQLxUJqv2LevfuzerVq/Hw8KBRo0YUFhayaNEiunXrRpMmTSoNb509ezb79u1DX18fPz8/SktLqwxyPXr0qCp89WnCbR917tw5iouLKSgoICkpicaNG6Ojo0NGRgZ2dnacPXsWCwsLLly4QG5uLpGRkaSnp+Pu7k7v3r0f25aNjQ2LFy/G0tKSEydOkJGRAVQfXGtnZ8eZM2fo168f169f57PPPitXOuvPQkJCCA0Nxc7OjpUrV3Ljxg3VNUpLS9HV1eXOnTsUFxeTm5ureo9t586dDBkyBD8/P1avXk1MTAyTJ0+u0L4E1aqPbJ9XPxlj9ZMxVi8Z35rnpZ+g6evrs2jRImbPnk1paSm5ubn07t0bT09Pjh49Wuk5gwcPxs3NDUNDQ8zMzEhPT68yyLVp06aEh4fTqlWrpwq3fVRRURHjx48nOzubiRMnYmpqysiRIwkODqZBgwaYm5sDYG1tzRdffMH27dvR1tbmo48+eqK2goKC8PPzo7i4GHg4mXo0WLYy7u7uBAQEMGLECIqLiwkICODixYtVHv/2228zadIk6tatW+5du/bt2zNjxgzWrVtH9+7dGTp0KI0aNaJx48YA/Otf/8Lf3586deqgra1NcHBwtf0SQgghhATVql1CQgKbN29m+fLlNaqtmkSCatVLfjNWPxlj9ZMxVi8ZX/V72qDaf0QOmhBCCCHEP8lLMUGLjIzk3//+d7WBqTVV586dn8mKV1xcHD///HOFtnx8fCgoKMDf359Dhw795fYfF0j7pCp7v6zMn0NyhRBCCFG5l+IdtJ07d+Lk5MR3331XYwNgX5Sa9rizLF+uMtWF5EpQrRBCiJpIgmqrkJCQQKNGjXB3d2f69Om4uLjg5eVFs2bNuHjxInXq1MHBwYFffvmFnJwc1q1bR3x8PAcOHCAvL4+MjAxGjhxJfHw8Fy9eZMaMGfTr148dO3awYcMGdHR0sLa2Jjg4mJSUFGbOnImWlhaamposWbKEK1euPFU4bGhoKNra2ri5ufHll1/i4OBAYmIiNjY21K1bl+PHj6Ojo0NkZCQPHjxg+vTpKJVKVQWErl274uTkhIODAxcvXsTIyIhly5YB8Pvvv/Pee++RmZmJh4cHw4YNo0+fPnz//feq8YqLi+PSpUv4+vqSn5/PW2+9xf79+/n666/Zvn07CoWCDh064OfnV2Gsg4KCVLsvP//8czQ1NZk1axb37t0jKysLV1dXPD098fLywsTEhJycHAYOHKjKZfvoo4/w9fXl119/rfR6ZSG5ZfEeQgghhKhcjZ+gxcbG4urqiq2tLTo6Ovz+++8AtGnThtmzZzN27Fhq1arFV199hZ+fH8eOHQMgNzeXdevW8d1337F+/XpiYmJISEhg48aNdOzYkbCwML799lv09fVZsGABW7ZsQUNDg1atWuHv78/x48e5e/cu8HThsPn5+cTGxgKwcuVKBg0aRMeOHXF0dGTmzJn4+PgwYsQIkpKS2LFjB926dWPUqFGkpaXh4eHBvn37yMvLw9nZmU6dOrFkyRK2bNmCkZERWlpafPnll9y4cYMJEyYwbNiwJx7HuLg4AgMDadeuHd988w1FRUWqXLgy7777Lg4ODvj7+/Prr7/SuHFjBg4cyIABA0hLS8PLywtPT08AnJ2d6d+/P3FxcRgaGhIeHv7Y6wkhhBAvGwmqrcTdu3c5dOgQmZmZbNq0CaVSSVRUFACtWrUCwNDQkCZNmqj+XPYeVdlOCQMDA+zs7NDQ0MDIyIj8/HyuX79OkyZNVGGrnTp14pdffiEgIIA1a9Ywbtw4DAwMVIXWnyYctux/yzzaTzs7u3L9TE5OxtnZGXgYnquvr09mZiZaWlp06tQJgA4dOnDo0CHatWtHy5Yt0dDQoF69euTl5T12/B7doLtw4ULWrVtHaGgo7dq1o7LNu61btwbAzMyMvLw8zMzM2LBhAz/88AP6+vrlJlmP3uef7/lJryeEEELUdBJUW4kdO3bw7rvvqh7HPXjwgL59+2JiYvLYc6sLabWysiI5OZn79+9Tp04djh49io2NDfHx8XTs2JHJkyeza9cu1q5dyzvvvPNU4bAKRfl9F48Liz1+/DgtW7YkLS2NnJwcjI2NKSoqUgXinjhxQjUBra6tMrq6uqq+/PHHH6rPY2JimDt3Lrq6uowdO5ZTp07x+uuvV9vXdevW0a5dOzw9PTly5AgHDx6s9Ng/33NV16uOBNWqj2yfVz8ZY/WTMVYvGd+ap0ZP0GJjY1myZInq77Vr12bAgAFs3br1b7VramqKt7c3I0eORKFQ0KhRI3x9fUlLS2P69OmEhYWhUCiYOXMmSqXymYXD/tn7779PQEAAe/fuJS8vj+DgYNVjxzVr1pCamoqlpSU+Pj7s2rXridrs0aMH0dHReHh40KpVK1Vd0mbNmjF06FBMTEywsLCgbdu2j22rd+/eBAUFsXPnToyNjdHU1KSgoOCJ+lHZ9aorJSWEEEKI/5Gg2sd4EeGwZS/+6+rqPrdrvkgSVKte8pux+skYq5+MsXrJ+KqfBNUKIYQQQrzkavQjzpqgc+fOdO7c+blec//+/c/1ekIIIYSoWWSCVo2EhASmTp2qekk/Pz8fZ2dnvLy8Xmi/8vPz2bFjB66uroSFhWFmZoaHh8ffbjcnJ4fx48ejp6eHubn5c80sk6BaIYQQz9LLvvlMHnE+RpcuXdi0aRObNm0iKiqKr776ipycnBfap4yMDFXW2rOUmJiIubk569ate+ZtCyGEEOLJyQraU1AqlSgUCjQ1NZ+okkC9evX47LPP0NXVVR1jYGDA3Llz+b//+z/MzMy4ceMG4eHhfP755+jo6HDjxg3S09NZtGgRrVq1Iioqih9++IGioiIMDAwICwsjIiKCpKQkVVml+Ph49uzZQ3Z2NlOmTKFPnz50796dX3/9FXhYr9Pd3R1zc/MKlRIsLCwAKCgoYN68eaSnp7Ny5cpy9/znagKOjo4MHz6c3bt3o6Ghwdy5c+nWrRsbN24kKCgIOzs7oqOjuX37NhMmTGDKlCkolUry8vKYPn36c39kLIQQ4tXzrAJmn5V/VFBtTXDkyBG8vLzQ0NBAW1ubwMBA9PT0HltJoLS0lL59+xIdHY2FhQUbNmwgPDycjh07kp2dzdatW8nMzGTAgAGqa1laWhIcHExMTAxbtmwhKCiI7Oxs1q9fj0KhYOzYsZw5c4YPPviAxMREJk+eTFhYGBYWFoSEhJCQkMDatWvp06dPpfdy+PDhCpUSyiZoOjo6BAQEsHnzZj766CP8/f0BuHr1aqXVBJo1a8bx48dp27YtR48eZdasWWzcuLHCNa9du8bt27dZv349d+7c4cqVK8/+SxJCCCH+pKbtSv1HBdXWBF26dKk0YuNxlQSysrLQ19dXTYA6derEsmXLMDExoV27dsDDPDZbW1tVm2VfXP369Tl58iQKhQJtbW2mTZtGnTp1uHXrVqUlk8qqFZRVAPizsiSVoUOHVlopoTpVVRNwc3Pj22+/JSMjgz59+lQoG1V2TXt7e4YPH860adMoKip64e/vCSGEEC8DmaD9RY+rJGBiYoJSqSQ9PR1zc3OOHj2KtbU19vb2/Oc//wEelrJ6dEXpz0n+58+fZ9++fcTGxvLgwQNcXFwoLS1FoVBQUlJS5XkARUVF5Obmoq2tTVJSEkCllRIWLlxY7X1WVU2ga9euLF26lLS0NObMmQM8XIXLyMjAzs6Os2fPYmFhwYULF8jNzSUyMpL09HTc3d3p3bt3heu87C9z1mSSb6R+MsbqJ2OsXjK+NY9M0P6ix1US0NDQYP78+Xh7e6vqgC5cuBATExMOHTqEu7s7ZmZm1KpVC21t7Uqv0bhxY2rXro2Liws6OjrUq1eP9PR02rdvT2FhIUuXLqVWrVqVnjty5EiGDRuGlZUVlpaWwMNam3+ulPA4VVUT0NHR4c033+Tw4cM0btxYdc3g4GAaNGiAubk5ANbW1nzxxRds374dbW1tPvrooycfZCGEEOIVJZUEnrPk5GTOnz/PwIEDycrKYtCgQRw4cEBVjP1VJJUE1Et+M1Y/GWP1kzFWLxlf9XvaSgKygvacNWjQgNDQUDZs2EBxcTG+vr6v9ORMCCGEEBX9YyZo169fZ8mSJWRnZ1NYWEjz5s3x9fVFX1//b7f9aGTF31WnTh3Cw8Of6hx/f//nGhr7V0RFRTFixIi/fL4E1QohhHiWXvZ3m/8RQbV5eXlMmjSJcePGsWnTJjZv3kzbtm35+OOPX3TXXhlPO+kUQgghRNX+EStoP/30E506daJt27aqz4YMGUJ0dDTXr1/niy++qBACm5WVRUxMjCqU1d3dnZUrV3Lw4EGio6MpKSmhb9++eHt7U1BQwMcff0xqairGxsasXLmSBw8eMH36dJRKJcXFxUyZMoWuXbvi7OyMg4MDiYmJ2NjYULduXY4fP46Ojg6RkZF4eXkxb9487O3tOXjwID/99BODBg1i8eLFaGlpYWhoSGhoaKUrf4WFhXzyySdcvXqVkpISpk6dSufOnenTpw/ff/89urq6hIaGYmtryzvvvMP8+fM5ffo0hYWFeHt7069fPxYtWqTKXxk0aBCjRo3i6tWr+Pv7o6WlRcOGDblx44aqcsKfQ3Jv3LhRIew2Li6Ou3fvEhQUxKxZsyrt46BBg7C2tkZHR4dly5Y9n38YQgghxEvqHzFBu379Oo0aNarwuZWVFampqUDFENi5c+cyf/587t69S0ZGBiYmJmhqarJmzRp27NiBjo4OixYtIjc3l/v37+Pj44OVlRVeXl6cO3eO77//nm7dujFq1CjS0tLw8PBg37595ObmMmjQIDp27IijoyMzZ87Ex8eHESNGkJSUhKurK99++y0zZsxg27ZtvP/+++zatYv+/fszduxY9u/fT05OTqUTtNjYWExMTFiwYAFZWVmMGDGC7777rtIxiY+PJysri61bt5KRkUFUVBSampqkpKQQExNDUVERnp6edOnShZUrV/LBBx/wxhtvEBMTw40bNygpKak0JPf8+fMVwm4nTpxIVFQUQUFBfPPNN5X28f79+0yaNImWLVs+2y9fCCGEqIRUEqgBLCwsOH36dIXPr1y5ooqY+HMIrIaGBm+//Ta7du0iJSWFoUOHcv36dezt7VXRFQEBAQAYGRlhZWUFPAxuffDgAcnJyTg7O6uur6+vT2ZmJvC/4FhDQ0Ps7OxUf87Pz8fJyYkhQ4YwduxYbt26RatWrbCysiIiIoJRo0ZhYWFBmzZtKr3PxMRETpw4obrXoqIisrKyyh1Ttin38uXLqkDcevXq4ePjw9q1a3FwcFBVRWjbti3JyckkJyfTvn17ADp27MjOnTurDMl9XNhtdX0sC/EVQggh1K2m7Up9JSsJ9O3bl4iICE6fPq2a3MTGxmJqasprr70GVB7m+u677+Lr68uDBw/4+OOPycnJ4dKlS6qcr48++ohZs2ZVeq6dnR3Hjx+nZcuWpKWlkZOTg7GxcZXXKlO7dm06d+5MSEgIgwcPBmDnzp0MGTIEPz8/Vq9eTUxMDJMnT65wrq2tLfXr1+eDDz4gLy+P8PBwjIyM0NHRIT09HSsrK86fP4+dnR22trbs2bMHgHv37jF16lRGjBhBXFwco0ePprCwkFOnTjFkyBCaNm3KqVOneOONN/j999+BqkNyqwq7LZsYVtVH+F+Ib2Ve9pc5azLZPq9+MsbqJ2OsXjK+Nc8/YoKmp6dHREQECxYsIDs7m+LiYpo1a/bYd50sLCzQ09OjXbt2aGlpYWpqyvjx4xkxYgQaGhr07t1bVarpz95//30CAgLYu3cveXl5BAcHVyh3VBU3Nzc8PDwICgoC4F//+hf+/v7UqVMHbW1tgoODKz3P3d2d2bNnM2LECJRKJZ6enigUCsaNG8eECRNo2LAhhoaGwMNJ62+//YaHhwfFxcV8+OGHvPHGGxw9epRhw4ZRWFiIo6MjrVq1wtfXl4CAANatW4eBgQFaWlpVhuS2a9eu0rBbOzs7fH19WbBgQaV9FEIIIcSTe+WDassmWmVp+M/D6dOniYqKYsmSJc/tmtXZsWMHbdu2pXHjxsTGxnLy5MnHloB6liSoVr3kN2P1kzFWPxlj9ZLxVT8Jqn1CeXl5eHp60qNHj+c6OYuKimLbtm2q3aM1QYMGDfDx8aF27dooFAoWLFjworskhBBCvNJe2WdPtWrVIi4ursJL7o+6ePEiEyZMwMvLi3fffZeVK1dSWlpKQkJCtedVZ8SIEXz77bdoamqyf//+Jz7Pzc2NlJQU4uLiiI+P/0vXrkpJSQmNGzfm66+/ZtOmTar39iqTkZGhejTbp08f8vPzn/g6j54rhBBCiKq9sitoj5OTk8O0adMICwvD2tpalXW2efNmbG1t/3b7R44c4dKlS/Tp0+epznNxcfnb1/476tWr95cnWdWdK5UEhBBCPEsv++YzmaBVIT4+ns6dO2NtbQ2ApqYmixcvRltbm1OnTnH16lXGjRtHZmYmvXv3xtvbm6NHj/L5558DDx+hLl68GBsbGzZt2sSuXbvQ0NDAycmJ4cOHExkZSV5eHu3bt6dBgwbMmzcPTU1NdHV1mTdvHpaWlixfvpyff/6Z+vXrq6IqwsLCMDMzw9bWloiICBQKBRkZGQwbNozhw4fj5eVFUFAQdnZ2REdHc/v2bSZMmMCUKVNQKpXk5eUxffp0OnfuXO5+r169ytixY8nKysLDwwNXV9dK76cseiMmJkZ17s2bNwkMDCQ/P1/V/0OHDnHlyhX8/PwoLi7mnXfeYcWKFfj7+5c7VwghhBAVyQStCunp6RUe9enp6an+nJ+fz6pVqyguLqZXr154e3tz8eJFli5dioWFBREREezZs4f+/fuze/duvvnmGzQ0NBg9ejT//ve/mTBhApcuXaJv3764uLgQEhJCixYt2LdvH4sWLWLy5MkcO3aMrVu3cv/+fQYMGFChj2lpaWzfvp2SkhKcnZ1xdHSs9F6uXbvG7du3Wb9+PXfu3OHKlSsVjiksLCQ8PJySkhIGDx5M3759K72fsuy3Ry1evBgvLy/eeOMNfvvtN0JDQ5k7dy4uLi74+vry888/07lzZykKL4QQ4rmRoNp/KEtLS86ePVvus+vXr3Pr1i0A7O3tVROOsngNCwsLQkJCqFOnDmlpaXTo0IHExERSU1MZPXo0AHfv3uXatWvl2k1PT1ft7OjUqROffvopSUlJtG7dGoVCgb6+Pk2bNq3Qx/bt26v6YG9vX6Hdsg269vb2DB8+nGnTplFUVISXl1eFttq1a6dqy87OjpSUlErvpzKJiYmsXr2atWvXUlpaira2Nvr6+nTq1IlffvmFuLg4Jk2aVMVICyGEEM9eTduV+koG1apD7969Wb16NR4eHjRq1IjCwkIWLVpEt27daNKkSaVhtLNnz2bfvn3o6+vj5+dHaWkptra2NGnShLVr16KhocH69etp2rQpR48epaSkBABzc3POnz9P8+bNOXbsGNbW1tjY2LBx40ZKSkrIy8sjKSmpwvXOnTtHcXExBQUFJCUl0bhxY3R0dMjIyMDOzo6zZ89iYWHBhQsXyM3NJTIykvT0dNzd3endu3e5ts6ePUtRUREFBQUkJyfTqFEjJkyYUOF+KmNra8t7771Hhw4dSE5O5tixY8DDjQ1r1qwhKyuL5s2bk5KSUuV4v+zvCtRksn1e/WSM1U/GWL1kfGsemaBVQV9fn0WLFjF79mxKS0vJzc2ld+/eeHp6cvTo0UrPGTx4MG5ubhgaGmJmZkZ6ejrNmzena9eueHh4UFBQQJs2bbCwsKBp06aEh4fTqlUr5s+fz7x58ygtLUVTU5MFCxbw2muv4ejoyNChQzE3N6du3boVrldUVMT48ePJzs5m4sSJmJqaMnLkSIKDg2nQoAHm5uYAWFtb88UXX7B9+3a0tbX56KOPKrSlq6vL+PHjycnJwdvbG2Nj40rvpzJ+fn4EBQWRn59PXl4es2bNAqBt27ZcvXqV4cOH/9WvQQghhHglvfJBtS+rhIQENm/ezPLly190V6pUUlKCh4cHX375ZaXF38tIUK16yW/G6idjrH4yxuol46t+TxtU+8rmoAn1un79OkOGDGHw4MHVTs6EEEIIUZFM0NQgISGBrl274uXlxYgRI3B3d2f37t3Awxl0WXTFXxUaGsqNGzdq9OqZubk59+7dw9PTk5CQEFJTU9USsiuEEEL8E8k7aGrSpUsX1QQqNzcXLy8vbGxsaNGixSu3jFz2Tlp1IbsSVCuEEOJZetk3n8kE7TnQ09Nj2LBh7Nmzh5ycHNW7Y3379qVt27Zcu3YNe3t7QkJCUCqVTJ8+HaVSqape0LVrV/bu3Ut4eDimpqYUFhaqqhksWrRItV130KBBjBo1Cn9/f7S0tEhNTaWgoAAnJycOHDjAzZs3WbVqFVu3bsXCwoLhw4dz9+5dxowZw9q1a5k6dSqlpaUUFhYyd+5cmjVrprqHwsJCAgICuH79OsXFxYwZMwYnJye8vLwwMTEhJyeHsLAwZsyYQU5ODo0aNVKdWxaeu3v3bszMzPDw8Hi+X4AQQgjxkpEJ2nNSt25d/vjjj3KfpaWlMWXKFBo3bsyUKVPYt28fp06dolu3bowaNYq0tDQ8PDzYt28fS5cuJTY2FmNjYyZMmADAgQMHSElJISYmhqKiIjw9PenSpQsADRs2ZP78+cyZM4eUlBTWrFnDypUr2b9/P66urkybNo3hw4eza9cunJ2dOX36NAYGBqoMNqVSWa6vW7ZswcTEhKVLl6JUKnFxcVFdy9nZmf79+xMVFUXTpk3x8fHh999/JyEh4TmMrBBCCFGRBNWKJ5Kamkr9+vXLfdagQQMaN24MPAydvXz5MsnJyaq0fgsLC/T19cnMzERfXx8TExPVsQDJyck4ODigoaGBtrY2bdu2JTk5GYCWLVsCYGhoqFptMzQ0pKCggNdeew09PT2SkpLYuXMnq1atwtjYmCtXrjBp0iS0tLSYOHFiub4mJyfTrVs34GEEiZ2dHdevXwfAxsYGeFhcvkePHsDDiI2yAF8hhBDieatprxNJUG0NpFQqiY2NZcWKFWRkZKg+T0tLIyMjg3r16nHy5EkGDx5MdnY2x48fp2XLlqSlpZGTk4OxsTH37t0jMzMTU1NTzpw5Q/369bGzsyMuLo7Ro0dTWFjIqVOnGDJkCEClQbqPcnNzIzw8HAsLC0xNTfntt98wNzdn3bp1nDp1imXLlrFp0ybV8XZ2dhw/fpz+/fujVCpJTEzEysqq3LVsbW3573//S79+/VTBt0/qZX9XoCaT7fPqJ2OsfjLG6iXjW/PIBE1Njhw5gpeXFwqFguLiYry9vbG1tS03QdPR0WHevHncvHmTtm3b0qdPHzp27EhAQAB79+4lLy+P4OBgtLS0WLhwIWPHjsXIyEi1MtW7d2+OHj3KsGHDKCwsxNHRkVatWj1R//r160dwcDBLly4FoHnz5vj4+LBhwwYUCgUffvhhuePd3NwIDAzEw8OD/Px8Jk+eXCE8d/jw4cycORMPDw9sbW3R1tb+O0MohBBCvLIkqPYF6t69O7/++usLufaDBw8YMWIEsbGxKBQvNm1FgmrVS34zVj8ZY/WTMVYvGV/1k6Ba8VgnT57Ezc2NSZMmvfDJmRBCCCEqkkecL9CLWj3r0KEDO3fufCHXFkIIIcTj/SMmaJGRkRw+fBiFQoGGhgY+Pj60bt36RXdLpU+fPnz//ffo6uqqPjt06BA3b96ke/fuTJs2jZiYGLX3IyQkhDFjxrBt27Yal0cmQbVCCCGepZd989lLP0FLSkpi//79REdHo6Ghwblz5/Dz82PHjh0vumvV6tmzJwApKSnP7Zplif5CCCGEqNle+gmaqakpqampbN26lZ49e9KiRQu2bt0KoCqvdPnyZUpLS1m+fDn16tXj008/5dixY5SWljJ69Gjeeuutcon4AwcO5NChQ+Tl5ZGRkcHIkSOJj4/n4sWLzJgxg379+rFjxw42bNiAjo4O1tbWBAcHs3PnTuLj41EqlWRlZfHhhx/y5ptvAhAUFKSajH3++efEx8dz6dIl3N3dVffy6EpbaGgotra29OrVq9qE/8uXLzNz5ky0tLTQ1NRkyZIlXLlyhYiICBQKBRkZGQwbNozhw4erEv0fVVklgh9++IE1a9agpaVFw4YNWbJkSZUVDpydnXFwcCAxMREbGxvq1q3L8ePH0dHRITIykjt37hAUFER+fj7Z2dl8+OGH9OvXT53/JIQQQggJqn3RTE1NCQ8PJyoqii+++IJatWrh4+Ojmhh16NCB4OBgvv76a1avXk2PHj1ISUlh8+bN5Ofn4+bmRvfu3YH/JeLHxcWRm5vLunXr+O6771i/fj0xMTEkJCSwceNGOnbsSFhYGN9++y36+vosWLCALVu2UKdOHe7fv89XX31FZmYmrq6u9O3bF4B3330XBwcH/P39n+rds8cl/B8+fJhWrVrh7+/P8ePHuXv3LvAwY2379u2UlJTg7OyMo6NjhbarqkSwa9cuRo8ezcCBA9m+fTtKpZLw8PBKKxzk5uYyaNAgOnbsiKOjIzNnzsTHx4cRI0aQlJREVlYWY8aMoXPnzpw8eZKwsDCZoAkhhFC7mrYr9ZULqr169Sr6+vosXLgQgDNnzjBhwgQ6d+4MoCpH1KFDB/bv34+FhQV//PEHXl5eABQVFZGamgr8LxEf/vfFGhgYYGdnh4aGBkZGRuTn53P9+nWaNGmCvr4+AJ06deKXX36hbdu2dOrUCYVCgZmZGYaGhmRmZgKo3okzMzMjLy/vsfdVln7Ss2fPahP+hw4dypo1axg3bhwGBgb4+PgAD6sN6OjoAGBvb8+1a9cqXKOqSgQzZ85k9erVREdHY2trS79+/aqscACostcMDQ2xs7NT/Tk/P5969eoRHh7O1q1b0dDQeKrwWiGEEOJV9dJP0C5cuEB0dDQRERHo6upiY2ODgYEBmpqaAPzf//0f9evX5+TJkzRp0gRbW1s6d+7MvHnzKCkpYdWqVRUS8f/85z+zsrIiOTmZ+/fvU6dOHY4ePaqa3JXV27x9+zZKpVIV5vq4ZH94GFybnp6OlZUV58+fx87OjoSEhGoT/uPj4+nYsSOTJ09m165drF27lnfeeYdz585RXFxMQUEBSUlJqpJSj6qqEsGWLVvw9vambt26zJkzhx9//FFVSeDPFQ4ed28rVqzA1dWVN954g23btvHtt99WetzL/jJnTSb5RuonY6x+MsbqJeNb87z0E7QBAwaQnJyMq6srderUobS0lBkzZmBgYADAt99+y/r166lduzZLlizB2NiYo0eP4unpyf379+nXr59qJexJmZqa4u3tzciRI1EoFDRq1AhfX1++++47bt++zahRo7h37x6ffPKJaqL4JMaNG8eECRNo2LAhhoaGwOMT/lu3bs306dMJCwtDoVAwc+ZMlEolRUVFjB8/nuzsbCZOnIipqWmF61VViSAtLY0xY8ZgbGyMnp4evXr1onfv3pVWOHgcR0dHQkJCWL16NQ0aNCArK+uJx0MIIYR4Vf2jKwmUvRRf9thN3eLi4rh06RK+vr7P5XpVSUhIYPPmzSxfvvyF9uNJSSUB9ZLfjNVPxlj9ZIzVS8ZX/aSSgBBCCCHES+4fvYL2NJ4m7La6lbm4uDiMjIzQ19d/KVaxfHx8cHd3V22q+LNnsQo5efJkPv/8c1VQrqWlZbmfnzhxgsjIyL/cvhBCiL9n6tSpsoKmZk+7gvbSv4P2LDzLsFsXFxfg4WNG8dDnn38OSFCuEEII8aRkgkbVYbf37t1jyJAh7N27F01NTZYuXVpuVc3FxYWVK1diZWXF999/z4kTJzAyMsLMzAxbW1vVcVFRUfzwww8UFRVhYGBAWFgYJSUlzJgxg/T0dBo0aMCxY8f45Zdfyq1YRUdHc/v2bSZMmMCUKVNQKpXk5eUxffr0citexcXFzJkzh1u3bpGVlUXPnj2ZOnUq/v7+ODk50bNnTw4dOsTu3btZtGgRX3/9NbGxsdSrV487d+4A5d+fy8/P56233mL//v0ArFy5kqysLHR0dFiyZAmmpqaVBtz6+/ujo6PDjRs3SE9PZ9GiRbRq1Yru3bvz66+/Pvd3AoUQQoiXlUzQqD7stmPHjvzyyy/8+9//5tChQ0yZMoVvvvkGeJhBtn37diZPnsy3336Lr68ve/fuLdd2SUkJ2dnZrF+/HoVCwdixYzlz5gz/93//h5WVFStXriQ5OZlBgwZV2b9r165x+/Zt1q9fz507d7hy5Uq5n9+8eZN27drh6upKfn6+aoJWmXv37rFx40Z27tyJhoaGasWvOgMGDGDgwIGqsN8uXbpUGnALYGlpSXBwMDExMWzZsoXg4ODHti+EEOLFetqUe/H0XrlKAs9CdWG3rq6ubNq0iZKSErp166YKfwV4++238fDwwNXVFaVSSdOmTStM0BQKBdra2kybNo06depw69YtioqKSE5OVtXjtLOzqzQGo+z1QHt7e4YPH860adMoKipSheyWMTY25syZMxw5cgR9fX0KCgqqbOvSpUs0adJEdR9t2rSp8tgyDg4OwMOw34MHD1KvXr1KA27hfwG/ZdlzQgghar5atWrJO2hq9spVEngWqgu7dXBwYMGCBWzdurXCqpS+vj6tW7dm4cKFVa5EnT9/nn379hEbG8uDBw9wcXGhtLSUpk2bcurUKfr168e1a9dU+WA6OjpkZGRgZ2fH2bNnsbCw4MKFC+Tm5hIZGUl6ejru7u707t1bdY24uDgMDAwIDg7m6tWrxMTEUFpaqmoL4OzZswC89tprJCUlkZeXh7a2NufOnePtt99GV1dXdWxZ2G6ZM2fOYGFhwfHjx7G3t68y4BaeLJC3MhJUqz6yfV79ZIzVT8ZYvWT1rOaRCRqPD7t1dnZmz5492NvbVzjX1dWVcePGsWDBgkrbbty4MbVr18bFxQUdHR3q1atHeno6Q4cOxd/fn+HDh2NpaYmuri4AI0eOJDg4mAYNGmBubg6AtbU1X3zxBdu3b0dbW5uPPvqo3DW6du3KtGnTOHHiBLVr16Zx48akp6fj6upKQEAAO3fuxNraGnj4OHfKlCm4u7tjampK7dq1AejRowfR0dF4eHjQqlUr9PT0VO3v27ePDRs2oKenx+LFizEyMqo04FYIIYQQz4bEbDyBNWvWYGJiwtChQ59ZmydPnuT+/fv8+9//5sqVK4wbN459+/Y9s/ZfJhJUq16y8qB+MsbqJ2OsXjK+6icxG8+Yv78/WVlZhIWFPdN2X3vtNaZNm8bnn39OUVERc+bMeabtCyGEEOLl9dhKAhcvXmTChAl4eXnx7rvvsnLlygovkauLl5eX6uXzxwkLCyM6OvqZXj8uLg4zMzNWr15dbnPAX20rNDRU9fd69eqxadMmNm/erIr3UJeMjAyCgoKeSVshISGkpqaqxjshIQEfH59n0rYQQgghHqp2BS0nJ4dp06YRFhaGtbU1xcXFTJkyhc2bN+Ph4fG8+ij+pnr16j2zCZq6wmbff/99tbQrhBA1lWyOEtWpdoIWHx9P586dVS+Ya2pqsnjxYrS1tasNR9XS0iI1NZWCggKcnJw4cOAAN2/eZNWqVdy8eZOIiAgUCgUZGRkMGzaMt99+u9pA2JycHKZPn45SqVRNErt27cqgQYOwtrZGR0cHGxsb4uPj2bNnD9nZ2UyZMgUdHR1iYmJYuXIlAO7u7qxcuZIRI0bQoUMHLl++TN26dQkLC6OwsJCZM2eSmppKYWEhgYGBAPz++++89957ZGZm4uHhwbBhw+jTpw/ff/89urq6hIaGYmtrS69evZg6dSqlpaUUFhYyd+5cmjVrVm48//vf/zJq1CiUSiXe3t706tWrwj2YmZnh4eFBcnIyQUFBbNq0CWdnZ15//XUuXLiAhoYGq1at4uzZs6xZswZtbW1SUlJwcnJi4sSJ3Lx5k8DAQPLz89HV1WXevHkUFxczbdo0YmJiOHDggCrZv2XLlsydO5cffviBr7/+WtXPFStWcPHixQrf0/Dhw1Vhs5UpC6SF/5WQMjc3Z+bMmWhpaaGpqcmSJUuwsLB4in+iQgghxKun2glaeno6r732WrnPynb3paSkVBmO2rBhQ+bPn8+cOXNISUlhzZo1rFy5kv3799OiRQvS0tLYvn07JSUlODs74+joWG0gbHh4ON26dWPUqFGkpaXh4eHBvn37uH//PpMmTaJly5aEhYVhYWFBSEgICQkJrF27lsjISObPn8/du3fJyMjAxMQEc3Nzrl+/zoYNG2jQoAHu7u6cOXOG//73vzRs2JDly5eTmJjI4cOHMTQ0REtLiy+//JIbN24wYcIEhg0bVulYnT59GgMDAz799FOSkpJQKpUVjqlduzaRkZFkZmbi6upKz549K9xDZXJzcxk4cCCBgYF8/PHHHDp0CDMzM1JTU9mxYwcFBQX06NGDiRMnsnjxYry8vHjjjTf47bffCA0NVT2CLCoqYt68ecTGxlK3bl0+//xzbt26xZUrV4iMjKR27drMmTOHX375BQsLi0q/p6d1+PBhWrVqhb+/P8ePH+fu3bsyQRNCCGpWtIUE1arfMw2qtbS0VOVnlbl+/Tq3bt2iRYsWVYajtmzZEgBDQ0NVySNDQ0PVMe3bt1e902Vvb8+1a9eqDYRNTk7G2dkZAAsLC/T19cnMzATAxsZGdVxZ1IOZmRl5eXloaGjw9ttvs2vXLlJSUlS7ME1MTGjQoAEADRo0ID8/n0uXLqneA2vatClNmzYlLi6Oli1boqGhQb169cjLy6swRmXv4/Xs2ZMrV64wadIktLS0mDhxYoVjO3bsiIaGBnXr1sXAwIDs7OwK91CVsjEt629ZP7W0tNDS0qJWrVoAJCYmsnr1atauXUtpaSna2tqqNrKysjA0NKRu3brAwyLmAHXr1sXPzw89PT0uXbpEu3btgMq/pydVNi5Dhw5lzZo1jBs3DgMDA3lfTQgh/r+atGtSdnGq3zMNqu3duzerV6/Gw8ODRo0aUVhYyKJFi+jWrRvnzp2rNBwVHh9Weu7cOYqLiykoKCApKYnGjRtjampaZSCsnZ0dx48fp2XLlqSlpZGTk4OxsTHwMKm/TGXXfffdd/H19eXBgwd8/PHHVR5nZ2fHmTNn6NevH9evX+ezzz6je/fulR6ro6NDeno6VlZWnD9/Hjs7OxISEjA3N2fdunWcOnWKZcuWsWnTpnLnnTlzBnj40v79+/cxMTEpdw/VhcVW1o/KPrO1teW9996jQ4cOJCcnc+zYMdXP6tatS05ODtnZ2RgbGzN//nwGDBjAypUr+emnnwAYM2aM6nus7HuqTlFREbm5uWhra5OUlAQ8fEzesWNHJk+ezK5du1i7dq2qYsOj5F0M9ZH/8KqfjLH6yRiLV021EzR9fX0WLVrE7NmzKS0tJTc3l969e+Pp6UlSUlKl4ahPoqioiPHjx5Odnc3EiRNVZY6qCoR9//33CQgIYO/eveTl5REcHIyW1pMlhFhYWKCnp0e7du2qPcfd3Z2AgABGjBhBcXExAQEBXLx4sdJjx40bx4QJE2jYsCGGhoYANG/eHB8fHzZs2IBCoeDDDz+scF5eXh4jR47k/v37BAcHV5hgvfXWW0ydOpVjx46Vewfvafj5+REUFER+fj55eXnlXupXKBR88sknvP/++ygUClq2bEmnTp3o0KEDQ4YMoU6dOhgaGqomn1V9T1UZOXIkw4YNw8rKCktLSwBat27N9OnTCQsLQ6FQMHPmzL90X0IIIcSr5LkH1SYkJLB582aWL19e4WfqCISF/03wHrcCJP6nuu/pWZOgWvWSlQf1kzFWPxlj9ZLxVb+nDap9bA7a81L2Evnbb7/9zNrMy8vDxcWF5s2by+RMCCGEEC+N5z5B69y5c6WrMosWLXomgbCPqlWrFnFxcX/7xfTIyEhGjx7Ne++9x9ixY/m///s/4H+hreoUGhpKXFzcXz6/qiDZx/W9su/Jx8en3GYQgEOHDuHv7/+X+yeEEEKIiqTU02MkJSWxf/9+oqOj0dDQ4Ny5c/j5+bFjxw61hbY+D3+l7+p83ClBtUKIV41sjhLVkQnaY5iampKamqoqx9SiRQu2bt0KoAptNTExwdfXl4KCAmxsbDhy5Ag//vgjzs7OODg4kJiYiI2NDXXr1uX48ePo6OgQGRnJgwcPKg3g3bt3L+Hh4ZiamlJYWKiKKlm0aJFqa+6gQYMYNWoU/v7+6OjocOPGDdLT01m0aJEqbqTM1atXGTduHJmZmfTu3Rtvb29V37Ozs1m8eDFaWloYGhoSGhrKDz/8QHx8PEqlkqysLD788EPefPNNVUBvSkoKAQEB1K5dm9q1a2NkZARIUK0QQgjxrMgE7TFMTU0JDw8nKiqKL774glq1auHj48Obb76pOiYiIoK+ffsyfPhwfv31V9UkJTc3l0GDBtGxY0ccHR2ZOXMmPj4+jBgxgqSkJHbs2FFpAO/SpUuJjY3F2NiYCRMmAHDgwAFSUlKIiYmhqKgIT09PunTpAjzMqwsODiYmJoYtW7YQHBxc7h7y8/NZtWoVxcXF9OrVC29vb9XP9u3bR//+/Rk7diz79+8nJycHgPv37/PVV1+pQnX79u2rOmfFihV89NFHdO/encjISC5dulTl+ElQrRBCVK4mBcNKUK36PdOgWvFw9UlfX1+V3XXmzBkmTJhA586dVcckJyczZMgQABwcHMqdX7aaZWhoiJ2dnerP+fn5VQbw6uvrqzLS2rdvr7qGg4MDGhoaaGtr07ZtW1Uh+bJdIfXr1+fkyZMV7sHe3l71bt+fo0Y++OADIiIiGDVqFBYWFrRp0waATp06oVAoMDMzw9DQUBUMDHDx4kXVcR06dKh0giZBtUIIUb2atGtSdnGq3zMNqhVw4cIFoqOjiYiIQFdXFxsbGwwMDNDU1FQd07RpU06dOkWLFi3473//W+786kJ7qwrgvXfvHpmZmZiamnLmzBnq16+PnZ0dcXFxjB49msLCQk6dOqWaFD4uGLi6n+/cuZMhQ4bg5+fH6tWriYmJwdLSUhWUe/v2bZRKpar6ADwMwz116hQ9e/ZUbZgACaqtqeQ/vOonY6x+MsbiVSMTtMcYMGAAycnJuLq6UqdOHUpLS5kxYwYGBgaqY8aPH8+MGTP4/vvvMTc3f+IQ3aoCeBcuXMjYsWMxMjJStdW7d2+OHj3KsGHDKCwsxNHRscK7Zn/Fv/71L/z9/alTpw7a2toEBwdz7Ngxbt++zahRo7h37x6ffPJJuQnpJ598go+PD19++SWmpqbo6uoCElQrhBBCPCvPPaj2n+jgwYOYmJjQpk0bDh8+TEREBBs3bnzR3frL4uLiuHTpEr6+vs/lehJUq16y8qB+MsbqJ2OsXjK+6ve0QbWygvYMWFlZERAQgKamJiUlJS91/IYQQgghXjyZoD0DdnZ2bNmy5UV345lxcXF50V0QQgghXmkvdIKWkJDA1KlTadKkCfAwlsLKyorQ0NAqKwqEhIQwZswY6tSpw88//4yzszP+/v44OTnRs2fPv9UfNzc3li1bhpWV1VOdFxUVxYgRI/7WtZ9WTk4O48ePR09Pj3Xr1lV6zKO5ZDWdBNUKIV4WsqlJPA8vvBZnly5d2LRpE5s2bSIuLg5tbW32799f5fGzZs3C0tKSCxcuVHvc8xQeHv7cr5mYmIi5uXmVkzMhhBBCvLxq1CPOgoIC0tPTVcn0n376KceOHaO0tJTRo0fz1ltvqRLwIyIiOH/+vOrR4pYtW1i7di1KpZKgoCBMTU2ZOHEixsbG9OzZk+7duzNv3jw0NTXR1dVl3rx5WFpasnz5cn7++Wfq169PVlYW8HB1qrKEf2dnZ15//XUuXLiAhoYGq1atIioqirt37xIUFMSsWbMICAjg+vXrFBcXM2bMGJycnPDy8qJZs2ZcvHiROnXq4ODgwC+//EJOTg7r1q0jODgYZ2dnevXqRXJyMosXL2bmzJlVJvAXFBQwb9480tPTWblyJampqaoVxEOHDrF7924WLVoEQGZmJsOHD2f37t1oaGgwd+5cunXrRqNGjZg/fz4AxsbGLFiwgMLCQqZOnUppaSmFhYXMnTuXZs2asWrVKvbt20dxcTEeHh64u7uzadMmdu3ahYaGBk5OTowcObLKqgb+/v5cu3aN/Px8xo4di5OT0/P+pyWEEM/MPzHQVYJq1e+lC6o9cuQIXl5e3LlzB4VCgZubG127duXgwYOkpKSwefNm8vPzcXNzo3v37qrzPvjgAzZv3sywYcM4deoUrVq1YtKkScTFxREXF8e4cePIyMhg27Zt6Ojo4OLiQkhICC1atGDfvn0sWrSIyZMnc+zYMbZu3cr9+/cZMGAA8HBFrLKE/9zcXAYOHEhgYCAff/wxhw4dYuLEiURFRREUFERUVBQmJiYsXboUpVKJi4uLKu2/TZs2zJ49m7Fjx1KrVi2++uor/Pz8OHbsGK6urkRHR9OrVy+2bt3K0KFDq03g19HRISAggM2bN/PRRx9VW6zc1NSUZs2acfz4cdq2bcvRo0eZNWsWnp6eLFiwgCZNmhAbG8vatWtp3749BgYGfPrppyQlJaFUKjl79iyHDh0iNjaWgoICPv30Uy5evMju3bv55ptv0NDQYPTo0fz73/8GKlY1mDFjBgkJCWzbtg3gpXnkKoQQVfkn7naUXZzq99IF1Xbp0oXly5eTlZXFe++9p3r/KzExkT/++AMvLy/gYQhqampqle2UZYKZmZmRl5cHPNxdWfYuW3p6umpgOnXqpJqEtG7dGoVCgb6+Pk2bNgWoMuEfoGXLlgA0aNCA/Pz8cn1ITk6mW7duAOjr62NnZ8f169fL9c/Q0FD1zl1ZRYG+ffsSEhLCnTt3+PXXX5k2bRolJSV/KYG/stQUNzc3vv32WzIyMujTpw9aWlokJyczd+5cAAoLC7GxsaFnz55cuXKFSZMmoaWlxcSJE7l8+TJt2rRBU1OT2rVrM3v2bHbv3k1qaiqjR48G4O7du1y7dg2oWNVAX1+fwMBAAgMDUSqVvP322090H0IIIcSr7IVP0MqUrTyNHDmS7du3Y2trS+fOnZk3bx4lJSWsWrWq3Mv7CoWCkpIS1d8rS8tXKP73ip25uTnnz5+nefPmHDt2DGtra2xsbNi4cSMlJSXk5eWp0u+rSviv6jplk6Ky8/r3749SqSQxMfGJNhxoaGjg7OxMSEgI3bt3R1tbm927dz9RAj88XFHLyMgA4OzZsxV+3rVrV5YuXUpaWhpz5swBwMbGhsWLF2NpacmJEyfIyMggISFB9V7bqVOnWLZsGQEBAURHR1NSUkJxcTETJkzAz8+PJk2asHbtWjQ0NFi/fj1NmzZlz549FcYnPT2dP/74gy+++IL8/HzeeOMNBg8eXCHMV166VR/5zVj9ZIzVT8ZYvGpqzAQNoEmTJnh5eTF//nxWrFjB0aNH8fT05P79+/Tr1w99fX3VsY0aNSIxMZH169c/Udvz589n3rx5lJaWoqmpyYIFC3jttddwdHRk6NChmJubq8oZVZXwXxU7Ozt8fX1ZsGABgYGBeHh4kJ+fz+TJk8uVSKqOi4sLvXr14j//+Q/wdAn8rq6uBAQEsHPnTqytrSv8XENDgzfffJPDhw/TuHFjAIKCgvDz86O4uBh4uDvW2NgYHx8fNmzYgEKh4MMPP6RFixb06NEDDw8PSkpK8PDwoHnz5nTt2hUPDw8KCgpo06ZNlQXQ69WrR0ZGBu+88w516tThvffee+JKC0IIIcSrSioJ1BBpaWnMmDGDDRs2vOiuPHdSSUC9ZOVB/WSM1U/GWL1kfNXvaSsJvPCYDQF79+5l3LhxfPzxxy+6K0IIIYSoAeRZ03P0aDBvaWkpRUVFjBw5EicnJxo1akR8fDxt2rT5y+2HhoZia2v7UlYCkKBaIUR1pk6d+qK7IMRzJRO056xs1yo8rJzg5eWFjY0NLVq0kOVlIYQQQgAyQXuh9PT0GDZsGHv27CEnJ4fNmzezfPly+vbtS9u2bbl27Rr29vaEhISgVCorDc/du3cv4eHhmJqaUlhYiK2tLQCLFi1S5awMGjSIUaNG4e/vj5aWFqmpqRQUFODk5MSBAwe4efMmq1atYuvWrVhYWDB8+HDu3r3LmDFjWLt2baXhtWUuX75cIVD3ypUrREREoFAoyMjIYNiwYQwfPvyFjLEQQgjxMpIJ2gtWt25d/vjjj3KfpaWlMWXKFBo3bsyUKVPYt28fp06dqjQ8d+nSpcTGxmJsbMyECRMAOHDgACkpKcTExFBUVISnp6cqMLdhw4bMnz+fOXPmkJKSwpo1a1i5ciX79+/H1dWVadOmMXz4cHbt2oWzszOnT5+uEF77qMoCdcvuYfv27ZSUlODs7Iyjo+MT72gVQog/k6R79ZLxVb+XrpLAqy41NZX69euX+6xBgwaqOIz27dtz+fLlKsNz9fX1MTExUR0LDwNzHRwc0NDQQFtbm7Zt25KcnAz8L2jX0NBQtdpmaGhIQUEBr732Gnp6eiQlJbFz505WrVqFsbFxhfDaRw0dOrTSQN327durQoLt7e25du2aTNCEEH9ZrVq15DUQNZJdnOr30lUSeJUplUpiY2NZsWKFKmgWHq4+ZWRkUK9ePU6ePMngwYPJzs6uNDz33r17ZGZmYmpqypkzZ6hfvz52dnbExcUxevRoCgsLOXXqFEOGDAEqD9p9lJubG+Hh4VhYWGBqaspvv/1WIbx206ZNquPj4+MrBOq+8847nDt3juLiYgoKCkhKSlJNOKsiQbXqI//hVT8ZY/WT1R3xqpEJ2nNWVntUoVBQXFyMt7c3tra25SZoOjo6zJs3j5s3b9K2bVv69OlDx44dKw3PXbhwIWPHjsXIyEgVANu7d2+OHj3KsGHDKCwsxNHRUVVq6nH69etHcHAwS5cuBaB58+YVwmsfVVmgrlKppKioiPHjx5Odnc3EiRMxNTVl586d3L9/n2HDhj2j0RRCCCH+mSSotgbq3r37Cysq/uDBA0aMGEFsbGy5UllPIyEhQbXh4UlIUK16yeqO+skYq5+MsXrJ+KqfBNWKv+zkyZO4ubkxadKkvzw5E0IIIcTfJ/8v/BwkJCTQtWtXvLy88PLyws3NTfUeV0hICKmpqeWOf3T1bPLkyQB4eXmpXvR/WikpKbi5uVX43N/fn0OHDqn+3qFDB3bu3Enfvn3/0nXKdO7c+YlXz4QQQghRkbyD9pw8GlBbUFCAo6MjgwcPZtasWdWe9/nnnz+P7r1wUklACFEdqSQgXjUyQXsBlEolCoUCTU1NvLy8CAoKYvfu3Vy6dIk7d+6Qk5PD7NmzcXBwqPA+Wk5OTqWBtY9atWoV+/bto7i4GA8PD/7973+TmZnJpEmTyMjIoFmzZsyfP191fGFhIQEBAVy/fp3i4mLGjBmDk5MTXl5emJiYkJOTw8CBA7l69Sq+vr7k5+fz1ltvsX///ic65uuvv2b79u0oFAo6dOiAn5/fcxtrIYQQ4mUkE7TnpGz3Zlk2WWBgIHp6euWOqVWrFhs3buTixYt8/PHH7Nixo0I74eHhlQbWlr0zdvbsWQ4dOkRsbCwFBQV8+umndO/eHaVSycKFCzEwMKB///7cuXNH1eaWLVswMTFh6dKlKJVKXFxcVMG2zs7O9O/fn7i4uCrv7XHHxMXFERgYSLt27fjmm28oKipS7TgVQognIUGq6iXjq34SVFtDPfqIs7pj4GGw6+3btys9pqrAWjMzM+Bh6aU2bdqgqalJ7dq1mT17NikpKbz22msYGRkBD6sXPHjwoFyb3bp1A0BfXx87OzuuX78OgI2NTYU+/Hnj7+OOWbhwIevWrSM0NJR27dpVOF8IIR5HgmrVS3Zxqp8E1b7E/vjjDwYPHkxiYiIWFhaVHmNnZ1dpYG0ZW1tboqOjKSkpobi4mAkTJhAYGFhtQG1Zm/3790epVJKYmIiVlRXwv2BbXV1dVVbbn0tTPe6YmJgY5s6di66uLmPHjuXUqVO8/vrr5dqQoFr1kf/wqp+MsfrJ6o541cgErQY5d+4co0aN4sGDB8ybN6/SY95///1KA2vLtGjRgh49euDh4UFJSQkeHh6qkktVcXNzIzAwEA8PD/Lz85k8eXKFskw9evQgOjoaDw8PWrVqVeHxbHXHNGvWjKFDh2JiYoKFhQVt27Z92qERQgghXikSVFtDhIWFYWZmhoeHx4vuynMnQbXqJas76idjrH4yxuol46t+ElQrhBBCCPGSe6UecSYkJDB16lSaNGkCQH5+Ps7Oznh5eb3gnoG3t/cza+tpSy0JIYQQomZ5pSZoUHVgrKGh4Qvu2atNgmqFkM0yQoj/eeUmaI96NDD2woULqvBWY2NjFixYwNmzZwkNDUVbWxs3Nzfq1avHZ599hq6uruqYc+fOERkZiba2Nrdu3cLd3Z0jR45w/vx5Ro4cSdeuXZk+fTpbt24FHqZhv/fee8THx3PkyBFKSkoYOHAgo0eP5vfffyckJITS0lIsLCwIDQ1l/PjxBAUFYWdnR3R0NLdv32bChAlMmTIFpVJJXl4e06dPp3PnzpXe4/fff8/69etRKBR07NgRX1/fcu+7JScnExQUxKZNmzhw4ICqckHLli2ZO3cuv/32W6X3HBERgUKhICMjg2HDhjF8+HBV6O5f7asQQgghHnrlJmhVBcYGBgayYMECmjRpQmxsLGvXrqVbt27k5+cTGxtLaWkpffv2JTo6GgsLCzZs2EB4eDi9evXi1q1bbN++nT/++IMpU6bw448/kpaWxuTJk/H09KRWrVokJSVhZmZGSkoKbdq0wdvbm6ioKCwsLFQBr4GBgSxfvhw7Ozu+/vrrKmtvXrt2jdu3b7N+/Xru3LnDlStXKj0uOzubsLAwtm3bRu3atZk+fXq5qgSPKioqYt68ecTGxlK3bl0+//xzbt68SWBgYKX3nJaWxvbt2ykpKcHZ2RlHR8e/1VchhERJVEeCVNVLxlf9JKj2MaoKjE1OTmbu3LnAw9JHZeGrZf+blZWFvr6+Kp+sU6dOLFu2jF69emFvb4+2tjYGBgY0atQIHR0djIyMyM/PB8DV1ZW4uDgsLS15++23AVi2bBnLli3j9u3b9OjRA4A7d+5gZ2cHwPDhwyv0sWzDrb29PcOHD2fatGkUFRVV+Q7dtWvXyMzMZMKECQDk5uaqAmj/LCsrC0NDQ1W8xuTJk8nMzKzyntu3b6+K77C3t+fatWt/q69CCGQXXTVkl6F6yfiqnwTV/kU2NjYsXrwYS0tLTpw4oQpcLSuhZGJiglKpJD09HXNzc44ePYq1tTVAtSGwAI6Ojqxbtw5jY2NWrFhBQUEBe/bsYdmyZZSWljJw4EAGDhyIubk5V65cwdramsjISGxsbNDR0SEjIwM7OzvOnj2LhYUFFy5cIDc3l8jISNLT03F3d6d3794VrmtlZUWDBg1Yt24d2traxMXF0aJFC37++ecKgbJ169YlJyeH7OxsjI2NmT9/Ps7OzlXe87lz5yguLqagoICkpCQaN278t/oq796oj/yHV/1kjIUQz5pM0P6/oKAg/Pz8KC4uBiAkJIT09HTVzzU0NJg/fz7e3t5oaGhgZGTEwoULuXjx4mPb1tXVpVOnTmRmZqpS/42MjBg8eDBGRkZ0794dS0tL5s6dS0BAAAqFgnr16jF69Gh0dHQIDg6mQYMGmJubA2Btbc0XX3zB9u3b0dbW5qOPPqr0uqampowePRovLy+Ki4tp2LAhb731Fvr6+kydOpVjx47RunVr4OFE9JNPPuH9999HoVDQsmVL2rRpU+U9FxUVMX78eLKzs5k4cSKmpqaMHDnyL/dVCCGEEP8jQbXPSVBQEG+++SZdu3Z90V352551jIcE1aqXrO6on4yx+skYq5eMr/pJUG0N9N5775GXl/ePmJwJIYQQQv3kEedzsG7duhfdhWeqc+fOEpUhhBBCqNErP0GLjIzk8OHDKBQKNDQ08PHxoXXr1oSEhDBmzBgsLS3Vdu3Q0FBsbW1xcXH5y23MmDGDK1eusHDhQtUO0Ec9mk32Z3FxcRgZGdG3b9+/fP0yW7ZswcXFBW1t7b90vgTVipfZ1KlTX3QXhBD/MK/0BC0pKYn9+/cTHR2NhoYG586dw8/Pjx07djBr1qwX3b0n8ssvv3D48OG/dO7fmRj+2erVq3nnnXeeWXtCCCHEq+yVnqCZmpqSmprK1q1b6dmzJy1atFAl/petPJmYmODr60tBQQE2NjYcOXKEH3/8EWdnZxwcHEhMTMTGxoa6dety/PhxdHR0iIyM5MGDB0yfPh2lUklxcTFTpkyha9eu7N27l/DwcExNTSksLMTW1haARYsWqXJRBg0axKhRo/D390dHR4cbN26Qnp7OokWLaNWqlar/QUFB5OTkMHHiRPr378+lS5fw9fUlPz+ft956i/3796uOdXFxYeXKlVhZWfH9999z4sQJjIyMMDMz48qVKzRv3pwhQ4aQkZHB+++/T1xcHJ9++inHjh2jtLSU0aNH89Zbb+Hl5UXz5s25ePEiSqWSFStWcPjwYTIyMvDx8WHVqlVVnmdiYkJOTg5ffvklmpqaz/GbFkK9JORT/WSM1UvGV/0kqPYpmJqaEh4eTlRUFF988QW1atXCx8eHN998U3VMREQEffv2Zfjw4fz666+qJP7c3FwGDRpEx44dcXR0ZObMmfj4+DBixAiSkpLYsWMH3bp1Y9SoUaSlpeHh4cG+fftYunQpsbGxGBsbqwJkDxw4QEpKCjExMRQVFeHp6UmXLl0AsLS0JDg4mJiYGLZs2UJwcLCqb0FBQfz444+Eh4erqhFUZejQoWzfvp3Jkyfz7bff4uvry969ewFwc3Nj7ty5DBkyhP/85z+4uLhw8OBBUlJS2Lx5M/n5+bi5udG9e3cA2rRpw6xZs1i+fDnfffcdEyZMIDw8nOXLl1d7nrOzM/37939G354QNUetWrVkB5yayS5D9ZLxVb+nDap9pXdxXr16FX19fRYuXMhPP/3E0qVLCQoKIjs7W3VMcnIyHTp0AMDBwaHc+WWrWYaGhqp3vAwNDcnPzyc5OZlOnToBYGFhgb6+viqZ38TEBA0NDdq3b6+6hoODg6r8VNu2bVVlnsq+zPr161NQUPBE91VZcsrbb7/N3r17SUtLQ6lU0rRpU9XP7OzsKC4u5saNG+zevZu3336bxMRE/vjjD7y8vBg3bhxFRUWkpqYCD+t0lvWprFpCmerOK6vKIIQQQojqvdIraBcuXCA6OpqIiAh0dXWxsbHBwMCg3OO3pk2bcurUKVq0aMF///vfcudXV0HAzs6O48eP07JlS9LS0sjJycHY2Jh79+6RmZmJqakpZ86coX79+tjZ2REXF8fo0aMpLCzk1KlTDBky5LHXeJSurm6F6gCP0tfXp3Xr1ixcuLDSd8+GDh3K0qVLadKkCYaGhtja2tK5c2fmzZtHSUkJq1atwsrKqsrra2hoUFJSUu151d2LVBJQH/nNWP3k0ZAQ4ll7pSdoAwYMIDk5GVdXV+rUqUNpaSkzZszAwMBAdcz48eOZMWMG33//Pebm5mhpPdmQvf/++wQEBLB3717y8vIIDg5GS0uLhQsXMnbsWIyMjFRt9e7dm6NHjzJs2DAKCwtxdHQs967Zk+jRowfR0dF4eHjQqlUr9PT0Khzj6urKuHHjWLBgQYWfOTo6EhISQnh4OAB9+vTh6NGjeHp6cv/+ffr164e+vn6V13dwcGDChAls3Ljxqc4TQgghREVSSeAxDh48iImJCW3atOHw4cNERESwcePGF92tfxSpJKBesoKmfjLG6idjrF4yvur3tJUEXukVtCdhZWVFQEAAmpqalJSUvDTxG0IIIYR4eb1yE7SEhASmTp1KkyZNAMjPz8fZ2RkvL69Kj7ezs2PLli1q71d+fj47duzA1dWVsLAwzMzM8PDw+NvtVtXW5MmT+fzzz5+4nYyMDL744guCgoLKff4swnZBgmrFiyHvPgohaqpXboIG0KVLF1Wh74KCAhwdHRk8eDCGhoYvrE8ZGRnExsbi6ur6XK73NJMzgHr16lWYnAkhhBBCPV7JCdqjlEolCoUCTU1NLly4wPz58wEwNjZmwYIFnD17ltDQULS1tXFzc6NevXp89tln6Orqqo4xMDBg7ty5/N///R9mZmbcuHGD8PBwPv/880qDZqOiovjhhx8oKirCwMCAsLAwIiIiSEpKUk2c4uPj2bNnD9nZ2UyZMoU+ffrQvXt3VQ6bj48P7u7umJubM3PmTLS0tNDU1GTJkiVYWFiUu8fq2vr666/Zvn07CoWCDh064Ofnh7+/P6Wlpdy8eZP79++zePFidHV1mTZtGjExMZWG7SYkJLB582bVxLes/R9++IE1a9agpaVFw4YNWbJkCQrFK53uIoQQQjzWKzlBO3LkCF5eXqrcscDAQPT09AgMDGTBggU0adKE2NhY1q5dS7du3cjPzyc2NpbS0lL69u1LdHQ0FhYWbNiwgfDwcDp27Eh2djZbt24lMzOTAQMGqK7156DZspy19evXo1AoGDt2LGfOnOGDDz4gMTGRyZMnExYWhoWFBSEhISQkJLB27Vr69OlT6b0cPnyYVq1a4e/vz/Hjx7l7926FCVp1bcXFxREYGEi7du345ptvKCoqAuC1115j8eLFHDx4kKVLlzJ79mzVOZWF7VZl165djB49moEDB7J9+3aUSuULXakU4lHPKh5DUtjVT8ZYvWR81U8qCTyBRx9xPio5OZm5c+cCUFhYqApWLfvfrKws9PX1VROgTp06sWzZMkxMTGjXrh3wsDpBWfkmKB80e/LkSRQKBdra2kybNo06depw69Yt1aToUWUxG2ZmZuTl5VX4ednm26FDh7JmzRrGjRuHgYEBPj4+T9XWwoULWbduHaGhobRr107Vblklg/bt25eL5bh9+7YqbLfs55Upa2fmzJmsXr2a6OhobG1t6devX6XHC/EiPKtda7IDTv1kjNVLxlf9nraSwCs5QauKjY0NixcvxtLSkhMnTqiCX8seyZmYmKBUKklPT8fc3JyjR49ibW2Nvb09//nPfwC4e/cuV65cUbX553DW8+fPs2/fPmJjY3nw4AEuLi6UlpaiUCgoKSmp8jyAoqIicnNz0dbWJikpCXj4+LJjx45MnjyZXbt2sXbtWhYuXFjuvOoCYmNiYpg7dy66urqMHTuWU6dOAQ/Dbh0cHDh58iT29vaq46sK2300KPfGjRvcvXsXgC1btuDt7U3dunWZM2cOP/74oyqE91Hysrb6yH94hRDi5SMTtEcEBQXh5+dHcXExACEhIaSnp6t+rqGhwfz58/H29kZDQwMjIyMWLlyIiYkJhw4dwt3dHTMzM2rVqoW2tnal12jcuDG1a9fGxcUFHR0d6tWrR3p6Ou3bt6ewsJClS5dSq1atSs8dOXIkw4YNw8rKCktLSwBat27N9OnTCQsLQ6FQMHPmzKe652bNmjF06FBMTEywsLCgbdu2xMXFcejQIeLj4ykpKSk34asqbLd169YYGBjg6uqKnZ2dqnpAmzZtGDNmDMbGxujp6dGrV6+n6p8QQgjxKpKg2mcgOTmZ8+fPM3DgQLKyshg0aBAHDhxAR0fnRXftL/H398fJyYmePXs+l+tJUK16yQqa+skYq5+MsXrJ+KqfBNW+AA0aNCA0NJQNGzZQXFyMr6/vSzs5E0IIIcSLV+MnaBcvXmTp0qU8ePCA+/fv88Ybb6geMVbmea/+ANSpU0dVw7Is0LWy96zU6Vne96JFi55Bj4QQQgjxV9XoCVpOTg7Tpk0jLCwMa2triouLmTJlCps3b34mKfvqIIGuf41UEhAvgmxOEULUVDV6ghYfH0/nzp2xtrYGQFNTk8WLF6OtrU1xcTFz5szh1q1bZGVl0bNnT6ZOnao6V6lUMmvWLO7du0dWVhaurq54enri5eVFs2bNuHjxInXq1MHBwYFffvmFnJwc1q1bR506dQgICOD69esUFxczZswYnJycnjrQdePGjYwfPx54uPvy999/Z8+ePZw9e5avv/5a1c8VK1Zgamqq+ntYWBhXr14lKyuLu3fv4unpyQ8//MDly5dZvHgx7dq1Y9OmTezatQsNDQ2cnJwYOXLkE9138+bNuXjxIkqlkhUrVtCwYUPWrVvHd999h5aWFg4ODkyfPp07d+7g7+/PvXv3KC0tZfHixZiamjJ9+nSUSqVqoty1a1cGDRqEtbU1Ojo6pKamMm/ePOzt7Tl48CA//fQTgwYNYvHixWhpaWFoaEhoaCj6+vrq/YcjhBBCvORq9AQtPT2d1157rdxnenp6AKSkpNCuXTtcXV3Jz8+vMEG7evUqAwcOZMCAAaSlpeHl5YWnpyfwcGfh7NmzGTt2LLVq1eKrr77Cz8+PY8eOcevWLUxMTFi6dClKpRIXFxe6dOny1IGutWrVYtOmTZSWljJ9+nTeeecdGjVqxO7du4mMjKR27drMmTOHX375hbfffrvcPdaqVYsvv/ySyMhIDh48SEREBNu2beO7775DX1+f3bt3880336ChocHo0aP597///cT3PWvWLJYvX853333HG2+8wffff8/mzZvR0tLC29ubAwcO8Ouvv9KnTx88PDz47bffOH36NOfOnaNbt26MGjWKtLQ0PDw82LdvH/fv32fSpEm0bNmSbdu28e233zJjxgy2bdvG+++/z65du+jfvz9jx45l//795OTkyARN1BgSVPvykDFWLxlf9ftHBdVaWlpy9uzZcp9dv36dW7du0aJFC86cOcORI0fQ19enoKCg3HFmZmZs2LCBH374AX19/XJhsGXBrYaGhqqi6YaGhuTn55OcnEy3bt0A0NfXx87OjuvXrz91oGuZefPmYWNjw7BhwwCoW7cufn5+6OnpcenSJVXA7aNatmwJgIGBgap/RkZG5Ofnk5iYSGpqKqNHjwYe5q5du3btie67rN369etz+/ZtLl26RNu2bVWRIA4ODly8eJHLly8zdOhQALp27Qo8rAjg7OwMPKxMoK+vT2ZmJvC/IF8nJyeGDBnC2LFjuXXrFq1atcLKyoqIiAhGjRqFhYUFbdq0qXC/QrwoElT78pAxVi8ZX/X7RwXV9u7dm9WrV+Ph4UGjRo0oLCxk0aJFdOvWjXPnzmFgYEBwcDBXr14lJiaGRxND1q1bR7t27fD09OTIkSMcPHjwia5pZ2fH8ePH6d+/P0qlksTERKysrAgPD3+qQFeAzz77jNLSUj788EMA7t27x8qVK/npp58AGDNmDJWlnFQXLGtra0uTJk1Yu3YtGhoarF+/nqZNm7Jnz56nvm9bW1u++uorioqK0NTU5NixY7zzzjvcvn2bM2fO0Lx5c44dO8ZPP/2kGpeWLVuSlpZGTk4OxsbGwP+CfGvXrk3nzp0JCQlh8ODBAOzcuZMhQ4bg5+fH6tWriYmJYfLkyRX6Iu8CqY/8h1cIIV4+NXqCpq+vz6JFi5g9ezalpaXk5ubSu3dvPD09SUpKYtq0aZw4cYLatWvTuHHjcqGyvXv3JigoiJ07d2JsbIympmaFVbbKuLm5ERgYiIeHB/n5+UyePJm6des+daDr6dOniYyM5PXXX8fLywuASZMm0aFDB4YMGUKdOnUwNDQs1+cn0bx5c7p27YqHhwcFBQW0adOmXO3Np7nvZs2a8dZbb+Hh4UFJSQkdO3akX79+dOzYkYCAAHbs2AGgKggfEBDA3r17ycvLIzg4WBVS++fx8/DwUG2U+Ne//oW/vz916tRBW1ub4ODgp7pfIYQQ4lUkQbV/w4uI9KjpTp8+TVRUFEuWLHnicySoVr1kBU39ZIzVT8ZYvWR81U+CasULExUVxbZt21i5cuWL7ooQQgjxUpMJ2t/wogJdExISmDp1qmoDQW5uLlZWVoSGhj5RBYNDhw6xe/fup+7/sWPHMDAwoHnz5pX+fMSIEfy/9u49ruf7///4rXf1Lp1LyiGmg7NhxsfpIzkbiw9T1ETDjI1RyyrHlBzDPnLIKcd9IsQXYwfsM5vNcfZBQweHlUNJkUrnfn/06zWtcpo3xeP6F/V6PV/P96Pm8tjr9Xren8OGDXuqMYUQQghRljRoVVT79u1ZsmSJ8vfPPvuMw4cP06dPH41dc+fOnfTt27fCBu3vkKBa8bRkYYkQ4lUmDdorIDc3l+TkZExNTYHiO3slS3jfffddRowYQXx8PFOmTKFatWpUq1ZNOfbAgQNs2LABlUrF22+/jY+PD6GhoSQmJnLnzh1u3LiBv78/5ubm/Pjjj0RHR+Pg4EDt2rUBSE1NZdKkSRQVFZGXl8esWbMwNDRk4sSJ1KhRg6SkJBwdHfHy8no5xRFCCCGqIGnQqqhjx47h4eHBnTt3UKlUuLq60qFDB77//nsSExOJjIwkPz8fd3d32rdvz/Lly/n000/p1KkTq1ev5vLly9y9e5fQ0FB27txJtWrVmDx5MkePHgVArVazdu1ajh49Snh4OOvWraNz58707dtXac6geFGAsbExixYtIi4ujoyMDAwNDbl+/Trr1q3D2NgYd3d3oqOjlfw5IZ6HyhSqKSGfmic11iypr+a9UkG1omIljzjT0tIYOXIkNjY2AMTHx9OmTRu0tLTQ1dWlZcuWxMfHExsbq4TEtm7dmsuXL/PHH3+QmprKmDFjgOJ32RISEoA/Azxr1qz5yHgSR0dHrl69yscff4yOjg7jxo0DiuNASnLSWrRowZUrV6RBE89VZVpxJivgNE9qrFlSX817pYJqxeOVbEs1fPhwdu/ejb29PVFRUXh6epKXl8eZM2cYOHAgdnZ2nDlzBkdHR86fPw+AjY0NtWrVIjw8HF1dXaKiomjSpAkHDx4sNyxXS0urTLDu8ePHsbKyIjw8nDNnzrB48WLmzp1LfHw8Dx48QK1Wc/bsWd57771Hfg55n0hz5B9eIYSoeqRBewU4ODjg4eHB7NmzWbp0KSdOnGDIkCHk5eXRp08fmjVrxsyZM/Hy8mLdunVYWFigp6eHhYUFnp6eeHh4UFBQQJ06dXjnnXcqvE7Lli0JCQnBxsYGe3t7oPhOmZeXFxs3bkSlUim7Jujq6jJx4kRSUlLo06cPjRs35pdffuH06dPl7iQghBBCiD9JUK147hITE/H29iYyMvKJjpegWs2SO2iaJzXWPKmxZkl9Ne9pg2pVL2JSQgghhBDiyUmDJp47GxubJ757JoQQQoiyXol30FavXs3PP/+MSqVCS0sLLy8vmjdvTnBwMB988EGpWIjnLSQkBDs7OwYNGqSxa5R42Xt/btmyhWHDhhEVFcXly5fx8fF5bmNLUK14WrKwRAjxKqvyDVpcXByHDx8mIiICLS0tLly4gK+vL3v27GHq1Kkve3qvlJUrV8pWTkIIIcQLUOUbNAsLC27cuMGOHTtwdHSkSZMm7NixAwAPDw8CAgIwNzfHx8eH3NxcbG1tOXbsGN999x3Ozs60adOGmJgYbG1tqV69OqdOnUKtVrN69WoePHjA5MmTycjIoKCggIkTJ9KhQwe++eYbVq5ciYWFBXl5edjZ2QHlJ/j7+fmhVqu5fv06ycnJzJs3r0weWHnnXb16lWnTppGXl4e+vr6yrdO2bdtYu3YtGRkZBAQEYGFhwbhx4zAzM8PR0ZFOnToRFBSEtrY2enp6BAUFUbt2bZYvX87BgwexsLDgwYMHTJw4kRMnTpTZMaBz5858/fXXfPnll8r8/v3vf7Nt2zbu3btHQEAALVq04H//+x8jR44kNTUVNzc3hgwZQrdu3Thw4AB6enrKnUUnJ6cyOw00atRI478X4tVXmUI1JeRT86TGmiX11bzXLqjWwsKClStXsmXLFpYvX46+vj5eXl707t1bOSYsLIzu3bvz/vvvc/ToUSUtPzMzk3fffZe3336bPn364O/vj5eXF8OGDSMuLo49e/bQsWNHRowYQVJSEm5ubhw8eJCFCxeyfft2zMzMlJDXihL8AWrXrk1gYCCRkZFs27aNwMBAZW4VnffFF18wZswYHB0d2b9/P7///jsAzZo14+OPPyYqKoqoqChGjx7N7du32blzJ2q1mkGDBhEcHKzkmc2bN4+PP/6YH3/8kR07dpCXl4ezs7Ny/b/uGNC5c2euXr3K6tWrqVatGjNmzOCnn35i3LhxbNmyhYCAAKKiotDR0WHdunVcv36dMWPGMGTIkHJ/PuXtNCDE81CZVpzJCjjNkxprltRX8167oNpr165hZGTE3LlzATh37hxjxoyhXbt2yjHx8fEMHDgQgDZt2pQ6v+RulomJiZLtZWJiQk5ODvHx8UozY21tjZGREampqRgZGWFubg7AW2+9pVyjvAR/KJ3K/+uvv5a6fkXnXblyRRm7b9++AOzbt0+Zr6WlJdnZ2UDxS/lqtRqA5ORk5Xpt27Zl0aJFxMfH8+abb6KtrY22tjbNmzdXrl/ejgHVq1fH19cXQ0NDLl++TKtWrcrUvWnTpmhpaVGjRg1lHg8rSW+paKcBIYQQQlSsyjdoly5dIiIigrCwMPT09LC1tcXY2BhtbW3lmIYNG3LmzBmaNGnCb7/9Vur88hLzS9jb23Pq1CmaNm1KUlIS6enpmJmZcf/+fVJTU7GwsODcuXPUrFmzwgT/J7lGeefZ29tz7tw5OnbsyJ49e7h3716FY6lUfy7GtbKy4uLFizRu3JiTJ09Sv359HBwc2Lx5M4WFheTn5yt348ob7/79+yxdupT//ve/AHzwwQdKs/VwZF5581Cr1SQnJ2NjY8PFixext7cvd6eBzZs3lzlXXvjWHPk/YyGEqHqqfIPWq1cv4uPjcXFxwcDAgKKiIj7//HOMjY2VYz788EM+//xzDhw4gJWVFTo6T/axP/roI6ZMmcI333xDdnY2gYGB6OjoMHfuXEaNGoWpqakyVteuXctN8H+cis77/PPPmTFjBitXrkRfX5+FCxcSHR392PFmz55NUFAQRUVFaGtrM2fOHOrWrUuXLl1wdXXF3NwcXV3dCmtgZGRE69atGThwIAYGBpiYmJCcnAwUN5M+Pj507Nix3HNHjx7NmDFjqFOnDiYmJkDFOw0IIYQQomKvxU4CP/zwA+bm5rRo0YKff/6ZsLAwNm3a9LKn9cLcuXOHr7/+mvfff5/c3Fz69evHxo0bNRo/8jRkJwHNkjtomic11jypsWZJfTXvaXcSqPJ30J6EjY0NU6ZMQVtbm8LCwtcufsPc3Jzz58/z3nvvoaWlhYuLS6VpzoQQQghR1mvRoNnb27Nt27bHHhcbG8vChQt58OABWVlZdOnShQkTJlT4DllJcGxKSgqXL19mxIgRLF++nICAgL895+cZBqtSqZRFFC/CpUuXSE9Pp23btk98jgTViqcl7y0KIV5lstXT/5eeno63tzdTpkxh8+bNREZGEhMTw9atW594jBo1ajyX5qyq+/bbb4mLi3vZ0xBCCCGqrNfiDtqTOHToEO3ataN+/foAaGtrM3/+fHR1dSkoKGDGjBncunWLtLQ0HB0dmTRpUpkxEhMT8fb2JjIykr59+9KmTRtiY2MxNTVl8eLF6OrqMnPmTK5du0ZhYSGTJk2iXbt25R77sEWLFnH+/HkyMzOxt7cvczfsyy+/ZPfu3ahUKlq3bo2vry9xcXFMmTKFatWqUadOHQoLC5k3bx6dOnVScuC8vLwYOnQozZo1Y+rUqdy/f5+0tDRcXFxwd3fHw8ODRo0aERsbi4GBAW3atOGnn34iPT2d8PBwtLW1y5zXvXt3du3aha6uLs2aNePGjRtlQm8tLCye7w9PCCGEeMVIg/b/JScnU7du3VJfMzQ0BIobr1atWuHi4kJOTk6FDdrDsrOzcXZ2pm3btixYsIBt27ahp6eHubk5c+bMIS0tjWHDhvHVV1+Ve6ypqSkAGRkZmJiYsH79egoLC+nXrx9JSUlYW1sr14qKimL69Om0atWK//znP+Tn5zN//nwmTpxIp06dCAsL4+rVqxXO9dq1a/Tr149evXqRlJSEh4cH7u7uALRo0YJp06YxatQo9PX1Wb9+Pb6+vpw8eZJatWqVe97AgQOxtLRUFmX8NfS2f//+z/ATEqK0ypR6Linsmic11iypr+a9djsJPC+1a9culQ8GkJCQwK1bt2jSpAnnzp3j2LFjGBkZKYGuj6Kjo6O8g9W6dWuOHDmCSqXi9OnTnD17FoD8/HzS0tLKPbYkHFZPT4/U1FS8vb0xMDAgKyuLvLy8UteaO3cu4eHhhISE0KpVK4qKikhMTKRFixYAtGvXrtwGrWQBr6WlJRs3buTbb7/FyMiI/Px85ZiHg3wdHByUP+fk5DzyvBJPEnorxLOoTCvOZAWc5kmNNUvqq3mv3U4Cz0vXrl1ZtWoVbm5u1KtXj7y8PObNm0fHjh25cOECxsbGBAYGcu3aNSIjI3lcOkl+fr4SGHv69GmlualZsyZjx44lOzublStXYmpqWuGxAEeOHOHmzZt88cUXpKam8t1335W5dmRkJLNmzUJPT49Ro0Zx5swZGjVqxK+//kqXLl04f/58qXllZmaiq6urvCcWHh5Oq1atcHd359ixY/zwww9PVLOKztPS0qKwsPCRobd/JS98a478wyuEEFWPNGj/n5GREfPmzWPatGkUFRWRmZlJ165dcXd3Jy4uDm9vb06fPk21atV44403lPDWR1mzZg03btygdu3aeHl5ATBt2jSGDRtGRkYG7u7uyi4Afz123759QPEjxhUrVuDq6oparaZu3bplHsc2atSIwYMHY25ujrW1NS1btqROnTpMnTqV8PBw1Go11atXB2D48OEMGTIEGxsbJWqja9euBAQEsHfvXszMzNDW1n6iu4QVnde8eXMWLFiAvb19haG3QgghhKjYaxFU+zJ069aNAwcOoKen91yPfRZHjhxh//79zJs3TyPj/10SVKtZcgdN86TGmic11iypr+Y9bVCtxGwIIYQQQlQy8ohTQw4fPqz8OSEhgQULFnD37l3y8vJo3LgxPj4+GBkZlTn2aT0cm1ERR0dHHB0dn/kaQgghhHixpEHTsOzsbD7++GNmz55Ny5YtAdi1axefffaZvBj/ENlJQDwt+e9HCPEqkwZNw/773//Stm1bpTkDGDhwIBERESQkJLB8+XLUajXXr18nOTmZefPmkZaWRmRkJEuXLgVg6NChLF26lB9++IGIiAgKCwvp3r07EyZMIDc3l88++4wbN25gZmbG0qVLefDgAZMnTyYjI4OCggImTpxIhw4dcHZ2pk2bNsTExGBra0v16tU5deoUarWa1atX4+HhQVBQEA0aNOCHH37gv//9L++++y7z589HR0cHExMTQkJClDt/ULxrwJo1a9DR0aFOnTosWLCA5cuXc/nyZe7cuUN6ejrTpk2jTZs2L7z2QgghRFUlDZqGJSQkUK9evTJft7Gx4caNG0BxBltgYCCRkZFs27aNWbNmMXv2bO7du8ft27cxNzdHW1ubNWvWsGfPHtRqNfPmzSMzM5OsrCy8vLywsbHBw8ODCxcucODAATp27MiIESNISkrCzc2NgwcPkpmZybvvvsvbb79Nnz598Pf3x8vLi2HDhhEXF4eLiwu7du3i888/Z+fOnXz00Ufs27ePnj17MmrUKA4fPkx6enqpBm3fvn14enrSr18/du/eTUZGBgD6+vps2rSJ2NhYPvvsM/bs2fNiCi5eG5UpVFNCPjVPaqxZUl/Nk6DaSsba2loJpn3Y1atXlZiLklUdNWvW5Ndff0VLS4v+/fuzb98+EhMTGTx4MAkJCTRo0AB9fX0ApkyZAoCpqSk2NjZAceDsgwcPiI+Px9nZWbm+kZERqampQOngWXt7e+XPOTk59O3bl4EDBzJq1Chu3bpFs2bNsLGxISwsjBEjRmBtba2E35bw9/dn1apVREREYGdnR48ePQBo3749AA0aNCAlJeU5VVOIP1WmFWeyAk7zpMaaJfXVPAmqrWS6d+9OWFgYZ8+eVZqb7du3Y2FhoWSZaWlplTnvvffew8fHhwcPHvDZZ5+Rnp7O5cuXyc3NRa1W8+mnnzJ16tRyz7W3t+fUqVM0bdqUpKQk0tPTMTMzq/BaJapVq0a7du0IDg5mwIABAOzdu5eBAwfi6+vLqlWriIyMZPz48co527ZtY8KECVSvXp0ZM2bw3XffARAdHc2AAQOIiYkptS1VReR9Is2Rf3iFEKLqkQZNwwwNDQkLC2POnDncvXuXgoICGjVqVGZD9L+ytrbG0NCQVq1aoaOjg4WFBR9++CHDhg1DS0uLrl27Vtj4fPTRR0yZMoVvvvmG7OxsAgMD0dF5sh+1q6srbm5uBAQEAPDmm2/i5+eHgYEBurq6BAYGljq+RYsWfPDBB5iZmWFoaIiTkxNbtmzhwoULjBgxggcPHhAUFATAggUL6NOnT5m7cEIIIYQoTYJqK7GSRuuNN954Ydc8e/YsW7ZsYcGCBc88RmhoKJaWlri5uT3R8RJUq1lyB03zpMaaJzXWLKmv5j1tUK3cQauEsrOzcXd3p3Pnzi+0OduyZQs7d+5UVo8KIYQQ4uWQBu0FOH78OJMmTcLBwYGioiLy8/MJDg5WXtL/q/v379OiRQtl/84XxdramrCwsCd6Z6xEeXfLJkyYUO6xFy5c4NChQ6XeYRNCCCFEWdKgvSDt27dnyZIlAPz0008sWLCgwhfja9SoobwD9iJt2rSJgICAp2rQnkaTJk0qvIUuQbXiacnCEiHEq0watJcgPT2dOnXqAHDixAmWLVsGFD/anD9/Prq6unh7exMZGcnRo0f54osv0NPTw8zMjDlz5nDhwgVWr16Nrq4ut27dYujQoRw7doyLFy8yfPhwOnTowOTJk9mxYwcAkyZNYuTIkRw6dIhjx45RWFhIv3798PT0VOb03//+lwsXLuDr68t//vMfQkNDOX/+PJmZmdjb2zN37lyGDh1aJsjWwsJCGWPevHnK0uF3332XESNG4Ofnx927d7l79y6jRo1i//79SqMqhBBCiPJJg/aCHDt2DA8PD3Jzc7l06ZLyf/+xsbEsXLhQebz49ddfKxlmRUVFTJ8+nYiICKytrdm4cSMrV67EycmJW7dusXv3bqKjo5k4cSLfffcdSUlJjB8/Hnd3d/T19YmLi8PS0pLExERatGjBhAkT2LJlC9bW1kRFRZWan5OTE02aNCEgIIDc3FxMTExYv3690swlJSWVG2Rbso/o999/T2JiIpGRkeTn5+Pu7q5kobVv3x5PT0+OHz/+AisuXnWVKVRTQj41T2qsWVJfzZOg2krq4Uecly9fZujQoRw5cgRra2uCg4MxMDAgKSmJ1q1bK+ekpaVhZGSkPHJs27YtixcvxsnJiQYNGqCrq4uxsTH16tVDrVZjampKTk4OAC4uLkRFRVG7dm369+8PwOLFi1m8eDEpKSl07ty5wrnq6emRmpqKt7c3BgYGZGVlkZeXV26QbUmDFh8fT5s2bdDS0kJXV5eWLVsSHx8PgK2t7fMvqHjtVaYVZ7ICTvOkxpol9dU8CaqtAiwtLZU/T5s2jYMHD2JkZISvry8Pp56Ym5uTkZFBcnIyVlZWnDhxgvr16wOPDpwF6NOnD+Hh4ZiZmfHvf/+b3Nxcvv76axYvXkxRURH9+vWjX79+yqPWkjGLioo4cuQIN2/e5IsvviA1NZXvvvuOoqKicoNsS9jb2xMVFYWnpyd5eXmcOXOGgQMHPtFcQd4n0iT5h1cIIaoeadBekJJHnCqViszMTPz8/NDX12fAgAG4urpiYmKCpaUlycnJyjlaWlrMnj2bCRMmoKWlhampKXPnziU2Nvax19PT06Nt27akpqYquwiYmpoyYMAATE1N6dSpk7LVVIm33nqLzz//nJUrV7JixQpcXV1Rq9XUrVuX5ORk6tatWybItkTXrl05ceIEQ4YMIS8vjz59+ijbSgkhhBDi6UhQ7SssICCA3r1706FDh+c25vMIsv0rCarVLLmDpnlSY82TGmuW1FfzJKhWADBy5EisrKyea3MmQbZCCCHEiyEN2isqPDz8uY85bNgwhg0b9tzHFUIIIURpr12D9nCqP0BOTg7Ozs54eHi80HncvXuXH3/8UYnUqExeRuK/BNW+PmRBiBBCPN5r16BB6ciL3Nxc+vTpw4ABAzAxMXlhc7h06RKHDx+ulA3aoxL/hRBCCKF5r2WD9rCMjAxUKhXa2tr8/vvvBAUFoa2tjZ6eHkFBQdSuXZvw8HC++uordHR0aNOmDZMnT+b+/ftMnTqVtLQ0oDguo1GjRmzfvp2IiAgKCwvp3r07EyZM4MCBA2zYsAGVSsXbb7+Nj48PYWFhXLx4kW3btuHo6Mj06dPJyclRrmthYcHEiRPJyMggOzubyZMn065dO2XeRUVFzJo1i/Pnz2Npacn169dZuXIly5YtU5L7V65cSUhICLdu3SItLQ1HR0cmTZqEn58fOjo63Lhxg9zcXPr27cv333/PzZs3WbFiBTdv3mTr1q0sWbKEXr160bp1a65cuUL16tUJDQ2lsLCQmTNncu3aNQoLC5k0aRLt2rWjW7duHDhwAD09PUJCQrCzs8PJyYlJkyZRVFREXl4es2bNolGjRi/rxy0qgVcxDFNCPjVPaqxZUl/Nk6DaJ1ASeVESqjp9+nQMDQ2ZNm0awcHBNGnShIMHDzJv3jw++eQTDhw4wNatW9HR0WHChAl8//33nDp1ivbt2+Pu7s7Vq1fx9/dn2bJlrFmzhj179qBWq5k3bx43btwgNDSUnTt3Uq1aNSZPnszRo0cZO3YsW7duZciQIUyaNAkPDw+6dOnCL7/8QkhICGPHjiUlJYUNGzZw584drl69WuozHDp0iLt377Jjxw5SU1Pp1auX8r2S5P7ExERatWqFi4sLOTk5SoMGUKdOHWbPns2MGTNITExkzZo1LF26lMOHD5e6e5aQkMDGjRupVasWQ4cO5dy5c/z++++Ym5szZ84c0tLSGDZsGF999VW5tT579izGxsYsWrSIuLg4MjIynvvPU1Qtr+LdWVkBp3lSY82S+mqeBNU+gYcfcT4sOTlZKV7btm1ZtGgRly9fpmXLlujq6gLQpk0bYmNjiYmJ4dixYxw4cAAo3l8zISGBBg0aoK+vD8CUKVM4e/YsqampjBkzBoDMzEwSEhJKpevHxMSwatUq1q5dS1FREbq6ujRo0ID3338fb29v8vPzy7wjd/nyZVq1agWAhYUFdnZ2yvdKxjYzM+PcuXMcO3YMIyMjcnNzlWOaNm0KgImJiXKuiYlJqWOgOCy3Vq1aANSqVYucnBxiYmI4ffo0Z8+eBSA/P1+5k1iiJL3F0dGRq1ev8vHHH6Ojo8O4ceMq+rEIIYQQ4v97LRu0ilhZWXHx4kUaN27MyZMnqV+/PnZ2dqxfv578/Hy0tbU5efIk//rXv7hz5w79+/fH2dmZO3fusH37durVq8fly5fJzc1FrVbz6aef4uvrS61atQgPD0dXV5eoqCiaNGlCRkYGhYWFANjZ2TFy5Ehat25NfHw8J0+e5NKlS2RmZrJ69WqSk5MZOnQoXbt2VebaoEED/u///g+Ae/fulbrDVpLcHxUVhbGxMYGBgVy7do3IyEilcXqSdP+KjrOzs6NmzZqMHTuW7OxsVq5ciampKWq1muTkZGxsbLh48SL29vYcP34cKysrwsPDOXPmDIsXL2bz5s1lxpQXxzVH/s9YCCGqHmnQHjJ79myCgoIoKipCW1ubOXPmULduXd555x3c3NwoLCzk7bffpkePHrRp04apU6cSGRlJRkYG48ePx8LCgg8//JBhw4ahpaVF165dqVOnDp6ennh4eFBQUECdOnV45513SE9PJyYmhg0bNuDr60tAQAA5OTlkZ2czdepU6tevz/Lly9m9eze6urp8+umnpebq5OTEkSNHGDp0KJaWlujr6yt3+Up06NABb29vTp8+TbVq1XjjjTdK7VTwrIYOHcq0adMYNmwYGRkZuLu7o1KpGD16NGPGjKFOnTrKgovGjRvj5eXFxo0bUalUfPLJJ3/7+kIIIcSrTnYSqKLi4+O5ePEi/fr1Iy0tjXfffZfvv/8etVr9sqf21GQnAc2SO2iaJzXWPKmxZkl9NU92EnhN1KpVi5CQEDZu3EhBQQE+Pj5VsjkTQgghRFmVpkH7a4BsZmYmNjY2hISEVNh4BAcH88EHH2BgYKCEvvr5+dG3b18cHR3/1nxcXV1ZvHgxNjY2T3Xeli1bXkjavoGBAStXrtTI2CdPnsTY2JjGjRtrZPzySFBt5SfvCQohxIujetkTeFj79u3ZvHkzmzdvJioqCl1dXQ4fPlzh8VOnTqV27dpK6GtloKmm6UXauXPnc3lXTQghhBDPptLcQfur3NxckpOTMTU1BWDRokWcPHmSoqIiPD09eeedd/Dw8CAgIKBU6CvAtm3bWLt2LRkZGQQEBGBhYcG4ceMwMzPD0dGRTp06lRtIu2TJEn788Udq1qypxEakp6czefJkMjIyKCgoYOLEiXTo0AFnZ2f+8Y9/cOnSJbS0tFixYgVbtmzh3r17BAQEMHXqVKZMmUJCQgIFBQV88MEH9O3bFw8PDxo1akRsbCwGBga0adOGn376ifT0dMLDwwkMDMTZ2RknJyfi4+OZP38+/v7++Pv7o6Ojg7a2NgsWLMDa2lqpVWhoKNeuXSMtLY179+7h7u7Ot99+y5UrV5g/fz6tWrUqN2w3NDSUxMRE7ty5w40bN/D398fc3Jwff/yR6OhoHBwcOHz4MN9++y35+fkYGxsTGhrKvn37+OGHH8jOzuaPP/7gww8/ZNCgQcrPw97enoiICFJSUhgzZswjA3eFEEIIUValatBKAmTv3LmDSqXC1dWVDh068MMPP5CYmMjWrVvJycnB1dWVTp06Kec9HPp65swZmjVrxscff0xUVBRRUVGMHj2a27dvs3PnTtRqNYMGDSoTSDt+/HhOnjzJjh07yMrKUoJfV65cSceOHRkxYgRJSUm4ublx8OBBMjMz6devH9OnT+ezzz7jyJEjjBs3ji1bthAQEMCWLVswNzdn4cKFZGRkMGjQINq3bw9AixYtmDZtGqNGjUJfX5/169fj6+vLyZMncXFxISIiAicnJ3bs2MHgwYP5+eefadasGX5+fpw6dYp79+6VatAA9PX1WbduHatXr+aHH34gLCyMnTt38tVXX1GtWrVyw3YB1Go1a9eu5ejRo4SHh7Nu3To6d+5M3759qVmzJnfv3lV2QRg1ahTnzp0DindgWLduHVevXmXs2LEMGjSo3J/pH3/88cjAXVF1SMp4xSSFXfOkxpol9dW8Kr2TQEmAbFpaGiNHjlTe/4qJiSE6OloJa83Pz+fGjRsVjtOsWTMALC0tyc7OBsDGxkZ5l628QNq4uDiaN2+OSqXCyMiIhg0bAsWrJUv2y7S2tsbIyIjU1FTgz7DXkgDXh8XHx9OxY0cAjIyMsLe3JyEhodT8TExMlHfuTExMyMnJoXv37gQHB3Pnzh2OHj2Kt7c3hYWFrFmzhtGjR2NsbIyXl1eZz1wyF2NjY2VMU1NTcnJyKgzbhT9T3WvWrFkmpFalUqGrq4u3tzcGBgbcunWL/Px8AOX9tFq1apU5D/4Mqn1c4K6oOmSFV8VkBZzmSY01S+qrea/ETgIld56GDx/O7t27sbOzo127dgQFBVFYWMiKFStKvbyvUqmU0FcoP1xVpfrzdbvyAmltbW3ZtGkThYWFZGdnExcXB4C9vT2nTp2iadOmJCUlkZ6ejpmZWYXXKWlMSs7r2bMnGRkZxMTEPNGCAy0tLZydnQkODqZTp07o6uqyf/9+3n77bcaPH8++fftYu3Ytc+fOLXNeRSoK27148WK552lpaVFUVMTFixc5ePAg27dv58GDBwwaNOiRQbdqtZrbt29jb2/P77//jrW19WMDd0vIC+iaI//wCiFE1VMpGzQABwcHPDw8mD17Nv/+9785ceIE7u7uZGVl0aNHD4yMjJRj69Wrp4S+PomKAmn79OnD4MGDsbKyonr16kDx6sIpU6bwzTffkJ2dTWBgIDo6FZfN3t4eHx8f5syZw/Tp03FzcyMnJ4fx48crYz7OoEGDcHJyUnYKaN68ufLOmEqlwt/f/4nGKdGoUaNyw3YvXrxY7vEtW7YkJCSExYsXU61aNQYNGoRaraZGjRqPXDwwfPhwAgMDqVWrFlZWVgCPDdwVQgghRFkSVFsJJSUl8fnnn7Nx48aXPZUXQoJqNUvuoGme1FjzpMaaJfXVvKcNqq1UMRsCvvnmG0aPHs1nn332sqcihBBCiJdEGrRKpnfv3uzdu5cWLVo88xjHjx+nQ4cOeHh44OHhgaurq7JBeXBw8CMXWIwfPx4ADw8P4uPjn3kOQgghhHh2lfYdNPH3lKyIheJMuT59+jBgwACmTp36yPOWLVv2IqZXhuwkoDmTJk162VMQQgjxlKRBew1kZGSgUqnQ1tZWwmT379/P5cuXuXPnDunp6UybNo02bdrQqVMnjh49qpxbUVBviZycnHKDaLt3707Lli35448/aNCgAcHBwaVW0gohhBCiYtKgvaJKQn+1tLTQ1dVl+vTpGBoaljpGX1+fTZs2ERsby2effcaePXvKjFNRUG9Js1VREG1SUhITJ07kjTfeYOLEiRw8eFAJ/xUvlgRQap7UWPOkxpol9dW8Kh1UK56fhx9xPuoYKA6TTUlJKfeYioJ6LS0tlXPLC6KtVasWb7zxBgBvvfUWV65ceS6fSzw9fX19WZ2lYbICTvOkxpol9dW8VyKoVrwY0dHRDBgwgJiYmDJbR5V4VFAvUGEQbVJSErdv36ZGjRr8+uuvDBgw4JFzkaBazZH/KxZCiKpHGrTX2IULFxgxYgQPHjwgKCio3GMeF9RbURCtWq0mKCiImzdv0rJlS7p160ZcXJyyV6kQQgghKiZBta+p0NBQLC0tcXNz08j4f11s8CgSVKtZ8uhC86TGmic11iypr+ZJUK0QQgghRBUnDdor4vjx43h5eZX5upeXF7m5uWW+PmHChKe+e3bkyBH8/Pye6NgnvXsmhBBCiLLkHbRX3ONWclYWElRbPlk8IYQQrydp0F5x3bp148CBAwQHBytRF+fPn2fGjBk0a9aMefPmUVhYqITVtm7dmq5du2JnZ4ednR1Dhw5lypQpVKtWjWrVqmFqalpq/NTUVCZNmkRRURF5eXnMmjULQ0NDJk6cSI0aNUhKSsLR0bHcu3tCCCGEKJ80aK+JwMBAALZu3UrNmjX517/+xYEDB/D19aVRo0bs3buXqKgoWrduzc2bN4mKisLc3JxPP/2UTz/9lE6dOrF69WouX75catyzZ89ibGzMokWLiIuLIyMjA0NDQ65fv866deswNjbG3d2d6OhomjVr9jI+epX2PCIyJIBS86TGmic11iypr+ZJUK2o0P79+zl06BArVqxAS0sLKysrVqxYgb6+PpmZmRgZGQFgbm6Oubk5ALGxscrG7a1bty7ToDk6OnL16lU+/vhjdHR0GDduHACNGzdW8tJatGjBlStXpEF7Bs9jVZWsztI8qbHmSY01S+qreRJUK8p15MgRtmzZwtq1a9HV1QUgODiYkJAQ7O3tWbp0KdevXwcotWemnZ0dZ86cwdHRkfPnz5cZ9/jx41hZWREeHs6ZM2dYvHgxc+fOJT4+ngcPHqBWqzl79izvvffeI+cn71oJIYQQf5IG7RVy9OhRBg0apPx90aJFyp8//fRTGjZsqLyM361bN/r378/HH39M9erVqVmzJmlpaWXGnDlzJl5eXqxbtw4LCwv09PRKfb9x48Z4eXmxceNGVCoVn3zyCQC6urpMnDiRlJQU+vTpQ+PGjfnll184ffo048eP18THF0IIIV4ZElQrnrvExES8vb2JjIx8ouMlqFaz5NGF5kmNNU9qrFlSX82ToFohhBBCiCpOGjTx3NnY2Dzx3TMhhBBClFWl30GLjY1l4cKFPHjwgKysLLp06cKECRM4ceIEW7du/VshrTdu3ODixYt069btiY53dXVl8eLFnDhxAlNTU7p37/7M1/6rCxcucOjQoQrf3crJyWHPnj24uLg8t2s+TkREBCkpKQwdOpTly5f/7Q3QJai2fLJ4QgghXk9VtkFLT0/H29ub0NBQ6tevT0FBARMnTmTr1q3Y2dn97fGPHTvG5cuXn7hBK/HwS/rPS5MmTR75bsDt27fZvn37C23QStSoUeNvN2dCCCGEKK3KNmiHDh2iXbt21K9fHwBtbW3mz5+Prq4uZ86c4dq1a4wePZrU1FS6du2q3FlbtmwZUBwYN3/+fGxtbdm8eTP79u1DS0uLvn378v7777N69Wqys7N56623qFWrFkFBQWhra6Onp0dQUBC1a9dmyZIl/Pjjj6VWQIaGhmJpaYmdnR1hYWGoVCpu377NkCFDeP/99/Hw8CAgIAB7e3vlLtSYMWOYOHEiGRkZZGdnM3nyZNq1a6d81uPHjyt3BHv16kXr1q25cuUK1atXJzQ0lLCwMOLi4li2bBkjRoxg6tSpynymTZtGo0aNSu0OcP/+fXR0dLhx4wa5ubn07duX77//nps3b7JixQrq1avHokWLOHnyJEVFRXh6evLOO+9w6tQp5syZg6mpKSqVilatWpVaEFCya4Genh4hISHY2dnh5ORUZqeBRo0avdhflipMgmqrBqmx5kmNNUvqq3mvTVBtcnIydevWLfU1Q0ND5c85OTmsWLGCgoICnJycmDBhgvJI1NramrCwML7++mt69uzJ/v37+c9//oOWlhaenp7885//ZMyYMVy+fJnu3bszaNAggoODadKkCQcPHmTevHmMHz+ekydPsmPHDrKysujVq1eZOSYlJbF7924KCwtxdnamT58+5X6WP/74g5SUFDZs2MCdO3e4evVqhZ87ISGBjRs3UqtWLYYOHcq5c+cYO3YsMTExjB8/noULF9K+fXvc3d25evUq/v7+RERElNodwM/Pjzp16jB79mxmzJhBYmIia9asYenSpRw+fBhbW1sSExPZunUrOTk5uLq60qlTJ+bOncuiRYuwtbVl5syZT/RzKm+nAfHkJKi2apAaa57UWLOkvpr32gTV1q5dm99//73U1xISErh16xYADRo0QK1WA6CjU/wxra2tCQ4OxsDAgKSkJFq3bk1MTAw3btzA09MTgHv37vHHH3+UGjc5OVkpatu2bZVmo3nz5qhUKoyMjGjYsGGZOb711lvKHBo0aFBm3JKEkwYNGvD+++/j7e1Nfn4+Hh4eFX5uc3NzatWqBUCtWrXIyckp9f2YmBiOHTvGgQMHgOJHwSXnlewOANC0aVMATExMlEfCJiYm5ObmEhMTQ3R0tDKP/Px8bty4QVJSEra2tkDxrgJ//TzlfbaKdhoQQgghRMWqbIPWtWtXVq1ahZubG/Xq1SMvL4958+bRsWNHHBwc0NLSKnPOtGnTOHjwIEZGRvj6+lJUVISdnR0ODg6sXbsWLS0tNmzYQMOGDTlx4gSFhYUAWFlZcfHiRRo3bszJkyepX78+tra2bNq0icLCQrKzs4mLiytzvQsXLlBQUEBubi5xcXG88cYbqNVqbt++jb29Pb///jvW1tZcunSJzMxMVq9eTXJyMkOHDqVr167lfu7yPpdKpVLmamdnR//+/XF2dubOnTts375dOeZx45Sws7OjXbt2BAUFUVhYyIoVK7CxsaFGjRrEx8djb2/PuXPnymycrlarSU5OxsbGhosXL2Jvb1/uTgObN28uc015GV4IIYT4U5Vt0IyMjJg3bx7Tpk2jqKiIzMxMunbtiru7OydOnCj3nAEDBuDq6oqJiQmWlpYkJyfTuHFjOnTogJubG7m5ubRo0QJra2saNmzIypUradasGbNnzyYoKIiioiK0tbWZM2cOdevWpU+fPgwePBgrKyuqV69e5nr5+fl8+OGH3L17l3HjxmFhYcHw4cMJDAykVq1aWFlZAVC/fn2WL1/O7t270dXV5dNPP32qWlSvXp28vDwWLlzI2LFjmTp1KpGRkWRkZDxTan+3bt04ceIE7u7uZGVl0aNHD4yMjFi4cCG+vr4YGhpiaGhYpkEbPXo0Y8aMoU6dOpiYmAAV7zQghBBCiIrJTgIa8vCL/eLRZCcBzZJ3SzRPaqx5UmPNkvpqnuwkIIQQQghRxVXZR5yVnYWFBZmZmXh4eLzSIbrPiwTVlk/ezRNCiNeTNGga8DqF6AohhBDi+ZMGTQNepxDd1NTUMkG0hoaGTJw4kRo1apCUlISjoyNeXl4v/OcghBBCVFXSoGnA6xSiW14QraGhIdevX2fdunUYGxvj7u5OdHQ0zZo1+/vFfc3ITgJVg9RY86TGmiX11bzXZieByux1CtGtKIi2cePGmJmZAdCiRQuuXLkiDdozkJ0EqgapseZJjTVL6qt5r81OApXZ6xSiW14Q7dy5c4mPj+fBgweo1WrOnj3Le++998iaycvwQgghxJ+kQdOA1ylEt6IgWl1dXSZOnEhKSgp9+vShcePG/PLLL5w+ffqZwnOFEEKI14kE1b6GNB2im5iYiLe3N5GRkU90vATVapY8utA8qbHmSY01S+qreRJUK4QQQghRxb2WDdrq1avx9PRk5MiRjBo1ivPnzz/V+cePH6/SsRHt2rVT7p65urqSmJhY4bHdunUjJyenwu9/9913JCUllfqajY3NE989E0IIIURZr907aHFxcRw+fJiIiAi0tLS4cOECvr6+7Nmz52VPrUratGkTAQEBWFtb/61xZCeB8sniCSGEeD29dg2ahYUFN27cYMeOHTg6OtKkSRN27NgBwP/+9z+Cg4MpKirC2tqakJAQrl27xuzZswEwMzNjzpw5pcbbs2cPGzduRK1WU79+fQIDA9m7dy+HDh0iIyODtLQ0PvnkE3r37s3Ro0f54osv0NPTU8a6cOECISEh6Orq4urqytKlSzlw4AB6enqEhIRgZ2eHk5NTmTDYRo0aKXOIiori8uXL+Pj4kJOTwzvvvMPhw4fx8PCgcePGxMbGkpGRwb///W/q1KnzyBBbNzc34uPjCQgIYPPmzco1YmJimDdvHoWFhaSnpzNt2jTS09OVBnfhwoX4+voqd85KtpdKSkpi/vz56OjoYGJiQkhICEZGRhr9GQshhBBV3WvZoK1cuZItW7awfPly9PX18fLyonfv3kyfPp0lS5Zgb2/Pl19+SXx8PLNmzWLOnDk4ODiwfft21q5dS8eOHQFIS0sjNDSUXbt2YWRkxJw5c9i2bRsGBgZkZWWxfv16UlNTcXFxoVu3bkyfPp2IiAisra3ZuHEjK1euxMnJiZycHLZv3w7A0qVLy8y5vDDYJ9WiRQumTp3KkiVL+Oqrr3BycnpsiG154uLi8PX1pVGjRuzdu5eoqChmz55NkyZNCAgIQFdXt9zzDh48SM+ePRk1ahSHDx8mPT1dGrSnIEG1VYPUWPOkxpol9dU8Cap9jGvXrmFkZMTcuXMBOHfuHGPGjKFdu3bcuXMHe3t7AN5//30ApUkDyMvLw9bWVhkrISEBBwcHpeFo27YtP/30Ey1btqRt27aoVCosLS0xMTEhJSUFIyMj5VFg27ZtWbx4MU5OTqXGfFjJAtuKwmAfdU6Jpk2bAlCzZk1SUlKeKMS2PFZWVqxYsQJ9fX0yMzMf22SVzGPs2LGEhYUxYsQIrK2tadGixRNdTxSToNqqQWqseVJjzZL6ap4E1T7GpUuXiIiIICwsDD09PWxtbTE2NkZbWxsrKyuuXr1K/fr1Wb16Nba2ttja2jJ//nxq167N6dOnuX37tjKWjY0N8fHxZGVlYWBgwIkTJ5RmKzo6GoCUlBQyMjKwsrIiIyOD5ORkrKysOHHihLJXp0r151oNtVpNcnIyNjY2XLx4EXt7+3LDYB9+/Kinp6fMq+S6FakoxPZxYwQHBxMSEoK9vT1Lly7l+vXrAGhpaVFUVISenh537tyhoKCAzMxMZeHB3r17GThwIL6+vqxatYrIyMhyc9DkXSshhBDiT69dg9arVy/i4+NxcXHBwMCAoqIiPv/8c4yNjZk1axZTpkxBpVJRo0YNPD09qVWrFr6+vhQUFADFjUpycjJQ/Lh0woQJDB8+HJVKRb169fDx8eGrr74iJSWFESNGcP/+fWbOnIm2tjazZ89mwoQJaGlpYWpqyty5c4mNjS01v9GjRzNmzBjq1KmDiYkJUHEYbInOnTsTERGBm5sbzZo1K7Xv5181adKk3BDbd955h0mTJnHy5EmaN29e5rz+/fvz8ccfU7169VLvrr311lt8/vnnhIeH06lTJwYPHky9evV44403AHjzzTfx8/PDwMAAXV1dAgMDn+XHJoQQQrxWJKhWAx5+aV88ngTVapY8utA8qbHmSY01S+qreRJUK4QQQghRxb12jzhfhEGDBj3X8VavXs3PP/+MSqVCS0sLLy+vch9DCiGEEOLVIA1aJfe6BOu+akG1suhBCCHE3yENWiX3qGBdDw8PbG1tuXLlCkVFRSxZsgQLCwtmzJjBrVu3SEtLw9HRkUmTJuHn58fdu3e5e/cuo0aNYvXq1Uo4bo0aNcoE6Pr5+TFu3DjefPNNevfujY+PDz179mTkyJHMnTtXiQtJTU0tE6JraGjIxIkTqVGjBklJSTg6OlbprbGEEEKIF00atEruUcG6AK1btyYwMJAvv/ySVatW4enpSatWrXBxcSEnJ0dp0ADat2+Pp6cnx48fV8Jxi4qK6N69e5kA3V69enHkyBHMzMzQ09Pj6NGjtG/fnpycnFLbOpUXomtoaMj169dZt24dxsbGuLu7Ex0dTbNmzV5GCV+KyhT4KAGUmic11jypsWZJfTVPgmpfMY8K1oXipguKG7XDhw9jZmbGuXPnOHbsGEZGRuTm5ipjPRyIW/LntLS0cgN0x44dy8cff4y5uTkffvgh69ev58iRI3Tt2rXU/CoK0W3cuDFmZmZA8W4GV65cea0atMq0GkpWZ2me1FjzpMaaJfXVPAmqfcU8KlgX4Pz589SsWZNff/0VBwcHoqKiMDY2JjAwkGvXrhEZGamk+mtpaSnjloTjmpublxuga2pqir6+PgcOHCA0NJRvvvmGjRs3EhISUmp+5YXozp07l/j4eB48eIBarebs2bO89957j/yc8s6WEEII8Sdp0Cq5RwXrAuzatYsNGzZQrVo1FixYQEpKCt7e3pw+fZpq1arxxhtvKMG65dHS0io3QBege/fuREVFYWZmxj//+U/+85//UK9evVLnVxSiq6ury8SJE0lJSaFPnz40btyYX375hdOnT5e7k4AQQggh/iRBtVWYh4cHAQEByv6hlUViYiLe3t5ERkY+0fESVKtZ8uhC86TGmic11iypr+ZJUK0QQgghRBUnjzirsIc3TK9MbGxsnvjumRBCCCHKkgatEjp+/DiTJk3CwcEBgJycHJydnfHw8CA4OJgPPviA2rVrl3vu+PHjWbZs2VM9/lyyZAk//vgjvr6+yurQF02CaoUQQog/SYNWSbVv354lS5YAkJubS58+fRgwYABTp0595HnLli176mvt37+fXbt2YWRk9ExzFUIIIcTzJQ1aFZCRkYFKpUJbW1u5M7Z//34uX77MnTt3SE9PZ9q0abRp04ZOnTpx9OhR5dz09HQmT55MRkYGBQUFTJw4kQ4dOijfX7ZsGbdu3eKjjz5izJgx7N69W2kMS8b69ttvWbNmDTo6OtSpU4cFCxaQlpaGn58f9+/fp6ioiPnz57N3714sLS1xc3MjPj6egIAANm/ezJIlSzh27BiFhYX069cPT0/PF13CF64yBT5KAKXmSY01T2qsWVJfzZOg2lfEsWPH8PDwQEtLC11dXaZPn46hoWGpY/T19dm0aROxsbF89tln5e7PuXLlSjp27MiIESNISkrCzc2NgwcPKjlo48ePJyoqivDwcH777bdy57Jv3z48PT3p168fu3fvJiMjg5UrV9KtWzfc3Nz45ZdfOHv2bIWfZffu3WzZsgVra2uioqKevShVSGVaDSWrszRPaqx5UmPNkvpqngTVviIefsT5qGMAGjRoQEpKSrnHxMfH4+zsDIC1tTVGRkakpqZiaWn52DmUJLD4+/uzatUqIiIisLOzo0ePHly5coXBgwcDKHfkQkNDyx1n8eLFLF68mJSUFDp37vzY6wohhBCvO2nQqrDo6GgGDBhATExMqf0xH2Zvb8+pU6do2rQpSUlJpKenK1sw/ZWenh63b98G4Pr169y7dw+Abdu2MWHCBKpXr86MGTP47rvvsLe359y5czRu3JiTJ0/y3//+F1NTU+X86OhooPj9ua+//prFixdTVFREv3796NevH3Xq1Cl1bXmpXgghhPiTNGhV2IULFxgxYgQPHjwgKCio3GM++ugjpkyZwjfffEN2djaBgYHo6JT/Y2/evDnGxsa4uLhgb2+PjY0NULyX5gcffICZmRmGhoY4OTnRpUsXpkyZojxWnTNnDgCTJk3i5MmTNG/eHAC1Wo2pqSkDBgzA1NSUTp06VbgCVQghhBDFZCeBKio0NFR5Ib+qk50ENEveLdE8qbHmSY01S+qrebKTgBBCCCFEFffKP+I8ceJEqZfXb926hZmZGdu3b//bY+fk5LBnzx5cXFxKff327dssX76cgICAcs/r1q0bBw4cQE9PT/nakSNHuHnzJkOGDHnsdV/GHpzHjx9n69atj1248KwqS1CtvAsnhBCiMnjlG7R//OMfypZIKSkpuLu74+fn91zGvn37Ntu3by/ToNWoUaPC5qwijo6Oz2VOQgghhKj6XvkGrUReXh6ffvopo0aNUp77zps3T8kieffddxkxYgR+fn6o1WquX79OcnIy8+bNo1mzZuzZs4eNGzeiVqupX78+gYGBhIWFERcXx7JlyygqKuLMmTNkZWURHByMv78/kZGRfP/990q6f9OmTZk1axYAAQEBJCYmAsVhsYcOHeLy5cv4+PiwaNEizp8/T2ZmJvb29sydO7fcz3T//n2mTp1KWloaANOmTaNRo0alwmq9vLwYOnQoLVu2xN/fnxs3bpCXl8f06dNp3rw5U6ZMISEhgYKCAj744AP69u2Lh4cHtra2XLlyhaKiIuWu2bVr1xg9ejSpqal07dqVCRMm4OHhgbm5Oenp6VhYWNC/f3+cnJyIj49n/vz5+Pv74+/vj46ODtra2ixYsKDCFadCCCGEKPbaNGjBwcE4ODgojxC///57EhMTiYyMJD8/H3d3dyVXrHbt2gQGBhIZGcm2bdvw8vIiNDRU2Q5pzpw5bNu2jbFjxxITE8P48eMJDQ3Fzs6OadOmKY1Xfn4+QUFBbN++nerVqyup/QDvvfcebdq0wc/Pr1Tyf0ZGBiYmJqxfv15J3k9KSiq3qQkLC6N9+/a4u7tz9epV/P39iYiIKPfzb926lTp16rBkyRJiYmL4+eefiY6OxtzcnIULF5KRkcGgQYOUGrRu3ZrAwEC+/PJLVq1aRc+ePcnJyWHFihUUFBTg5OTEhAkTAHB2dqZnz54cO3aMiIgInJyc2LFjB4MHD+bnn3+mWbNm+Pn5cerUKe7du1epG7RXMUlbEsI1T2qseVJjzZL6ap7sJFCOnTt3cunSJTZt2qR8LT4+njZt2ihJ/S1btiQ+Ph74MwW+Zs2a/PrrryQkJODg4KDsVdm2bVt++uknnJycSl3H1ta21N/T0tIwMTGhevXqQHFqf4mSGApLS0uys7OVr+vp6ZGamoq3tzcGBgZkZWWRl5dX7ueKiYnh2LFjHDhwACje1umvShbpXr58WXmM2rBhQxo2bMisWbPo2LEjAEZGRtjb25OQkABQqlE7fPgwUByIq1arAUpFdZR87nbt2hEcHMydO3c4evQo3t7eFBYWsmbNGkaPHo2xsTFeXl7lfpbK4lVcxSSrszRPaqx5UmPNkvpqnuwk8Bdnz55l1apV/Oc//0FXV1f5ur29PVFRUXh6epKXl8eZM2cYOHAgAFpaWqXGsLGxIT4+nqysLAwMDDhx4gS2traoVCoKCwuV40q2TypRvXp10tPTuXv3LmZmZsyePZv+/fuXe40SJYsFvvjiC1JTU/nuu++oKAnFzs6O/v374+zszJ07d5SFD/n5+WRmZqKrq0tcXJzyec+dO0ePHj1ISEjgiy++4K233uLUqVP07NmTjIwMYmJilOyz8+fPKw2qg4PDI+dc8nUtLS2cnZ0JDg6mU6dO6Orqsn//ft5++23Gjx/Pvn37WLt2bbmPbOXlfCGEEOJPr3yDtmTJEoqKikrduTEwMGDVqlWcOHGCIUOGkJeXR58+fWjWrFm5Y1hYWDBhwgSGDx+OSqWiXr16+Pj4AMXvti1cuBB9ff0y56lUKmbOnMlHH32ESqWiadOmvPnmm4+cb4sWLVixYgWurq6o1Wrq1q1LcnIydevWLXPs2LFjmTp1KpGRkWRkZCh36IYPH86QIUOwsbFRQmGHDh3KlClTGDZsGAUFBUyZMoVGjRoxffp03NzcyMnJYfz48crdvl27drFhwwaqVavGggULiImJeYJqw6BBg3BycuL//u//gOI7hZMnTyY0NBSVSoW/v/8TjSOEEEK8ziSoVpTxd2I8kpKS+Pzzz9m4ceMTnyNBtZoljy40T2qseVJjzZL6ap4E1YqX5ptvvmH06NF89tlnL3sqQgghRJUmDRrFIawdOnTAw8MDDw8PBg0axKeffkpubm6F5wQHB3Pjxg3u3r3L3r17AfDz8+PIkSN/ez6urq7KStCnsWXLlr99bYDNmzc/092z3r17s3fvXlq0aPFc5iGEEEK8rl75d9CeVPv27Uul5H/22WccPnyYPn36lHv81KlTgeLm7vDhwzg7O7+QeT7KypUrGTZs2MuexjORnQSEEEKIP0mDVo7c3FySk5MxNTUFYNGiRZw8eZKioiI8PT155513lPe0wsLCuHjxItu2bQNg27ZtrF27loyMDAICArCwsGDcuHGYmZnh6OhIp06dCAoKQltbGz09PYKCgqhduzZLlizhxx9/pGbNmkrwbHp6OpMnTyYjI4OCggImTpxIhw4dcHZ25h//+AeXLl1CS0uLFStWsGXLFu7du0dAQABTp06tMIC2UaNGxMbGYmBgQJs2bfjpp59IT08nPDycwMBAnJ2dnypo9vTp08yfPx8dHR1MTEwICQnh22+/5dChQ2RkZJCWlsYnn3xC7969X/wPUgghhKiipEH7/44dO4aHhwd37txBpVLh6upKhw4d+OGHH0hMTGTr1q3k5OTg6upKp06dlPPGjh3L1q1bGTJkCGfOnKFZs2Z8/PHHREVFERUVxejRo7l9+zY7d+5ErVYzaNAggoODadKkCQcPHmTevHmMHz+ekydPsmPHDrKysujVqxdQfEesY8eOjBgxgqSkJNzc3Dh48CCZmZn069eP6dOn89lnn3HkyBHGjRvHli1bCAgIYMuWLRUG0LZo0YJp06YxatQo9PX1Wb9+Pb6+vpw8eRIXF5enDpo9ePAgPXv2ZNSoURw+fFjJYsvKymL9+vWkpqbi4uJC9+7dS2WnVVavYlCjBFBqntRY86TGmiX11TwJqn1GJY8409LSGDlypJIHFhMTQ3R0NB4eHkBxxtiNGzcqHKckquPhAFobGxsl4DU5OVlZxdG2bVsWLVpEXFwczZs3R6VSYWRkRMOGDYHiMN2SR6fW1tYYGRmRmpoKFG8bBVCrVi1ycnJKzSE+Pr7CANqS+ZmYmCj5ZiYmJuTk5NC9e/enDpodO3YsYWFhjBgxAmtra+X9s7Zt26JSqbC0tMTExITU1FSsrKye9Mfx0ryKq5hkdZbmSY01T2qsWVJfzZOg2r+p5M7T8OHD2b17N3Z2drRr146goCAKCwtZsWKF0rwBZcJqywtzfTjA1srKiosXL9K4cWNOnjxJ/fr1sbW1ZdOmTRQWFpKdnV0qXPbUqVM0bdqUpKQk0tPTMTMzq/A6JYkpJeeVF0D7KM8SNLt3714GDhyIr68vq1atIjIyktq1axMdHQ0Ub1CfkZGh5KtVRN79EkIIIf4kDVo5HBwc8PDwYPbs2fz73//mxIkTuLu7k5WVRY8ePZQtnwDq1atHTEwMGzZseKKxZ8+eTVBQEEVFRWhrazNnzhzq1q1Lnz59GDx4MFZWVkoz89FHHzFlyhS++eYbsrOzCQwMfORjQnt7e3x8fJgzZ06FAbSP87RBs2+++SZ+fn4YGBigq6tLYGAgJ0+eJCUlhREjRnD//n1mzpyJtrY269evp169enTv3v2J5iKEEEK8riSoVpTyLEGzfxUVFcXly5eV3RYeR4JqNUseXWie1FjzpMaaJfXVPAmqFc9MgmaFEEKIyqFSN2irV6/mn//8Z5mX4DUpJyeHbt26vbDrVSbPK2h20KBBT3z3TAghhBBlVep30Pbu3Uvfvn356quvGDRo0MuejtAgCaoVQggh/lRpG7Tjx49Tr149hg4dyuTJkxk0aNBjg1YPHTrE999/T3Z2Nrdv32b48OEcOnSI2NhYPv/8c3r06MGePXvYuHEjarWa+vXrExgYSG5uLj4+PqSnp1OvXj1lDh4eHpibm5Oenk5oaCjTpk3j/v37pKWl4eLigru7+xPNqeR9rJycHN555x0OHz7Ml19+ye7du1GpVLRu3RpfX99Sn3/JkiUcO3aMwsJC+vXrh6enJydOnGDZsmVAcZ7K/Pnz+fHHH0lPT2f8+PHk5ubSv39/9uzZQ2hoKOfPnyczMxN7e3vmzp1LaGgoiYmJ3Llzhxs3buDv70/nzp3LDb41MDBgxowZ3Lp1i7S0NBwdHZk0aRJ+fn7cvXuXu3fvMmrUKPbv36/swNCpUyeOHj2Kn58fOjo63Lhxg9zcXPr27cv333/PzZs3WbFiRakaCyGEEKKsStugbd++HRcXF+zs7FCr1fzvf/8DHh20CpCZmUl4eDhfffUVGzZsIDIykuPHj7Np0ybefvttQkND2bVrF0ZGRsyZM0fZAaBhw4Z4eXnxv//9j+PHjyvzcHZ2pmfPnkRHR9OvXz969epFUlISHh4euLu7P9GcyhMVFcX06dNp1aoV//nPf8jPzy+1QnP37t1s2bIFa2troqKiAIiNjWXhwoVYW1sTFhbG119/jbu7O+7u7nzyySccOnSIrl27kpubi4mJCevXr1cavKSkJADUajVr167l6NGjhIeH07lz53KDb1u2bEmrVq1wcXEhJydHadCgODPO09OzVJ3+qk6dOsyePZsZM2aQmJjImjVrWLp0KYcPH8bT0/MpfxtenFcxqFECKDVPaqx5UmPNkvpq3isRVHvv3j2OHDlCamoqmzdvJiMjQ9kI/FFBq/Bn0KixsTH29vZoaWlhampKTk4OCQkJODg4KDEZbdu25aeffgKgc+fOALRs2bJUo2RrawsUB89u3LiRb7/9FiMjI/Lz85VjHjenEg8vmJ07dy7h4eGEhITQqlUr/rqYdvHixSxevJiUlBRlbtbW1gQHB2NgYEBSUhKtW7fG1NSUJk2acPr0aXbt2oWvry96enqkpqbi7e2NgYEBWVlZ5OXllapPzZo1S20G/9fgWzMzM86dO8exY8cwMjIqdWxJTf7q4c9QMp6JiQl2dnbKnx+1AX1l8CquYpLVWZonNdY8qbFmSX0175UIqt2zZw/vvfee8tjvwYMHdO/eHXNz88eeW16AawkbGxvi4+PJysrCwMCAEydOYGtri5aWFr/99hs9evTg999/L9V8lYwXHh5Oq1atcHd359ixY/zwww9P9Fn09PS4ffs2gBLeChAZGcmsWbPQ09Nj1KhRnDlzhn/84x9A8V6gX3/9NYsXL6aoqIh+/frRr18/pk2bxsGDBzEyMsLX11dpiFxdXdm4cSPZ2dnY29tz6NAhbt68yRdffEFqairfffedcmxF9fnr16OiojA2NiYwMJBr164RGRlZZoyHP9v169e5d+9eheM9jrz7JYQQQvypUjZo27dvZ8GCBcrfq1WrRq9evdixY8ffGtfCwoIJEyYwfPhwVCoV9erVw8fHB21tbfz9/XFzc8POzg5dXd0y53bt2pWAgAD27t2LmZkZ2traT3Q3qHPnzkRERODm5kazZs0wNDQEoFGjRgwePBhzc3Osra1p2bKlco5arcbU1JQBAwZgampKp06dqF27NgMGDMDV1RUTExMsLS1JTk4G4B//+AfTp09n3LhxQPEj1xUrVuDq6oparaZu3brKsU+qQ4cOeHt7c/r0aapVq8Ybb7xRZozmzZtjbGyMi4sL9vb2T7RbgRBCCCEeT4JqxUsnQbWaJY8uNE9qrHlSY82S+mqeBNUKIYQQQlRx0qAJIYQQQlQylfIdtBelJLbiwYMHZGVl0aVLFyZMmPDUL7g/TnBwMB988AG1a9dWvhYfH09AQACbN29+qrE8PDwICAjA3t7+uc6xIpcuXSI9PZ22bdvi5eXF/PnzUavVjz1v9erVtG/f/ol3JXgeQbWy0EAIIcSr4rVt0NLT0/H29iY0NJT69etTUFDAxIkT2bp1K25ubs/1WlOnTn2u471I3377LZaWlrRt21YJpH0SY8aM0eCshBBCiFfba9ugHTp0iHbt2lG/fn0AtLW1mT9/Prq6uhw/fpw1a9agq6tLYmIiffv2Zdy4cdy8eZPp06eTk5ODnp4eQUFBFBQU4OXlRa1atUhMTKRfv37Exsby+++/4+TkhLe3t3LXy9jYGB8fH4qKiqhRo4Yyl6NHj/LFF1+gp6eHmZkZc+bM4cKFC4SFhaFSqbh9+zZDhgzh/fffB2D58uWkpKTw4MEDFi9eTN26dZk3b56Sq/Luu+8yYsSIJ0r9//bbb1mzZg06OjrUqVOHBQsWoFIVP/lOSkpi165d6Orq0qxZMyZNmsSBAwe4deuWsltAnTp1uH79Ops3b6Zr167Y2dlhZ2fH/fv36du3L3Xr1sXf3x8dHR20tbVZsGAB1tbWGvmZSshi+SSAUvOkxponNdYsqa/mvRJBtS9CcnIydevWLfW1kggMgBs3brBnzx5yc3Pp3Lkz48aNY/78+Xh4eNClSxd++eUXQkJC8PLyIiEhgfDwcLKzs+nevTtHjhyhWrVqdO3aFW9vb2XM9evX8+677+Lq6sr+/fuJiIigqKiI6dOnExERgbW1NRs3bmTlypU4OTmRlJTE7t27KSwsxNnZmT59+gDQpUsXBgwYQGhoKF9//TUODg4kJiYSGRlJfn4+7u7utG/fHnh86v++ffvw9PSkX79+7N69m4yMDExMTIDiYNyBAwdiaWlZ6lHlggULGDt2LF26dCEyMpLr168DcPPmTaKiojA3N8fPzw+An3/+mWbNmuHn58epU6e4d++exho0WYFUPlmdpXlSY82TGmuW1Ffznjao9rVdJFC7dm1u3bpV6msJCQnK9kwNGzZER0cHAwMD9PX1AYiJiWHVqlV4eHiwfPlyUlNTAahbty7GxsZKPpmZmRl6enpl3mWLjY1VGp3WrVsDkJaWhpGRkdK0tG3bltjYWADeeust1Go1+vr6NGjQgD/++AMozh+D4t0NsrOziY+Pp02bNmhpaaGrq0vLli2Jj48HHp/67+/vz8mTJxk2bBi//vqrcvfsUeLj43nrrbcASi0TNjc3LxMmXJL1Nnr0aL788ku0tbUfO74QQgjxuntt76B17dqVVatW4ebmRr169cjLy2PevHl07NgRBweHchcK2NnZMXLkSFq3bk18fLzSzD3pogI7OzvOnDlD48aNOXfuHFDc1GRkZJCcnIyVlRUnTpxQHrteuHCBgoICcnNziYuL44033ih3XHt7e6KiovD09CQvL48zZ84wcODAUnOrKPV/27ZtTJgwgerVqzNjxgy+++475dyS8wsLC0tdr2HDhpw5c4YuXbooe6QC5TZ3hw4d4u2332b8+PHs27ePtWvXMnfu3DLHyQv+QgghxJ9e2wbNyMiIefPmMW3aNIqKisjMzKRr1664u7tz4sSJcs/x9fUlICCAnJwcsrOzn/rl/4kTJ+Ll5cX+/fuV1H0tLS1mz56trB41NTVl7ty5xMbGkp+fz4cffsjdu3cZN24cFhYW5Y7btWtXTpw4wZAhQ8jLy6NPnz7K/qAlKkr9b9GiBR988AFmZmYYGhri5ORU5rwFCxaUWjXq4+PDlClTCA8Px9jYuNTepX/VvHlzJk+eTGhoKCqVCn9//6eqmRBCCPE6kp0EKqnjx4+zdevWp1o5+aLs2bOHli1b8sYbb7B9+3Z+/fXXcu+KPSnZSUCz5N0SzZMaa57UWLOkvpr3tDsJvLZ30MSzq1WrFl5eXlSrVg2VSsWcOXNe9pSEEEKIV0qlb9Be1zDZdu3a0a5du2c+vyJRUVGYmprSvXv3Zx6jbdu2REVFPcdZSVCtEEII8bBK3aBJmOzzN2jQoJc9BSGEEEI8RqVu0CRM9vFhslD6jl1ERAQpKSkMHDiQzz77jJo1a5KQkMCbb77JrFmzCA0NxdLSEjs7u3LnfuLECZYtWwYUh+qV1HvcuHGYmZnh6OiIo6Mjs2fPBlBq8fvvv5f783jc3IUQQghRVqVu0CRMttijwmQf5erVq6xbt45q1arRo0cPJWajRHlzL3mkbG1tTVhYGF9//TXOzs7cvn2bnTt3olarcXV1Zc6cOTg4OLB9+3bWrl1Lx44dy/15POvcn4WkYJdPEsI1T2qseVJjzZL6at4rtZNA7dq1+f3330t9LSEhQQmYLQmT1dHRKRMmu3btWoqKitDV1QX+DJNVq9VKmCyUzTCLjY1lwIABQHGYbERERLlhsosXL8bJyUkJkwUqDJNNSUn522Gyq1atIiIiAjs7O3r06FFhzR5elFuvXj2MjIwAqFGjBjk5OaWOLW/u1tbWBAcHY2BgQFJSkhKoa2NjoxwbHx/PrFmzAMjLy1PmX97P42nm/nfJCqTyyeoszZMaa57UWLOkvpr3tDsJVOoGTcJknyxMVq1Wc/v2bezt7fn999+VRvJxn7m8uY8bN46DBw9iZGSEr6+v0vA9/FjS1taW+fPnU7t2bU6fPq3MubzrPW7uJeQFfyGEEOJPlbpBkzDZJwuTHT58OIGBgdSqVQsrK6sn/qzlzX3AgAG4uroq21YlJyeXOS8gIABfX18KCgqA4hWw5R33JHMXQgghRFkSVPs3VOYw2cepTHOXoFrNkkcXmic11jypsWZJfTXvaYNqZTmdEEIIIUQlIw3aY8TGxjJmzBg8PDx47733WLp0qfJeVrt27R57B2rLli2P/L6Hh4eyWOBFKpn7353fyZMnuXjx4vOenhBCCPFaq9TvoL1szyMod+XKlQwbNkzDM312f3d+O3fupG/fvjRu3PhvzUN2EhBCCCH+JA3aIzwuKDckJARdXV1cXV2pUaNGmSDbL7/8knv37hEQEICPjw9Tp07l/v37pKWl4eLigru7u3KtkgBZNze3UltMLVmyhGPHjlFYWEi/fv3w9PQsNUc/Pz/++OMPcnJyGDVqFH379uX7779XwmabNm3KrFmz6NGjBwcOHEBPT4+QkBDs7OxISkp64vndunVLWXxx9+5dPvnkE2rWrMmPP/5IdHQ0Dg4OuLi4cPToUQC8vLwYOnQoVlZW+Pv7o6Ojg7a2NgsWLFBWmQohhBCifNKgPcLjgnJzcnLYvn07RUVFdO/evUyQra+vL1u2bCEgIIDo6Gj69etHr169SEpKwsPDo1QDVJHdu3ezZcsWrK2ty+x/mZGRwfHjx9m5cydQvNtBfn4+QUFBbN++nerVq7Ns2TIlN+6vxo0b98Tzu3z5Mh988AHt2rXj119/JTQ0lPXr19O5c2f69u1bag/Th/388880a9YMPz8/Tp06xb179zTWoEnIYvkkgFLzpMaaJzXWLKmv5r1SQbUv2+OCcksCWisKsn2YpaUlGzdu5Ntvv8XIyIj8/PwnmsPixYtZvHgxKSkpdO7cudT3jIyMmD59OtOnTycjI4P+/fuTlpaGiYkJ1atXB2D8+PFlxixv4e7j5lejRg1WrlzJjh070NLSeuz8S64xePBg1qxZw+jRozE2NsbLy+uJPvezkBVI5ZPVWZonNdY8qbFmSX0175UKqn3ZHheUWxLe+qgg25JGJTw8nFatWuHu7s6xY8f44YcfSl3r4ZDa6OhoAHJzc/n6669ZvHgxRUVF9OvXj379+lGnTh2g+A5fdHQ0y5cvJycnhy5duuDs7Ex6ejp3797FzMyM2bNn079/f9RqNcnJydjY2HDx4kXs7e2fan7//ve/cXFxoUuXLuzcuZNdu3YBxRlxJWPk5+eTmZmJrq4ucXFxQPFj4rfffpvx48ezb98+1q5dy9y5c8vUWt4fE0IIIf4kDdojPGlQbkVBtlC8g4CPjw+DBw8mICCAvXv3YmZmhra2Nrm5ucoY77zzDpMmTeLkyZPKNlFqtRpTU1MGDBiAqakpnTp1KvUosUaNGty+fZt//etfGBgYMHLkSNRqNTNnzuSjjz5CpVLRtGlT3nzzTUaPHs2YMWOoU6dOqb0wn3R+ffr0ITg4mFWrVlGrVi3S0tIAaNmyJSEhIdjY2DB8+HCGDBmCjY2NMs/mzZszefJkQkNDUalU+Pv7a+AnJYQQQrxaJKhWvHQSVKtZ8uhC86TGmic11iypr+ZJUK0QQgghRBUnDdoL9qjg2yfxMoJvy1tocOTIEbZt21bm666uriQmJhIVFcWhQ4ee6zyEEEKI14W8g/YCVdXg25JMtYc5Ojo+8pxBgwY91TUkqFYIIYT4kzRoL1BlD749dOgQBw8eVBY4/Otf/2LdunX079+fo0eP4uHhgbm5Oenp6fTr149r167h4+PDkiVL+PHHH6lZs6ayeKDk+r1792bSpEkUFRWRl5fHrFmzaNSo0QuruRBCCFEVSYP2AlX24FsnJycWLlxIVlYWcXFx1KtXT8lTK+Hs7EzPnj2Vc2NiYjh58iQ7duwgKyuLXr16lTr+7NmzGBsbs2jRIuLi4sjIyHiqmj0NCVksnwRQap7UWPOkxpol9dU8CaqtxCp78K22tja9e/fm22+/5bfffsPFxaXM+SVzLBEXF0fz5s1RqVQYGRnRsGHDUt93dHTk6tWrfPzxx+jo6DBu3LgnmuezkBVI5ZPVWZonNdY8qbFmSX01T4JqK7HKHnwLxcn/M2fOJC0tjRkzZpT5DFpaWqX+bmtry6ZNmygsLCQ7O1sJqC1x/PhxrKysCA8P58yZMyxevJjNmzeXGVfeHxNCCCH+JA3aC1TZg28B5RFs9+7dlYbxUZo0aUKfPn0YPHgwVlZWZR6JNm7cGC8vLzZu3IhKpeKTTz55tuIJIYQQrxEJqhUvnQTVapY8utA8qbHmSY01S+qreRJUK4QQQghRxUmDJoQQQghRycg7aM/J6tWr+fnnn1GpVGhpaeHl5aW8+/Ukjh8/ztatW1myZIkGZ/n3REVFcfnyZXx8fB57bGJiIt7e3kRGRipfu337NsuXLycgIKDM8RJUK4QQQvxJGrTnIC4ujsOHDxMREYGWlhYXLlzA19eXPXv2vOypVSo1atQotzkTQgghRGnSoD0HFhYW3Lhxgx07duDo6EiTJk3YsWMHAP/73/8IDg6mqKgIa2trQkJCuHbtGrNnzwZQdgl42J49e9i4cSNqtZr69esTGBjI3r17OXToEBkZGaSlpfHJJ5/Qu3dvjh49WmbHgQsXLpTalWDp0qUcOHAAPT09QkJCsLOzw8nJ6ZEJ/9nZ2fj7+3Pjxg3y8vKYPn16qTkuWrSI8+fPk5mZib29PXPnziU0NJQzZ86QlZVFcHAwAAUFBfj5+dGgQQP69u1b5q7a8yQhi+WTAErNkxprntRYs6S+midBtS+BhYUFK1euZMuWLSxfvhx9fX28vLzo3bs306dPZ8mSJdjb2/Pll18SHx/PrFmzmDNnDg4ODmzfvp21a9fSsWNHoDikNjQ0lF27dmFkZMScOXPYtm0bBgYGZGVlsX79elJTU3FxcaFbt25Mnz69zI4DTk5Oyq4EAEuXLi0z58cl/G/dupU6deqwZMkSYmJi+PnnnzExMQEgIyMDExMT1q9fr2wZlZSUBICdnR3Tpk0jMTGR/Px8fHx8aNOmDe+//z6JiYma/DHICqQKyOoszZMaa57UWLOkvponQbUvwbVr1zAyMlKyys6dO8eYMWNo164dd+7cwd7eHoD3338fQGnSAPLy8kql8yckJODg4ICRkRFQvIvATz/9RMuWLWnbti0qlQpLS0tMTExISUkpd8cBJyenMon/JUpSVR6X8H/58mVlQ/SGDRvSsGFDZXsnPT09UlNT8fb2VhrHvLw8oPROA5cuXcLIyIisrKxnLa0QQgjxWpIG7Tm4dOkSERERhIWFoaenh62tLcbGxmhra2NlZcXVq1epX78+q1evxtbWFltbW+bPn0/t2rU5ffq0kvgPYGNjQ3x8PFlZWRgYGHDixAml6SnZESAlJYWMjAysrKwq3HHg4ZBZtVpNcnIyNjY2XLx4EXt7+8cm/Nvb23Pu3Dl69OhBQkICX3zxBZ06dQLgyJEj3Lx5ky+++ILU1FS+++47pfF7+LrNmjVj9erVuLi40LlzZ6XpLI+84C+EEEL8SRq056BXr17Ex8fj4uKCgYEBRUVFfP755xgbGzNr1iymTJmCSqWiRo0aeHp6UqtWLXx9fSkoKAAgODiY5ORkoPhx6YQJExg+fDgqlYp69erh4+PDV199RUpKCiNGjOD+/fvMnDkTbW3tcncciI2NLTW/0aNHM2bMGOrUqaM8pnxcwv/QoUOZMmUKw4YNo6CggClTpijjtmjRghUrVuDq6oparaZu3brK/P9KX1+fgIAAfH19K/UKVSGEEKIykZ0EqoinibioamQnAc2Sd0s0T2qseVJjzZL6ap7sJCCEEEIIUcVV6kecfzf8VdO6deumxFeUKHk/q1OnTn8rUiInJ4c9e/bg4uICwKBBg55pnG3btjFo0CDi4uI4dOgQ48ePf6ZxKhIREUFKSgoTJkz4W+NIUK0QQgjxp0rboFXV8NeSlY9/N1Li9u3bbN++XWnQntWqVav417/+RZMmTeT2tRBCCFFFVNoG7VHhrx4eHtja2nLlyhWKiopYsmQJNWrUYNGiRZw8eZKioiI8PT1555138PDwwNzcnPT0dPr168eRI0fIzs7m9u3bDB8+nEOHDhEbG8vnn39Ojx49niokFiAgIEBpxpYtW8ahQ4e4fPkyQ4cOVT7Lw3fanjQoNiwsjLi4OJYtW8aIESOYOnUqaWlpAEybNo1GjRrRtWtX7OzssLOzY+TIkUyfPp2cnBz09PQICgrip59+4vbt23h5eTFixAhlK6nt27cTERFBYWEh3bt3Z8KECWzZsoVvv/2W/Px8jI2NCQ0NZd++fcp7bzk5ObzzzjscPnyYU6dOMWfOHExNTVGpVLRq1arM1k6urq4sXryYpKQk5s+fj46ODiYmJoSEhDxyNacQQgghKnmDVlH4K0Dr1q0JDAzkyy+/ZNWqVXTu3JnExES2bt1KTk4Orq6uSiyEs7MzPXv2JCoqiszMTMLDw/nqq6/YsGEDkZGRHD9+nE2bNvH2228/cUhs9+7dAXjvvfdo06YNfn5+HD169Ik/3+OCYseOHUtMTAzjx49n4cKFtG/fHnd3d65evYq/vz8RERHcvHmTqKgozM3NmTRpEh4eHnTp0oVffvmFkJAQFi1axMqVK1myZAm//fYbAHfu3GHNmjXs2bMHtVrNvHnzyMjI4O7du2zYsAGVSsWoUaM4d+5chXOfO3cuixYtwtbWlpkzZz7ycx48eJCePXsyatQoDh8+THp6usYaNEnBLp8khGue1FjzpMaaJfXVvFdmJ4FHhb8CtG/fHihu1A4fPoy1tTXR0dF4eHgAkJ+fz40bN4DS4aklj/mMjY2xt7dX4ilycnKeKiQ2NTUVQHknztLSkuzs7Md+ricNin1YTEwMx44d48CBAwCkp6cDYG5ujrm5uXLMqlWrWLt2LUVFRejq6pY7VkJCAg0aNEBfXx+AKVOmAKCrq6sEz966dYv8/Pxy5w2QlJSk1LR169b88ccfFX7OsWPHEhYWxogRI7C2tqZFixaPqdCzk0e45ZPVWZonNdY8qbFmSX0175XZSeBR4a8A58+fp2bNmvz66684ODhgZ2dHu3btCAoKorCwkBUrVmBjYwOAlpaWMu7Df/6rpwmJrV69+mPHK/EsQbEqlYrCwkKgePuk/v374+zszJ07d5QtnB4OhS15zNm6dWvi4+M5efKkMr+ScQDq1avH5cuXyc3NRa1W8+mnnzJs2DAOHjzI9u3befDgAYMGDaKoqAg9PT0lRLfk80Pxpufx8fFKmK2pqSl6enrcuXOHgoICMjMzlce+e/fuZeDAgfj6+rJq1SoiIyPLXaggL/gLIYQQf6q0Ddqjwl8Bdu3axYYNG6hWrRoLFizAzMyMEydO4O7uTlZWFj169HjqR2lPGxL7pJ4lKLZ69erk5eWxcOFCxo4dy9SpU4mMjCQjI6PcBsfX15eAgABycnLIzs5m6tSpALRp04YxY8Yo41tYWPDhhx8ybNgwtLS06Nq1K2+++SbVqlVj0KBBqNVqatSoQXJyMk5OTkRERODm5kazZs0wNDQEYOHChfj6+mJoaIihoSGmpqbUqFGDTp06MXjwYOrVq8cbb7wBwJtvvomfnx8GBgbo6uoSGBj4VD8TIYQQ4nVUJYNqPTw8CAgIUPa41LRXOSS2MniSW71CCCHEq+RxQbWV9g6aeH3ILgJCCCFEaVXyDpoQQgghxKtMtnoSQgghhKhkpEETQgghhKhk5B008VIUFhYSEBDApUuXUKvVzJ49W1n5KZ6ff/3rX8rKZxsbGyVXUPw9//vf/wgJCWHz5s1cu3YNPz8/tLS0aNCgATNnziwVgSOezcM1jo6OZuzYsdSvXx8ANzc3+vbt+3InWIXl5eUxZcoUrl+/Tm5uLuPGjcPBwUF+j5+T8upbs2bNp/4dlgZNvBQHDx4kNzeXbdu28dtvvzFv3jxWrlz5sqf1SsnJyQEola8n/r6SnTiqVasGFO+sMWnSJNq1a8eMGTM4dOgQPXv2fMmzrNr+WuPff/+dDz74gJEjR77kmb0a9uzZg5mZGQsXLiQtLY2BAwfSuHFj+T1+Tsqr7yeffPLUv8PSHouX4vTp03Tu3BmAVq1acf78+Zc8o1fPxYsXefDgASNHjmT48OHKdl/i76lXrx6hoaHK36Ojo/nHP/4BFO8Q8vPPP7+sqb0y/lrj8+fP89///pf333+fKVOmlNkaTzydPn36MHHiROXv2tra8nv8HJVX32f5HZYGTbwUGRkZpYKEtbW1y2wvJf4efX19Ro0axbp165g1axY+Pj5S4+egd+/e6Oj8+fChqKhI2VHE0NCQ+/fvv6ypvTL+WuMWLVrw+eef8+WXX1K3bl2WL1/+EmdX9RkaGmJkZERGRgaffvopkyZNkt/j56i8+j7L77A0aOKlMDIyIjMzU/l7YWFhqX+Qxd9na2tL//790dLSwtbWFjMzM2XrLvH8PPyeTmZmprJbiHh+evbsqex73LNnT37//feXPKOq7+bNmwwfPpwBAwbg7Owsv8fP2V/r+yy/w9KgiZeidevWHDlyBIDffvuNhg0bvuQZvXp27NjBvHnzgOIN7jMyMqhRo8ZLntWrp2nTphw/fhyAI0eO0KZNm5c8o1fPqFGjOHv2LAC//PILzZo1e8kzqtpSUlIYOXIkkydPZvDgwYD8Hj9P5dX3WX6HJahWvBQlqzhjYmIoKipizpw5L2zrrtdFbm4u/v7+3LhxAy0tLXx8fGjduvXLntYrITExEW9vbyIjI7ly5QrTp08nLy8POzs7Zs+e/VR79YryPVzj6OhogoKC0NXVxdLSkqCgoKfea1n8afbs2Rw4cAA7Ozvla1OnTmX27Nnye/wclFffSZMmsXDhwqf6HZYGTQghhBCikpFHnEIIIYQQlYw0aEIIIYQQlYw0aEIIIYQQlYw0aEIIIYQQlYw0aEIIIYQQlYw0aEII8QIdP36cNm3acPPmTeVrISEhREVFPfOYiYmJuLq6Po/plVFQUMCoUaNwc3Pj3r17jzz2+PHjeHl5Vfj9nJwctm/f/rynKMQrSRo0IYR4wXR1dfH396cqpBzdvn2btLQ0IiIiMDU1/dtjSYMmxJORvXWEEOIFa9++PYWFhXz55ZcMGzZM+frD4awArq6uLF68mF27dnHt2jXS0tK4d+8e7u7ufPvtt1y5coX58+djaWlJamoqY8eOJTU1lS5duvDJJ59w8+ZNpk+fTk5ODnp6egQFBVFQUMC4ceMwMzPD0dGRDz/8ULn+nj172LhxI2q1mvr16xMYGMj06dO5evUqM2bMIDAwUDnWw8MDW1tbrly5QlFREUuWLCn1GcsbKywsjLi4OJYtW0aHDh2YP38+Ojo6mJiYEBISIuGzQjxE7qAJIcRLEBAQwIYNG7h69eoTHa+vr8+6devo1asXP/zwA2FhYYwZM4avvvoKgKysLBYuXEhERAQ//vgjFy9eZP78+Xh4eLB582ZGjRpFSEgIUHwna926daWas7S0NEJDQ9m4cSMREREYGxuzbds2Zs6ciYODQ6nmrETr1q3ZvHkz77zzDqtWrXrsWGPHjsXBwYHx48dz8OBBevbsyZYtWxg8eDDp6el/o5pCvHqkQRNCiJfA3NycKVOm4OfnR2FhYbnHPPwItGnTpgAYGxvj4OAAgKmpKTk5OQA0btwYY2NjtLW1efPNN7ly5QoxMTGsWrUKDw8Pli9fTmpqKgA2Njao1epS10pISMDBwUG5i9W2bVtiY2Mf+Rnat28PFDdqV65ceaqxSu72jRgxgq+//hodHXmgI8TDpEETQoiXpFu3btja2rJr1y4A9PT0uHPnDgUFBaSnp5OYmKgcq6Wl9cix4uPjyczMJD8/n7Nnz9KgQQPs7Ozw8fFh8+bNzJo1i969ewOgUpX9p9/Gxob4+HiysrIAOHHiBLa2to+85vnz5wH49ddflabxUWOpVCqlGd27dy8DBw5k8+bNNGjQQHmsK4QoJv/LIoQQL9HUqVM5duwYADVq1KBTp04MHjyYevXq8cYbbzzxOKampnh5eZGamkrfvn1xcHDA19eXgIAAcnJyyM7OZurUqRWeb2FhwYQJExg+fDgqlYp69erh4+PD7du3Kzxn165dbNiwgWrVqrFgwQJiYmIeORZAXl4eCxcupFevXvj5+WFgYICurm65j1CFeJ3JZulCCCGemoeHBwEBAdjb27/sqQjxSpJHnEIIIYQQlYzcQRNCCCGEqGTkDpoQQgghRCUjDZoQQgghRCUjDZoQQgghRCUjDZoQQgghRCUjDZoQQgghRCXz/wB+Z1iR8XK6bAAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -2275,7 +3008,9 @@ "cell_type": "code", "execution_count": 30, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2362,7 +3097,9 @@ "cell_type": "code", "execution_count": 31, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2371,10 +3108,8 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": { - "tags": [] - }, + "execution_count": 32, + "metadata": {}, "outputs": [ { "data": { @@ -2446,7 +3181,7 @@ "5 495 553" ] }, - "execution_count": 31, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -2464,7 +3199,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -2473,13 +3208,13 @@ "" ] }, - "execution_count": 32, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -2513,24 +3248,26 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 34, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 33, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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NmzaSpKZNm1Yv/AYGBqq0tFStW7fWwoUL1bhxY5WUlCggIOCycQsLC/Xcc89JksrLyxUSEuJWP26F6FmzZmnVqlXatGmTOnTooNGjR7s1OAAAAGCF0NBQPfLII3r44Yd1+vRprVmzRtKFs8j9nBkzZmjevHnq0KGDXnzxRR09evSyn4eEhGjOnDlq06aNCgoKdOrUKbf6cStE+/n5aciQIW4NCAAAAFht5MiRmjx5svLy8uRyuTR27Fi37vfII49o9OjRuvHGG/Vv//Zv1cdUX5SRkaHk5GRVVlZKuhC63eFWiAYAAAAk7192vW3btsrLy5MkLVy48IqfX3qauku/fv311yVJQ4cO1dChQ3/yfp07d1Z2drbpvviEIAAAAGASIRoAAAAwiRANAAAAmESIBgAAAEwiRAMAAAAmcXYOAACABuqrqbe7tV3wlD0e7qThIUQDAExz9wp53j4VFgDPczeYu8sTAX7dunX617/+pT/96U+Wj30Rh3MAAAAAJrESDQAArikconB9WbdunTZu3Kjz58/r1KlTSkhIUH5+vg4ePKgJEyboxIkTWr9+vSoqKhQYGKgFCxZcdv/s7Gy9+eabstlsevDBB5WQYM1/yLweok+fPq0BAwZo2bJl8vX1VUpKimw2mzp16qT09HTZ7Xbl5eUpNzdXvr6+GjVqlHr37u3tNgEAAOotdw+pei3Qw414SUlJiZYtW6a33npLWVlZysvL044dO5SVlaXOnTsrKytLdrtdw4cP1549P/zxdOjQIb399ttauXKlbDabhgwZonvuuUehoaG17smrIbq8vFxTpkxR48aNJUmzZs1SYmKioqKiNGXKFOXn56tLly7Kzs7W2rVrVVpaKqfTqZ49e8rhcHizVQAAANQT4eHhkqTAwEB16NBBNptNzZo1U3l5uRo1aqRnn31WTZs21YkTJ1RRUVF9vwMHDujYsWMaMmSIJOn//u//9NVXX117IXrOnDkaNGiQlixZIknau3evevToIUmKjo7Wli1bZLfb1bVrVzkcDjkcDgUHB2v//v2KiIi4Yrx9+/Z5pE9PjUuN67uGN7Cv3NdQ9lV9r9FQXi/uqu/PBzWuzRrecOnjuBhY6xObzVbj7eXl5dqwYYPWrFmjc+fOacCAATIMo/rnoaGh6tixo15++WXZbDZlZWUpLCzMkp68FqLXrVunFi1aqFevXtUh2jCM6p3i7++v4uJiuVwuBQb+8L8Hf39/uVyuGsf84UneaWmvNb94qHH91fAG9pX7Gsq+ur5q1Mc348vVn31FjYZUwxsayuOoHV9fXzVp0kQDBgyQw+FQq1at9M0331T//JZbbtFdd92luLg4lZWVKSIiQr/61a+sqW3JKG5Yu3atbDabtm3bpn379ik5OVnfffdd9c9LSkoUFBSkgIAAlZSUXHb7paEaAAAAdcfbH9gcMGBA9dfR0dGKjo6WdCH4L1u27Bfv/9RTT+mpp56yvC+vneJuxYoVysnJUXZ2tsLDwzVnzhxFR0drx44dkqTNmzere/fuioiIUEFBgUpLS1VcXKzCwkLLlt0BAAAAK9TpKe6Sk5OVlpamzMxMhYaGKiYmRj4+PoqPj5fT6ZRhGEpKSpKfn19dtgkAAABcpk5CdHZ2dvXXOTk5V/w8NjZWsbGx3mwJAOABnM8XQEPFFQsBAAAAkwjRAAAAgEmEaAAAAMAkQjQAAABgEiEaAAAAMIkQDQAAAJhEiAYAAABMIkQDAAAAJtXpFQuB+ixy/HK3tiuYm+DhTgAAQH3DSjQAAABgEiEaAAAAMIkQDQAAAJhEiAYAAABM4oOFQC19NfV2t7YLnrLHw50AAABvYSUaAAAAMIkQDQAAAJjE4RwAgGsah1QBqAusRAMAAAAmEaIBAAAAkwjRAAAAgEmEaAAAAMAkQjQAAABgEiEaAAAAMMlrp7grLy/XpEmTdPToUZWVlWnUqFHq2LGjUlJSZLPZ1KlTJ6Wnp8tutysvL0+5ubny9fXVqFGj1Lt3b2+1CQAAAPwir4Xov/3tb2revLnmzp2roqIi/e53v9Mtt9yixMRERUVFacqUKcrPz1eXLl2UnZ2ttWvXqrS0VE6nUz179pTD4fBWqwCAeiBy/HK3tnst0MONAEANvBai77//fsXExFR/7+Pjo71796pHjx6SpOjoaG3ZskV2u11du3aVw+GQw+FQcHCw9u/fr4iICG+1CgAAAPwsr4Vof39/SZLL5dLTTz+txMREzZkzRzabrfrnxcXFcrlcCgwMvOx+LperxjH37dvnkV49NS41qEGN+qOh7CtqUIMaDb+GN1z6OMLDw+uwk2uHVy/7ffz4cY0ZM0ZOp1MPP/yw5s6dW/2zkpISBQUFKSAgQCUlJZfdfmmovtQPT/JOS/us+cVDDWpQ46dreEND2VfUoAY1Gn4N99TukvX153Fcr7x2do5vv/1Ww4YN0/jx4zVw4EBJ0q233qodO3ZIkjZv3qzu3bsrIiJCBQUFKi0tVXFxsQoLCxUWFuatNgEAAIBf5LWV6EWLFuns2bNauHChFi5cKEmaPHmypk+frszMTIWGhiomJkY+Pj6Kj4+X0+mUYRhKSkqSn5+ft9oEAAAAfpHXQnRqaqpSU1OvuD0nJ+eK22JjYxUbG+uNtgAAAADTuNgKAAAAYJJXP1gIAADQ0HGO8+sDK9EAAACASYRoAAAAwCQO5wBQa+7+67JgboKHOwEAwDsI0QC8pnYXFgAAoP7gcA4AAADAJEI0AAAAYBIhGgAAADCJEA0AAACYRIgGAAAATCJEAwAAACYRogEAAACTCNEAAACASYRoAAAAwCRCNAAAAGASIRoAAAAwiRANAAAAmESIBgAAAEwiRAMAAAAmEaIBAAAAkwjRAAAAgEmEaAAAAMAkQjQAAABgkm9dN1CTqqoqZWRk6PPPP5fD4dD06dPVvn37um4LAAAAkFRPV6I3bNigsrIyrV69WuPGjdPs2bPruiUAAACgms0wDKOum/ixWbNmKSIiQg899JAkqVevXvrHP/5x2TYFBQV10RoAAECDFxkZWdct1Hv18nAOl8ulgICA6u99fHxUUVEhX98f2uXJBQAAQF2pl4dzBAQEqKSkpPr7qqqqywI0AAAAUJfqZYju1q2bNm/eLEnatWuXwsLC6rgjAAAA4Af18pjoi2fnOHDggAzD0MyZM9WhQ4e6bgsAAACQVE9Xou12u6ZOnarc3FytXr3akgD9ySefKD4+3oLurlReXq7x48fL6XRq4MCBys/Pt7xGZWWlJk6cqEGDBmnw4MH66quvLK9x0enTp3XvvfeqsLDQI+M/+uijio+PV3x8vCZOnOiRGosXL9bjjz+uAQMGaM2aNZaPv27duurHEBsbq9tvv11nz561tEZ5ebnGjRunQYMGyel0euT5KCsr07hx4xQbG6thw4bpyy+/tHT8S+fd4cOHFRcXJ6fTqfT0dFVVVXmkjiS9//77GjdunEfG37dvn5xOp+Lj4zV8+HB9++23ltc4dOiQ4uLiNGjQIGVkZKiystLyGhe98cYbevzxxy0Z/8c19u7dq169elXPlbffftvyGqdPn9aoUaM0ePBgDRo0yLLfjZfWSEpKqn4Mffr0UVJSkuU19u3bp9jYWMXFxWnixImWzY8fPx8DBw6U0+nUtGnTLKlR0/uf1XP9595jZ86cqVWrVtX2YdRYw+q5XlMNq+f6z+0rq+c6JBnXgSVLlhj9+vUzHnvsMY+M/+qrrxrTp083DMMwvvvuO+Pee++1vMb7779vpKSkGIZhGNu3bzdGjhxpeQ3DMIyysjJj9OjRxm9/+1vj0KFDlo9//vx5o3///paPe6nt27cbf/jDH4zKykrD5XIZL774okfrZWRkGLm5uZaP+/777xtPP/20YRiG8eGHHxpjx461vEZ2draRmppqGIZhFBYWGsOGDbNs7B/Puz/84Q/G9u3bDcMwjLS0NGP9+vUeqTNt2jQjJibGSExM9Mj4gwcPNj777DPDMAxj1apVxsyZMy2vMWrUKOOf//ynYRiGkZycbMm+qun34GeffWYkJCRY9rvxxzXy8vKMV155xZKxf6pGcnKy8dZbbxmGYRjbtm0zNm7caHmNi86cOWM88sgjxsmTJy2vMXr0aOPvf/+7YRiG8eyzzxr5+fmW1/jd735nFBQUGIZhGJmZmcZf//rXWteo6f3P6rleU43Tp08bw4cPN37zm98YK1eurN2D+IkaVs/1mmpYPdd/Ko9YPddxQb1cibZacHCwFixY4LHx77//fj3zzDPV3/v4+Fheo2/fvpo2bZok6dixY2rZsqXlNSRpzpw5GjRokFq3bu2R8ffv369z585p2LBhSkhI0K5duyyv8eGHHyosLExjxozRyJEj9Z//+Z+W17hoz549OnTokEf+ug8JCVFlZaWqqqrkcrk88uHaQ4cOKTo6WpIUGhpq6Wr3j+fd3r171aNHD0lSdHS0tm7d6pE63bp1U0ZGhiVj1zR+ZmamwsPDJV34D5Gfn5/lNRYsWKA77rhDZWVlOnXqlG688UbLaxQVFWnevHmaNGlSrcf+qRqffvqp/v73v2vw4MGaNGmSXC6X5TU+/vhjnTx5UkOGDNEbb7xR/RqzssZFCxYs0BNPPGHJ78cf1wgPD9eZM2dkGIZKSkosme8/rnHy5El169ZN0oV5YsWpYmt6/7N6rtdUo6SkRH/84x/Vv3//Wo39czWsnus11bB6rtdUwxNzHRdcFyE6JibGo2f38Pf3V0BAgFwul55++mklJiZ6pI6vr6+Sk5M1bdo0xcTEWD7+unXr1KJFC/Xq1cvysS9q3Lixhg8frldeeUXPPfec/vSnP6miosLSGkVFRfr000/1wgsvVNcwPHTo/+LFizVmzBiPjN20aVMdPXpUDzzwgNLS0jxyOFJ4eLg2btwowzC0a9cunTx50rJDB3487wzDkM1mk3RhzhQXF3ukzoMPPlhdxxPjXwxQH3/8sXJycjRkyBDLa/j4+Ojo0aPq16+fioqKFBISYmmNyspKTZ48WZMmTZK/v3+tx66phiRFRERowoQJWrFihdq1a6f//u//trzG0aNHFRQUpKysLN10001aunSp5TWkC4eNbNu2TQMGDKj1+DXVuPnmmzVjxgw98MADOn36tKKioiyv0a5dO/3zn/+UJG3cuFHnzp2rdY2a3v+snus11WjXrp3+4z/+o9b9/1wNq+d6TTWsnus/rvHMM894ZK7jgusiRHvD8ePHlZCQoP79++vhhx/2WJ05c+bovffeU1pamr7//ntLx167dq22bt2q+Ph47du3T8nJyTp16pSlNUJCQvTII4/IZrMpJCREzZs3t7xG8+bNdc8998jhcCg0NFR+fn767rvvLK0hSWfPntW//vUv3XnnnZaPLUlZWVm655579N577+n1119XSkqKSktLLa3x+9//XgEBAUpISNDGjRt12223eeQ/KdKFzzpcVFJSoqCgII/U8Ya3335b6enpWrJkiVq0aOGRGr/+9a+1fv16xcXFWX7V1r179+rw4cPKyMjQs88+q0OHDmnGjBmW1pCk++67T507d67++rPPPrO8RvPmzdWnTx9JUp8+ffTpp59aXkOS3n33XfXr189j82PGjBlasWKF3n33XT366KMeuVLvzJkztXjxYo0YMUI33nijbrjhBkvG/fH7nyfmujfeY2uqYfVcr6mG1XP90ho333yzV+b69YoQbYFvv/1Ww4YN0/jx4zVw4ECP1PjrX/+qxYsXS5KaNGkim81m+S/zFStWKCcnR9nZ2QoPD9ecOXPUqlUrS2u8+uqr1b8kTp48KZfLZXmNyMhI/eMf/5BhGDp58qTOnTun5s2bW1pDknbu3Km7777b8nEvCgoKUmBgoCSpWbNmqqiosGyV+KI9e/YoMjJS2dnZ6tu3r9q1a2fp+Je69dZbtWPHDknS5s2b1b17d4/V8qTXX3+9ep54an+NHDmy+kOe/v7+l4USK0REROitt95Sdna2MjMz1bFjR02ePNnSGpI0fPhw7d69W5K0bds23XbbbZbXiIyM1KZNmyRdmJMdO3a0vIZ0of+Lhz55QrNmzaovMta6dWvLP6gsSZs2bdLMmTO1ZMkSnTlzRj179qz1mDW9/1k9173xHltTDavnek01rJ7rP67hrbl+veIKJhZYtGiRzp49q4ULF2rhwoWSpKVLl6px48aW1fjtb3+riRMnavDgwaqoqNCkSZMsORbT2wYOHKiJEycqLi5ONptNM2fOtPxQm969e2vnzp0aOHCgDMPQlClTPLJ69MUXX6ht27aWj3vRkCFDNGnSJDmdTpWXlyspKUlNmza1tEb79u31wgsvaNmyZQoMDPToCkVycrLS0tKUmZmp0NBQjxyS5GmVlZWaMWOGbrrpJv3xj3+UJN1xxx16+umnLa0zYsQIpaSkqFGjRmrSpImmT59u6fjekpGRoWnTpqlRo0Zq2bJl9ec6rJScnKzU1FTl5uYqICBAzz//vOU1pAvz3ZN/ZE6fPl1JSUny9fVVo0aNPLKv2rdvrxEjRqhJkyaKiorSvffeW+sxa3r/mzx5sqZPn27ZXPfGe+yPa1RWVurgwYNq06aNZXO9pseRmJho6Vz3xr7CD+rleaIBAACA+ozDOQAAAACTCNEAAACASYRoAAAAwCRCNAAAAGASIRoAAAAwiRANALpwSedVq1a5tW1paanWrFkj6cKVPvPz8926X3x8vKWXVpekI0eOKDY2VpKUlJSksrIyHTt2TB988IGldQAAlyNEA4BJp06dqg7RAwYM0G9+85s67uiC//qv/5LD4dD27dv18ccf13U7ANCgcbEVAA3O2LFjlZCQoB49emj37t166aWX1LJlSx0+fFhVVVVKTExUVFSU+vXrp5tvvlkOh0MhISHasGGD3nnnHZ0/f16pqamKiIhQTk6O1q9fr4qKCgUGBmrBggVatGiRDh06pJdeekmGYahly5YKDQ3VkiVL1KhRI504cUKDBg3S9u3btX//fiUkJMjpdNbYa3l5uSZNmqSvv/5alZWVGjp0qB588EF98sknmjFjhgzD0K9+9SvNmzev+rFI0vnz5zVnzhw1atSoeqw+ffrozTff1JIlS3T+/Hl16dJFs2fP1nvvvScfHx/NnTtXnTt31gMPPOCV5wEAGjJWogE0OI899phee+01SdJrr72mXr166YYbbtCKFSu0cOFCTZ06VZL0/fffa/To0crMzJQk/frXv9by5cs1Y8YMpaenq6qqSmfOnFFWVpZWrlypiooK7dmzRyNHjlTHjh01duzYy+qeOHFCCxYsUEZGhv7yl7/oz3/+s5YuXarVq1f/ZK+rV6/WDTfcoNzcXP3P//yP5s+fr++++05paWmaNWuW1qxZo7vuukuFhYU6ePCg5s6dq+XLl6tPnz569913rxjPx8dHI0aMUL9+/dS3b19FRkbqww8/VGVlpTZv3lxvVs0B4FrHSjSABqdXr16aO3euzpw5o48++khVVVX6+OOPtXv3bklSRUWFioqKJEkhISHV97vjjjskSZ06ddKpU6dkt9vVqFEjPfvss2ratKlOnDihioqKn6zbqVMnNWrUSIGBgQoODpbD4VCzZs1UWlr6k/cpLCzU3XffLUkKCAhQhw4d9PXXX+v06dPq0KGDJGnw4MGSpOPHj2vGjBlq2rSpTp48qW7duv3ivnjssceUnZ2tqqoq3X333XI4HL94HwDAL2MlGkCDY7fbdf/99ysjI0N9+/ZVhw4d9NBDDyk7O1tLly7V/fffr2bNmlVve9HFkP3555+rTZs22r9/vzZs2KD58+crLS1NVVVVMgxDdrtdVVVVV9S12Wyme+3QoYM++ugjSZLL5dKBAwfUtm1btW7dWl9++aUkacmSJXr//feVmpqqmTNnavbs2WrdurUMw/jJx3+xv+7du+vrr7/Wq6++qoEDB5ruDwBQM1aiATRIv//979W3b1+99957at26tVJTU/XEE0/I5XLJ6XReFp4vOnLkiBISElRWVqapU6eqffv2atKkiQYMGCCHw6FWrVrpm2++UdeuXVVeXq65c+eqcePGpvp65plnqleDo6KilJSUpLS0NMXFxam0tFRjx47VjTfeqOeee06TJk2S3W5Xq1atNGTIEPXv31+xsbEKCgpSy5Yt9c0339RYIywsTH/5y19022236aGHHtLDDz+sd999V506dTK/IwEANbIZP7WUAQBoEJYuXaobbriBlWgAsBAr0QDQgKWkpKioqEgLFiyo61YAoEFhJRoAAAAwiQ8WAgAAACYRogEAAACTCNEAAACASYRoAAAAwCRCNAAAAGDS/wNTiYtPBFTowgAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -2565,24 +3302,26 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 35, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 34, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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NmzaSpKZNm1Yv/AYGBqq0tFStW7fWwoUL1bhxY5WUlCggIOCycQsLC/Xcc89JksrLyxUSEuJWP26F6FmzZmnVqlXatGmTOnTooNGjR7s1OAAAAGCF0NBQPfLII3r44Yd1+vRprVmzRtKFs8j9nBkzZmjevHnq0KGDXnzxRR09evSyn4eEhGjOnDlq06aNCgoKdOrUKbf6cStE+/n5aciQIW4NCAAAAFht5MiRmjx5svLy8uRyuTR27Fi37vfII49o9OjRuvHGG/Vv//Zv1cdUX5SRkaHk5GRVVlZKuhC63eFWiAYAAAAk7192vW3btsrLy5MkLVy48IqfX3qauku/fv311yVJQ4cO1dChQ3/yfp07d1Z2drbpvviEIAAAAGASIRoAAAAwiRANAAAAmESIBgAAAEwiRAMAAAAmcXYOAACABuqrqbe7tV3wlD0e7qThIUQDAExz9wp53j4VFgDPczeYu8sTAX7dunX617/+pT/96U+Wj30Rh3MAAAAAJrESDQAArikconB9WbdunTZu3Kjz58/r1KlTSkhIUH5+vg4ePKgJEyboxIkTWr9+vSoqKhQYGKgFCxZcdv/s7Gy9+eabstlsevDBB5WQYM1/yLweok+fPq0BAwZo2bJl8vX1VUpKimw2mzp16qT09HTZ7Xbl5eUpNzdXvr6+GjVqlHr37u3tNgEAAOotdw+pei3Qw414SUlJiZYtW6a33npLWVlZysvL044dO5SVlaXOnTsrKytLdrtdw4cP1549P/zxdOjQIb399ttauXKlbDabhgwZonvuuUehoaG17smrIbq8vFxTpkxR48aNJUmzZs1SYmKioqKiNGXKFOXn56tLly7Kzs7W2rVrVVpaKqfTqZ49e8rhcHizVQAAANQT4eHhkqTAwEB16NBBNptNzZo1U3l5uRo1aqRnn31WTZs21YkTJ1RRUVF9vwMHDujYsWMaMmSIJOn//u//9NVXX117IXrOnDkaNGiQlixZIknau3evevToIUmKjo7Wli1bZLfb1bVrVzkcDjkcDgUHB2v//v2KiIi4Yrx9+/Z5pE9PjUuN67uGN7Cv3NdQ9lV9r9FQXi/uqu/PBzWuzRrecOnjuBhY6xObzVbj7eXl5dqwYYPWrFmjc+fOacCAATIMo/rnoaGh6tixo15++WXZbDZlZWUpLCzMkp68FqLXrVunFi1aqFevXtUh2jCM6p3i7++v4uJiuVwuBQb+8L8Hf39/uVyuGsf84UneaWmvNb94qHH91fAG9pX7Gsq+ur5q1Mc348vVn31FjYZUwxsayuOoHV9fXzVp0kQDBgyQw+FQq1at9M0331T//JZbbtFdd92luLg4lZWVKSIiQr/61a+sqW3JKG5Yu3atbDabtm3bpn379ik5OVnfffdd9c9LSkoUFBSkgIAAlZSUXHb7paEaAAAAdcfbH9gcMGBA9dfR0dGKjo6WdCH4L1u27Bfv/9RTT+mpp56yvC+vneJuxYoVysnJUXZ2tsLDwzVnzhxFR0drx44dkqTNmzere/fuioiIUEFBgUpLS1VcXKzCwkLLlt0BAAAAK9TpKe6Sk5OVlpamzMxMhYaGKiYmRj4+PoqPj5fT6ZRhGEpKSpKfn19dtgkAAABcpk5CdHZ2dvXXOTk5V/w8NjZWsbGx3mwJAOABnM8XQEPFFQsBAAAAkwjRAAAAgEmEaAAAAMAkQjQAAABgEiEaAAAAMIkQDQAAAJhEiAYAAABMIkQDAAAAJtXpFQuB+ixy/HK3tiuYm+DhTgAAQH3DSjQAAABgEiEaAAAAMIkQDQAAAJhEiAYAAABM4oOFQC19NfV2t7YLnrLHw50AAABvYSUaAAAAMIkQDQAAAJjE4RwAgGsah1QBqAusRAMAAAAmEaIBAAAAkwjRAAAAgEmEaAAAAMAkQjQAAABgEiEaAAAAMMlrp7grLy/XpEmTdPToUZWVlWnUqFHq2LGjUlJSZLPZ1KlTJ6Wnp8tutysvL0+5ubny9fXVqFGj1Lt3b2+1CQAAAPwir4Xov/3tb2revLnmzp2roqIi/e53v9Mtt9yixMRERUVFacqUKcrPz1eXLl2UnZ2ttWvXqrS0VE6nUz179pTD4fBWqwCAeiBy/HK3tnst0MONAEANvBai77//fsXExFR/7+Pjo71796pHjx6SpOjoaG3ZskV2u11du3aVw+GQw+FQcHCw9u/fr4iICG+1CgAAAPwsr4Vof39/SZLL5dLTTz+txMREzZkzRzabrfrnxcXFcrlcCgwMvOx+LperxjH37dvnkV49NS41qEGN+qOh7CtqUIMaDb+GN1z6OMLDw+uwk2uHVy/7ffz4cY0ZM0ZOp1MPP/yw5s6dW/2zkpISBQUFKSAgQCUlJZfdfmmovtQPT/JOS/us+cVDDWpQ46dreEND2VfUoAY1Gn4N99TukvX153Fcr7x2do5vv/1Ww4YN0/jx4zVw4EBJ0q233qodO3ZIkjZv3qzu3bsrIiJCBQUFKi0tVXFxsQoLCxUWFuatNgEAAIBf5LWV6EWLFuns2bNauHChFi5cKEmaPHmypk+frszMTIWGhiomJkY+Pj6Kj4+X0+mUYRhKSkqSn5+ft9oEAAAAfpHXQnRqaqpSU1OvuD0nJ+eK22JjYxUbG+uNtgAAAADTuNgKAAAAYJJXP1gIAADQ0HGO8+sDK9EAAACASYRoAAAAwCQO5wBQa+7+67JgboKHOwEAwDsI0QC8pnYXFgAAoP7gcA4AAADAJEI0AAAAYBIhGgAAADCJEA0AAACYRIgGAAAATCJEAwAAACYRogEAAACTCNEAAACASYRoAAAAwCRCNAAAAGASIRoAAAAwiRANAAAAmESIBgAAAEwiRAMAAAAmEaIBAAAAkwjRAAAAgEmEaAAAAMAkQjQAAABgkm9dN1CTqqoqZWRk6PPPP5fD4dD06dPVvn37um4LAAAAkFRPV6I3bNigsrIyrV69WuPGjdPs2bPruiUAAACgms0wDKOum/ixWbNmKSIiQg899JAkqVevXvrHP/5x2TYFBQV10RoAAECDFxkZWdct1Hv18nAOl8ulgICA6u99fHxUUVEhX98f2uXJBQAAQF2pl4dzBAQEqKSkpPr7qqqqywI0AAAAUJfqZYju1q2bNm/eLEnatWuXwsLC6rgjAAAA4Af18pjoi2fnOHDggAzD0MyZM9WhQ4e6bgsAAACQVE9Xou12u6ZOnarc3FytXr3akgD9ySefKD4+3oLurlReXq7x48fL6XRq4MCBys/Pt7xGZWWlJk6cqEGDBmnw4MH66quvLK9x0enTp3XvvfeqsLDQI+M/+uijio+PV3x8vCZOnOiRGosXL9bjjz+uAQMGaM2aNZaPv27duurHEBsbq9tvv11nz561tEZ5ebnGjRunQYMGyel0euT5KCsr07hx4xQbG6thw4bpyy+/tHT8S+fd4cOHFRcXJ6fTqfT0dFVVVXmkjiS9//77GjdunEfG37dvn5xOp+Lj4zV8+HB9++23ltc4dOiQ4uLiNGjQIGVkZKiystLyGhe98cYbevzxxy0Z/8c19u7dq169elXPlbffftvyGqdPn9aoUaM0ePBgDRo0yLLfjZfWSEpKqn4Mffr0UVJSkuU19u3bp9jYWMXFxWnixImWzY8fPx8DBw6U0+nUtGnTLKlR0/uf1XP9595jZ86cqVWrVtX2YdRYw+q5XlMNq+f6z+0rq+c6JBnXgSVLlhj9+vUzHnvsMY+M/+qrrxrTp083DMMwvvvuO+Pee++1vMb7779vpKSkGIZhGNu3bzdGjhxpeQ3DMIyysjJj9OjRxm9/+1vj0KFDlo9//vx5o3///paPe6nt27cbf/jDH4zKykrD5XIZL774okfrZWRkGLm5uZaP+/777xtPP/20YRiG8eGHHxpjx461vEZ2draRmppqGIZhFBYWGsOGDbNs7B/Puz/84Q/G9u3bDcMwjLS0NGP9+vUeqTNt2jQjJibGSExM9Mj4gwcPNj777DPDMAxj1apVxsyZMy2vMWrUKOOf//ynYRiGkZycbMm+qun34GeffWYkJCRY9rvxxzXy8vKMV155xZKxf6pGcnKy8dZbbxmGYRjbtm0zNm7caHmNi86cOWM88sgjxsmTJy2vMXr0aOPvf/+7YRiG8eyzzxr5+fmW1/jd735nFBQUGIZhGJmZmcZf//rXWteo6f3P6rleU43Tp08bw4cPN37zm98YK1eurN2D+IkaVs/1mmpYPdd/Ko9YPddxQb1cibZacHCwFixY4LHx77//fj3zzDPV3/v4+Fheo2/fvpo2bZok6dixY2rZsqXlNSRpzpw5GjRokFq3bu2R8ffv369z585p2LBhSkhI0K5duyyv8eGHHyosLExjxozRyJEj9Z//+Z+W17hoz549OnTokEf+ug8JCVFlZaWqqqrkcrk88uHaQ4cOKTo6WpIUGhpq6Wr3j+fd3r171aNHD0lSdHS0tm7d6pE63bp1U0ZGhiVj1zR+ZmamwsPDJV34D5Gfn5/lNRYsWKA77rhDZWVlOnXqlG688UbLaxQVFWnevHmaNGlSrcf+qRqffvqp/v73v2vw4MGaNGmSXC6X5TU+/vhjnTx5UkOGDNEbb7xR/RqzssZFCxYs0BNPPGHJ78cf1wgPD9eZM2dkGIZKSkosme8/rnHy5El169ZN0oV5YsWpYmt6/7N6rtdUo6SkRH/84x/Vv3//Wo39czWsnus11bB6rtdUwxNzHRdcFyE6JibGo2f38Pf3V0BAgFwul55++mklJiZ6pI6vr6+Sk5M1bdo0xcTEWD7+unXr1KJFC/Xq1cvysS9q3Lixhg8frldeeUXPPfec/vSnP6miosLSGkVFRfr000/1wgsvVNcwPHTo/+LFizVmzBiPjN20aVMdPXpUDzzwgNLS0jxyOFJ4eLg2btwowzC0a9cunTx50rJDB3487wzDkM1mk3RhzhQXF3ukzoMPPlhdxxPjXwxQH3/8sXJycjRkyBDLa/j4+Ojo0aPq16+fioqKFBISYmmNyspKTZ48WZMmTZK/v3+tx66phiRFRERowoQJWrFihdq1a6f//u//trzG0aNHFRQUpKysLN10001aunSp5TWkC4eNbNu2TQMGDKj1+DXVuPnmmzVjxgw98MADOn36tKKioiyv0a5dO/3zn/+UJG3cuFHnzp2rdY2a3v+snus11WjXrp3+4z/+o9b9/1wNq+d6TTWsnus/rvHMM894ZK7jgusiRHvD8ePHlZCQoP79++vhhx/2WJ05c+bovffeU1pamr7//ntLx167dq22bt2q+Ph47du3T8nJyTp16pSlNUJCQvTII4/IZrMpJCREzZs3t7xG8+bNdc8998jhcCg0NFR+fn767rvvLK0hSWfPntW//vUv3XnnnZaPLUlZWVm655579N577+n1119XSkqKSktLLa3x+9//XgEBAUpISNDGjRt12223eeQ/KdKFzzpcVFJSoqCgII/U8Ya3335b6enpWrJkiVq0aOGRGr/+9a+1fv16xcXFWX7V1r179+rw4cPKyMjQs88+q0OHDmnGjBmW1pCk++67T507d67++rPPPrO8RvPmzdWnTx9JUp8+ffTpp59aXkOS3n33XfXr189j82PGjBlasWKF3n33XT366KMeuVLvzJkztXjxYo0YMUI33nijbrjhBkvG/fH7nyfmujfeY2uqYfVcr6mG1XP90ho333yzV+b69YoQbYFvv/1Ww4YN0/jx4zVw4ECP1PjrX/+qxYsXS5KaNGkim81m+S/zFStWKCcnR9nZ2QoPD9ecOXPUqlUrS2u8+uqr1b8kTp48KZfLZXmNyMhI/eMf/5BhGDp58qTOnTun5s2bW1pDknbu3Km7777b8nEvCgoKUmBgoCSpWbNmqqiosGyV+KI9e/YoMjJS2dnZ6tu3r9q1a2fp+Je69dZbtWPHDknS5s2b1b17d4/V8qTXX3+9ep54an+NHDmy+kOe/v7+l4USK0REROitt95Sdna2MjMz1bFjR02ePNnSGpI0fPhw7d69W5K0bds23XbbbZbXiIyM1KZNmyRdmJMdO3a0vIZ0of+Lhz55QrNmzaovMta6dWvLP6gsSZs2bdLMmTO1ZMkSnTlzRj179qz1mDW9/1k9173xHltTDavnek01rJ7rP67hrbl+veIKJhZYtGiRzp49q4ULF2rhwoWSpKVLl6px48aW1fjtb3+riRMnavDgwaqoqNCkSZMsORbT2wYOHKiJEycqLi5ONptNM2fOtPxQm969e2vnzp0aOHCgDMPQlClTPLJ69MUXX6ht27aWj3vRkCFDNGnSJDmdTpWXlyspKUlNmza1tEb79u31wgsvaNmyZQoMDPToCkVycrLS0tKUmZmp0NBQjxyS5GmVlZWaMWOGbrrpJv3xj3+UJN1xxx16+umnLa0zYsQIpaSkqFGjRmrSpImmT59u6fjekpGRoWnTpqlRo0Zq2bJl9ec6rJScnKzU1FTl5uYqICBAzz//vOU1pAvz3ZN/ZE6fPl1JSUny9fVVo0aNPLKv2rdvrxEjRqhJkyaKiorSvffeW+sxa3r/mzx5sqZPn27ZXPfGe+yPa1RWVurgwYNq06aNZXO9pseRmJho6Vz3xr7CD+rleaIBAACA+ozDOQAAAACTCNEAAACASYRoAAAAwCRCNAAAAGASIRoAAAAwiRANALpwSedVq1a5tW1paanWrFkj6cKVPvPz8926X3x8vKWXVpekI0eOKDY2VpKUlJSksrIyHTt2TB988IGldQAAlyNEA4BJp06dqg7RAwYM0G9+85s67uiC//qv/5LD4dD27dv18ccf13U7ANCgcbEVAA3O2LFjlZCQoB49emj37t166aWX1LJlSx0+fFhVVVVKTExUVFSU+vXrp5tvvlkOh0MhISHasGGD3nnnHZ0/f16pqamKiIhQTk6O1q9fr4qKCgUGBmrBggVatGiRDh06pJdeekmGYahly5YKDQ3VkiVL1KhRI504cUKDBg3S9u3btX//fiUkJMjpdNbYa3l5uSZNmqSvv/5alZWVGjp0qB588EF98sknmjFjhgzD0K9+9SvNmzev+rFI0vnz5zVnzhw1atSoeqw+ffrozTff1JIlS3T+/Hl16dJFs2fP1nvvvScfHx/NnTtXnTt31gMPPOCV5wEAGjJWogE0OI899phee+01SdJrr72mXr166YYbbtCKFSu0cOFCTZ06VZL0/fffa/To0crMzJQk/frXv9by5cs1Y8YMpaenq6qqSmfOnFFWVpZWrlypiooK7dmzRyNHjlTHjh01duzYy+qeOHFCCxYsUEZGhv7yl7/oz3/+s5YuXarVq1f/ZK+rV6/WDTfcoNzcXP3P//yP5s+fr++++05paWmaNWuW1qxZo7vuukuFhYU6ePCg5s6dq+XLl6tPnz569913rxjPx8dHI0aMUL9+/dS3b19FRkbqww8/VGVlpTZv3lxvVs0B4FrHSjSABqdXr16aO3euzpw5o48++khVVVX6+OOPtXv3bklSRUWFioqKJEkhISHV97vjjjskSZ06ddKpU6dkt9vVqFEjPfvss2ratKlOnDihioqKn6zbqVMnNWrUSIGBgQoODpbD4VCzZs1UWlr6k/cpLCzU3XffLUkKCAhQhw4d9PXXX+v06dPq0KGDJGnw4MGSpOPHj2vGjBlq2rSpTp48qW7duv3ivnjssceUnZ2tqqoq3X333XI4HL94HwDAL2MlGkCDY7fbdf/99ysjI0N9+/ZVhw4d9NBDDyk7O1tLly7V/fffr2bNmlVve9HFkP3555+rTZs22r9/vzZs2KD58+crLS1NVVVVMgxDdrtdVVVVV9S12Wyme+3QoYM++ugjSZLL5dKBAwfUtm1btW7dWl9++aUkacmSJXr//feVmpqqmTNnavbs2WrdurUMw/jJx3+xv+7du+vrr7/Wq6++qoEDB5ruDwBQM1aiATRIv//979W3b1+99957at26tVJTU/XEE0/I5XLJ6XReFp4vOnLkiBISElRWVqapU6eqffv2atKkiQYMGCCHw6FWrVrpm2++UdeuXVVeXq65c+eqcePGpvp65plnqleDo6KilJSUpLS0NMXFxam0tFRjx47VjTfeqOeee06TJk2S3W5Xq1atNGTIEPXv31+xsbEKCgpSy5Yt9c0339RYIywsTH/5y19022236aGHHtLDDz+sd999V506dTK/IwEANbIZP7WUAQBoEJYuXaobbriBlWgAsBAr0QDQgKWkpKioqEgLFiyo61YAoEFhJRoAAAAwiQ8WAgAAACYRogEAAACTCNEAAACASYRoAAAAwCRCNAAAAGDS/wNTiYtPBFTowgAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -2618,7 +3357,9 @@ "cell_type": "code", "execution_count": 35, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2636,7 +3377,9 @@ "cell_type": "code", "execution_count": 36, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2694,7 +3437,9 @@ "cell_type": "code", "execution_count": 37, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2738,13 +3483,13 @@ "**EXERCISE**\n", "\n", "- Create a table, called `heatmap_prep`, based on the `survey_data` DataFrame with the row index the individual years, in the column the months of the year (1-> 12) and as values of the table, the counts for each of these year/month combinations.\n", - "- Using the seaborn documentation make a heatmap starting from the `heatmap_prep` variable.\n", + "- Using the seaborn documentation, make a heatmap starting from the `heatmap_prep` variable.\n", "\n", "
Hints\n", "\n", "- The `.dt` accessor can be used to get the `year`, `month`,... from a `datetime` column\n", "- Use `pivot_table` and provide the years to `index` and the months to `columns`. Do not forget to `count` the number for each combination (`aggfunc`).\n", - "- `resample` needs an aggregation function on how to combine the values within a single 'group' (in this case data within a year). In this example, we want to know the `size` of each group, i.e. the number of records within each year.\n", + "- Seaborn has an `heatmap` function which requires a short-form DataFrame, comparable to giving each element in a table a color value.\n", "\n", "
" ] @@ -2753,7 +3498,9 @@ "cell_type": "code", "execution_count": 39, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2818,7 +3565,9 @@ "cell_type": "code", "execution_count": 40, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2829,7 +3578,9 @@ "cell_type": "code", "execution_count": 41, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2873,7 +3624,9 @@ "cell_type": "code", "execution_count": 42, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2885,7 +3638,9 @@ "cell_type": "code", "execution_count": 43, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2896,7 +3651,9 @@ "cell_type": "code", "execution_count": 45, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2923,7 +3680,15 @@ "\n", "**EXERCISE**\n", "\n", - "Recreate the same plot as in the previous exercise using Seaborn `relplot` functon with the `month_evolution` variable." + "Recreate the same plot as in the previous exercise using Seaborn `relplot` functon with the `month_evolution` variable.\n", + " \n", + "
Hints\n", + "\n", + "- We want to have the `counts` as a function of `eventDate`, so link these columns to y and x respectively.\n", + "- To create subplots in Seaborn, the usage of _facetting_ (splitting data sets to multiple facets) is used by linking a column name to the `row`/`col` parameter. \n", + "- Using `height` and `widht`, the figure size can be optimized.\n", + " \n", + "
" ] }, { @@ -2937,7 +3702,9 @@ "cell_type": "code", "execution_count": 46, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -3035,7 +3802,9 @@ "cell_type": "code", "execution_count": 47, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -3087,7 +3856,9 @@ "cell_type": "code", "execution_count": 48, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -3100,7 +3871,9 @@ "cell_type": "code", "execution_count": 49, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -3149,14 +3922,16 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 44, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "image/png": 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AwJpj586dy+rVq1mwYAE9e/bEMAyOHj1aU3toaCjHjx/HarXi5uZGQkICXl5enDt3jsrKSvr06UNycjIXLlxg9+7dJCQkOLTP5sJut5tdQoMpLS1tVv3cjCv1CurXmd00iL788ktyc3NZs2YNv/nNbwCorq5m3bp1bN682WFF1XYOyt3dncLCQrp06cJXX31FQEAA8N1jzL+3fv16ZsyYgYeHB6NHj2bfvn0EBwezb98+wsPDycnJAeDw4cNs376dDRs2cPXqVaKiojAMA4vFQmRkJMnJyfTt2/eG58jkWiEhIWaX0GDsdnuz6udmXKlXUL/OwGaz1Tp+0yBq06YNhYWFlJeXU1hYCHwXEi+//HLDV/hPjBgxgpkzZ9KhQwf8/f1rPebuu+9m6NChtG/fnoCAAHr06MG0adOIj49n1apV+Pr64uHhQadOnfD09CQqKgp3d3f8/PwoKCgAICoqioiICD744IPGbE9ExGVZjB9fiVCL/Pz8mhVIc5efn8/kyZN56623bniMzWYjNU8XMXyvOd3ixxl/inQUV+oV1K8zsNlstT5YtU63+Pn8889ZuXIl5eXlNVtYf/7znxu8SLNt27aNN998k+TkZLNLERFxGXUKov/6r/9ixYoVdOjQwdH1mGrAgAEMGDDA7DJERFxKnYIoKCiITp06OboWERFxQXUKolatWjFmzBhCQkJqrmhz9Uubm9N5kZtxxn1mEWle6hREDz30kKPrEBERF1WnJ7RGRkZSWVnJ6dOnueOOOxRMIiLSYOoURNOmTSMvL4/du3dTXFxMYmKio+sSEREXUacgOnXqFC+99BLu7u48/PDDXLlyxdF1iYiIi6hTEFVVVXHx4kUsFgtFRUXX3FZHRETkVtTpYoX4+HiGDRtGYWEhv/71r3n11VcdXZeIiLiIOgWRj48P27Zt4+LFi7Rv377BHownIiJSpz22P/zhDzz99NNs376dkpISR9ckIiIupE5BtGLFCpYuXcrly5cZPXq0tuZERKTB1Pmqg8rKSsrLy6murqZFixaOrElERFxInc4RjRw5krKyMvr378+aNWto3bq1o+sSEREXUacVUf/+/SkqKmLTpk3893//Nxs2bHB0XSIi4iLqFERbt24lPT2d22+/nXHjxpGRkeHoukRExEXUKYisVivt2rXDYrHg4eGhrTkREWkwdQqijh07snDhQi5dukRqaip33HGHo+sSEREXUaeLFWbMmMGGDRsICwvD09OTWbNmOboupxeXFWd2CY3n2K1P4SrPbxKRf12dgqhly5YMGzbM0bWIiIgL0t1LRUTEVAoiERExVYMH0YgRIzhw4AAA5eXlhIWFsWrVqpr3hw8fzuHDh286R25uLrGxsQ1dGtnZ2SQlJTX4vCIiUn8NHkT9+vXjyy+/BMBms9GvXz8+/fRTAMrKyjh79izdunVr6G8rIiJNVJ0uVvhXPPDAAyxbtoznnnuOnTt3Eh0dzYIFC7hy5QqHDh2id+/efPTRR6SlpWG1WgkLC2PSpEkUFBQwadIkDMPAz8+vZr7IyEh69+7NkSNHsFgsLFu2DB8fHxYuXMgXX3yBYRiMGjWKgQMHsm7dOt5//32sViuhoaEkJiaSm5vLlClT8PT0xNPTk7Zt2wKQnp7Oxx9/TGVlJT4+PixdupRXXnmFyMhIIiIiyM3NJSUlhdTU1Ib+iERE5AcafEV0zz33cPz4cQzD4IsvvqB3797cf//9/OUvf2Hv3r08+OCDLF26lLS0NDIyMsjPz2f37t2sWbOGJ598krVr19K/f/+a+YqLi3niiSdIT0/H39+f7Oxsdu7cyZkzZ3jnnXf405/+xIoVK7h8+TKZmZm8+uqrvPvuuwQFBVFZWcnixYuZMGECaWlp3HvvvQBUV1dz6dIl0tLSePvtt6msrOTgwYNER0fz3nvvAbBx40aGDh3a0B+PiIj8SIOviKxWK926dSM7Oxs/Pz/c3d0JDw/n008/5fDhw0RERHDx4kXGjh0LfBc0p0+f5ujRowwePBiA0NDQa24jdM899wDQoUMHysrKyMvL49ChQzXnkSorK8nLy2Pu3LmsXr2aBQsW0LNnTwzD4OjRo3Tv3r1m3uPHj2O1WnFzcyMhIQEvLy/OnTtHZWUlffr0ITk5mQsXLrB7924SEhIa+uNxWXa73ewS6qS0tLTJ1HqrXKlXUL/OrMGDCKBv376sXLmSJ554AoCwsDCWLVuG1WolMDCQDh06sHr1atzc3MjMzCQkJITjx4+zb98+unXrxsGDB6+Z78dPhA0ODqZPnz7MmjWL6upqli1bRmBgIH/4wx+YMWMGHh4ejB49mn379hEcHMy+ffsIDw8nJycHgMOHD7N9+3Y2bNjA1atXiYqKwjAMLBYLkZGRJCcn07dvX9zc3Bzx8bikkJAQs0uoE7vd3mRqvVWu1CuoX2dgs9lqHXdIED3wwAO89tprvPHGGwC4u7vj4+PDPffcg6+vL6NGjSI2Npaqqip++tOfMnDgQF566SXi4+PZsmULgYGBN53/4YcfZu/evTzzzDOUlJTQv39/vL29ufvuuxk6dCjt27cnICCAHj16MG3aNOLj41m1ahW+vr54eHjQqVMnPD09iYqKwt3dHT8/PwoKCgCIiooiIiKCDz74wBEfjYiI/IjFMAzD7CKcSX5+PpMnT+att9664TE2m43UPF3E8K9oKrf4ccafIh3FlXoF9esMbDYbYWFh143rF1p/YNu2bYwZM4aJEyeaXYqIiMtwyNZcUzVgwAAGDBhgdhkiIi5FKyIRETGVVkT11FTOedwqZ9xnFpHmRSsiERExlYJIRERMpSASERFTKYhERMRUCiIRETGVgkhEREylIBIREVMpiERExFQKIhERMZWCSERETKUgEhERUymIRETEVAoiERExlYJIRERMpSASERFT6XlE9RSXFWd2CY3n2D8/xFWezyQiDU8rIhERMZWCSERETKUgEhERUymIRETEVE51scK8efM4dOgQhYWFlJaWEhQURPv27VmyZEmDzF9WVsbAgQPZsWNHg8wnIiK3zqmCKCkpCYDMzEyOHz/OpEmTTK5IREQczamCqDZJSUk8/vjjhIeHk52dzZYtW5g3bx4fffQRaWlpWK1WwsLCmDRpEjabjZSUFFq2bEmbNm1YsGABFouFSZMmcfnyZTp27Fgz7969e3nzzTcBKC0tJSUlhb1793LixAkSExOpqqriqaeeYtOmTbi7u5vVvohIs+f0QVSbS5cusXTpUjZt2oSnpycvv/wyu3fvZteuXTzyyCOMHj2aHTt2cPnyZXbs2EHXrl2Jj4/n73//O3v27AHg6NGjzJ8/n4CAAFasWMHWrVuJjY0lKiqKSZMm8dlnn9GnTx+FUB3Z7XazS2gQpaWlzaaXf8aVegX168yaVBAZhgHAqVOnuHjxImPHjgWguLiY06dPM27cOFasWMHIkSMJCAige/fuHD16lAcffBCAHj160LLldy0HBASQnJyMl5cX+fn5hIaG4u3tzX333ceuXbvIzMxk/Pjx5jTaBIWEhJhdQoOw2+3Nppd/xpV6BfXrDGw2W63jTn/VnLu7O4WFhQB89dVXAAQGBtKhQwdWr17N2rVrGT58OD169CArK4shQ4awdu1a7rrrLtavX09wcDD79++v+frKykoAXnvtNebMmcO8efPw9/evCbmYmBg2bNjAhQsX6NatW+M3LCLiYpx+RRQdHc2UKVPIysriZz/7GQC+vr6MGjWK2NhYqqqq+OlPf8rAgQMpLy8nKSkJLy8v3NzcmDlzJh06dOCVV15h2LBhBAcH4+bmBsDgwYOJiYmhTZs23H777RQUFADfrZpOnjzJs88+a1bLIiIuxWJ8vxQQAKqrqxk2bBirVq3C29u71mNsNhupeamNXJlzay73mnPG7QxHcaVeQf06A5vNRlhY2HXjTr8115hOnz7NkCFDGDx48A1DSEREGpbTb801pqCgID744AOzyxARcSkKonpqLltR/4wzLu9FpHnR1pyIiJhKQSQiIqZSEImIiKkURCIiYioFkYiImEpBJCIiplIQiYiIqRREIiJiKgWRiIiYSkEkIiKmUhCJiIipFEQiImIqBZGIiJhKQSQiIqZSEImIiKn0PKJ6isuKM7uExnPM7AKu5SrPghJxFVoRiYiIqRREIiJiKgWRiIiYSkEkIiKmctog2rNnD3fffTdbtmy5ZjwyMpKkpKR6z5uRkcHSpUtvtTwREWkgThtEAMHBwWzevLnm9ZEjR7h69aqJFYmISENz6su3u3XrxokTJ7h8+TJt2rThww8/JDIykrNnz/Lhhx/y1ltv4e7uzs9+9jNmzpxJVlYWO3fupLS0lFOnTvHb3/6WqKgovvzyS+bMmUPbtm2xWq307NkTgIULF5KTk0NxcTFdunRh7ty5PP3008yaNYu77rqLnTt38umnnzJt2jRzPwgRkWbMqYMI4JFHHuGTTz4hKiqKAwcO8Nvf/ha73c7SpUt577338Pb2Zs6cObz77rt4eXlRVFTEqlWrOHHiBOPGjSMqKoq5c+eycOFCOnfuXBMqRUVFtGnThjVr1lBdXc0TTzxBfn4+0dHRvPfee0yePJlNmzYRF+dCvy/URNjtdofNXVpa6tD5nYkr9Qrq15k5fRBFRkYyffp0goKC6NWrFwDV1dXceeedeHt7A3Dfffexa9cuevToQbdu3QDo0KED5eXlAOTn59O5c2cAQkNDOXXqFB4eHly8eJGEhAS8vLwoKSmhoqKCxx9/nCFDhjB69GjOnTvHv/3bv5nQtdxMSEiIw+a22+0Ond+ZuFKvoH6dgc1mq3Xcqc8RAQQFBVFSUsLatWsZNGgQABaLhdzcXEpKSgDYu3dvTdBYLJbr5vDz8yM3NxeAgwcPApCdnc3Zs2f5/e9/T0JCAqWlpRiGgaenJ3369CE5OZnBgwc3RosiIi7N6YMI4PHHH+fs2bM1YdO+fXtefPFFRowYQUxMDN988w3Dhg274dfPnz+fxMRERo4cSV5eHgDdu3fn9OnTxMTEMGHCBIKCgigoKAAgJiaG7du3ExkZ6fjmRERcnMUwDMPsIpzNgQMHSE9P54033qj1fZvNRmpeaiNXJd9z5L3mnHE7w1FcqVdQv87AZrMRFhZ23bjTnyNqbOnp6WzatIklS5aYXYqIiEtQEP3I8OHDGT58uNlliIi4jCZxjkhERJovrYjqyVWeieOM+8wi0rxoRSQiIqZSEImIiKkURCIiYioFkYiImEpBJCIiplIQiYiIqXSLn3q40R1kRUTk5mq7xY+CSERETKWtORERMZWCSERETKVb/NRRdXU106dP58iRI7i7uzN79mw6depkdln1UlFRwZQpU/j6668pLy/n+eef58477yQpKQmLxcJdd93FtGnTsFqtrF+/nnfeeYeWLVvy/PPP84tf/ILS0lJefvllLly4QOvWrUlJScHX19fstv6pCxcuEBUVxerVq2nZsmWz7nflypXs2LGDiooKhg0bRu/evZtlvxUVFSQlJfH1119jtVqZNWtWs/13+/e//50FCxawdu1aTp48ecs97t+/n+TkZFq0aEG/fv144YUXzGvOkDrZtm2bkZiYaBiGYezbt88YN26cyRXV38aNG43Zs2cbhmEYFy9eNB566CEjLi7O+Otf/2oYhmFMnTrV+Pjjj42CggLjySefNMrKyozLly/X/Hn16tXGkiVLDMMwjM2bNxuzZs0yrZe6Ki8vN8aPH288+uijxrFjx5p1v3/961+NuLg4o6qqyigqKjKWLFnSbPv95JNPjAkTJhiGYRi7du0yXnjhhWbZa2pqqvHkk08a0dHRhmEYDdLjoEGDjJMnTxrV1dXGmDFjjJycHHOaMwxDW3N1ZLPZePDBBwHo2bMnOTk5JldUf4899hgvvfRSzesWLVpw6NAhevfuDUB4eDh/+ctfOHDgAPfeey/u7u74+PjQsWNHDh8+fM1nER4ezueff25KH/+KlJQUnn76afz9/QGadb+7du2ia9eu/O53v2PcuHFEREQ02347d+5MVVUV1dXVFBUV0bJly2bZa8eOHVm6dGnN61vtsaioiPLycjp27IjFYqFfv36m9q4gqqOioiK8vb1rXrdo0YLKykoTK6q/1q1b4+3tTVFRERMmTOA///M/MQwDi8VS8/6VK1coKirCx8fnmq8rKiq6Zvz7Y51ZZmYmvr6+Nf8xAs2632+++YacnBwWL17MjBkzmDRpUrPt18vLi6+//pqBAwcydepUYmNjm2WvAwYMoGXL/zuTcqs9/vj/Z2b3rnNEdeTt7U1xcXHN6+rq6mv+YjQ1Z8+e5Xe/+x3PPPMMkZGRzJ8/v+a94uJi2rRpc13PxcXF+Pj4XDP+/bHObNOmTVgsFj7//HPsdjuJiYlcvHix5v3m1m+7du0IDg7G3d2d4OBgPDw8OHfuXM37zanftLQ0+vXrx8SJEzl79iwjR46koqKi5v3m1OsPWa3/t4aoT4+1HWtm71oR1VFoaCjZ2dkA7N+/n65du5pcUf2dP3+e5557jpdffpmhQ4cCcM8997Bnzx4AsrOz6dWrF927d8dms1FWVsaVK1fIzc2la9euhIaGsnPnzppja/sFNWeybt060tPTWbt2LSEhIaSkpBAeHt5s+w0LC+Ozzz7DMAzy8/O5evUq999/f7Pst02bNjU/7bdt25bKyspm/Xf5e7fao7e3N25ubpw6dQrDMNi1axe9evUyrR/9QmsdfX/V3D/+8Q8Mw2DOnDl06dLF7LLqZfbs2Xz00UcEBwfXjL366qvMnj2biooKgoODmT17Ni1atGD9+vW8++67GIZBXFwcAwYM4OrVqyQmJlJYWIibmxsLFy7Ez8/PxI7qLjY2lunTp2O1Wpk6dWqz7feNN95gz549GIZBfHw8gYGBzbLf4uJipkyZQmFhIRUVFYwYMYJ///d/b5a9njlzhoSEBNavX8///u//3nKP+/fvZ86cOVRVVdGvXz/i4+NN601BJCIiptLWnIiImEpBJCIiplIQiYiIqRREIiJiKgWRiIiYSkEkIiKmUhCJiIipFEQiImKq/wfMNG7slP8QCwAAAABJRU5ErkJggg==\n", 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cuTNxcXHs3r2bCRMm8B//8R9UqFCB0NBQTp06xZ49e7BYLHTu3JmxY8cSExPDmjVrqFu3LoZh0KBBA65fv86UKVO4ceMGubm5TJs2DavVSmxsLIsWLQLg3XffpUuXLnTt2tXu/YqIOKuHhlGfPn2wWq0P3Gdv586dY9WqVVSvXp1OnTpx7dq1B742NTWVuLg4qlatyjvvvMM333yDq6srmzdvxjAMlixZwvbt26lUqZJteS4zM5PBgwfTrVs34uPjWb16NR988AFz584lLy8PDw8Pjhw5ct+lShERKTkPDaMJEyYAEBcXR+fOne/aFxsba7+q/l9AQAA+Pj4A1KhRg+zs7Ae+tnbt2lStWhWA4OBgXn/9dUJCQujbty9WqxUvLy+qV68O3L7W3p0xV65cydq1a8nPz6dChQq4urrSqVMn9u/fj4+PD61atSrRJUlHlJqaanYJJSY3N9eh+vlX1K/jKmu9PjSMkpOTSUlJ4ZNPPiE9Pd22PT8/n/Xr1xMSEmLX4n56zMowDNutz4G7bn3u7u5uezxr1izOnDnDzp07CQ0NZd26dVgslrvGAfj444/x9fVl0aJFpKSksHDhQgBefvllVq9eTa1atezeoyNo1KiR2SWUmNTUVIfq519Rv46rNPaamJj4wH0PvTadj48PFSpUoKCgAKvVavvvxo0bzJ8/v8QLLQ4vLy8yMzOB+zd2/fp1li9fTv369ZkwYQJVqlTBYrGQnZ3NtWvXKCgoICkpCQCr1UpAQAAAe/fupaCgALj9j2tGRgbJycm0bt36CXUmIuK8Hjozeuqpp+jfvz8dO3bEw8OD7Oxs26zCLP369eO3v/0tu3fvvm/qe3t7Y7VaGTRoEBUqVKB58+ZUqVKFCRMmEBoaSq1atWjQoIFtrPDwcHbt2sXw4cOJjY1l+/btDBw4kPbt25OTk3PXTExEROzDxShGukybNo39+/dTs2ZN4J/LZdu2bbN7gWYwDIPXX3+dWbNmUadOnXv2JyYmsip9lQmVlU6OdG260ri0YU/q13GVxl4TExNp2bLlffcV69p0J06cYP/+/U4xS7jz+6aXXnrpvkEkIiIlr1hhFBgYiNVqpVq1avaux3T+/v52ueqDiIg8WLHCKC0tjW7dulGnTh1cXV0dfpmuOBxpaepfKY3TfRFxLMUKI7POnBMREedQrNuOV65cmR07drBhwwZq1apFWloaFStWtHdtIiLiJIoVRhEREVSqVImUlBQArly5wpQpU+xamIiIOI9ihVFOTg6vvvqq7SoHvXr1Ijc3166FiYiI8yhWGBUVFfG///u/tlO7v/76a4qKiuxamIiIOI9incAwffp0pk+fzvHjx+nQoQMNGzZk9uzZ9q5NREScRLHC6Ntvv2XhwoW2KzCIiIiUpGKFkdVqZdy4cZQvX54ePXoQHByMn5+fvWsTEREnUaxjRhMmTGD79u289957uLm5MX36dF555RV71yYiIk6iWGEEt2/NkJSUxJEjR8jMzNQv8kVEpMQUa5lu1KhRZGZm0rFjR4YPH07z5s3tXZeIiDiRYs2MOnfujJubG/v27aN58+YsWbKEAwcO2Ls2ERFxEsUKoz179vDxxx/bzqYbOXIky5cvt2thIiLiPIoVRm5ublStWtX2o9fq1as7xb2NRETkySjWMSN/f3+WLl2K1Wrliy++YM+ePbZbd4uIiDyuYoXRnDlz2LFjBy1btuTIkSN07dqVnj172ru2Um3MjjFml/BknX68tzvT/Z9E5OcrVhhZLBb69etHv3797F2PiIg4oWL/zkhERMReFEYiImI6u4RRSEgIaWlptuc9e/Zk//79tufjx4/nm2++eegYOTk5dOnSpcRri4qKYtmyZSU+roiIPDq7hFHbtm05dOgQcPuusLm5ufz1r3+17U9OTqZFixb2+GgRESmDinUCw8/Vtm1b4uLiGDhwIElJSfTt25fExEQAzpw5g7+/P9988w3r1q3Dzc2Nxo0bExERwfXr15k4cSIATZs2tY3XvXt3hg4dSlxcHPn5+axfvx5PT0+mTZtGWloahYWFTJo0iRdffJE//elPREVF4e7uTmBgIDNmzCA+Pp65c+fi7+9PxYoVqV27NoWFhYSHh5ORkcGNGzeYOHEiAQEBTJ8+nU2bNgGwcuVKvL29GTlypD2+JhER+X92mRm1adPGFj6HDx+mXbt23Lp1yzZDatKkCR9++CGffPIJUVFR/P3vfycxMZGYmBgaNGjA+vXradiwoW28W7du8Ytf/IJNmzbh7+/Pt99+y44dO/Dx8WHjxo2sWLGCuXPnArB27VqWLVvG5s2bady4Mbm5ubz33nssWrSIDz/8EKvVCsDVq1fp0KEDUVFRLF26lGXLllG/fn3y8vK4dOkSAPv376dXr172+IpERORH7DIzqlKlCp6enmRkZHDs2DEmT55M06ZNOXr0KIcPH+bZZ58lPT2dN954A4Ds7GzS09M5c+YMrVu3Bm4H2o+1atUKAD8/P7Kzszl69CiJiYkkJSUBkJeXR35+PiEhIYwfP56+ffsSEhJC+fLluXjxIoGBgQC0bt2avLw8KlWqREpKClu2bMFisZCVlQVA37592blzJ71798bb25saNWrY4ytyOqmpqWaXUCy5ubllptaSoH4dV1nr1S5hBLeX6g4cOICLiwvly5e3/WA2JSWF4cOHk5CQwNq1a+96T1JSEhbL7claUVHRXftcXV1tjw3DwN3dnbFjxxISEnLX68aMGUOfPn3YvXs3o0aNIioqyjbmnfcCxMbGcvXqVT799FOysrIYNGgQcPvki4kTJ+Lp6XnP2PLoysotR1JTU8tMrSVB/Tqu0tjrnRWz+7Hbqd1t27Zly5YtPP/88wC0bNmSr776ipo1axIYGMiZM2f44YcfAPj9739PRkYG9erV4/jx4wAkJCQ8dPxmzZqxd+9eAH744Qfef/99ioqKWLJkCT4+Prz++us8//zzpKen4+vry9mzZzEMw3ZihdVqxd/fH4vFwp49e8jPzwegWrVqVK5cmZiYGLp3726Pr0ZERH7CbmHUpk0bTpw4QcuWLYHbF1fNysqiTZs2eHp6MnXqVN58802GDRtGVlYWNWvW5OWXX+bo0aOMGjWK77///qHj9+zZEy8vL4YNG8bYsWNp2bIlFosFLy8vhg4dyqhRo3BxcaFRo0ZMnjyZsLAwxo4da7tdeo8ePdi3bx+jRo3C09MTPz8/VqxYAUBwcDC+vr54e3vb6+sREZEfcTHurFuJTXh4OP379+eFF1647/7ExERWpa96wlWVbWXl2nSlcWnDntSv4yqNvSYmJtomKD+lKzD8SF5eHkOGDMHb2/uBQSQiIiXPbicwlEXlypVj69atZpchIuJ0FEaPqKwsO5WE0jjdFxHHomU6ERExncJIRERMpzASERHTKYxERMR0CiMRETGdwkhEREynMBIREdMpjERExHQKIxERMZ3CSERETKcwEhER0ymMRETEdAojERExncJIRERMpzASERHT6X5Gj2jMjjFml/Bknf7XL3GmezyJSMnSzEhEREynMBIREdMpjERExHSl7pjR/PnzOXHiBJmZmdy8eZOAgAAqV67M8uXLS2T8kydPMmfOHDZu3Fgi44mIyOMrdWEUEREBQHR0NKdOnSI8PNzkikRExN7KxDJdREQEcXFxAMTFxdkCa9OmTQwbNoxXX32VdevWAfDdd98xdOhQRowYwRtvvMG1a9e4dOkSQ4cOZfTo0Xz22We2cdetW8fQoUMZPHgwy5cv59atW3Tv3p2cnBwADh8+zIQJE55wtyIizqdMhNH9pKWlsWvXLjZv3symTZv4y1/+Qnp6OtHR0bzyyits3LiR0aNHk5mZySeffEKvXr1Ys2YNPj4+d43z6aefsnXrVqKjo7l58ybdunVj3759AOzbt4+QkBAz2hMRcSqlbpmuuFJSUjh//jwjR44EICcnh4sXL9K1a1dmzpzJuXPn6NWrF/Xr1+fMmTO89NJLALRt25YDBw4AUL58eUJDQ3Fzc8NqtZKVlcXLL7/MBx98QJ8+fTh06BBhYWGm9VjWpKamml3CY8vNzXWIPopL/TqustZrmQgjFxcX2+PCwkIA3N3d6dSpE7Nnz77n9du2bbMt57399tsYhoHFcnsSWFRUBMDFixfZsGEDf/zjH/Hy8rLNgBo2bMjly5dJTk6mQYMGlCtXzt7tOYxGjRqZXcJjS01NdYg+ikv9Oq7S2GtiYuID95WJZTovLy8yMzOBfzbzy1/+koSEBG7evIlhGPzud78jNzeXqKgosrKy6Nu3L6NGjSI1NZV69epx/PhxABISEgCwWq1Uq1YNLy8vTpw4wcWLFykoKACgZ8+ezJ49mz59+pjQrYiI8ykTM6N+/frx29/+lt27d9uS/umnn2bkyJEMHz4cV1dXunXrRvny5QkICCAsLIyKFSvi4eHBvHnzyMvLY/LkyezZs4dnn30WuP1XvJeXF8OGDaNly5YMGzaMWbNmsWHDBnr16sW6deto27atmW2LiDiNUhtGAwYMsD1u0qQJu3fvvuc1w4cPZ/jw4XdtCwoKIigo6J7X/vgsujvWrl1738/+7//+b4YMGYKrq+vPLVtERB5BqQ0js0RGRpKWlsaKFSvMLkVExGkojH7id7/7ndkliIg4HYXRI3Km2yWUxrNyRMSxlImz6URExLEpjERExHQKIxERMZ3CSERETKcwEhER0ymMRETEdAojERExncJIRERMpzASERHTKYxERMR0CiMRETGdwkhEREynMBIREdMpjERExHQKIxERMZ3uZ/SIxuwYY3YJT9Zpswu4mzPdT0rEGWhmJCIiplMYiYiI6RRGIiJiulIdRhcuXKBhw4YcPXr0ru0DBgwgIiLikcddsGAB0dHRj1mdiIiUlFIdRgC1a9cmNjbW9vz8+fNkZ2ebWJGIiJS0Un82XbNmzTh48CC3bt3C1dWVP//5z7Rv357c3FwSEhJYsmQJbm5u+Pr6Mm/ePGJjY0lMTOTKlSt8//33vPHGGwwePJiYmBjWrFlD3bp1MQyDBg0acP36daZMmcKNGzfIzc1l2rRpWK1WYmNjWbRoEQDvvvsuXbp0oWvXriZ/EyIijqvUz4zc3d1p1qwZCQkJAHz55Zd07NgRgBkzZrBkyRKioqKoXLkyO3bsAODkyZMsX76cFStWEBUVhWEYLFmyhA0bNvD+++9z/vx5ADIzMxk8eDAbN27kN7/5DatXr6ZDhw4kJyeTl5eHYRgcOXKEX/3qV+Y0LyLiJEr9zAjgpZdeIjY2Fh8fH3x9falQoQJZWVm4uLjw1FNPAdCqVSuSkpJ47rnneP7553F1dcXPz4/s7GysViteXl5Ur14dgBYtWgBQo0YNVq5cydq1a8nPz6dChQq4urrSqVMn9u/fj4+PD61atcLDw8O03uX+UlNT7TJubm6u3cYujdSv4yprvZaJMGrXrh2zZ8/Gx8eH4OBgAFxcXDAMw/aaoqIiXFxcAHBzu7cti+Wfk8A77/v444/x9fVl0aJFpKSksHDhQgBefvllVq9eTa1atQgJCbFbX/LoGjVqZJdxU1NT7TZ2aaR+HVdp7DUxMfGB+0r9Mh3cXqpr3bo127dvp0uXLgBUrlwZFxcX0tPTATh06BCNGze+7/urVKlCdnY2165do6CggKSkJACsVisBAQEA7N27l4KCAuD2P3QZGRkkJyfTunVre7cnIuL0ykQYwe2luueee46KFSvats2ZM4cpU6YwYsQICgoK6N27933fa7FYmDBhAqGhoUyaNIkGDRoA0K9fP9avX8+//du/0bRpUzIzM9m+fTsA7du3p3HjxrbZloiI2I+L8eO1LgFuL+O9/vrrzJo1izp16tyzPzExkVXpq0yoTO6w17XpSuPShj2pX8dVGntNTEykZcuW991XZmZGT8qFCxcYOHAg7dq1u28QiYhIySsTJzA8Sf7+/ro6g4jIE6aZkYiImE4zo0fkTPfTKY1rzyLiWDQzEhER0ymMRETEdAojERExncJIRERMpzASERHTKYxERMR0uhzQI3jYlWdFROTBHnQ5IIWRiIiYTst0IiJiOoWRiIiYTpcD+pnmzp3LsWPHcHFxYerUqTRt2tTskh7ZwoULSUxMpLCwkDFjxtCkSRPefvttbt26hY+PD4sWLcLDw4PPP/+cjz/+GIvFwtChQxk0aBAFBQVERESQnp6Oq6sr8+bNo3bt2ma39FC5ubn07t2b8ePH8+KLLzp0r59//jlr1qzBzc2NsLAwnn32WYftNycnh/DwcK5evUpBQQHjx4/nmWeecbh+T548ya9//Wtee+01QkND+fvf//7YPf7tb39j5syZADRs2JBZs2aZ16AhxZaQkGC89dZbhmEYxqlTp4xBgwaZXNGji4+PN0aPHm0YhmFcuXLF6NixoxEREWF88cUXhmEYxoIFC4xNmzYZOTk5Ro8ePYxr164ZN2/eNIKDgw2r1WpER0cbM2fONAzDML766isjLCzMrFaK7f333zcGDBhgbN++3aF7vXLlitGjRw8jOzvbyMjIMCIjIx26340bNxqLFy82DMMwLl26ZAQHBztcvzk5OUZoaKgRGRlpbNy40TAMo0R6DA0NNY4dO2YYhmFMmjTJ+Oqrr558c/9Py3Q/Q3x8PN26dQPgmWee4dq1a1y/ft3kqh5N69atWbp0KXD7Fu43b94kISGBrl27AtC1a1fi4+M5duwYTZo0oWLFipQvX55WrVqRlJREfHw83bt3B6BDhw6l/gzDM2fOcPr0aTp16gTg0L3Gx8fz4osv4u3tTc2aNZkzZ45D91u1alWysrIAuHbtGlWrVnW4fj08PFi9ejU1a9a0bXvcHvPz87l48aJtdefOGGZRGP0Mly9fpmrVqrbn1atXJzMz08SKHp2rqysVKlQA4LPPPiMoKIibN2/i4eEBgI+PD5mZmVy+fJlq1arZ3lejRo17tru6umKxWMjPz3/yjRTTggULiIiIsD135F4vXLiAYRhMnjyZV199lfj4eIfut3fv3qSnp9O9e3dCQ0MJDw93uH7d3NwoX778Xdset8fLly9TqVIl22vvjGEWHTP6GYyfnAVvGAYuLi4mVVMy9u7dy7Zt21i3bh3BwcG27Xd6fVDPZem7+NOf/sTzzz9/13GAH9fqSL3ekZGRwfLly0lPT2fkyJEO3W9MTAxPP/00a9eu5W9/+xvvvvuuQ/d7x+P2eL9tZtLM6Gfw9fXl8uXLtuf/+Mc/qFGjhokVPZ4DBw7wX//1X6xevZqKFSvi6elJbm4ucPsfs5o1a963Zx8fH3x9fW1/RRUUFGAYBu7u7qb08a989dVXfPnllwwZMoTPPvuMlStXOmyvcHvG3rx5c9zc3AgICMDLy8uh+01KSqJDhw4ABAYGkpGR4dD93vG4PdasWdO2vPnjMcyiMPoZ2rdvz+7duwH47rvvqFmzJt7e3iZX9Wiys7NZuHAhH330EVWqVAGgXbt2tv7+8pe/8Ktf/YpmzZqRkpLCtWvXyMnJISkpiVatWtG+fXt27doFQFxcHG3btjWrlX/pgw8+YPv27WzdupXBgwfz61//2mF7hdvHBL799luKioq4cuUKN27ccOh+69Spw7FjxwC4ePEiXl5eDt3vHY/bo7u7O7/4xS84fPjwXWOYRVdg+JkWL17M4cOHcXFxYcaMGQQGBppd0iPZsmULy5Yto169erZt8+fPJzIykry8PJ5++mnmzZuHu7s7u3btYu3atbi4uBAaGkrfvn25desWkZGRnDt3Dg8PD+bPn89TTz1lYkfFs2zZMmrVqkWHDh0IDw932F7/8Ic/8Oc//5mbN28ybtw4mjRp4rD95uTkMHXqVH744QcKCwsJCwujfv36DtXv8ePHWbBgARcvXsTNzQ1fX18WL15MRETEY/V4+vRppk+fTlFREc2aNeOdd94xrUeFkYiImE7LdCIiYjqFkYiImE5hJCIiplMYiYiI6RRGIiJiOoWRiIiYTmEkIiKmUxiJiIjp/g+IQ7qMD6s0RgAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] @@ -3182,8 +3957,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -3197,7 +3975,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/_solved/case2_observations_processing.ipynb b/_solved/case2_observations_processing.ipynb index bc097b0..00d3771 100644 --- a/_solved/case2_observations_processing.ipynb +++ b/_solved/case2_observations_processing.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Observation data - data cleaning and enrichment

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -95,7 +92,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -104,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -207,7 +204,7 @@ "4 5 7 16 1977 3 DM M NaN" ] }, - "execution_count": 3, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -231,9 +228,11 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -242,7 +241,7 @@ "35549" ] }, - "execution_count": 4, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -289,7 +288,7 @@ "\n", "**EXERCISE**\n", "\n", - "- Add a new column, `datasetName`, to the survey data set with `datasetname` as value for all of the records (static value for the entire data set)\n", + "Add a new column, `datasetName`, to the survey data set with `datasetname` as value for all of the records (static value for the entire data set)\n", "\n", "
Hints\n", "\n", @@ -305,7 +304,9 @@ "cell_type": "code", "execution_count": 6, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -316,7 +317,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Cleaning the sex_char column into a DwC called [sex](http://rs.tdwg.org/dwc/terms/#sex) column" + "### Cleaning the `sex_char` column into a DwC called [sex](http://rs.tdwg.org/dwc/terms/#sex) column" ] }, { @@ -342,7 +343,9 @@ "cell_type": "code", "execution_count": 7, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -413,7 +416,7 @@ "\n", "
Hints\n", "\n", - "- A dictionary is a Python standard library data structure - no Pandas magic involved when you need a key/value mapping.\n", + "- A dictionary is a Python standard library data structure, see https://docs.python.org/3/tutorial/datastructures.html#dictionaries - no Pandas magic involved when you need a key/value mapping.\n", "- When you need to replace values, look for the Pandas method `replace`.\n", "\n", "
\n", @@ -425,7 +428,9 @@ "cell_type": "code", "execution_count": 9, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -440,7 +445,9 @@ "cell_type": "code", "execution_count": 10, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -505,7 +512,9 @@ "cell_type": "code", "execution_count": 12, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -520,7 +529,7 @@ }, { "data": { - "image/png": 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" ] @@ -1007,7 +1016,9 @@ "cell_type": "code", "execution_count": 21, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1617,7 +1628,9 @@ "cell_type": "code", "execution_count": 30, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1857,7 +1870,9 @@ "cell_type": "code", "execution_count": 35, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1907,12 +1922,14 @@ "cell_type": "code", "execution_count": 37, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "image/png": 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JUkAMVpIkSQExWEmSJAXEYCVJkhSQrNl5PRTakukSJElSDsuGp7i4YiVJkhQQg5UkSVJALulUYF9fH9/4xjfo6Oigv7+fRx99lHA4THFxMZs3b2bKlCm0trbyd3/3dxQUFHDfffdx++2309rayo9+9CMATp48ydtvv82rr746oROSJEnKlDGDVVtbG3v27CESiQDQ2NhIQ0MDsViMbdu20dXVxfz583nppZd44YUXAFixYgW33nor9fX11NfXA7Bu3Tq+/OUvT+BUJEmSMmvMU4FFRUW0tLSMHg8ODhKLxQCIxWIkEgmOHDlCWVkZ+fn55OfnE41GOXz48OhnXn75ZaZPn85tt902AVOQJEnKDmOuWFVXVzMwMDB6XFhYSG9vL2VlZXR3d5NKpbjxxhtpbW1leHiYs2fPcvDgQZYvXz76mWeffZannnpqYmYgSZIEJJNJRkZGSCaTGath3NstxONxmpubaW9vp6SkhHA4zJw5c1i5ciVr164lGo1y8803M2PGDABef/11pk+fTjQaDbx4SZKkf1NcXEwymaS4uHhC/z2JROKiY+MOVj09PcTjca6//nqampqorKzk2LFjHD9+nF27djE0NMTq1auZO3cuAAcOHKCysvKDVy9JkpQjxh2sotEo9fX1RCIRysvLqaqqIp1OMzAwwNKlS5k6dSobN24kLy8PgDfeeIOKiorAC5ckSco2oXQ6nc50EYlEgoULuzJdhiRJymHp9JZJOxVYWlr6nmNZ80ibbNiGXmObjP/D6vdnn3KHvcod9kqXwp3XJUmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAGKwkSZICkjU7r4dCWzJdgiRpDD4lQ3p/rlhJkiQFxGAlSZIUkEsKVn19fdTV1QHQ399PTU0NtbW1NDU1cf78eQBaW1tZsmQJK1eupLu7G4Bz586xdetWVqxYwT333DP6uiRJ0uVozGus2tra2LNnD5FIBIDGxkYaGhqIxWJs27aNrq4u5s+fz0svvcQLL7wAwIoVK7j11lv54Q9/yLvvvsvu3bsZHBzkhz/84cTORpIkKYPGXLEqKiqipaVl9HhwcJBYLAZALBYjkUhw5MgRysrKyM/PJz8/n2g0yuHDh/nxj3/MDTfcQH19PQ0NDSxatGjiZiJJkpRhY65YVVdXMzAwMHpcWFhIb28vZWVldHd3k0qluPHGG2ltbWV4eJizZ89y8OBBli9fzvHjx/nlL3/Js88+yz/8wz/w1a9+leeff35CJyRJmjjJZDLTJWTMyMjIFT3/XJHpPo17u4V4PE5zczPt7e2UlJQQDoeZM2cOK1euZO3atUSjUW6++WZmzJjBddddxx/90R8RCoUoKyvjn//5nydgCpKkyVJcXJzpEjImmUxe0fPPFZPRp0QicdGxcd8V2NPTQzwep7W1lRMnTlBRUcGxY8c4fvw4u3btYvPmzbz55pvMnTuX0tJSenp6ADh06BAzZ8784LOQJEnKcuNesYpGo9TX1xOJRCgvL6eqqop0Os3AwABLly5l6tSpbNy4kby8PJYtW8ajjz7KsmXLSKfTfO1rX5uIOUiSJGWFUDqdTme6iEQiwcKFXZkuQ5I0hit553VPBeaGyToVWFpa+p5jWfNImyv5y5pL/MOSG+xT7rBX0uXFndclSZICYrCSJEkKiMFKkiQpIAYrSZKkgBisJEmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgKSNTuvh0JbMl2CpCzhkxgk5SpXrCRJkgJisJIkSQrIJQWrvr4+6urqAOjv76empoba2lqampo4f/48AK2trSxZsoSVK1fS3d0NQDqd5rbbbqOuro66ujqefPLJCZqGJElS5o15jVVbWxt79uwhEokA0NjYSENDA7FYjG3bttHV1cX8+fN56aWXeOGFFwBYsWIFt956K0ePHuXTn/403/72tyd2FpIkSVlgzBWroqIiWlpaRo8HBweJxWIAxGIxEokER44coaysjPz8fPLz84lGoxw+fJj+/n4GBwepq6tj7dq1/OIXv5i4mUiSJGXYmCtW1dXVDAwMjB4XFhbS29tLWVkZ3d3dpFIpbrzxRlpbWxkeHubs2bMcPHiQ5cuX89GPfpT6+nr+5E/+hJ/+9Kds2LCBF198cUInJCn3JZPJTJcwaUZGRq6o+eYye5UbMt2ncW+3EI/HaW5upr29nZKSEsLhMHPmzGHlypWsXbuWaDTKzTffzIwZM4hGo+Tl5QGwcOFCBgcHSafThEKhwCci6fJRXFyc6RImTTKZvKLmm8vsVW6YjD4lEomLjo37rsCenh7i8Titra2cOHGCiooKjh07xvHjx9m1axebN2/mzTffZO7cuTzzzDP81V/9FQCHDh1i1qxZhipJknTZGveKVTQapb6+nkgkQnl5OVVVVaTTaQYGBli6dClTp05l48aN5OXlUV9fz4YNG+jp6SEvL4+vf/3rEzEHSZKkrHBJwWr27Nl0dnYCsGjRIhYtWnTBeCgU4rHHHvudz1177bW0trYGUKYkSVL2y5pH2vgIi9zgNQa5wT5JUma487okSVJADFaSJEkBMVhJkiQFxGAlSZIUEIOVJElSQAxWkiRJATFYSZIkBcRgJUmSFBCDlSRJUkCyZuf1UGhLpktQDnLHfklSNnHFSpIkKSCXFKz6+vqoq6sDoL+/n5qaGmpra2lqauL8+fMAtLa2smTJElauXEl3d/cFnz9y5AilpaWcPn064PIlSZKyx5inAtva2tizZw+RSASAxsZGGhoaiMVibNu2ja6uLubPn89LL73ECy+8AMCKFSu49dZbiUQiDA8P8/jjjxMOhyd2JpIkSRk25opVUVERLS0to8eDg4PEYjEAYrEYiUSCI0eOUFZWRn5+Pvn5+USjUQ4fPkw6naaxsZGHH354NJhJkiRdrsZcsaqurmZgYGD0uLCwkN7eXsrKyuju7iaVSnHjjTfS2trK8PAwZ8+e5eDBgyxfvpxnnnmGqqoq5s+fP6GT0JUrmUxmuoSsNDIy4u8mR9ir3GGvckOm+zTuuwLj8TjNzc20t7dTUlJCOBxmzpw5rFy5krVr1xKNRrn55puZMWMGe/bs4YYbbuDFF1/krbfeYvXq1Tz//PMTMQ9doYqLizNdQlZKJpP+bnKEvcod9io3TEafEonERcfGHax6enqIx+Ncf/31NDU1UVlZybFjxzh+/Di7du1iaGiI1atXM3fuXPbu3Tv6uUWLFvHcc899sBlIkiTlgHEHq2g0Sn19PZFIhPLycqqqqkin0wwMDLB06VKmTp3Kxo0bycvLm4h6JUmSstYlBavZs2fT2dkJ/OvK06JFiy4YD4VCPPbYY+/7M1555ZUPWKIkSVJucINQSZKkgGTNI218NElu8OJNSZIuzhUrSZKkgBisJEmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAZM3O66HQlkyXoCuUu/5LkoLiipUkSVJALilY9fX1UVdXB0B/fz81NTXU1tbS1NTE+fPnAWhtbWXJkiWsXLmS7u5uAH7729+yfv16amtrWbNmDceOHZugaUiSJGXemMGqra2NhoYGTp8+DUBjYyObNm1i586dFBQU0NXVxeHDh3nppZfo7Ozkueee4+mnnyaVStHZ2cmnP/1pdu7cyeLFi9m+ffuET0iSJClTxrzGqqioiJaWFjZu3AjA4OAgsVgMgFgsxr59+5g6dSplZWXk5+cDEI1GOXz4MKtWreLcuXMA/PrXv+YjH/nIRM1DkiQp48YMVtXV1QwMDIweFxYW0tvbS1lZGd3d3aRSKW688UZaW1sZHh7m7NmzHDx4kOXLlwOQl5fH5z73OX7+85/zne98Z+JmIn1AyWQy0yUEbmRk5LKc1+XIXuUOe5UbMt2ncd8VGI/HaW5upr29nZKSEsLhMHPmzGHlypWsXbuWaDTKzTffzIwZM0Y/89d//dccOXKEdevW8fd///eBTkD6fRUXF2e6hMAlk8nLcl6XI3uVO+xVbpiMPiUSiYuOjfuuwJ6eHuLxOK2trZw4cYKKigqOHTvG8ePH2bVrF5s3b+bNN99k7ty5PPvss/zt3/4tAH/wB39AXl7eB56EJElSthv3ilU0GqW+vp5IJEJ5eTlVVVWk02kGBgZYunQpU6dOZePGjeTl5bF06VIeeeQRXnzxRc6dO0c8Hp+IOUiSJGWFSwpWs2fPprOzE4BFixaxaNGiC8ZDoRCPPfbY73zuIx/5CDt27AigTEmSpOznBqGSJEkByZpH2vhYkdzgxZuSJF2cK1aSJEkBMVhJkiQFxGAlSZIUEIOVJElSQAxWkiRJATFYSZIkBcRgJUmSFBCDlSRJUkAMVpIkSQHJmp3XQ6EtmS5BumL4pANJmhiuWEmSJAXkkoJVX18fdXV1APT391NTU0NtbS1NTU2cP38egNbWVpYsWcLKlSvp7u4GYGhoiPvvv58///M/Z/ny5Rw8eHCCpiFJkpR5Y54KbGtrY8+ePUQiEQAaGxtpaGggFouxbds2urq6mD9/Pi+99BIvvPACACtWrODWW2/lO9/5DrfeeiurVq3iF7/4BV/60pf4wQ9+MLEzkiRJypAxV6yKiopoaWkZPR4cHCQWiwEQi8VIJBIcOXKEsrIy8vPzyc/PJxqNcvjwYVatWsWKFSsAOHfuHPn5+RM0DUmSpMwbc8WqurqagYGB0ePCwkJ6e3spKyuju7ubVCrFjTfeSGtrK8PDw5w9e5aDBw+yfPlypk+fDsBbb73Fhg0b2LRp08TNRNIlSyaTmS5B/7+RkRH7kSPsVW7IdJ/GfVdgPB6nubmZ9vZ2SkpKCIfDzJkzh5UrV7J27Vqi0Sg333wzM2bMAODw4cM8/PDDbNy4kbKyssAnIGn8iouLM12C/n/JZNJ+5Ah7lRsmo0+JROKiY+MOVj09PcTjca6//nqampqorKzk2LFjHD9+nF27djE0NMTq1auZO3cur7/+Og8++CB/+Zd/yfz583+vSUiSJGW7cQeraDRKfX09kUiE8vJyqqqqSKfTDAwMsHTpUqZOncrGjRvJy8vjySef5MyZMzQ3NwNQUFDAt771rcAnIUmSlA0uKVjNnj2bzs5OABYtWsSiRYsuGA+FQjz22GO/8zlDlCRJupJkzc7r7gSdG7zGIDfYJ0nKDHdelyRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAGKwkSZICYrCSJEkKiMFKkiQpIFnzSJtQaEumS5B0hfFRWpKC5oqVJElSQC4pWPX19VFXVwdAf38/NTU11NbW0tTUxPnz5wFobW1lyZIlrFy5ku7u7gs+v3fvXr70pS8FXLokSVJ2GfNUYFtbG3v27CESiQDQ2NhIQ0MDsViMbdu20dXVxfz583nppZd44YUXAFixYgW33norkUiErVu38uMf/5ji4uKJnYkkSVKGjbliVVRUREtLy+jx4OAgsVgMgFgsRiKR4MiRI5SVlZGfn09+fj7RaJTDhw+PvmfLli0TU70kSVIWGXPFqrq6moGBgdHjwsJCent7KSsro7u7m1QqxY033khrayvDw8OcPXuWgwcPsnz5cgDuuusuXnvttYmbgSR9QMlkMtMlMDIykhV1aGz2Kjdkuk/jviswHo/T3NxMe3s7JSUlhMNh5syZw8qVK1m7di3RaJSbb76ZGTNmTES9khSYbLhEIZlMZkUdGpu9yg2T0adEInHRsXEHq56eHuLxONdffz1NTU1UVlZy7Ngxjh8/zq5duxgaGmL16tXMnTv39ypakiQp14w7WEWjUerr64lEIpSXl1NVVUU6nWZgYIClS5cydepUNm7cSF5e3kTUK0mSlLUuKVjNnj2bzs5OABYtWsSiRYsuGA+FQjz22GMX/Xx5eTnl5eW/R5mSJEnZL2t2XncH5NzgNQa5wT5JUma487okSVJADFaSJEkBMVhJkiQFxGAlSZIUEIOVJElSQAxWkiRJATFYSZIkBcRgJUmSFBCDlSRJUkAMVpIkSQHJmkfahEJbMl2CpMuQj8uSNJlcsZIkSQrIJQWrvr4+6urqAOjv76empoba2lqampo4f/48AK2trSxZsoSVK1fS3d0NwMjICF/4wheora1l7dq1HDt2bIKmIUmSlHljBqu2tjYaGho4ffo0AI2NjWzatImdO3dSUFBAV1cXhw8f5qWXXqKzs5PnnnuOp59+mlQqxa5du5g3bx47d+7k7rvvZvv27RM+IUmSpEwZM1gVFRXR0tIyejw4OEgsFgMgFouRSCQ4cuQIZWVl5Ofnk5+fTzQa5fDhwyQSCW677TYAKisr+clPfjJB05AkScq8MS9er66uZmBgYPS4sLCQ3t5eysrK6O7uJpVKceONN9La2srw8DBnz57l4MGDLF++nOHhYaZNmwbANddcw9DQ0MTNRJLeQzKZzHQJ72tkZCTra9S/sle5IdN9GvddgfF4nObmZtrb2ykpKSEcDjNnzhxWrlzJ2rVriUaj3HzzzcyYMYOCggJOnToFwKlTp5g+fXrgE5Ck91NcXJzpEt5XMpnM+hr1r+xVbpiMPiUSiYuOjfuuwJ6eHuLxOK2trZw4cYKKigqOHTvG8ePH2bVrF5s3b+bNN99k7ty5xGIxenp6ANi/fz+lpaUffBaSJElZbtwrVtFolPr6eiKRCOXl5VRVVZFOpxkYGGDp0qVMnTqVjRs3kpeXx7333ssjjzzCvffey9SpU3nyyScnYg6SJElZ4ZKC1ezZs+ns7ARg0aJFLFq06ILxUCjEY4899jufi0QiPP300wGUKUmSlP2yZud1d0fODV5jkBvskyRlhjuvS5IkBcRgJUmSFBCDlSRJUkAMVpIkSQExWEmSJAXEYCVJkhQQg5UkSVJADFaSJEkBMVhJkiQFxGAlSZIUkKx5pE0otCXTJUhSTvFRYFL2ccVKkiQpIJcUrPr6+qirqwOgv7+fmpoaamtraWpq4vz58wDs2LGDe+65h6VLl7J3714ATpw4wdq1a7n33ntZv34977zzzgRNQ5IkKfPGDFZtbW00NDRw+vRpABobG9m0aRM7d+6koKCArq4uTp48SUdHB7t37+a5554jHo8D8Oyzz1JaWsquXbuoq6vjqaeemtjZSJIkZdCYwaqoqIiWlpbR48HBQWKxGACxWIxEIkEkEmHWrFmkUilSqRShUAiA119/ncrKygveK0mSdLka8+L16upqBgYGRo8LCwvp7e2lrKyM7u5uUqkUADNnzmTx4sWcO3eOdevWAVBcXMwrr7zCTTfdxCuvvMLIyMgETUOSrjzJZDLTJVxRRkZG/J3ngEz3adx3BcbjcZqbm2lvb6ekpIRwOMz+/fs5evQo+/btA2DNmjXEYjHq6+tpbm5m1apV3Hbbbdxwww2BT0CSrlTFxcWZLuGKkkwm/Z3ngMno0/udgRv3XYE9PT3E43FaW1s5ceIEFRUVXHvttVx99dWEw2Hy8/OZNm0aJ0+e5Kc//SlLlizhu9/9LrNnzx49hShJknQ5GveKVTQapb6+nkgkQnl5OVVVVQAcOHCAZcuWMWXKFGKxGBUVFfzLv/wLjzzyCAAf+9jHRi9qlyRJuhyF0ul0OtNFJBIJFi7synQZkpRT3CB0cnkqMDdM1qnA0tLS9xzLmp3X/QORG/zDkhvsU+6wV9LlxZ3XJUmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAGKwkSZICYrCSJEkKSNY80iYU2pLpEiRpQvjILunK4YqVJElSQC4pWPX19VFXVwdAf38/NTU11NbW0tTUxPnz5wHYsWMH99xzD0uXLmXv3r0ADA0Ncd9997Fy5UpWrVrFW2+9NUHTkCRJyrwxg1VbWxsNDQ2cPn0agMbGRjZt2sTOnTspKCigq6uLkydP0tHRwe7du3nuueeIx+MAfP/732fevHk8//zz3HXXXezYsWNiZyNJkpRBYwaroqIiWlpaRo8HBweJxWIAxGIxEokEkUiEWbNmkUqlSKVShEIhAObNm8epU6cAGB4e5qqrsuaSLkmSpMCNmXSqq6sZGBgYPS4sLKS3t5eysjK6u7tJpVIAzJw5k8WLF3Pu3DnWrVsHwIwZM3j11Ve56667+M1vfsPzzz8/QdOQpOyVTCYvOjYyMvK+48oe9io3ZLpP415CisfjNDc3097eTklJCeFwmP3793P06FH27dsHwJo1a4jFYrS2tnLfffexYsUKDh06xBe+8AW6uroCn4QkZbPi4uKLjiWTyfcdV/awV7lhMvqUSCQuOjbuuwJ7enqIx+O0trZy4sQJKioquPbaa7n66qsJh8Pk5+czbdo0Tp48yfTp05k2bRoAH/7wh0dPC0qSJF2Oxr1iFY1Gqa+vJxKJUF5eTlVVFQAHDhxg2bJlTJkyhVgsRkVFBXPnzqWhoYGdO3fy7rvv0tTUFPgEJEmSskUonU6nM11EIpFg4UJPEUq6PL3fBqGeXsod9io3TNapwNLS0vccy5rb9NyZODf4hyU32CdJygx3XpckSQqIwUqSJCkgBitJkqSAGKwkSZICYrCSJEkKiMFKkiQpIAYrSZKkgBisJEmSAmKwkiRJCojBSpIkKSBZ80ibUGhLpkuQpCuejxeTfj+uWEmSJAXkklas+vr6+MY3vkFHRwf9/f08+uijhMNhiouL2bx5M1OmTGHHjh383d/9HaFQiPvvv5877riD1tZWfvSjHwFw8uRJ3n77bV599dUJnZAkSVKmjBms2tra2LNnD5FIBIDGxkYaGhqIxWJs27aNrq4ubr/9djo6Onj55ZdJpVLcfffd3HHHHdTX11NfXw/AunXr+PKXvzyxs5EkScqgMU8FFhUV0dLSMno8ODhILBYDIBaLkUgkiEQizJo1i1QqRSqVIhQKXfAzXn75ZaZPn85tt90WcPmSJEnZY8wVq+rqagYGBkaPCwsL6e3tpaysjO7ublKpFAAzZ85k8eLFnDt3jnXr1l3wM5599lmeeuqpgEuXJAUtmUxmuoSsNTIy4u8nB2S6T+O+KzAej9Pc3Ex7ezslJSWEw2H279/P0aNH2bdvHwBr1qwhFouxYMECXn/9daZPn040Gg28eElSsIqLizNdQtZKJpP+fnLAZPQpkUhcdGzcdwX29PQQj8dpbW3lxIkTVFRUcO2113L11VcTDofJz89n2rRpnDx5EoADBw5QWVn5wauXJEnKEeNesYpGo9TX1xOJRCgvL6eqqgr41wC1bNkypkyZQiwWo6KiAoA33nhj9J8lSZIuZ6F0Op3OdBGJRIKFC7syXYYkXfHcIPTiPBWYGybrVGBpael7jmXNzut+mXODf1hyg33KHfZKury487okSVJADFaSJEkBMVhJkiQFxGAlSZIUEIOVJElSQAxWkiRJATFYSZIkBcRgJUmSFBCDlSRJUkCyZuf1UGhLpkuQspZPJpCk3OCKlSRJUkAMVpIkSQG5pGDV19dHXV0dAP39/dTU1FBbW0tTUxPnz58HYMeOHdxzzz0sXbqUvXv3AnDu3Dm2bt3KihUruOeee+ju7p6gaUiSJGXemNdYtbW1sWfPHiKRCACNjY00NDQQi8XYtm0bXV1d3H777XR0dPDyyy+TSqW4++67ueOOO/gf/+N/8O6777J7924GBwf54Q9/OOETkiRJypQxV6yKiopoaWkZPR4cHCQWiwEQi8VIJBJEIhFmzZpFKpUilUoRCoUA+PGPf8wNN9xAfX09DQ0NLFq0aIKmIUmSlHljrlhVV1czMDAwelxYWEhvby9lZWV0d3eTSqUAmDlzJosXL+bcuXOsW7cOgOPHj/PLX/6SZ599ln/4h3/gq1/9Ks8///wETUW6fCWTyXG9f2RkZNyfUWbYq9xhr3JDpvs07u0W4vE4zc3NtLe3U1JSQjgcZv/+/Rw9epR9+/YBsGbNGmKxGNdddx1/9Ed/RCgUoqysjH/+538Oun7pilBcXDyu9yeTyXF/Rplhr3KHvcoNk9GnRCJx0bFx3xXY09NDPB6ntbWVEydOUFFRwbXXXsvVV19NOBwmPz+fadOmcfLkSUpLS+np6QHg0KFDzJw584PPQpIkKcuNe8UqGo1SX19PJBKhvLycqqoqAA4cOMCyZcuYMmUKsViMiooKysrKePTRR1m2bBnpdJqvfe1rgU9AkiQpW4TS6XQ600UkEgkWLuzKdBlS1hrvzuuessgd9ip32KvcMFmnAktLS99zLGseaeMjO3KDf1gkSbo4d16XJEkKiMFKkiQpIAYrSZKkgBisJEmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQpI1uy8HgptyXQJkvR78QkSklyxkiRJCojBSpIkKSCXFKz6+vqoq6sDoL+/n5qaGmpra2lqauL8+fMA7Nixg3vuuYelS5eyd+9eANLpNLfddht1dXXU1dXx5JNPTtA0JEmSMm/Ma6za2trYs2cPkUgEgMbGRhoaGojFYmzbto2uri5uv/12Ojo6ePnll0mlUtx9993ccccd/Mu//Auf/vSn+fa3vz3hE5EkScq0MVesioqKaGlpGT0eHBwkFosBEIvFSCQSRCIRZs2aRSqVIpVKEQqFgH9d3RocHKSuro61a9fyi1/8YoKmIUmSlHljrlhVV1czMDAwelxYWEhvby9lZWV0d3eTSqUAmDlzJosXL+bcuXOsW7cOgI9+9KPU19fzJ3/yJ/z0pz9lw4YNvPjiixM0FUnKrGQyOe7PjIyMfKDPafLZq9yQ6T6Ne7uFeDxOc3Mz7e3tlJSUEA6H2b9/P0ePHmXfvn0ArFmzhlgsxh/+4R+Sl5cHwMKFCxkcHCSdTo+uaEnS5aS4uHjcn0kmkx/oc5p89io3TEafEonERcfGfVdgT08P8Xic1tZWTpw4QUVFBddeey1XX3014XCY/Px8pk2bxsmTJ3nmmWf4q7/6KwAOHTrErFmzDFWSJOmyNe4Vq2g0Sn19PZFIhPLycqqqqgA4cOAAy5YtY8qUKcRiMSoqKigpKWHDhg309PSQl5fH17/+9cAnIEmSlC1C6XQ6nekiEokECxd2ZboMSfq9fJCd1z29lDvsVW6YrFOBpaWl7zmWNY+08VEQucE/LLnBPklSZrjzuiRJUkAMVpIkSQExWEmSJAXEYCVJkhQQg5UkSVJADFaSJEkBMVhJkiQFxGAlSZIUEIOVJElSQLJm5/VQaEumS5Bylk8ukKTs4IqVJElSQC4pWPX19VFXVwdAf38/NTU11NbW0tTUxPnz5wHYsWMH99xzD0uXLmXv3r0XfP7IkSOUlpZy+vTpgMuXJEnKHmOeCmxra2PPnj1EIhEAGhsbaWhoIBaLsW3bNrq6urj99tvp6Ojg5ZdfJpVKcffdd3PHHXcAMDw8zOOPP044HJ7YmUiSJGXYmCtWRUVFtLS0jB4PDg4Si8UAiMViJBIJIpEIs2bNIpVKkUqlCIVCAKTTaRobG3n44YdHg5kkSdLlaswVq+rqagYGBkaPCwsL6e3tpaysjO7ublKpFAAzZ85k8eLFnDt3jnXr1gHwzDPPUFVVxfz58yeofEkAyWTyguORkZHfeU3ZyV7lDnuVGzLdp3HfFRiPx2lubqa9vZ2SkhLC4TD79+/n6NGj7Nu3D4A1a9YQi8XYs2cPN9xwAy+++CJvvfUWq1ev5vnnnw98EtKVrri4+ILjZDL5O68pO9mr3GGvcsNk9CmRSFx0bNzBqqenh3g8zvXXX09TUxOVlZVcc801XH311YTDYUKhENOmTePkyZMXXMS+aNEinnvuuQ82A0mSpBww7mAVjUapr68nEolQXl5OVVUVAAcOHGDZsmVMmTKFWCxGRUVF4MVKkiRls0sKVrNnz6azsxP415WnRYsW/c57HnjgAR544IGL/oxXXnnlA5YoSZKUG9wgVJIkKSBZ80gbH8mRG7x4U5Kki3PFSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAGKwkSZICYrCSJEkKiMFKkiQpIFmz83ootCXTJUiS8EkY0u/DFStJkqSAXFKw6uvro66uDoD+/n5qamqora2lqamJ8+fPA7Bjxw7uueceli5dyt69ewH47W9/y/r166mtrWXNmjUcO3ZsgqYhSZKUeWMGq7a2NhoaGjh9+jQAjY2NbNq0iZ07d1JQUEBXVxcnT56ko6OD3bt389xzzxGPxwHo7Ozk05/+NDt37mTx4sVs3759YmcjSZKUQWMGq6KiIlpaWkaPBwcHicViAMRiMRKJBJFIhFmzZpFKpUilUoRCIQBWrVrF+vXrAfj1r3/NRz7ykYmYgyRJUlYY8+L16upqBgYGRo8LCwvp7e2lrKyM7u5uUqkUADNnzmTx4sWcO3eOdevWjb4/Ly+Pz33uc/z85z/nO9/5zgRMQZIUpGQymekSstLIyIi/mxyQ6T6N+67AeDxOc3Mz7e3tlJSUEA6H2b9/P0ePHmXfvn0ArFmzhlgsxoIFCwD467/+a44cOcK6dev4+7//+2BnIEkKVHFxcaZLyErJZNLfTQ6YjD4lEomLjo37rsCenh7i8Titra2cOHGCiooKrr32Wq6++mrC4TD5+flMmzaNkydP8uyzz/K3f/u3APzBH/wBeXl5H3gSkiRJ2W7cK1bRaJT6+noikQjl5eVUVVUBcODAAZYtW8aUKVOIxWJUVFQwf/58HnnkEV588UXOnTs3elG7JEnS5SiUTqfTmS4ikUiwcGFXpsuQJOEGoRfjqcDcMFmnAktLS99zzA1CJUmSApI1j7Txv5Byg//FlhvsU+6wV9LlxRUrSZKkgBisJEmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAZM3O66HQlkyXIEkS4NNA9MG5YiVJkhSQSwpWfX191NXVAdDf309NTQ21tbU0NTVx/vx5AHbs2ME999zD0qVL2bt3LwBDQ0Pcf//9/Pmf/znLly/n4MGDEzQNSZKkzBvzVGBbWxt79uwhEokA0NjYSENDA7FYjG3bttHV1cXtt99OR0cHL7/8MqlUirvvvps77riD73znO9x6662sWrWKX/ziF3zpS1/iBz/4wYRPSpIkKRPGXLEqKiqipaVl9HhwcJBYLAZALBYjkUgQiUSYNWsWqVSKVCpFKBQCYNWqVaxYsQKAc+fOkZ+fPxFzkCRJygpjrlhVV1czMDAwelxYWEhvby9lZWV0d3eTSqUAmDlzJosXL+bcuXOsW7cOgOnTpwPw1ltvsWHDBjZt2jQRc5AkKVDJZPJ3XhsZGXnP15VdMt2ncd8VGI/HaW5upr29nZKSEsLhMPv37+fo0aPs27cPgDVr1hCLxViwYAGHDx/m4YcfZuPGjZSVlQU+AUmSglZcXPw7ryWTyfd8XdllMvqUSCQuOjbuYNXT00M8Huf666+nqamJyspKrrnmGq6++mrC4TChUIhp06Zx8uRJXn/9dR588EH+8i//kvnz5/9ek5AkScp24w5W0WiU+vp6IpEI5eXlVFVVAXDgwAGWLVvGlClTiMViVFRU8N/+23/jzJkzNDc3A1BQUMC3vvWtYGcgSZKUJULpdDqd6SISiQQLF3ZlugxJkoD33iDUU4G5YbJOBZaWlr7nmBuESpIkBSRrHmnj4wNyg//FlhvsU+6wV9LlxRUrSZKkgBisJEmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAZM3O66HQlkyXIEkTxqdLSFcGV6wkSZICcknBqq+vj7q6OgD6+/upqamhtraWpqYmzp8/D8COHTu45557WLp0KXv37r3g83v37uVLX/pSwKVLkiRllzFPBba1tbFnzx4ikQgAjY2NNDQ0EIvF2LZtG11dXdx+++10dHTw8ssvk0qluPvuu7njjjsA2Lp1Kz/+8Y99yKgkSbrsjbliVVRUREtLy+jx4OAgsVgMgFgsRiKRIBKJMGvWLFKpFKlUilAoNPr+WCzGli1bgq9ckiQpy4y5YlVdXc3AwMDocWFhIb29vZSVldHd3U0qlQJg5syZLF68mHPnzrFu3brR999111289tprE1C6JOWOZDL5nq+PjIxcdEzZxV7lhkz3adx3BcbjcZqbm2lvb6ekpIRwOMz+/fs5evQo+/btA2DNmjXEYjEWLFgQeMGSlIsudjlEMpn0UokcYa9yw2T0KZFIXHRs3HcF9vT0EI/HaW1t5cSJE1RUVHDttddy9dVXEw6Hyc/PZ9q0aZw8efL3KlqSJCnXjHvFKhqNUl9fTyQSoby8nKqqKgAOHDjAsmXLmDJlCrFYjIqKisCLlSRJymahdDqdznQRiUSChQu7Ml2GJE2Yi20Q6uml3GGvcsNknQosLS19z7Gs2XndXYlzg39YcoN9kqTMcOd1SZKkgBisJEmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAGKwkSZICkjWPtAmFtmS6BEm6ZD6GS9J7ccVKkiQpIJcUrPr6+qirqwOgv7+fmpoaamtraWpq4vz58wDs2LGDe+65h6VLl7J3714ARkZG+MIXvkBtbS1r167l2LFjEzQNSZKkzBszWLW1tdHQ0MDp06cBaGxsZNOmTezcuZOCggK6uro4efIkHR0d7N69m+eee454PA7Arl27mDdvHjt37uTuu+9m+/btEzsbSZKkDBozWBUVFdHS0jJ6PDg4SCwWAyAWi5FIJIhEIsyaNYtUKkUqlSIUCgGQSCS47bbbAKisrOQnP/nJRMxBkiQpK4x58Xp1dTUDAwOjx4WFhfT29lJWVkZ3dzepVAqAmTNnsnjxYs6dO8e6desAGB4eZtq0aQBcc801DA0NTcQcJGnSJZPJQH7OyMhIYD9LE8te5YZM92ncdwXG43Gam5tpb2+npKSEcDjM/v37OXr0KPv27QNgzZo1xGIxCgoKOHXqFACnTp1i+vTpwVYvSRlSXFwcyM9JJpOB/SxNLHuVGyajT4lE4qJj474rsKenh3g8TmtrKydOnKCiooJrr72Wq6++mnA4TH5+PtOmTePkyZPEYjF6enoA2L9/P6WlpR98FpIkSVlu3CtW0WiU+vp6IpEI5eXlVFVVAXDgwAGWLVvGlClTiMViVFRUUFpayiOPPMK9997L1KlTefLJJwOfgCRJUrYIpdPpdKaLSCQSLFzYlekyJOmSBbVBqKeXcoe9yg2TdSrwYmfhsmbndXcxzg3+YckN9kmSMsOd1yVJkgJisJIkSQqIwUqSJCkgBitJkqSAGKwkSZICYrCSJEkKiMFKkiQpIAYrSZKkgBisJEmSAmKwkiRJCkjWPNImFNqS6RJ0GfORSZKkyeCKlSRJUkAuKVj19fVRV1cHQH9/PzU1NdTW1tLU1MT58+dJJpPU1dWN/q+kpIT9+/dz4sQJ1q5dy7333sv69et55513JnQykiRJmTRmsGpra6OhoYHTp08D0NjYyKZNm9i5cycFBQV0dXVRXFxMR0cHHR0d1NbW8sd//MdUVlby7LPPUlpayq5du6irq+Opp56a8AlJkiRlypjBqqioiJaWltHjwcFBYrEYALFYjEQiMTr229/+lpaWFjZv3gzA66+/TmVl5Xu+V5Ik6XIz5sXr1dXVDAwMjB4XFhbS29tLWVkZ3d3dpFKp0bHvfe973HnnnXzoQx8CoLi4mFdeeYWbbrqJV155hZGRkQmYgjS2ZDKZ6RIm1cjIyBU351xlr3KHvcoNme7TuO8KjMfjNDc3097eTklJCeFweHSsq6uLp59+evS4vr6e5uZmVq1axW233cYNN9wQTNXSOBUXF2e6hEmVTCavuDnnKnuVO+xVbpiMPr3fGbhx3xXY09NDPB6ntbWVEydOUFFRAcDQ0BBnzpxh5syZo+/96U9/ypIlS/jud7/L7NmzR08hSpIkXY7GvWIVjUapr68nEolQXl5OVVUVAG+88QYf//jHL3jvJz7xCR555BEAPvaxjxGPxwMoWZIkKTtdUrCaPXs2nZ2dACxatIhFixb9znsWLFjA9u3bL3gtGo2ye/fuAMqUJEnKflmz87o7Y+cGrzGQJOni3HldkiQpIAYrSZKkgBisJEmSAmKwkiRJCojBSpIkKSAGK0mSpIAYrCRJkgJisJIkSQqIwUqSJCkgBitJkqSAZM0jbUKhLZkuQboi+TgpSQqOK1aSJEkBuaQVq76+Pr7xjW/Q0dFBf38/jz76KOFwmOLiYjZv3szhw4eJx+Oj7//Zz37GN7/5TW655Ra++MUvkkqlmDp1Kk888QQf/ehHJ2wykiRJmTTmilVbWxsNDQ2cPn0agMbGRjZt2sTOnTspKCigq6uL4uJiOjo66OjooLa2lj/+4z+msrKS73//+8ybN4/nn3+eu+66ix07dkz4hCRJkjJlzGBVVFRES0vL6PHg4CCxWAyAWCxGIpEYHfvtb39LS0sLmzdvBmDevHmcOnUKgOHhYa66Kmsu6ZIkSQrcmEmnurqagYGB0ePCwkJ6e3spKyuju7ubVCo1Ova9732PO++8kw996EMAzJgxg1dffZW77rqL3/zmNzz//PMTMAVJv49kMpnpEq5oIyMj9iBH2KvckOk+jXsJKR6P09zcTHt7OyUlJYTD4dGxrq4unn766dHjZ555hvvuu48VK1Zw6NAhvvCFL9DV1RVM5ZICUVxcnOkSrmjJZNIe5Ah7lRsmo0///mzdfzTuuwJ7enqIx+O0trZy4sQJKioqABgaGuLMmTPMnDlz9L3Tp09n2rRpAHz4wx8ePS0oSZJ0ORr3ilU0GqW+vp5IJEJ5eTlVVVUAvPHGG3z84x+/4L0PPvggDQ0N7Ny5k3fffZempqZgqpYkScpCoXQ6nc50EYlEgoULPUUoZYIbhGaWp5dyh73KDZN1KrC0tPQ9x7LmNj3/uOcG/7DkBvskSZnhzuuSJEkBMVhJkiQFxGAlSZIUEIOVJElSQAxWkiRJATFYSZIkBcRgJUmSFBCDlSRJUkAMVpIkSQExWEmSJAUkax5pEwptyXQJukQ+fkiSpPfmipUkSVJALmnFqq+vj2984xt0dHTQ39/Po48+Sjgcpri4mM2bN3P48GHi8fjo+3/2s5/xzW9+k0OHDvGjH/0IgJMnT/L222/z6quvTsxMJEmSMmzMYNXW1saePXuIRCIANDY20tDQQCwWY9u2bXR1dbFkyRI6OjoA+OEPf8jHPvYxKisrqayspL6+HoB169bx5S9/eQKnIkmSlFljngosKiqipaVl9HhwcJBYLAZALBYjkUiMjv32t7+lpaWFzZs3X/AzXn75ZaZPn85tt90WVN2SJElZZ8wVq+rqagYGBkaPCwsL6e3tpaysjO7ublKp1OjY9773Pe68804+9KEPXfAznn32WZ566qkAy1YmJZPJTJegMYyMjNinHGGvcoe9yg2Z7tO47wqMx+M0NzfT3t5OSUkJ4XB4dKyrq4unn376gve//vrrTJ8+nWg0+vtXq6xQXFyc6RI0hmQyaZ9yhL3KHfYqN0xGn/792br/aNx3Bfb09BCPx2ltbeXEiRNUVFQAMDQ0xJkzZ5g5c+YF7z9w4ACVlZXj/ddIkiTlnHGvWEWjUerr64lEIpSXl1NVVQXAG2+8wcc//vHfef8bb7wxGr4kSZIuZ5cUrGbPnk1nZycAixYtYtGiRb/zngULFrB9+/bfef3RRx/9PUuUJEnKDVmz87q7eecGL9yUJOni3HldkiQpIAYrSZKkgBisJEmSAmKwkiRJCkgonU6nM13E+220JUmSlG1KS0vf8/WsCFaSJEmXA08FSpIkBcRgJUmSFJCMbhB6/vx5tmzZwuHDhwmHw2zdutWHNWeBu+++m2nTpgH/uuv+/fffz1e+8hVCoRBz587l0UcfZcqUKXR2drJ7926uuuoq1q9fz+23357hyq8MfX19fOMb36Cjo4Nf/vKXl9ybkZERNmzYwDvvvMM111zD448/zoc+9KFMT+ey9u971d/fz/33389/+k//CYB7772Xu+66y15l2NmzZ9m0aRO/+tWvOHPmDOvXr+dTn/qU36ss8159uuGGG7LzO5XOoP/1v/5X+pFHHkmn0+n0wYMH0/fff38my1E6nR4ZGUkvWbLkgtfWrVuX/j//5/+k0+l0urGxMf3yyy+njx49mv7TP/3T9OnTp9MnT54c/WdNrNbW1vSf/umfpv/rf/2v6XR6fL157rnn0k8//XQ6nU6nX3rppXRTU1PG5nEl+I+96uzsTO/YseOC99irzPve976X3rp1azqdTqePHTuWrqqq8nuVhd6rT9n6ncroqcBEIsFtt90GwGc+8xn+6Z/+KZPlCDh06BCpVIrVq1fzuc99jp/97Gf09/dTVlYGQGVlJQcOHOAf//EfueWWWwiHw0ybNo2ioiIOHTqU4eovf0VFRbS0tIwej6c3//77VllZyU9+8pOMzOFK8R979U//9E/87//9v1m5ciWbNm1ieHjYXmWBO++8kwcffHD0OC8vz+9VFnqvPmXrdyqjwWp4eJiCgoLR47y8PN59990MVqSrr76aNWvWsGPHDr72ta/x5S9/mXQ6TSgUAuCaa65haGiI4eHh0dOF//b68PBwpsq+YlRXV3PVVf/vDP54evPvX/+392ri/MdeLViwgI0bN/L8889TWFjIN7/5TXuVBa655hoKCgoYHh7mgQce4KGHHvJ7lYXeq0/Z+p3KaLAqKCjg1KlTo8fnz5+/4A+RJt8nPvEJ/st/+S+EQiE+8YlPcN111/HOO++Mjp86dYrp06f/Tu9OnTp1wf+ZNTmmTPl/X+GxevPvX/+392ry3HHHHfzhH/7h6D//3//7f+1VlnjzzTf53Oc+x5IlS/jsZz/r9ypL/cc+Zet3KqPBKhaLsX//fgB+9rOfMW/evEyWI+B73/se//2//3cABgcHGR4epqKigtdeew2A/fv3s3DhQhYsWEAikeD06dMMDQ1x5MgR+5cBN9100yX3JhaL0dPTM/rei21up4mxZs0a/vEf/xGAn/zkJ3z605+2V1ng7bffZvXq1WzYsIGamhrA71U2eq8+Zet3KqMbhP7bXYE///nPSafTxONx5syZk6lyBJw5c4avfvWr/PrXvyYUCvHlL3+ZGTNm0NjYyNmzZ/nkJz/J1q1bycvLo7Ozk7/5m78hnU6zbt06qqurM13+FWFgYICHH36Yzs5O3njjjUvuTSqV4pFHHuGtt95i6tSpPPnkk3z0ox/N9HQua/++V/39/TQ1NTF16lQ+8pGP0NTUREFBgb3KsK1bt/LDH/6QT37yk6Ovbd68ma1bt/q9yiLv1aeHHnqIJ554Iuu+U+68LkmSFBA3CJUkSQqIwUqSJCkgBitJkqSAGKwkSZICYrCSJEkKiMFKkiQpIAYrSZKkgBisJEmSAvL/ASRyoqadI8k5AAAAAElFTkSuQmCC\n", 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\n", 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" ] @@ -1932,7 +1949,9 @@ "cell_type": "code", "execution_count": 38, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1947,7 +1966,7 @@ }, { "data": { - "image/png": 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3Wz6fT5IUDAY1ODgoSSovL1d5ebkkaf369Zo2bZqefvpp3X333ZKkhQsX6sEHH0xkVAC4ZOXk5JiOcFEJh8P8TJNAIuYUCoXOuy2h9yFrbm5WZ2enJMnv96ukpESxWEyrVq3S6OiohoaGFA6HNW/ePF111VU6dOiQJOmXv/ylrrrqqkRGBQAASBjbjpD19vaqsbFRAwMDcjqdCgQCqqurk9frlc/nU0FBgYqLiyVJZWVlqqysVFpamjZu3Cin06k77rhD999/v55//nlJ0v33329XVAAAAKMclmVZpkN8VKFQSHl5z5qOAQAXFW4M+/HilGVySNQpywULFpxzW9LfqZ8/HMmBP0jJgTklD2YFXFx4liUAAIBhFDIAAADDKGQAAACGUcgAAAAMo5ABAAAYRiEDAAAwjEIGAABgGIUMAADAMAoZAACAYUl/p36Hw2M6AgAASGLj4ak/HCEDAAAwzNYjZJFIRGvXrtXq1atVU1Ojvr4+PfDAA3I4HLr66qvl8XjkdDrV3t6uJ598UhMnTtRtt92mm2++WT/60Y/08ssvS5LOnDmj4eFhBQIBO+MCAAAYYVshGxkZkdfrVWFhYXytqalJtbW1WrRokbZt26aOjg5df/312rFjh5599llJ0le/+lUtWrRIa9as0Zo1ayRJTz/9tI4ePWpXVAAAAKNsO2XpcrnU0tKirKys+Fp/f79yc3MlSUVFReru7tbAwIBmzZql1NRUpaamau7cuTp06FB8n1gspt27d6umpsauqAAAAEbZVsicTqfS0tLOWsvOzlZXV5ckKRgManh4WDNnzlQkEtGxY8d04sQJHTx48KyjYS+88IJuuOGG97wWAADAxSKhn7Ksr6+Xx+OR3+9Xfn6+LMvS5MmTtWHDBq1du1aZmZmaPXu2LMuK7/PUU0/pwQcfTGRMAABwCQmHw4pGowqHw8YyJLSQud1u+Xw+Se8eIRscHJQklZeXq7y8XJK0fv16TZs2TdK716G99dZbmj59eiJjAgCAS0hOTo7C4bBycnJs/XdCodB5tyX0thfNzc3q7OyUJPn9fpWUlCgWi2nVqlUaHR3V0NCQwuGw5s2bJ0l6/fXXdc011yQyIgAAQMLZdoSst7dXjY2NGhgYkNPpVCAQUF1dnbxer3w+nwoKClRcXCxJKisrU2VlpdLS0rRx40Y5ne/GGhoa0pQpU+yKCAAAMC44rL++YCvJhEIh5eU9azoGAABIYpblSdgpywULFpxzW9I/Omk8PO4AF5aI/6Pj78eckgezSh7MCh8Ej04CAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGEYhAwAAMCzp79TvcHhMRwAAXABPVQHeH0fIAAAADLO1kEUiEZWWlqqtrU2S1NfXp+rqatXU1KihoUGxWEyS1N7ermXLlqmqqkqBQCC+//bt23Xrrbdq2bJlOnz4sJ1RAQAAjLHtlOXIyIi8Xq8KCwvja01NTaqtrdWiRYu0bds2dXR06Prrr9eOHTv07LPPSpK++tWvatGiRTpy5Ij+67/+S0899ZTeeOMNvfjii7r22mvtigsAAGCMbUfIXC6XWlpalJWVFV/r7+9Xbm6uJKmoqEjd3d0aGBjQrFmzlJqaqtTUVM2dO1eHDh3S/v37VV5eLqfTqc9+9rO688477YoKAABglG2FzOl0Ki0t7ay17OxsdXV1SZKCwaCGh4c1c+ZMRSIRHTt2TCdOnNDBgwd19OhRDQwM6NixY1q3bp2++tWv6vXXX7crKgAAgFEJ/ZRlfX29PB6P/H6/8vPzZVmWJk+erA0bNmjt2rXKzMzU7NmzZVmWLMvSyZMntXXrVoVCId1///166qmnEhkXAPAxCYfDpiMYE41GL+n3nyxMzymhhcztdsvn80l69wjZ4OCgJKm8vFzl5eWSpPXr12vatGm68sorNWvWLDkcDuXl5WlgYCCRUQEAH6OcnBzTEYwJh8OX9PtPFomYUygUOu+2hN72orm5WZ2dnZIkv9+vkpISxWIxrVq1SqOjoxoaGlI4HNa8efN04403KhgMSnr305lutzuRUQEAABLGtiNkvb29amxs1MDAgJxOpwKBgOrq6uT1euXz+VRQUKDi4mJJUllZmSorK5WWlqaNGzfK6XTqc5/7nILBoFatWqWxsTE98MADdkUFAAAwymFZlmU6xEcVCoWUl/es6RgAgAu4lO/UzynL5JCoU5YLFiw457akf3TSpfxLnkz4g5QcmFPyYFbAxYVHJwEAABhGIQMAADCMQgYAAGAYhQwAAMAwChkAAIBhFDIAAADDKGQAAACGUcgAAAAMo5ABAAAYlvR36nc4PKYjABgneHIHgGTFETIAAADDbC1kkUhEpaWlamtrkyT19fWpurpaNTU1amhoUCwWkyS1t7dr2bJlqqqqUiAQkCQFAgHddNNNWrVqlVatWqUf/ehHdkYFAAAwxrZTliMjI/J6vSosLIyvNTU1qba2VosWLdK2bdvU0dGh66+/Xjt27NCzzz4rSfrqV7+qRYsWaWRkRNXV1Vq9erVdEQEAAMYF246QuVwutbS0KCsrK77W39+v3NxcSVJRUZG6u7s1MDCgWbNmKTU1VampqZo7d64OHTqkEydO2BUNAABgXLGtkDmdTqWlpZ21lp2dra6uLklSMBjU8PCwZs6cqUgkomPHjunEiRM6ePCgjh49qpGREe3du1df+9rXdNttt+n111+3KyoAAIBRCf2UZX19vTwej/x+v/Lz82VZliZPnqwNGzZo7dq1yszM1OzZs2VZlj7/+c8rNzdXn//85/WLX/xCGzZsiJ/WBIBzCYfDpiMkTDQavaTebzJjVsnB9JwSWsjcbrd8Pp+kd4+QDQ4OSpLKy8tVXl4uSVq/fr2mTZsWP7UpSXl5eTp27JhOnz6tCRMmJDIygCSSk5NjOkLChMPhS+r9JjNmlRwSMadQKHTebQm97UVzc7M6OzslSX6/XyUlJYrFYlq1apVGR0c1NDSkcDisefPmadu2bfFPXEYiEU2ZMoUyBgAALkq2HSHr7e1VY2OjBgYG5HQ6FQgEVFdXJ6/XK5/Pp4KCAhUXF0uSysrKVFlZqbS0NG3cuFFOp1O33nqr7rvvPrW2tioWi+k73/mOXVEBAACMcliWZZkO8VGFQiHl5XFdGYB3XUp36uc0WPJgVskhUacsFyxYcM5tSf/opEvpD3Ay4w9ScmBOAGAGj04CAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGEYhAwAAMCzp79TvcHhMR0AS4gkPAIDxhCNkAAAAhtlayCKRiEpLS9XW1iZJ6uvrU3V1tWpqatTQ0KBYLCZJam9v17Jly1RVVaVAIHDWawwPD+u6665TT0+PnVEBAACMsa2QjYyMyOv1qrCwML7W1NSk2tpatbW1ye12q6OjQ0ePHtWOHTu0a9cu7dy5U4899pii0Wh8n82bN2vGjBl2xQQAADDOtkLmcrnU0tKirKys+Fp/f79yc3MlSUVFReru7tbAwIBmzZql1NRUpaamau7cuTp06JAk6cCBA/rkJz+p7Oxsu2ICAAAYZ9tF/U6nU07n2S+fnZ2trq4uVVRUKBgManh4WDNnzlQkEtGxY8eUmpqqgwcPKj8/X2NjY9q2bZt++MMfauPGjXbFxCUqHA6bjjAuRaNRfjZJglklD2aVHEzPKaGfsqyvr5fH45Hf71d+fr4sy9LkyZO1YcMGrV27VpmZmZo9e7Ysy9KPf/xjfeUrX9GnPvWpREbEJSInJ8d0hHEpHA7zs0kSzCp5MKvkkIg5hUKh825LaCFzu93y+XySpGAwqMHBQUlSeXm5ysvLJUnr16/XtGnT1NraqjNnzujxxx/XH/7wB/3yl7/Uww8/rM985jOJjAwAAGC7hBay5uZm5ebmqri4WH6/X7feeqtisZhuu+02Pfroozp+/LjC4bDmzZun9vb2+H733nuvvvzlL1PGAADARcm2Qtbb26vGxkYNDAzI6XQqEAiorq5OXq9XPp9PBQUFKi4uliSVlZWpsrJSaWlp2rhx43uuPQMAALiY2dZ85s2bp9bW1ves79mz5z1r1dXVqq6uPu9rbdq06WPNBgAAMJ4k/aEoHoGTHLioFQCA8+PRSQAAAIZRyAAAAAyjkAEAABhGIQMAADCMQgYAAGAYhQwAAMAwChkAAIBhFDIAAADDKGQAAACGJf2d+h0Oj+kIuETxlAgAwMeFI2QAAACG2VrIIpGISktL1dbWJknq6+tTdXW1ampq1NDQoFgsJklqb2/XsmXLVFVVpUAgIEk6evSovv71r2vVqlWqqqrSoUOH7IwKAABgjG2FbGRkRF6vV4WFhfG1pqYm1dbWqq2tTW63Wx0dHTp69Kh27NihXbt2aefOnXrssccUjUb1zDPP6NZbb1Vra6vWr1+vhx9+2K6oAAAARtlWyFwul1paWpSVlRVf6+/vV25uriSpqKhI3d3dGhgY0KxZs5SamqrU1FTNnTtXhw4d0m233aYvfelLkqQ//vGPmjp1ql1RAQAAjLLton6n0ymn8+yXz87OVldXlyoqKhQMBjU8PKyZM2cqEono2LFjSk1N1cGDB5Wfny9JGhoa0je/+U2dOHFCO3futCsq8JGEw2HTET520Wj0onxfFyNmlTyYVXIwPaeEfsqyvr5eHo9Hfr9f+fn5sixLkydP1oYNG7R27VplZmZq9uzZsixLkpSZmamnnnpKXV1duu+++7Rjx45ExgXeV05OjukIH7twOHxRvq+LEbNKHswqOSRiTqFQ6LzbEvopS7fbLZ/Pp3/7t3/T/PnzNW3aNElSeXm52tvb9YMf/ECWZWnatGl65ZVX9Kc//UmStGjRIr322muJjAoAAJAwCS1kzc3N6uzslCT5/X6VlJQoFotp1apVGh0d1dDQkMLhsObNm6cXXnhBTz/9tCTpjTfekNvtTmRUAACAhLHtlGVvb68aGxs1MDAgp9OpQCCguro6eb1e+Xw+FRQUqLi4WJJUVlamyspKpaWlaePGjXI6nVq7dq3uvfde7d27V2NjY/J4PHZFBQAAMMq2QjZv3jy1tra+Z33Pnj3vWauurlZ1dfVZa1OmTNGPf/xju+IBAACMG0n/6CQeX5McuKgVAIDz49FJAAAAhlHIAAAADKOQAQAAGEYhAwAAMIxCBgAAYBiFDAAAwDAKGQAAgGEUMgAAAMMoZAAAAIYl/Z36HQ6P6QjAJYMnYwCAPThCBgAAYJithSwSiai0tFRtbW2SpL6+PlVXV6umpkYNDQ2KxWKSpPb2di1btkxVVVUKBAKSpFgspvr6eq1cuVL/+I//qF/84hd2RgUAADDGtkI2MjIir9erwsLC+FpTU5Nqa2vV1tYmt9utjo4OHT16VDt27NCuXbu0c+dOPfbYY4pGo/qP//gPpaena9euXfrOd76jTZs22RUVAADAKNsKmcvlUktLi7KysuJr/f39ys3NlSQVFRWpu7tbAwMDmjVrllJTU5Wamqq5c+fq0KFDuuWWW3TfffdJkqZMmaJ33nnHrqgAAABG2XZRv9PplNN59stnZ2erq6tLFRUVCgaDGh4e1syZMxWJRHTs2DGlpqbq4MGDys/P18SJE+P77dy5U1/84hftigrgAwqHw6Yj4P+KRqPMI0kwq+Rgek4J/ZRlfX29PB6P/H6/8vPzZVmWJk+erA0bNmjt2rXKzMzU7NmzZVlWfJ/HH39cr732mh555JFERgVwDjk5OaYj4P8Kh8PMI0kwq+SQiDmFQqHzbktoIXO73fL5fJKkYDCowcFBSVJ5ebnKy8slSevXr9e0adMkSU8++aR+9rOf6Yc//OFZR8wAAAAuJgm97UVzc7M6OzslSX6/XyUlJYrFYlq1apVGR0c1NDSkcDisefPm6ciRI2pvb9fWrVuVmpqayJgAAAAJZdsRst7eXjU2NmpgYEBOp1OBQEB1dXXyer3y+XwqKChQcXGxJKmsrEyVlZVKS0vTxo0b5XQ69eSTT+qdd95RbW1t/DW3b98ul8tlV2QAAAAjHNZfX7CVZEKhkBYsWGA6Bj4ArqFIDswpeTCr5MGskkOiriE7X2/hTv0AAACGUcgAAAAMo5ABAAAYRiEDAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADLPtWZaJ4nB4TEcAcImxLI/pCAAuMhwhAwAAMMzWQhaJRFRaWqq2tjZJUl9fn6qrq1VTU6OGhgbFYjFJUnt7u5YtW6aqqioFAoH4/q+88ooKCwu1f/9+O2MCAAAYZVshGxkZkdfrVWFhYXytqalJtbW1amtrk9vtVkdHh44ePaodO3Zo165d2rlzpx577DFFo1H94Q9/0GOPPXbep6IDAABcLGwrZC6XSy0tLcrKyoqv9ff3Kzc3V5JUVFSk7u5uDQwMaNasWUpNTVVqaqrmzp2rQ4cOKTMzU1u3btWkSZPsiggAADAu2HZRv9PplNN59stnZ2erq6tLFRUVCgaDGh4e1syZMxWJRHTs2DGlpqbq4MGDys/PV3p6ul3RAODvEg6HTUdQNBodFzlwYcwqOZieU0I/ZVlfXy+PxyO/36/8/HxZlqXJkydrw4YNWrt2rTIzMzV79mxZlpXIWADwoeTk5JiOoHA4PC5y4MKYVXJIxJxCodB5tyW0kLndbvl8PklSMBjU4OCgJKm8vFzl5eWSpPXr12vatGmJjAUAAGBUQm970dzcrM7OTkmS3+9XSUmJYrGYVq1apdHRUQ0NDSkcDmvevHmJjAUAAGCUbUfIent71djYqIGBATmdTgUCAdXV1cnr9crn86mgoEDFxcWSpLKyMlVWViotLU0bN26U0+lUZ2entm/frt/+9rd67bXX1Nraqh07dtgVFwAAwBiHlcQXbIVCIW6LkSS4hiI5MKfkwaySB7NKDom6hux8vYU79QMAABhGIQMAADCMQgYAAGAYhQwAAMAwChkAAIBhFDIAAADDKGQAAACGUcgAAAAMo5ABAAAYRiEDAAAwzLZnWSaKw+ExHQHARciyPKYjALiEcIQMAADAMFsLWSQSUWlpqdra2iRJfX19qq6uVk1NjRoaGhSLxSRJ7e3tWrZsmaqqqhQIBCRJp06d0j333KMVK1aopqZGR44csTMqAACAMbYVspGREXm9XhUWFsbXmpqaVFtbq7a2NrndbnV0dOjo0aPasWOHdu3apZ07d+qxxx5TNBrVf/7nf+pTn/qUdu/erW984xv63ve+Z1dUAAAAo2wrZC6XSy0tLcrKyoqv9ff3Kzc3V5JUVFSk7u5uDQwMaNasWUpNTVVqaqrmzp2rQ4cO6cCBA7rpppskSTfccINCoZBdUQEAAIyy7aJ+p9Mpp/Psl8/OzlZXV5cqKioUDAY1PDysmTNnKhKJ6NixY0pNTdXBgweVn5+v4eFhTZkyRZI0YcIEpaSkaGxsTC6Xy67IABAXDodNR3hf0Wh03GfEu5hVcjA9p4R+yrK+vl4ej0d+v1/5+fmyLEuTJ0/Whg0btHbtWmVmZmr27NmyLEuWZZ21r2VZcjgciYwL4BKWk5NjOsL7CofD4z4j3sWskkMi5vR+Z/sSWsjcbrd8Pp8kKRgManBwUJJUXl6u8vJySdL69es1bdo0TZ06VUNDQ5o7d65OnToly7I0ceLERMYFAABIiAteQ/arX/3qY/vHmpub1dnZKUny+/0qKSlRLBbTqlWrNDo6qqGhIYXDYc2bN08LFy7U888/L0nav3+/CgoKPrYcAAAA48kFj5Bt2rRJO3bseM/1YBfS29urxsZGDQwMyOl0KhAIqK6uTl6vVz6fTwUFBSouLpYklZWVqbKyUmlpadq4caOcTqeWLl2ql19+WStWrJDL5dKmTZs+0hsEAAAY7xzW316s9Te++c1vKhKJaO7cuWedMnz44YdtD3choVBICxYsMB0DHwDXUCQH5pQ8mFXyYFbJIVHXkJ2vt1zwsNfXvva196wNDw///akAAAAg6QNcQ/YP//APGhkZ0Ztvvqk333xT/f39+td//ddEZAMAALgkXPAI2d13361PfvKTeuWVV1RSUqKenh790z/9UyKyAQAAXBIueITsT3/6kxobGzV9+nT9r//1v7Rr1y51dXUlIhsAAMAl4YKF7NSpUxoYGNCECRP0u9/9Ti6XS7/73e8SkQ0AAOCScMFTlnfddZcOHz6stWvX6hvf+Ib+8pe/qLq6OhHZAAAALgkXLGSFhYWSpFgspn379tkeCAAA4FJzwVOWPT09uuWWW/TFL35RkrRlyxYFg0HbgwEAAFwqLljImpubtXPnTmVmZkqS/uf//J/aunWr7cEAAAAuFRcsZBMmTNDll18uh8MhSbriiivi/xsAAAB/vwteQzZjxgw9/PDDevvtt/Xcc89p7969+sxnPpOIbB+Iw+ExHQEAkopleUxHAPA3LniE7Fe/+pVcLpfmzZun//N//o+WLFkij8fzgV48EomotLRUbW1tkqS+vj5VV1erpqZGDQ0NisVikt69Lq2qqkqVlZVqaWmRJI2MjOjOO+/UypUrdfvtt2toaOgjvkUAAIDx7YKF7JFHHtFll12mo0eP6re//a2i0ahGRkYu+MIjIyPyer3xT2lKUlNTk2pra9XW1ia3262Ojg5FIhH19PSovb1du3fvlt/v19DQkH76059qxowZ2rVrl9asWaPm5ua/750CAACMUxcsZFOnTtXKlSv14x//WHfddZeeeOIJlZaW6r777tPg4OB593O5XGppaVFWVlZ8rb+/X7m5uZKkoqIidXd3KyMjQ6OjoxobG9Po6KhSUlKUnp6u3//+9/HvzcvLUygU+nvfKwAAwLh0wUJ25MgR+Xw+LV++XD6fT9/4xjf00ksv6dZbb9Wdd9553v2cTqfS0tLOWsvOzo4/dikYDGp4eFhut1tlZWVavHixFi9erKqqKk2aNOms733llVf05ptv/j3vEwAAYNy64EX999xzj2699VY9+uijmjx5cnz985//vBYuXPih/rH6+np5PB75/X7l5+fLsiwdOXJEe/fu1b59+xSLxVRVVaWlS5dq+fLleuONN7RixQrl5+drypQpH/rNAQDeKxwOm45wSYlGo/zMk4DpOV2wkP30pz8977ZvfetbH+ofc7vd8vl8kt49QjY4OKjDhw9r/vz5Sk9PlyTNmTNHkUhEhYWFevDBByVJJ06c0Isvvvih/i0AwLnl5OSYjnBJCYfD/MyTQCLm9H6XX13wlOXHqbm5WZ2dnZIkv9+vkpISzZw5U729vTpz5oxOnTqlSCSiGTNmqKurS9///vclSc8884yKiooSGRUAACBhLniE7KPq7e1VY2OjBgYG5HQ6FQgEVFdXJ6/XK5/Pp4KCAhUXF0uSFi5cqJUrV8qyLC1fvlzTp0/XlVdeqccff1wrVqxQVlaWHnroIbuiAgAAGOWwLMsyHeKjCoVCyst71nQMAEgq3Bg2sThlmRwSdcpywYIF59xm2xGyROEPS3LgD1JyYE7Jg1kBF5eEXkMGAACA96KQAQAAGEYhAwAAMIxCBgAAYBiFDAAAwDAKGQAAgGEUMgAAAMMoZAAAAIZRyAAAAAyjkAEAABiW9I9Ocjg8piMAgC14NBxw6bD1CFkkElFpaana2tokSX19faqurlZNTY0aGhoUi8UkSVu2bFFVVZUqKyvV0tIiSXrrrbd0++23a9WqVaqurlZvb6+dUQEAAIyxrZCNjIzI6/WqsLAwvtbU1KTa2lq1tbXJ7Xaro6NDkUhEPT09am9v1+7du+X3+zU0NKSf/OQnuummm9Ta2qp77rlHW7ZssSsqAACAUbYVMpfLpZaWFmVlZcXX+vv7lZubK0kqKipSd3e3MjIyNDo6qrGxMY2OjiolJUXp6em6/PLL9c4770iSjh8/rssvv9yuqAAAAEbZdg2Z0+mU03n2y2dnZ6urq0sVFRUKBoMaHh6W2+1WWVmZFi9erNOnT2vdunWaNGmSVq9ereXLl+vf//3f9Ze//EW7d++2KyoAAIBRCb2ov76+Xh6PR36/X/n5+bIsS0eOHNHevXu1b98+xWIxVVVVaenSpXriiSdUXl6uNWvWaP/+/WpsbNTWrVsTGRcAjAqHw+fdFo1G33c7xg9mlRxMzymhhcztdsvn80mSgsGgBgcHdfjwYc2fP1/p6emSpDlz5igSiejVV1/V3XffLUlauHChHnzwwURGBQDjcnJyzrstHA6/73aMH8wqOSRiTqFQ6LzbEnofsubmZnV2dkqS/H6/SkpKNHPmTPX29urMmTM6deqUIpGIZsyYoauuukqHDh2SJP3yl7/UVVddlcioAAAACWPbEbLe3l41NjZqYGBATqdTgUBAdXV18nq98vl8KigoUHFxsaR3j4CtXLlSlmVp+fLlmj59uu644w7df//9ev755yVJ999/v11RAQAAjHJYlmWZDvFRhUIh5eU9azoGANji/W4My2mw5MGskkOiTlkuWLDgnNuS/k793Mk6OfAHKTkwJwAwg2dZAgAAGEYhAwAAMIxCBgAAYBiFDAAAwDAKGQAAgGEUMgAAAMMoZAAAAIZRyAAAAAyjkAEAABhGIQMAADAs6R+d5HB4TEcAgEsej7ED/j62FrJIJKK1a9dq9erVqqmpUV9fnx544AE5HA5dffXV8ng8cjqd2rJli3p6emRZlkpLS/WNb3xDP/rRj/Tyyy9Lks6cOaPh4WEFAgE74wIAABhhWyEbGRmR1+tVYWFhfK2pqUm1tbVatGiRtm3bpo6ODs2ZM0c9PT1qb2/XmTNn9IUvfEEVFRVas2aN1qxZI0l6+umndfToUbuiAgAAGGXbNWQul0stLS3KysqKr/X39ys3N1eSVFRUpO7ubmVkZGh0dFRjY2MaHR1VSkqK0tPT4/vEYjHt3r1bNTU1dkUFAAAwyrZC5nQ6lZaWdtZadna2urq6JEnBYFDDw8Nyu90qKyvT4sWLtXjxYlVVVWnSpEnxfV544QXdcMMN73ktAACAi0VCL+qvr6+Xx+OR3+9Xfn6+LMvSkSNHtHfvXu3bt0+xWExVVVVaunSprrjiCknSU089pQcffDCRMQEAH1I4HDYdYdyKRqP8fJKA6TkltJC53W75fD5J7x4hGxwc1OHDhzV//vz4aco5c+YoEomosLBQIyMjeuuttzR9+vRExgQAfEg5OTmmI4xb4XCYn08SSMScQqHQebcl9D5kzc3N6uzslCT5/X6VlJRo5syZ6u3t1ZkzZ3Tq1ClFIhHNmDFDkvT666/rmmuuSWREAACAhLPtCFlvb68aGxs1MDAgp9OpQCCguro6eb1e+Xw+FRQUqLi4WJK0cOFCrVy5UpZlafny5fEjYkNDQ5oyZYpdEQEAAMYFh2VZlukQH1UoFFJe3rOmYwDAJY8bw54fpyyTQ6JOWS5YsOCc25L+Tv38EUgO/EFKDswpeTAr4OLCsywBAAAMo5ABAAAYRiEDAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADEv6O/U7HB7TEYBxiydZAEBy4AgZAACAYbYWskgkotLSUrW1tUmS+vr6VF1drZqaGjU0NCgWi0mStmzZoqqqKlVWVqqlpSW+//bt23Xrrbdq2bJlOnz4sJ1RAQAAjLHtlOXIyIi8Xq8KCwvja01NTaqtrdWiRYu0bds2dXR0aM6cOerp6VF7e7vOnDmjL3zhC6qoqNA777yj//qv/9JTTz2lN954Qy+++KKuvfZau+ICAAAYY9sRMpfLpZaWFmVlZcXX+vv7lZubK0kqKipSd3e3MjIyNDo6qrGxMY2OjiolJUXp6enav3+/ysvL5XQ69dnPflZ33nmnXVEBAACMsq2QOZ1OpaWlnbWWnZ2trq4uSVIwGNTw8LDcbrfKysq0ePFiLV68WFVVVZo0aZIGBgZ07NgxrVu3Tl/96lf1+uuv2xUVAADAqIR+yrK+vl4ej0d+v1/5+fmyLEtHjhzR3r17tW/fPsViMVVVVWnp0qWyLEsnT57U1q1bFQqFdP/99+upp55KZFwg6YXD4Q/1/dFo9EPvAzOYVfJgVsnB9JwSWsjcbrd8Pp+kd4+QDQ4O6vDhw5o/f77S09MlSXPmzFEkEtGVV16pWbNmyeFwKC8vTwMDA4mMClwUcnJyPtT3h8PhD70PzGBWyYNZJYdEzCkUCp13W0Jve9Hc3KzOzk5Jkt/vV0lJiWbOnKne3l6dOXNGp06dUiQS0YwZM3TjjTcqGAxKevfTmW63O5FRAQAAEsa2I2S9vb1qbGzUwMCAnE6nAoGA6urq5PV65fP5VFBQoOLiYknSwoULtXLlSlmWpeXLl2v69OmaPn26gsGgVq1apbGxMT3wwAN2RQUAADDKtkI2b948tba2vmd9z54971m78847z/kpym9961u2ZAMAABhPkv7RSTwaJjlwDQUAAOfHo5MAAAAMo5ABAAAYRiEDAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADEv6O/U7HB7TEQDg78ITRwBwhAwAAMAwWwtZJBJRaWmp2traJEl9fX2qrq5WTU2NGhoaFIvFJElbtmxRVVWVKisr1dLSIkkKBAK66aabtGrVKq1atUo/+tGP7IwKAABgjG2nLEdGRuT1elVYWBhfa2pqUm1trRYtWqRt27apo6NDc+bMUU9Pj9rb23XmzBl94QtfUEVFhUZGRlRdXa3Vq1fbFREAAGBcsO0ImcvlUktLi7KysuJr/f39ys3NlSQVFRWpu7tbGRkZGh0d1djYmEZHR5WSkqL09HSdOHHCrmgAAADjim2FzOl0Ki0t7ay17OxsdXV1SZKCwaCGh4fldrtVVlamxYsXa/HixaqqqtKkSZM0MjKivXv36mtf+5puu+02vf7663ZFBQAAMCqhn7Ksr6+Xx+OR3+9Xfn6+LMvSkSNHtHfvXu3bt0+xWExVVVVaunSpPv/5zys3N1ef//zn9Ytf/EIbNmzQs88+m8i4AJAQ4XD4Q+8TjUY/0n5IPGaVHEzPKaGFzO12y+fzSXr3CNng4KAOHz6s+fPnKz09XZI0Z84cRSKRs649y8vL07Fjx3T69GlNmDAhkZEBwHY5OTkfep9wOPyR9kPiMavkkIg5hUKh825L6G0vmpub1dnZKUny+/0qKSnRzJkz1dvbqzNnzujUqVOKRCKaMWOGtm3bpkAgIOndT2tOmTKFMgYAAC5Kth0h6+3tVWNjowYGBuR0OhUIBFRXVyev1yufz6eCggIVFxdLkhYuXKiVK1fKsiwtX75c06dP16233qr77rtPra2tisVi+s53vmNXVAAAAKMclmVZpkN8VKFQSHl5XFcGILl9lDv1cxoseTCr5JCoU5YLFiw457akf3QSjxxJDvxBSg7MCQDM4NFJAAAAhlHIAAAADKOQAQAAGEYhAwAAMIxCBgAAYBiFDAAAwDAKGQAAgGEUMgAAAMMoZAAAAIYl/Z36HQ6P6QhA0uJJFwAwPnCEDAAAwDBbC1kkElFpaana2tokSX19faqurlZNTY0aGhoUi8UkSVu2bFFVVZUqKyvV0tJy1msMDw/ruuuuU09Pj51RAQAAjLGtkI2MjMjr9aqwsDC+1tTUpNraWrW1tcntdqujo0ORSEQ9PT1qb2/X7t275ff7NTQ0FN9n8+bNmjFjhl0xAQAAjLOtkLlcLrW0tCgrKyu+1t/fr9zcXElSUVGRuru7lZGRodHRUY2NjWl0dFQpKSlKT0+XJB04cECf/OQnlZ2dbVdMAAAA42y7qN/pdMrpPPvls7Oz1dXVpYqKCgWDQQ0PD8vtdqusrEyLFy/W6dOntW7dOk2aNEljY2Patm2bfvjDH2rjxo12xQQuaeFw+Kyvo9Hoe9YwPjGr5MGskoPpOSX0U5b19fXyeDzy+/3Kz8+XZVk6cuSI9u7dq3379ikWi6mqqkpLly7V7t279ZWvfEWf+tSnEhkRuKTk5OSc9XU4HH7PGsYnZpU8mFVySMScQqHQebcltJC53W75fD5JUjAY1ODgoA4fPqz58+fHT1POmTNHkUhEL730ks6cOaPHH39cf/jDH/TLX/5SDz/8sD7zmc8kMjIAAIDtElrImpublZubq+LiYvn9ft1666268sortXPnTp05c0anT59WJBLRjBkz1N7eHt/v3nvv1Ze//GXKGAAAuCjZVsh6e3vV2NiogYEBOZ1OBQIB1dXVyev1yufzqaCgQMXFxZKkhQsXauXKlbIsS8uXL9f06dPtigUAADDu2FbI5s2bp9bW1ves79mz5z1rd955p+68887zvtamTZs+1mwAAADjSdI/OolHvyQHLmoFAOD8eHQSAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGEYhAwAAMIxCBgAAYBiFDAAAwDAKGQAAgGFJf6d+h8NjOgIAQDw5Bfh7cIQMAADAMFsLWSQSUWlpqdra2iRJfX19qq6uVk1NjRoaGhSLxSRJW7ZsUVVVlSorK9XS0iJJOnr0qL7+9a9r1apVqqqq0qFDh+yMCgAAYIxthWxkZERer1eFhYXxtaamJtXW1qqtrU1ut1sdHR2KRCLq6elRe3u7du/eLb/fr6GhIT3zzDO69dZb1draqvXr1+vhhx+2KyoAAIBRthUyl8ullpYWZWVlxdf6+/uVm5srSSoqKlJ3d7cyMjI0OjqqsbExjY6OKiUlRenp6brtttv0pS99SZL0xz/+UVOnTrUrKgAAgFG2XdTvdDrldJ798tnZ2erq6lJFRYWCwaCGh4fldrtVVlamxYsX6/Tp01q3bp0mTZokSRoaGtI3v/lNnThxQjt37rQrKgDgYxAOh01HGJei0Sg/myRgek4J/ZRlfX29PB6P/H6/8vPzZVmWjhw5or1792rfvn2KxWKqqqrS0qVLdcUVVygzM1NPPfWUurq6dN9992nHjh2JjAsA+BBycnJMRxiXwuEwP5skkIg5hUKh825LaCFzu93y+XySpGAwqMHBQR0+fFjz589Xenq6JGnOnDmKRCKaMGGC5syZo8suu0yLFi3St7/97URGBQAASJiE3vaiublZnZ2dkiS/36+SkhLNnDlTvb29OnPmjE6dOqVIJKIZM2bohRde0NNPPy1JeuONN+R2uxMZFQAAIGFsO0LW29urxsZGDQwMyOl0KhAIqK6uTl6vVz6fTwUFBSouLpYkLVy4UCtXrpRlWVq+fLmmT5+utWvX6t5779XevXs1NjYmj8djV1QAAACjHJZlWaZDfFShUEh5ec+ajgEAEHfqPx+uIUsOibqGbMGCBefclvSPTuIPQHLgD1JyYE7Jg1kBFxcenQQAAGAYhQwAAMAwChkAAIBhFDIAAADDKGQAAACGUcgAAAAMo5ABAAAYRiEDAAAwjEIGAABgWNLfqd/h8JiOAACAJJ4eg4+OI2QAAACG2VrIIpGISktL1dbWJknq6+tTdXW1ampq1NDQoFgsJknasmWLqqqqVFlZqZaWFklSLBZTfX29Vq5cqX/8x3/UL37xCzujAgAAGGNbIRsZGZHX61VhYWF8rampSbW1tWpra5Pb7VZHR4cikYh6enrU3t6u3bt3y+/3a2hoSP/xH/+h9PR07dq1S9/5zne0adMmu6ICAAAYZVshc7lcamlpUVZWVnytv79fubm5kqSioiJ1d3crIyNDo6OjGhsb0+joqFJSUpSenq5bbrlF9913nyRpypQpeuedd+yKCgAAYJRtF/U7nU45nWe/fHZ2trq6ulRRUaFgMKjh4WG53W6VlZVp8eLFOn36tNatW6dJkyadtd/OnTv1xS9+0a6oAAB8LMLh8HvWotHoOdcxvpieU0I/ZVlfXy+PxyO/36/8/HxZlqUjR45o79692rdvn2KxmKqqqrR06VJdccUVkqTHH39cr732mh555JFERgUA4EPLycl5z1o4HD7nOsaXRMwpFAqdd1tCC5nb7ZbP55MkBYNBDQ4O6vDhw5o/f77S09MlSXPmzFEkElFhYaGefPJJ/exnP9MPf/hDTZw4MZFRAQAAEiaht71obm5WZ2enJMnv96ukpEQzZ85Ub2+vzpw5o1OnTikSiWjGjBk6cuSI2tvbtXXrVqWmpiYyJgAAQELZdoSst7dXjY2NGhgYkNPpVCAQUF1dnbxer3w+nwoKClRcXCxJWrhwoVauXCnLsrR8+XJNnz5d//qv/6p33nlHtbW18dfcvn27XC6XXZEBAACMcFiWZZkO8VGFQiHl5T1rOgYAAJLOfad+riFLDom6hmzBggXn3Jb0j07iMRXJgT9IyYE5JQ9mBVxceHQSAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGEYhAwAAMIxCBgAAYBiFDAAAwDAKGQAAgGFJf6d+h8NjOgIA2IankQCXBo6QAQAAGGZrIYtEIiotLVVbW5skqa+vT9XV1aqpqVFDQ4NisZgkacuWLaqqqlJlZaVaWlri+7/yyisqLCzU/v377YwJAABglG2nLEdGRuT1elVYWBhfa2pqUm1trRYtWqRt27apo6NDc+bMUU9Pj9rb23XmzBl94QtfUEVFhU6ePKnHHnvsvE9FBwAAuFjYdoTM5XKppaVFWVlZ8bX+/n7l5uZKkoqKitTd3a2MjAyNjo5qbGxMo6OjSklJUXp6ujIzM7V161ZNmjTJrogAAADjgm1HyJxOp5zOs18+OztbXV1dqqioUDAY1PDwsNxut8rKyrR48WKdPn1a69ato4QBwP8VDofPuR6NRs+7DeMLs0oOpueU0E9Z1tfXy+PxyO/3Kz8/X5Zl6ciRI9q7d6/27dunWCymqqoqLV26VFdccUUiowHAuJSTk3PO9XA4fN5tGF+YVXJIxJxCodB5tyW0kLndbvl8PklSMBjU4OCgDh8+rPnz5ys9PV2SNGfOHEUikbOuPQMAALiYJfS2F83Nzers7JQk+f1+lZSUaObMmert7dWZM2d06tQpRSIRzZgxI5GxAAAAjLLtCFlvb68aGxs1MDAgp9OpQCCguro6eb1e+Xw+FRQUqLi4WJK0cOFCrVy5UpZlafny5Zo+fbo6Ozu1fft2/fa3v9Vrr72m1tZW7dixw664AAAAxjgsy7JMh/ioQqEQt8VIElxDkRyYU/JgVsmDWSWHRF1Ddr7ewp36AQAADKOQAQAAGEYhAwAAMIxCBgAAYBiFDAAAwDAKGQAAgGEUMgAAAMMoZAAAAIZRyAAAAAyjkAEAABhm27MsE8Xh8JiOAAAfmGV5TEcAMA5xhAwAAMAwWwtZJBJRaWmp2traJEl9fX2qrq5WTU2NGhoaFIvFJElbtmxRVVWVKisr1dLSIkk6deqU7rnnHq1YsUI1NTU6cuSInVEBAACMsa2QjYyMyOv1qrCwML7W1NSk2tpatbW1ye12q6OjQ5FIRD09PWpvb9fu3bvl9/s1NDSk//zP/9SnPvUp7d69W9/4xjf0ve99z66oAAAARtlWyFwul1paWpSVlRVf6+/vV25uriSpqKhI3d3dysjI0OjoqMbGxjQ6OqqUlBSlp6frwIEDuummmyRJN9xwg0KhkF1RAQAAjLLton6n0ymn8+yXz87OVldXlyoqKhQMBjU8PCy3262ysjItXrxYp0+f1rp16zRp0iQNDw9rypQpkqQJEyYoJSVFY2NjcrlcdkUGANuFw+GP5XWi0ejH9lqwF7NKDqbnlNBPWdbX18vj8cjv9ys/P1+WZenIkSPau3ev9u3bp1gspqqqKi1dulSWZZ21r2VZcjgciYwLAB+7nJycj+V1wuHwx/ZasBezSg6JmNP7ne1LaCFzu93y+XySpGAwqMHBQR0+fFjz589Xenq6JGnOnDmKRCKaOnWqhoaGNHfuXJ06dUqWZWnixImJjAsAAJAQCb3tRXNzszo7OyVJfr9fJSUlmjlzpnp7e3XmzBmdOnVKkUhEM2bM0MKFC/X8889Lkvbv36+CgoJERgUAAEgY246Q9fb2qrGxUQMDA3I6nQoEAqqrq5PX65XP51NBQYGKi4slSQsXLtTKlStlWZaWL1+u6dOny+126+WXX9aKFSvkcrm0adMmu6ICAAAY5bD+9mKtJBIKhbRgwQLTMfABcA1FcmBOyYNZJQ9mlRwSdQ3Z+XoLd+oHAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGEYhAwAAMIxCBgAAYJhtz7JMFIfDYzoCLmKW5TEdAQBwCeAIGQAAgGG2HiGLRCJau3atVq9erZqaGvX19emBBx6Qw+HQ1VdfLY/Ho9dff12NjY3xfX7zm99o27Ztmjt3ru69914NDw8rPT1dmzZtUmZmpp1xAQAAjLDtCNnIyIi8Xq8KCwvja01NTaqtrVVbW5vcbrc6Ojo0b948tba2qrW1Vdu2bdOsWbP0uc99Tj/96U81Y8YM7dq1S2vWrFFzc7NdUQEAAIyyrZC5XC61tLQoKysrvtbf36/c3FxJUlFRkbq7u8/aZ/v27Vq9erVSUlL0+9//Pv69eXl5CoVCdkUFAAAwyrZTlk6nU07n2S+fnZ2trq4uVVRUKBgManh4OL4tGo3qpZde0l133XXW995888165ZVX9Oabb9oVFTivcDhsOkJCRaPRS+49JytmlTyYVXIwPaeEfsqyvr5eHo9Hfr9f+fn5siwrvm3fvn0qLi5WSsq7B+2WL1+uN954QytWrFB+fr6mTJmSyKiAJCknJ8d0hIQKh8OX3HtOVswqeTCr5JCIOb3f2b6EFjK32y2fzydJCgaDGhwcjG/bv3+/VqxYEf/a5XLpwQcflCSdOHFCL774YiKjAgAAJExCb3vR3Nyszs5OSZLf71dJSUl8W29vr+bOnRv/uqurS9///vclSc8884yKiooSGRUAACBhbDtC1tvbq8bGRg0MDMjpdCoQCKiurk5er1c+n08FBQUqLi6Of//x48c1adKk+NcFBQV6/PHHtWLFCmVlZemhhx6yKyoAAIBRthWy/3c7i7+1Z8+ec37/gQMHzvo6LS1NP/7xjy/473An9eTANRQAAJwfd+oHAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGEYhAwAAMIxCBgAAYJhtj05KFIfDYzoCcEnisWUA8PGxtZBFIhGtXbtWq1evVk1Njfr6+vTAAw/I4XDo6quvlsfj0euvv67Gxsb4Pr/5zW+0bds2TZs2Tf/8z/+ssbExnTlzRvfdd5/mzZtnZ1wAAAAjbDtlOTIyIq/Xq8LCwvhaU1OTamtr1dbWJrfbrY6OjvhDyFtbW7Vt2zbNmjVLn/vc5/STn/xEN910k1pbW3XPPfdoy5YtdkUFAAAwyrZC5nK51NLSoqysrPhaf3+/cnNzJUlFRUXq7u4+a5/t27dr9erVSklJ0eWXX6533nlHknT8+HFdfvnldkUFAAAwyrZC5nQ6lZaWdtZadna2urq6JEnBYFDDw8PxbdFoVC+99JKWLFkiSVq9erWee+45lZWVqaGhQXfddZddUQEAAIxK6EX99fX18ng88vv9ys/Pl2VZ8W379u1TcXGxUlLe7YiPPvqoysvLtWbNGu3fv1+NjY3aunVrIuMCeB/hcNh0hEtaNBplBkmCWSUH03NKaCFzu93y+XyS3j1CNjg4GN+2f/9+rVixIv71q6++qrvvvluStHDhQj344IOJjArgAnJyckxHuKSFw2FmkCSYVXJIxJxCodB5tyX0PmTNzc3q7OyUJPn9fpWUlMS39fb2au7cufGvr7rqKh06dEiS9Mtf/lJXXXVVIqMCAAAkjG1HyHp7e9XY2KiBgQE5nU4FAgHV1dXJ6/XK5/OpoKBAxcXF8e8/fvy4Jk2aFP/6jjvu0P3336/nn39eknT//ffbFRUAAMAo2wrZ/7udxd/as2fPOb//wIEDZ32dlZWllpYWW7IBAACMJ0l/p37uFp4cuIYiOTAnADCDZ1kCAAAYRiEDAAAwjEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGEYhAwAAMCzpH53kcHhMR8AHxGOuAAA4N1sLWSQS0dq1a7V69WrV1NSor69PDzzwgBwOh66++mp5PB69/vrramxsjO/zm9/8Rtu2bVNPT49efvllSdKZM2c0PDysQCBgZ1wAAAAjbCtkIyMj8nq9KiwsjK81NTWptrZWixYt0rZt29TR0aEvfelLam1tlSQdP35ca9as0ec+9zn9wz/8g9asWSNJevrpp3X06FG7ogIAABhl2zVkLpdLLS0tysrKiq/19/crNzdXklRUVKTu7u6z9tm+fbtWr16tlJT/P1YsFtPu3btVU1NjV1QAAACjbCtkTqdTaWlpZ61lZ2erq6tLkhQMBjU8PBzfFo1G9dJLL2nJkiVn7fPCCy/ohhtueM9rAQAAXCwSelF/fX29PB6P/H6/8vPzZVlWfNu+fftUXFx81tExSXrqqaf04IMPJjImbBIOh01HwAVEo1HmlCSYVfJgVsnB9JwSWsjcbrd8Pp+kd4+QDQ4Oxrft379fK1asOOv7R0ZG9NZbb2n69OmJjAmb5OTkmI6ACwiHw8wpSTCr5MGskkMi5hQKhc67LaH3IWtublZnZ6ckye/3q6SkJL6tt7dXc+fOPev7X3/9dV1zzTWJjAgAAJBwth0h6+3tVWNjowYGBuR0OhUIBFRXVyev1yufz6eCggIVFxfHv//48eOaNGnSWa8xNDSkKVOm2BURAABgXLCtkM2bNy9+O4u/tmfPnnN+/4EDB96zdvPNN+vmm2/+2LMBAACMJ0l/p37u/p4cuKAVAIDz41mWAAAAhlHIAAAADKOQAQAAGEYhAwAAMMxh/fXt8pPM+91gDQAAYLxZsGDBOdeTupABAABcDDhlCQAAYBiFDAAAwLCkvTHsxo0bdejQITkcDv3zP/+zcnNzTUe6pPX29mrt2rW66qqrJEnZ2dn6+te/rm9/+9s6ffq0MjMz9d3vflcul0vPPPOMdu7cqZSUFFVWVmr58uWG018aIpGI1q5dq9WrV6umpkZ//OMfP/B8Tp06pXvvvVdvvvmmJkyYoIceekgzZsww/ZYuSn87J6/Xq4MHD+qTn/ykJOn2229XcXExcxoHNm/erFAopFgspjvuuEPXXnstv1Pj0N/OqaenZ3z+TllJqKenx6qtrbUsy7J+/etfW8uXLzecCD09Pda//Mu/nLV27733Ws8995xlWZbV2NhoPf7449aJEyes//7f/7t1/Phx6+TJk9bNN99svf322wYSX1pOnDhh1dTUWA0NDVZra6tlWR9uPn6/3/J4PJZlWVZnZ6d11113mXorF7XzzelXv/rVe76POZl14MAB6+tf/7plWZZ17Ngxa9GiRfxOjUPnm9N4/J1KylOWBw4cUGlpqSRp9uzZOn78uP7yl78YTnVpO3HixHvWenp6tGTJEknSkiVLdODAAR06dEjXXnutMjIylJaWpry8PL366quJjnvJcblcamlpUVZWVnztw8znwIEDuummmyRJN9xwA59wtsm55nSu3y3mZN51112nhx9+WJJ02WWX6eTJk/xOjUPnmtPx48ff833jYU5JecpyeHhYn/3sZ+NfX3HFFRoaGtKkSZMMprq0jYyMKBQK6etf/7pOnjypb33rWzp58qRcLpckKTMzU0NDQxoeHtaUKVPi+1155ZUaGhoyFfuS4XQ65XSe/ev+Yebz1+sTJkxQSkqKxsbG4vvj43GuOZ04cUJbt27V8ePHNXXqVDU0NDCncWDChAn6xCc+IUl68skndeONN+qll17id2qcOdecjh07Ni5/p5KykFl/c6cOy7LkcDgMpYEkzZ07V+vWrdOSJUv0u9/9TrfddptisVh8+/+bGbMbP/76536h+TA3c6qqqjR79mxdc801+tGPfqQf/OAHmj9//lnfw5zM2bdvn/bs2aMdO3bo5ptvjq/zOzW+/PWcfv7zn4/L36mkPGU5depUDQ8Px78eHBzUlVdeaTAR/tt/+2/xQ/XXXHONrrzySh0/flzRaFSS9NZbbykrK+ucs8vMzDSS+VKXnp7+geczderU+JHMU6dOybIsTZw40UjuS81NN92ka665Jv6/33jjDeY0TgSDQT3yyCNqaWlRRkYGv1Pj1N/Oabz+TiVlIVu4cKECgYAk6Ve/+pWysrI4XWnYnj179G//9m+SpKGhIR09elT/43/8j/icXnjhBRUVFWn+/Pk6fPiwjh8/rhMnTujVV19VXl6eyeiXrOuvv/4Dz2fhwoV6/vnnJUn79+9XQUGByeiXlG9+85t68803Jb173d9nPvMZ5jQO/PnPf9bmzZvl8/k0efJkSfxOjUfnmtN4/Z1K2jv1NzU16Re/+IUcDof+9//+35o7d67pSJe0P/3pT6qrq9PIyIjGxsb0T//0T8rJyVF9fb1GR0f16U9/Wg899JAmTpyo559/Xtu3b5fD4VBNTY1uueUW0/Ever29vWpsbNTAwICcTqemTp2qpqYm3XvvvR9oPqdPn1ZDQ4N+//vfy+VyadOmTXK73abf1kXnXHNasWKFtm/frk984hNKT0/XQw89pCuuuII5GfbEE0/oBz/4QfxIiyRt2rRJDQ0N/E6NI+ea07Jly9Ta2jrufqeStpABAABcLJLylCUAAMDFhEIGAABgGIUMAADAMAoZAACAYRQyAAAAwyhkAAAAhlHIAAAADKOQAQAAGPb/AdYRnn1XoDzjAAAAAElFTkSuQmCC\n", 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" ] @@ -2144,7 +2163,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 41, @@ -2179,7 +2198,9 @@ "cell_type": "code", "execution_count": 42, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2194,7 +2215,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -2241,12 +2262,14 @@ "cell_type": "code", "execution_count": 43, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -2329,21 +2352,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 2. Add coordinates from the plot locations" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Loading the coordinate data" + "## 2. Add species names to dataset" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The individual plots are only identified by a `plot` identification number. In order to provide sufficient information to external users, additional information about the coordinates should be added. The coordinates of the individual plots are saved in another file: `plot_location.xlsx`. We will use this information to further enrich our data set and add the Darwin Core Terms `decimalLongitude` and `decimalLatitude`." + "The column `species` only provides a short identifier in the survey overview. The name information is stored in a separate file `species.csv`. We want our data set to include this information, read in the data and add it to our survey data set:" ] }, { @@ -2354,11 +2370,11 @@ "\n", "**EXERCISE**\n", "\n", - "- Read the excel file 'plot_location.xlsx' and store the data as the variable `plot_data`, with 3 columns: plot, xutm, yutm.\n", + "- Read in the 'species.csv' file and save the resulting `DataFrame` as variable `species_data`.\n", "\n", "
Hints\n", "\n", - "- Pandas read methods all have a similar name, `read_...`.\n", + "- Check the delimiter (`sep`) parameter of the `read_csv` function.\n", "\n", "
\n", "\n", @@ -2369,11 +2385,13 @@ "cell_type": "code", "execution_count": 47, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "plot_data = pd.read_excel(\"data/plot_location.xlsx\", skiprows=3, index_col=0)" + "species_data = pd.read_csv(\"data/species.csv\", sep=\";\")" ] }, { @@ -2402,53 +2420,59 @@ " \n", " \n", " \n", - " plot\n", - " xutm\n", - " yutm\n", + " species_id\n", + " genus\n", + " species\n", + " taxa\n", " \n", " \n", " \n", " \n", " 0\n", - " 1\n", - " 681222.131658\n", - " 3.535262e+06\n", + " AB\n", + " Amphispiza\n", + " bilineata\n", + " Bird\n", " \n", " \n", " 1\n", - " 2\n", - " 681302.799361\n", - " 3.535268e+06\n", + " AH\n", + " Ammospermophilus\n", + " harrisi\n", + " Rodent-not censused\n", " \n", " \n", " 2\n", - " 3\n", - " 681375.294968\n", - " 3.535270e+06\n", + " AS\n", + " Ammodramus\n", + " savannarum\n", + " Bird\n", " \n", " \n", " 3\n", - " 4\n", - " 681450.837525\n", - " 3.535271e+06\n", + " BA\n", + " Baiomys\n", + " taylori\n", + " Rodent\n", " \n", " \n", " 4\n", - " 5\n", - " 681526.983040\n", - " 3.535281e+06\n", + " CB\n", + " Campylorhynchus\n", + " brunneicapillus\n", + " Bird\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " plot xutm yutm\n", - "0 1 681222.131658 3.535262e+06\n", - "1 2 681302.799361 3.535268e+06\n", - "2 3 681375.294968 3.535270e+06\n", - "3 4 681450.837525 3.535271e+06\n", - "4 5 681526.983040 3.535281e+06" + " species_id genus species taxa\n", + "0 AB Amphispiza bilineata Bird\n", + "1 AH Ammospermophilus harrisi Rodent-not censused\n", + "2 AS Ammodramus savannarum Bird\n", + "3 BA Baiomys taylori Rodent\n", + "4 CB Campylorhynchus brunneicapillus Bird" ] }, "execution_count": 48, @@ -2457,82 +2481,75 @@ } ], "source": [ - "plot_data.head()" + "species_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Transforming to other coordinate reference system" + "### Fix a wrong acronym naming" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "These coordinates are in meters, more specifically in the [UTM 12 N](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system) coordinate system. However, the agreed coordinate representation for Darwin Core is the [World Geodetic System 1984 (WGS84)](http://spatialreference.org/ref/epsg/wgs-84/).\n", - "\n", - "As this is not a GIS course, we will shortcut the discussion about different projection systems, but provide an example on how such a conversion from `UTM12N` to `WGS84` can be performed with the projection toolkit `pyproj` and by relying on the existing EPSG codes (a registry originally setup by the association of oil & gas producers)." + "When reviewing the metadata, you see that in the data-file the acronym `NE` is used to describe `Neotoma albigula`, whereas in the [metadata description](http://esapubs.org/archive/ecol/E090/118/Portal_rodent_metadata.htm), the acronym `NA` is used." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "First, we define out two projection systems, using their corresponding EPSG codes:" + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Convert the value of 'NE' to 'NA' by using Boolean indexing/Filtering for the `species_id` column.\n", + "\n", + "
Hints\n", + "\n", + "- To assign a new value, use the `loc` operator.\n", + "- With `loc`, specify both the selecting for the rows and for the columns (`df.loc[row_indexer, column_indexer] = ..`).\n", + "\n", + "
\n", + "\n", + "
" ] }, { "cell_type": "code", "execution_count": 49, - "metadata": {}, - "outputs": [], - "source": [ - "from pyproj import Transformer" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, "outputs": [], "source": [ - "transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")" + "species_data.loc[species_data[\"species_id\"] == \"NE\", \"species_id\"] = \"NA\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The reprojection can be done by the function `transform` of the projection toolkit, providing the coordinate systems and a set of x, y coordinates. For example, for a single coordinate, this can be applied as follows:" + "### Merging surveys and species" ] }, { - "cell_type": "code", - "execution_count": 51, + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(31.9388498837225, -109.08282902317859)" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "transformer.transform(681222.131658, 3.535262e+06)" + "As we now prepared the two series, we can combine the data, using again the `pd.merge` operation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Such a transformation is a function not supported by Pandas itself (it is in https://geopandas.org/). In such an situation, we want to _apply_ a custom function to _each row of the DataFrame_. Instead of writing a `for` loop to do this for each of the coordinates in the list, we can `.apply()` this function with Pandas." + "We want to add the data of the species to the survey data, in order to see the full species names in the combined data table." ] }, { @@ -2543,81 +2560,61 @@ "\n", "**EXERCISE**\n", "\n", - "Apply the pyproj function `transform` to plot_data, using the columns `xutm` and `yutm` and save the resulting output in 2 new columns, called `decimalLongitude` and `decimalLatitude`:\n", - "\n", - "- Create a function `transform_utm_to_wgs` that takes a row of a `DataFrame` and returns a `Series` of two elements with the longitude and latitude.\n", - "- Test this function on the first row of `plot_data`\n", - "- Now `apply` this function on all rows (use the `axis` parameter correct)\n", - "- Assign the result of the previous step to `decimalLongitude` and `decimalLatitude` columns\n", + "Combine the DataFrames `survey_data_plots` and the `DataFrame` `species_data` by adding the corresponding species information (name, class, kingdom,..) to the individual observations. Assign the output to a new variable `survey_data_species`.\n", "\n", "
Hints\n", "\n", - "- Convert the output of the transformer to a Series before returning (`pd.Series(....)`)\n", - "- A convenient way to select a single row is using the `.loc[0]` operator.\n", - "- `apply` can be used for both rows (`axis` 1) as columns (`axis` 0).\n", - "- To assign two columns at once, you can use a similar syntax as for selecting multiple columns with a list of column names (`df[['col1', 'col2']]`).\n", - "\n", - "
\n", + "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", + "- Take into account that our key-column is different for `species_data` and `survey_data_plots`, respectively `species` and `species_id`. The `pd.merge()` function has `left_on` and `right_on` keywords to specify the name of the column in the left and right `DataFrame` to merge on.\n", "\n", - "
" + "
" ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 51, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "def transform_utm_to_wgs(row):\n", - " \"\"\"Converts the x and y coordinates\n", - "\n", - " Parameters\n", - " ----------\n", - " row : pd.Series\n", - " Single DataFrame row\n", - "\n", - " Returns\n", - " -------\n", - " pd.Series with longitude and latitude\n", - " \"\"\"\n", - " transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")\n", - "\n", - " return pd.Series(transformer.transform(row['xutm'], row['yutm']))" + "survey_data_species = pd.merge(survey_data_decoupled, species_data, how=\"left\", # LEFT OR INNER?\n", + " left_on=\"species\", right_on=\"species_id\")" ] }, { "cell_type": "code", - "execution_count": 53, - "metadata": { - "clear_cell": true - }, + "execution_count": 52, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 31.938851\n", - "1 -109.082829\n", - "dtype: float64" + "35550" ] }, - "execution_count": 53, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# test the new function on a single row of the DataFrame\n", - "transform_utm_to_wgs(plot_data.loc[0])" + "len(survey_data_species) # check length after join operation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The join is ok, but we are left with some redundant columns and wrong naming:" ] }, { "cell_type": "code", - "execution_count": 54, - "metadata": { - "clear_cell": true - }, + "execution_count": 53, + "metadata": {}, "outputs": [ { "data": { @@ -2640,383 +2637,160 @@ " \n", " \n", " \n", - " 0\n", - " 1\n", + " plot\n", + " species_x\n", + " verbatimSex\n", + " wgt\n", + " datasetName\n", + " sex\n", + " occurrenceID\n", + " eventDate\n", + " species_id\n", + " genus\n", + " species_y\n", + " taxa\n", " \n", " \n", " \n", " \n", " 0\n", - " 31.938851\n", - " -109.082829\n", + " 2\n", + " NaN\n", + " M\n", + " NaN\n", + " Ecological Archives E090-118-D1.\n", + " male\n", + " 1\n", + " 1977-07-16\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", " 1\n", - " 31.938887\n", - " -109.081975\n", + " 3\n", + " NaN\n", + " M\n", + " NaN\n", + " Ecological Archives E090-118-D1.\n", + " male\n", + " 2\n", + " 1977-07-16\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", " 2\n", - " 31.938896\n", - " -109.081208\n", - " \n", - " \n", - " 3\n", - " 31.938894\n", - " -109.080409\n", - " \n", - " \n", - " 4\n", - " 31.938970\n", - " -109.079602\n", - " \n", - " \n", - " 5\n", - " 31.939078\n", - " -109.078836\n", - " \n", - " \n", - " 6\n", - " 31.938113\n", - " -109.082816\n", - " \n", - " \n", - " 7\n", - " 31.937884\n", - " -109.081680\n", - " \n", - " \n", - " 8\n", - " 31.937859\n", - " -109.080903\n", - " \n", - " \n", - " 9\n", - " 31.938017\n", - " -109.080091\n", - " \n", - " \n", - " 10\n", - " 31.938056\n", - " -109.079307\n", - " \n", - " \n", - " 11\n", - " 31.938203\n", - " -109.078519\n", - " \n", - " \n", - " 12\n", - " 31.937028\n", - " -109.082613\n", - " \n", - " \n", - " 13\n", - " 31.937054\n", - " -109.081827\n", - " \n", - " \n", - " 14\n", - " 31.937059\n", - " -109.081036\n", - " \n", - " \n", - " 15\n", - " 31.937094\n", - " -109.080244\n", - " \n", - " \n", - " 16\n", - " 31.937117\n", - " -109.079415\n", - " \n", - " \n", - " 17\n", - " 31.937126\n", - " -109.078633\n", - " \n", - " \n", - " 18\n", - " 31.937438\n", - " -109.077912\n", - " \n", - " \n", - " 19\n", - " 31.936334\n", - " -109.080191\n", - " \n", - " \n", - " 20\n", - " 31.936448\n", - " -109.079398\n", - " \n", - " \n", - " 21\n", - " 31.936441\n", - " -109.078602\n", - " \n", - " \n", - " 22\n", - " 31.936763\n", - " -109.077838\n", - " \n", - " \n", - " 23\n", - " 31.938560\n", - " -109.077736\n", - " \n", - " \n", - "\n", - "
" - ], - "text/plain": [ - " 0 1\n", - "0 31.938851 -109.082829\n", - "1 31.938887 -109.081975\n", - "2 31.938896 -109.081208\n", - "3 31.938894 -109.080409\n", - "4 31.938970 -109.079602\n", - "5 31.939078 -109.078836\n", - "6 31.938113 -109.082816\n", - "7 31.937884 -109.081680\n", - "8 31.937859 -109.080903\n", - "9 31.938017 -109.080091\n", - "10 31.938056 -109.079307\n", - "11 31.938203 -109.078519\n", - "12 31.937028 -109.082613\n", - "13 31.937054 -109.081827\n", - "14 31.937059 -109.081036\n", - "15 31.937094 -109.080244\n", - "16 31.937117 -109.079415\n", - "17 31.937126 -109.078633\n", - "18 31.937438 -109.077912\n", - "19 31.936334 -109.080191\n", - "20 31.936448 -109.079398\n", - "21 31.936441 -109.078602\n", - "22 31.936763 -109.077838\n", - "23 31.938560 -109.077736" - ] - }, - "execution_count": 54, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plot_data.apply(transform_utm_to_wgs, axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "plot_data[[\"decimalLongitude\" ,\"decimalLatitude\"]] = plot_data.apply(transform_utm_to_wgs, axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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plotxutmyutmdecimalLongitudedecimalLatitude
01681222.1316583.535262e+0631.938851-109.082829
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23681375.2949683.535270e+0631.938896-109.0812082DMFNaNEcological Archives E090-118-D1.female31977-07-16DMDipodomysmerriamiRodent
37DMMNaNEcological Archives E090-118-D1.male4681450.8375253.535271e+0631.938894-109.0804091977-07-16DMDipodomysmerriamiRodent
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\n", "
" ], "text/plain": [ - " plot xutm yutm decimalLongitude decimalLatitude\n", - "0 1 681222.131658 3.535262e+06 31.938851 -109.082829\n", - "1 2 681302.799361 3.535268e+06 31.938887 -109.081975\n", - "2 3 681375.294968 3.535270e+06 31.938896 -109.081208\n", - "3 4 681450.837525 3.535271e+06 31.938894 -109.080409\n", - "4 5 681526.983040 3.535281e+06 31.938970 -109.079602" + " plot species_x verbatimSex wgt datasetName sex \\\n", + "0 2 NaN M NaN Ecological Archives E090-118-D1. male \n", + "1 3 NaN M NaN Ecological Archives E090-118-D1. male \n", + "2 2 DM F NaN Ecological Archives E090-118-D1. female \n", + "3 7 DM M NaN Ecological Archives E090-118-D1. male \n", + "4 3 DM M NaN Ecological Archives E090-118-D1. male \n", + "\n", + " occurrenceID eventDate species_id genus species_y taxa \n", + "0 1 1977-07-16 NaN NaN NaN NaN \n", + "1 2 1977-07-16 NaN NaN NaN NaN \n", + "2 3 1977-07-16 DM Dipodomys merriami Rodent \n", + "3 4 1977-07-16 DM Dipodomys merriami Rodent \n", + "4 5 1977-07-16 DM Dipodomys merriami Rodent " ] }, - "execution_count": 56, + "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "plot_data.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The above function `transform_utm_to_wgs` you have created is a very specific function that knows the structure of the `DataFrame` you will apply it to (it assumes the 'xutm' and 'yutm' column names). We could also make a more generic function that just takes a X and Y coordinate and returns the `Series` of converted coordinates (`transform_utm_to_wgs2(X, Y)`).\n", - "\n", - "An alternative to apply such a custom function to the `plot_data` `DataFrame` is the usage of the `lambda` construct, which lets you specify a function on one line as an argument:\n", - "\n", - " transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")\n", - " plot_data.apply(lambda row : transformer.transform(row['xutm'], row['yutm']), axis=1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - "\n", - "__WARNING__\n", - "\n", - "Do not abuse the usage of the `apply` method, but always look for an existing Pandas function first as these are - in general - faster!\n", - "\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Join the coordinate information to the survey data set" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can extend our survey data set with this coordinate information. Making the combination of two data sets based on a common identifier is completely similar to the usage of `JOIN` operations in databases. In Pandas, this functionality is provided by [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/merging.html#database-style-DataFrame-joining-merging).\n", - "\n", - "In practice, we have to add the columns `decimalLongitude`/`decimalLatitude` to the current data set `survey_data_decoupled`, by using the plot identification number as key to join." + "survey_data_species.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", - "\n", - "**EXERCISE**\n", - "\n", - "- Extract only the columns to join to our survey dataset: the `plot` identifiers, `decimalLatitude` and `decimalLongitude` into a new variable named `plot_data_selection`\n", - "\n", - "
Hints\n", - "\n", - "- To select multiple columns, use a `list` of column names, e.g. `df[[\"my_col1\", \"my_col2\"]]`\n", - "\n", - "
\n", - "\n", - "
" + "We do not need the columns `species_x` and `species_id` column anymore, as we will use the scientific names from now on:" ] }, { "cell_type": "code", - "execution_count": 57, - "metadata": { - "clear_cell": true - }, + "execution_count": 54, + "metadata": {}, "outputs": [], "source": [ - "plot_data_selection = plot_data[[\"plot\", \"decimalLongitude\", \"decimalLatitude\"]]" + "survey_data_species = survey_data_species.drop([\"species_x\", \"species_id\"], axis=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", - "\n", - "**EXERCISE**\n", - "\n", - "Combine the `DataFrame` `plot_data_selection` and the `DataFrame` `survey_data_decoupled` by adding the corresponding coordinate information to the individual observations using the `pd.merge()` function. Assign the output to a new variable `survey_data_plots`.\n", - "\n", - "
Hints\n", - "\n", - "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", - "- The key-column is the `plot`.\n", - "\n", - "
" + "The column `species_y` could just be named `species`:" ] }, { "cell_type": "code", - "execution_count": 58, - "metadata": { - "clear_cell": true - }, + "execution_count": 55, + "metadata": {}, "outputs": [], "source": [ - "survey_data_plots = pd.merge(survey_data_decoupled, plot_data_selection,\n", - " how=\"left\", on=\"plot\")" + "survey_data_species = survey_data_species.rename(columns={\"species_y\": \"species\"})" ] }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 56, "metadata": {}, "outputs": [ { @@ -3041,140 +2815,153 @@ " \n", " \n", " plot\n", - " species\n", " verbatimSex\n", " wgt\n", " datasetName\n", " sex\n", " occurrenceID\n", " eventDate\n", - " decimalLongitude\n", - " decimalLatitude\n", + " genus\n", + " species\n", + " taxa\n", " \n", " \n", " \n", " \n", " 0\n", " 2\n", - " NaN\n", " M\n", " NaN\n", " Ecological Archives E090-118-D1.\n", " male\n", " 1\n", " 1977-07-16\n", - " 31.938887\n", - " -109.081975\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", " 1\n", " 3\n", - " NaN\n", " M\n", " NaN\n", " Ecological Archives E090-118-D1.\n", " male\n", " 2\n", " 1977-07-16\n", - " 31.938896\n", - " -109.081208\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", " 2\n", " 2\n", - " DM\n", " F\n", " NaN\n", " Ecological Archives E090-118-D1.\n", " female\n", " 3\n", " 1977-07-16\n", - " 31.938887\n", - " -109.081975\n", + " Dipodomys\n", + " merriami\n", + " Rodent\n", " \n", " \n", " 3\n", " 7\n", - " DM\n", " M\n", " NaN\n", " Ecological Archives E090-118-D1.\n", " male\n", " 4\n", " 1977-07-16\n", - " 31.938113\n", - " -109.082816\n", + " Dipodomys\n", + " merriami\n", + " Rodent\n", " \n", " \n", " 4\n", " 3\n", - " DM\n", " M\n", " NaN\n", " Ecological Archives E090-118-D1.\n", " male\n", " 5\n", " 1977-07-16\n", - " 31.938896\n", - " -109.081208\n", + " Dipodomys\n", + " merriami\n", + " Rodent\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " plot species verbatimSex wgt datasetName sex \\\n", - "0 2 NaN M NaN Ecological Archives E090-118-D1. male \n", - "1 3 NaN M NaN Ecological Archives E090-118-D1. male \n", - "2 2 DM F NaN Ecological Archives E090-118-D1. female \n", - "3 7 DM M NaN Ecological Archives E090-118-D1. male \n", - "4 3 DM M NaN Ecological Archives E090-118-D1. male \n", + " plot verbatimSex wgt datasetName sex \\\n", + "0 2 M NaN Ecological Archives E090-118-D1. male \n", + "1 3 M NaN Ecological Archives E090-118-D1. male \n", + "2 2 F NaN Ecological Archives E090-118-D1. female \n", + "3 7 M NaN Ecological Archives E090-118-D1. male \n", + "4 3 M NaN Ecological Archives E090-118-D1. male \n", "\n", - " occurrenceID eventDate decimalLongitude decimalLatitude \n", - "0 1 1977-07-16 31.938887 -109.081975 \n", - "1 2 1977-07-16 31.938896 -109.081208 \n", - "2 3 1977-07-16 31.938887 -109.081975 \n", - "3 4 1977-07-16 31.938113 -109.082816 \n", - "4 5 1977-07-16 31.938896 -109.081208 " + " occurrenceID eventDate genus species taxa \n", + "0 1 1977-07-16 NaN NaN NaN \n", + "1 2 1977-07-16 NaN NaN NaN \n", + "2 3 1977-07-16 Dipodomys merriami Rodent \n", + "3 4 1977-07-16 Dipodomys merriami Rodent \n", + "4 5 1977-07-16 Dipodomys merriami Rodent " ] }, - "execution_count": 59, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "survey_data_plots.head()" + "survey_data_species.head()" ] }, { - "cell_type": "markdown", - "metadata": {}, + "cell_type": "code", + "execution_count": 59, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "35550" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "The plot locations need to be stored with the variable name `verbatimLocality` indicating the identifier as integer value of the plot:" + "len(survey_data_species)" ] }, { - "cell_type": "code", - "execution_count": 60, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "survey_data_plots = survey_data_plots.rename(columns={'plot': 'verbatimLocality'})" + "## 3. Add coordinates from the plot locations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## 3. Add species names to dataset" + "### Loading the coordinate data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The column `species` only provides a short identifier in the survey overview. The name information is stored in a separate file `species.csv`. We want our data set to include this information, read in the data and add it to our survey data set:" + "The individual plots are only identified by a `plot` identification number. In order to provide sufficient information to external users, additional information about the coordinates should be added. The coordinates of the individual plots are saved in another file: `plot_location.xlsx`. We will use this information to further enrich our data set and add the Darwin Core Terms `decimalLongitude` and `decimalLatitude`." ] }, { @@ -3185,11 +2972,11 @@ "\n", "**EXERCISE**\n", "\n", - "- Read in the 'species.csv' file and save the resulting `DataFrame` as variable `species_data`.\n", + "- Read the excel file 'plot_location.xlsx' and store the data as the variable `plot_data`, with 3 columns: plot, xutm, yutm.\n", "\n", "
Hints\n", "\n", - "- Check the delimiter (`sep`) parameter of the `read_csv` function.\n", + "- Pandas read methods all have a similar name, `read_...`.\n", "\n", "
\n", "\n", @@ -3198,18 +2985,20 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 60, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "species_data = pd.read_csv(\"data/species.csv\", sep=\";\")" + "plot_data = pd.read_excel(\"data/plot_location.xlsx\", skiprows=3, index_col=0)" ] }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -3233,134 +3022,137 @@ " \n", " \n", " \n", - " species_id\n", - " genus\n", - " species\n", - " taxa\n", + " plot\n", + " xutm\n", + " yutm\n", " \n", " \n", " \n", " \n", " 0\n", - " AB\n", - " Amphispiza\n", - " bilineata\n", - " Bird\n", + " 1\n", + " 681222.131658\n", + " 3.535262e+06\n", " \n", " \n", " 1\n", - " AH\n", - " Ammospermophilus\n", - " harrisi\n", - " Rodent-not censused\n", + " 2\n", + " 681302.799361\n", + " 3.535268e+06\n", " \n", " \n", " 2\n", - " AS\n", - " Ammodramus\n", - " savannarum\n", - " Bird\n", - " \n", - " \n", - " 3\n", - " BA\n", - " Baiomys\n", - " taylori\n", - " Rodent\n", + " 3\n", + " 681375.294968\n", + " 3.535270e+06\n", + " \n", + " \n", + " 3\n", + " 4\n", + " 681450.837525\n", + " 3.535271e+06\n", " \n", " \n", " 4\n", - " CB\n", - " Campylorhynchus\n", - " brunneicapillus\n", - " Bird\n", + " 5\n", + " 681526.983040\n", + " 3.535281e+06\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " species_id genus species taxa\n", - "0 AB Amphispiza bilineata Bird\n", - "1 AH Ammospermophilus harrisi Rodent-not censused\n", - "2 AS Ammodramus savannarum Bird\n", - "3 BA Baiomys taylori Rodent\n", - "4 CB Campylorhynchus brunneicapillus Bird" + " plot xutm yutm\n", + "0 1 681222.131658 3.535262e+06\n", + "1 2 681302.799361 3.535268e+06\n", + "2 3 681375.294968 3.535270e+06\n", + "3 4 681450.837525 3.535271e+06\n", + "4 5 681526.983040 3.535281e+06" ] }, - "execution_count": 62, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "species_data.head()" + "plot_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Fix a wrong acronym naming" + "### Transforming to other coordinate reference system" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "When reviewing the metadata, you see that in the data-file the acronym `NE` is used to describe `Neotoma albigula`, whereas in the [metadata description](http://esapubs.org/archive/ecol/E090/118/Portal_rodent_metadata.htm), the acronym `NA` is used." + "These coordinates are in meters, more specifically in the [UTM 12 N](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system) coordinate system. However, the agreed coordinate representation for Darwin Core is the [World Geodetic System 1984 (WGS84)](http://spatialreference.org/ref/epsg/wgs-84/).\n", + "\n", + "As this is not a GIS course, we will shortcut the discussion about different projection systems, but provide an example on how such a conversion from `UTM12N` to `WGS84` can be performed with the projection toolkit `pyproj` and by relying on the existing EPSG codes (a registry originally setup by the association of oil & gas producers)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", - "\n", - "**EXERCISE**\n", - "\n", - "- Convert the value of 'NE' to 'NA' by using Boolean indexing/Filtering for the `species_id` column.\n", - "\n", - "
Hints\n", - "\n", - "- To assign a new value, use the `loc` operator.\n", - "- With `loc`, specify both the selecting for the rows and for the columns (`df.loc[row_indexer, column_indexer] = ..`).\n", - "\n", - "
\n", - "\n", - "
" + "First, we define out two projection systems, using their corresponding EPSG codes:" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "from pyproj import Transformer" ] }, { "cell_type": "code", "execution_count": 63, - "metadata": { - "clear_cell": true - }, + "metadata": {}, "outputs": [], "source": [ - "species_data.loc[species_data[\"species_id\"] == \"NE\", \"species_id\"] = \"NA\"" + "transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Merging surveys and species" + "The reprojection can be done by the function `transform` of the projection toolkit, providing the coordinate systems and a set of x, y coordinates. For example, for a single coordinate, this can be applied as follows:" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 64, "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(31.9388498837225, -109.08282902317859)" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "As we now prepared the two series, we can combine the data, using again the `pd.merge` operation." + "transformer.transform(681222.131658, 3.535262e+06)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We want to add the data of the species to the survey data, in order to see the full species names in the combined data table." + "Such a transformation is a function not supported by Pandas itself (it is in https://geopandas.org/). In such an situation, we want to _apply_ a custom function to _each row of the DataFrame_. Instead of writing a `for` loop to do this for each of the coordinates in the list, we can `.apply()` this function with Pandas." ] }, { @@ -3371,58 +3163,291 @@ "\n", "**EXERCISE**\n", "\n", - "Combine the `DataFrame` `survey_data_plots` and the `DataFrame` `species_data` by adding the corresponding species information (name, class, kingdom,..) to the individual observations. Assign the output to a new variable `survey_data_species`.\n", + "Apply the pyproj function `transform` to plot_data, using the columns `xutm` and `yutm` and save the resulting output in 2 new columns, called `decimalLongitude` and `decimalLatitude`:\n", + "\n", + "- Create a function `transform_utm_to_wgs` that takes a row of a `DataFrame` and returns a `Series` of two elements with the longitude and latitude.\n", + "- Test this function on the first row of `plot_data`\n", + "- Now `apply` this function on all rows (use the `axis` parameter correct)\n", + "- Assign the result of the previous step to `decimalLongitude` and `decimalLatitude` columns\n", "\n", "
Hints\n", "\n", - "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", - "- Take into account that our key-column is different for `species_data` and `survey_data_plots`, respectively `species` and `species_id`. The `pd.merge()` function has `left_on` and `right_on` keywords to specify the name of the column in the left and right `DataFrame` to merge on.\n", + "- Convert the output of the transformer to a Series before returning (`pd.Series(....)`)\n", + "- A convenient way to select a single row is using the `.loc[0]` operator.\n", + "- `apply` can be used for both rows (`axis` 1) as columns (`axis` 0).\n", + "- To assign two columns at once, you can use a similar syntax as for selecting multiple columns with a list of column names (`df[['col1', 'col2']]`).\n", "\n", - "
" + "\n", + "\n", + "
" ] }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 65, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "survey_data_species = pd.merge(survey_data_plots, species_data, how=\"left\", # LEFT OR INNER?\n", - " left_on=\"species\", right_on=\"species_id\")" + "def transform_utm_to_wgs(row):\n", + " \"\"\"Converts the x and y coordinates\n", + "\n", + " Parameters\n", + " ----------\n", + " row : pd.Series\n", + " Single DataFrame row\n", + "\n", + " Returns\n", + " -------\n", + " pd.Series with longitude and latitude\n", + " \"\"\"\n", + " transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")\n", + "\n", + " return pd.Series(transformer.transform(row['xutm'], row['yutm']))" ] }, { "cell_type": "code", - "execution_count": 65, - "metadata": {}, + "execution_count": 66, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0 31.938851\n", + "1 -109.082829\n", + "dtype: float64" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# test the new function on a single row of the DataFrame\n", + "transform_utm_to_wgs(plot_data.loc[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, "outputs": [ { "data": { + "text/html": [ + "
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" ], "text/plain": [ - " verbatimLocality species_x verbatimSex wgt \\\n", - "0 2 NaN M NaN \n", - "1 3 NaN M NaN \n", - "2 2 DM F NaN \n", - "3 7 DM M NaN \n", - "4 3 DM M NaN \n", - "\n", - " datasetName sex occurrenceID eventDate \\\n", - "0 Ecological Archives E090-118-D1. male 1 1977-07-16 \n", - "1 Ecological Archives E090-118-D1. male 2 1977-07-16 \n", - "2 Ecological Archives E090-118-D1. female 3 1977-07-16 \n", - "3 Ecological Archives E090-118-D1. male 4 1977-07-16 \n", - "4 Ecological Archives E090-118-D1. male 5 1977-07-16 \n", - "\n", - " decimalLongitude decimalLatitude species_id genus species_y taxa \n", - "0 31.938887 -109.081975 NaN NaN NaN NaN \n", - "1 31.938896 -109.081208 NaN NaN NaN NaN \n", - "2 31.938887 -109.081975 DM Dipodomys merriami Rodent \n", - "3 31.938113 -109.082816 DM Dipodomys merriami Rodent \n", - "4 31.938896 -109.081208 DM Dipodomys merriami Rodent " + " plot xutm yutm decimalLongitude decimalLatitude\n", + "0 1 681222.131658 3.535262e+06 31.938851 -109.082829\n", + "1 2 681302.799361 3.535268e+06 31.938887 -109.081975\n", + "2 3 681375.294968 3.535270e+06 31.938896 -109.081208\n", + "3 4 681450.837525 3.535271e+06 31.938894 -109.080409\n", + "4 5 681526.983040 3.535281e+06 31.938970 -109.079602" ] }, - "execution_count": 66, + "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "survey_data_species.head()" + "plot_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We do not need the columns `species_x` and `species_id` column anymore, as we will use the scientific names from now on:" + "The above function `transform_utm_to_wgs` you have created is a very specific function that knows the structure of the `DataFrame` you will apply it to (it assumes the 'xutm' and 'yutm' column names). We could also make a more generic function that just takes a X and Y coordinate and returns the `Series` of converted coordinates (`transform_utm_to_wgs2(X, Y)`).\n", + "\n", + "An alternative to apply such a custom function to the `plot_data` `DataFrame` is the usage of the `lambda` construct, which lets you specify a function on one line as an argument:\n", + "\n", + " transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")\n", + " plot_data.apply(lambda row : transformer.transform(row['xutm'], row['yutm']), axis=1)\n", + "\n", + "\n", + "
\n", + "\n", + "__WARNING__\n", + "\n", + "Do not abuse the usage of the `apply` method, but always look for an existing Pandas function first as these are - in general - faster!\n", + "\n", + "
" ] }, { - "cell_type": "code", - "execution_count": 67, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Join the coordinate information to the survey data set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can extend our survey data set with this coordinate information. Making the combination of two data sets based on a common identifier is completely similar to the usage of `JOIN` operations in databases. In Pandas, this functionality is provided by [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/merging.html#database-style-DataFrame-joining-merging).\n", + "\n", + "In practice, we have to add the columns `decimalLongitude`/`decimalLatitude` to the current data set `survey_data_decoupled`, by using the plot identification number as key to join." + ] + }, + { + "cell_type": "markdown", "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "- Extract only the columns to join to our survey dataset: the `plot` identifiers, `decimalLatitude` and `decimalLongitude` into a new variable named `plot_data_selection`\n", + "\n", + "
Hints\n", + "\n", + "- To select multiple columns, use a `list` of column names, e.g. `df[[\"my_col1\", \"my_col2\"]]`\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, "outputs": [], "source": [ - "survey_data_species = survey_data_species.drop([\"species_x\", \"species_id\"], axis=1)" + "plot_data_selection = plot_data[[\"plot\", \"decimalLongitude\", \"decimalLatitude\"]]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The column `species_y` could just be named `species`:" + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Combine the `DataFrame` `plot_data_selection` and the `DataFrame` `survey_data_decoupled` by adding the corresponding coordinate information to the individual observations using the `pd.merge()` function. Assign the output to a new variable `survey_data_plots`.\n", + "\n", + "
Hints\n", + "\n", + "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", + "- The key-column is the `plot`.\n", + "\n", + "
" ] }, { "cell_type": "code", - "execution_count": 68, - "metadata": {}, + "execution_count": 72, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, "outputs": [], "source": [ - "survey_data_species = survey_data_species.rename(columns={\"species_y\": \"species\"})" + "survey_data_plots = pd.merge(survey_data_species, plot_data_selection,\n", + " how=\"left\", on=\"plot\")" ] }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 73, "metadata": {}, "outputs": [ { @@ -3642,18 +3668,18 @@ " \n", " \n", " \n", - " verbatimLocality\n", + " plot\n", " verbatimSex\n", " wgt\n", " datasetName\n", " sex\n", " occurrenceID\n", " eventDate\n", - " decimalLongitude\n", - " decimalLatitude\n", " genus\n", " species\n", " taxa\n", + " decimalLongitude\n", + " decimalLatitude\n", " \n", " \n", " \n", @@ -3666,11 +3692,11 @@ " male\n", " 1\n", " 1977-07-16\n", - " 31.938887\n", - " -109.081975\n", " NaN\n", " NaN\n", " NaN\n", + " 31.938887\n", + " -109.081975\n", " \n", " \n", " 1\n", @@ -3681,11 +3707,11 @@ " male\n", " 2\n", " 1977-07-16\n", - " 31.938896\n", - " -109.081208\n", " NaN\n", " NaN\n", " NaN\n", + " 31.938896\n", + " -109.081208\n", " \n", " \n", " 2\n", @@ -3696,11 +3722,11 @@ " female\n", " 3\n", " 1977-07-16\n", - " 31.938887\n", - " -109.081975\n", " Dipodomys\n", " merriami\n", " Rodent\n", + " 31.938887\n", + " -109.081975\n", " \n", " \n", " 3\n", @@ -3711,11 +3737,11 @@ " male\n", " 4\n", " 1977-07-16\n", - " 31.938113\n", - " -109.082816\n", " Dipodomys\n", " merriami\n", " Rodent\n", + " 31.938113\n", + " -109.082816\n", " \n", " \n", " 4\n", @@ -3726,66 +3752,62 @@ " male\n", " 5\n", " 1977-07-16\n", - " 31.938896\n", - " -109.081208\n", " Dipodomys\n", " merriami\n", " Rodent\n", + " 31.938896\n", + " -109.081208\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " verbatimLocality verbatimSex wgt datasetName \\\n", - "0 2 M NaN Ecological Archives E090-118-D1. \n", - "1 3 M NaN Ecological Archives E090-118-D1. \n", - "2 2 F NaN Ecological Archives E090-118-D1. \n", - "3 7 M NaN Ecological Archives E090-118-D1. \n", - "4 3 M NaN Ecological Archives E090-118-D1. \n", + " plot verbatimSex wgt datasetName sex \\\n", + "0 2 M NaN Ecological Archives E090-118-D1. male \n", + "1 3 M NaN Ecological Archives E090-118-D1. male \n", + "2 2 F NaN Ecological Archives E090-118-D1. female \n", + "3 7 M NaN Ecological Archives E090-118-D1. male \n", + "4 3 M NaN Ecological Archives E090-118-D1. male \n", "\n", - " sex occurrenceID eventDate decimalLongitude decimalLatitude \\\n", - "0 male 1 1977-07-16 31.938887 -109.081975 \n", - "1 male 2 1977-07-16 31.938896 -109.081208 \n", - "2 female 3 1977-07-16 31.938887 -109.081975 \n", - "3 male 4 1977-07-16 31.938113 -109.082816 \n", - "4 male 5 1977-07-16 31.938896 -109.081208 \n", + " occurrenceID eventDate genus species taxa decimalLongitude \\\n", + "0 1 1977-07-16 NaN NaN NaN 31.938887 \n", + "1 2 1977-07-16 NaN NaN NaN 31.938896 \n", + "2 3 1977-07-16 Dipodomys merriami Rodent 31.938887 \n", + "3 4 1977-07-16 Dipodomys merriami Rodent 31.938113 \n", + "4 5 1977-07-16 Dipodomys merriami Rodent 31.938896 \n", "\n", - " genus species taxa \n", - "0 NaN NaN NaN \n", - "1 NaN NaN NaN \n", - "2 Dipodomys merriami Rodent \n", - "3 Dipodomys merriami Rodent \n", - "4 Dipodomys merriami Rodent " + " decimalLatitude \n", + "0 -109.081975 \n", + "1 -109.081208 \n", + "2 -109.081975 \n", + "3 -109.082816 \n", + "4 -109.081208 " ] }, - "execution_count": 69, + "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "survey_data_species.head()" + "survey_data_plots.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The plot locations need to be stored with the variable name `verbatimLocality` indicating the identifier as integer value of the plot:" ] }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 74, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "35550" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "len(survey_data_species)" + "survey_data_plots = survey_data_plots.rename(columns={'plot': 'verbatimLocality'})" ] }, { @@ -3797,11 +3819,11 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 76, "metadata": {}, "outputs": [], "source": [ - "survey_data_species.to_csv(\"interim_survey_data_species.csv\", index=False)" + "survey_data_plots.to_csv(\"interim_survey_data_species.csv\", index=False)" ] }, { @@ -3827,7 +3849,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 78, "metadata": {}, "outputs": [], "source": [ @@ -3850,7 +3872,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 79, "metadata": {}, "outputs": [], "source": [ @@ -3859,7 +3881,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 80, "metadata": {}, "outputs": [ { @@ -3889,7 +3911,7 @@ " 'class': 'Aves'}" ] }, - "execution_count": 74, + "execution_count": 80, "metadata": {}, "output_type": "execute_result" } @@ -3917,7 +3939,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 81, "metadata": {}, "outputs": [ { @@ -3947,7 +3969,7 @@ " 'class': 'Aves'}" ] }, - "execution_count": 75, + "execution_count": 81, "metadata": {}, "output_type": "execute_result" } @@ -3991,9 +4013,11 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 82, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -4045,7 +4069,7 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 83, "metadata": {}, "outputs": [ { @@ -4075,7 +4099,7 @@ " 'class': 'Aves'}" ] }, - "execution_count": 77, + "execution_count": 83, "metadata": {}, "output_type": "execute_result" } @@ -4095,7 +4119,7 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 84, "metadata": {}, "outputs": [ { @@ -4104,7 +4128,7 @@ "{'confidence': 100, 'matchType': 'NONE', 'synonym': False}" ] }, - "execution_count": 78, + "execution_count": 84, "metadata": {}, "output_type": "execute_result" } @@ -4150,19 +4174,21 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 86, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ "#%%timeit\n", - "unique_species = survey_data_species[[\"genus\", \"species\"]].drop_duplicates().dropna()" + "unique_species = survey_data_plots[[\"genus\", \"species\"]].drop_duplicates().dropna()" ] }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 87, "metadata": {}, "outputs": [ { @@ -4171,7 +4197,7 @@ "47" ] }, - "execution_count": 80, + "execution_count": 87, "metadata": {}, "output_type": "execute_result" } @@ -4202,20 +4228,22 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 88, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ "#%%timeit\n", "unique_species = \\\n", - " survey_data_species.groupby([\"genus\", \"species\"]).first().reset_index()[[\"genus\", \"species\"]]" + " survey_data_plots.groupby([\"genus\", \"species\"]).first().reset_index()[[\"genus\", \"species\"]]" ] }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 89, "metadata": {}, "outputs": [ { @@ -4224,7 +4252,7 @@ "47" ] }, - "execution_count": 82, + "execution_count": 89, "metadata": {}, "output_type": "execute_result" } @@ -4248,9 +4276,11 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 90, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -4261,7 +4291,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 91, "metadata": {}, "outputs": [ { @@ -4334,7 +4364,7 @@ "4 Calamospiza melanocorys Calamospiza melanocorys" ] }, - "execution_count": 84, + "execution_count": 91, "metadata": {}, "output_type": "execute_result" } @@ -4360,7 +4390,7 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 92, "metadata": {}, "outputs": [], "source": [ @@ -4372,7 +4402,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 93, "metadata": {}, "outputs": [], "source": [ @@ -4408,9 +4438,11 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 94, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -4419,7 +4451,7 @@ }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 95, "metadata": {}, "outputs": [ { @@ -4624,7 +4656,7 @@ "[5 rows x 24 columns]" ] }, - "execution_count": 88, + "execution_count": 95, "metadata": {}, "output_type": "execute_result" } @@ -4655,9 +4687,11 @@ }, { "cell_type": "code", - "execution_count": 89, + "execution_count": 96, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -4667,7 +4701,7 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 97, "metadata": {}, "outputs": [ { @@ -4771,7 +4805,7 @@ "4 Calamospiza melanocorys Stejneger, 1885 ACCEPTED 2491893 " ] }, - "execution_count": 90, + "execution_count": 97, "metadata": {}, "output_type": "execute_result" } @@ -4794,9 +4828,11 @@ }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 98, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -4806,9 +4842,140 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 99, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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genusspeciesnameclasskingdomorderphylumscientificNamestatususageKey
0AmmodramussavannarumAmmodramus savannarumAvesAnimaliaPasseriformesChordataAmmodramus savannarum (J.F.Gmelin, 1789)ACCEPTED2491123
1AmmospermophilusharrisiAmmospermophilus harrisiMammaliaAnimaliaRodentiaChordataAmmospermophilus harrisii (Audubon & Bachman, ...ACCEPTED2437568
2AmphispizabilineataAmphispiza bilineataAvesAnimaliaPasseriformesChordataAmphispiza bilineata (Cassin, 1850)ACCEPTED2491757
3BaiomystayloriBaiomys tayloriMammaliaAnimaliaRodentiaChordataBaiomys taylori (Thomas, 1887)ACCEPTED2438866
4CalamospizamelanocorysCalamospiza melanocorysAvesAnimaliaPasseriformesChordataCalamospiza melanocorys Stejneger, 1885ACCEPTED2491893
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" + ], + "text/plain": [ + " genus species name class \\\n", + "0 Ammodramus savannarum Ammodramus savannarum Aves \n", + "1 Ammospermophilus harrisi Ammospermophilus harrisi Mammalia \n", + "2 Amphispiza bilineata Amphispiza bilineata Aves \n", + "3 Baiomys taylori Baiomys taylori Mammalia \n", + "4 Calamospiza melanocorys Calamospiza melanocorys Aves \n", + "\n", + " kingdom order phylum \\\n", + "0 Animalia Passeriformes Chordata \n", + "1 Animalia Rodentia Chordata \n", + "2 Animalia Passeriformes Chordata \n", + "3 Animalia Rodentia Chordata \n", + "4 Animalia Passeriformes Chordata \n", + "\n", + " scientificName status usageKey \n", + "0 Ammodramus savannarum (J.F.Gmelin, 1789) ACCEPTED 2491123 \n", + "1 Ammospermophilus harrisii (Audubon & Bachman, ... ACCEPTED 2437568 \n", + "2 Amphispiza bilineata (Cassin, 1850) ACCEPTED 2491757 \n", + "3 Baiomys taylori (Thomas, 1887) ACCEPTED 2438866 \n", + "4 Calamospiza melanocorys Stejneger, 1885 ACCEPTED 2491893 " + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "unique_species_annotated.head()" ] @@ -4828,19 +4995,21 @@ }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 103, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "survey_data_completed = pd.merge(survey_data_species, unique_species_annotated,\n", + "survey_data_completed = pd.merge(survey_data_plots, unique_species_annotated,\n", " how='left', on= [\"genus\", \"species\"])" ] }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 104, "metadata": {}, "outputs": [ { @@ -4849,7 +5018,7 @@ "35550" ] }, - "execution_count": 93, + "execution_count": 104, "metadata": {}, "output_type": "execute_result" } @@ -4860,7 +5029,7 @@ }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 105, "metadata": {}, "outputs": [ { @@ -4891,11 +5060,11 @@ " sex\n", " occurrenceID\n", " eventDate\n", - " decimalLongitude\n", - " decimalLatitude\n", " genus\n", " species\n", " taxa\n", + " decimalLongitude\n", + " decimalLatitude\n", " name\n", " class\n", " kingdom\n", @@ -4916,11 +5085,11 @@ " male\n", " 1\n", " 1977-07-16\n", - " 31.938887\n", - " -109.081975\n", " NaN\n", " NaN\n", " NaN\n", + " 31.938887\n", + " -109.081975\n", " NaN\n", " NaN\n", " NaN\n", @@ -4939,11 +5108,11 @@ " male\n", " 2\n", " 1977-07-16\n", - " 31.938896\n", - " -109.081208\n", " NaN\n", " NaN\n", " NaN\n", + " 31.938896\n", + " -109.081208\n", " NaN\n", " NaN\n", " NaN\n", @@ -4962,11 +5131,11 @@ " female\n", " 3\n", " 1977-07-16\n", - " 31.938887\n", - " -109.081975\n", " Dipodomys\n", " merriami\n", " Rodent\n", + " 31.938887\n", + " -109.081975\n", " Dipodomys merriami\n", " Mammalia\n", " Animalia\n", @@ -4985,11 +5154,11 @@ " male\n", " 4\n", " 1977-07-16\n", - " 31.938113\n", - " -109.082816\n", " Dipodomys\n", " merriami\n", " Rodent\n", + " 31.938113\n", + " -109.082816\n", " Dipodomys merriami\n", " Mammalia\n", " Animalia\n", @@ -5008,11 +5177,11 @@ " male\n", " 5\n", " 1977-07-16\n", - " 31.938896\n", - " -109.081208\n", " Dipodomys\n", " merriami\n", " Rodent\n", + " 31.938896\n", + " -109.081208\n", " Dipodomys merriami\n", " Mammalia\n", " Animalia\n", @@ -5034,19 +5203,19 @@ "3 7 M NaN Ecological Archives E090-118-D1. \n", "4 3 M NaN Ecological Archives E090-118-D1. \n", "\n", - " sex occurrenceID eventDate decimalLongitude decimalLatitude \\\n", - "0 male 1 1977-07-16 31.938887 -109.081975 \n", - "1 male 2 1977-07-16 31.938896 -109.081208 \n", - "2 female 3 1977-07-16 31.938887 -109.081975 \n", - "3 male 4 1977-07-16 31.938113 -109.082816 \n", - "4 male 5 1977-07-16 31.938896 -109.081208 \n", + " sex occurrenceID eventDate genus species taxa \\\n", + "0 male 1 1977-07-16 NaN NaN NaN \n", + "1 male 2 1977-07-16 NaN NaN NaN \n", + "2 female 3 1977-07-16 Dipodomys merriami Rodent \n", + "3 male 4 1977-07-16 Dipodomys merriami Rodent \n", + "4 male 5 1977-07-16 Dipodomys merriami Rodent \n", "\n", - " genus species taxa name class kingdom \\\n", - "0 NaN NaN NaN NaN NaN NaN \n", - "1 NaN NaN NaN NaN NaN NaN \n", - "2 Dipodomys merriami Rodent Dipodomys merriami Mammalia Animalia \n", - "3 Dipodomys merriami Rodent Dipodomys merriami Mammalia Animalia \n", - "4 Dipodomys merriami Rodent Dipodomys merriami Mammalia Animalia \n", + " decimalLongitude decimalLatitude name class kingdom \\\n", + "0 31.938887 -109.081975 NaN NaN NaN \n", + "1 31.938896 -109.081208 NaN NaN NaN \n", + "2 31.938887 -109.081975 Dipodomys merriami Mammalia Animalia \n", + "3 31.938113 -109.082816 Dipodomys merriami Mammalia Animalia \n", + "4 31.938896 -109.081208 Dipodomys merriami Mammalia Animalia \n", "\n", " order phylum scientificName status usageKey \n", "0 NaN NaN NaN NaN NaN \n", @@ -5056,7 +5225,7 @@ "4 Rodentia Chordata Dipodomys merriami Mearns, 1890 ACCEPTED 2439521 " ] }, - "execution_count": 94, + "execution_count": 105, "metadata": {}, "output_type": "execute_result" } @@ -5078,7 +5247,7 @@ "metadata": {}, "outputs": [], "source": [ - "survey_data_completed.to_csv(\"survey_data_completed.csv\", index=False)" + "survey_data_completed.to_csv(\"survey_data_completed_.csv\", index=False)" ] }, { @@ -5101,6 +5270,9 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/_solved/case3_bacterial_resistance_lab_experiment.ipynb b/_solved/case3_bacterial_resistance_lab_experiment.ipynb index ec833c9..e96c709 100644 --- a/_solved/case3_bacterial_resistance_lab_experiment.ipynb +++ b/_solved/case3_bacterial_resistance_lab_experiment.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Bacterial resistance experiment

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -40,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -56,6 +53,13 @@ "## Reading and processing the data" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The data for this use case contains the evolution of different bacteria populations when combined with different phage treatments (viruses). The evolution of the bacterial population is measured by using the __optical density__ (OD) at 3 moments during the experiment: at the start (0h), after 20h and at the end (72h)." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -97,211 +101,15 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, - "outputs": [ - { - "data": { - "text/html": [ - "
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4RifD516GC_noPhage0.09780.67520.67001NaN
...........................
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954 rows × 8 columns

\n", - "
" - ], - "text/plain": [ - " AB_r Bacterial_genotype Phage_t OD_0h OD_20h OD_72h \\\n", - "0 Rif D516G C_noPhage 0.1971 0.5960 0.6900 \n", - "1 Rif D516G C_noPhage 0.1593 0.5702 0.6989 \n", - "2 Rif D516G C_noPhage 0.0926 0.6613 0.6474 \n", - "3 Rif D516G C_noPhage 0.1482 0.6465 0.7045 \n", - "4 Rif D516G C_noPhage 0.0978 0.6752 0.6700 \n", - ".. ... ... ... ... ... ... \n", - "949 sensitive MUT T7 0.0417 0.0402 0.3179 \n", - "950 sensitive MUT T7 0.0789 0.0276 0.3601 \n", - "951 sensitive MUT T7 0.0875 0.0216 0.3709 \n", - "952 sensitive MUT T7 0.0755 0.0418 0.3628 \n", - "953 sensitive MUT T7 0.0401 0.0345 0.3321 \n", - "\n", - " Survival_72h PhageR_72h \n", - "0 1 NaN \n", - "1 1 NaN \n", - "2 1 NaN \n", - "3 1 NaN \n", - "4 1 NaN \n", - ".. ... ... \n", - "949 1 1.0 \n", - "950 1 1.0 \n", - "951 1 1.0 \n", - "952 1 1.0 \n", - "953 1 1.0 \n", - "\n", - "[954 rows x 8 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "main_experiment = pd.read_excel(\"data/Dryad_Arias_Hall_v3.xlsx\",\n", " sheet_name=\"Main experiment\")\n", - "main_experiment" + "main_experiment = main_experiment.drop(columns=[\"AB_r\", \"Survival_72h\", \"PhageR_72h\"]) # focus on specific subset for this use case)" ] }, { @@ -313,12 +121,9 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -403,7 +208,7 @@ "4 T7 D516G -6.920474 -6.722230 -7.199283" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -445,12 +250,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -474,76 +276,58 @@ " \n", " \n", " \n", - " AB_r\n", " Bacterial_genotype\n", " Phage_t\n", " OD_0h\n", " OD_20h\n", " OD_72h\n", - " Survival_72h\n", - " PhageR_72h\n", " experiment_ID\n", " \n", " \n", " \n", " \n", " 0\n", - " Rif\n", " D516G\n", " C_noPhage\n", " 0.1971\n", " 0.5960\n", " 0.6900\n", - " 1\n", - " NaN\n", " ID_0\n", " \n", " \n", " 1\n", - " Rif\n", " D516G\n", " C_noPhage\n", " 0.1593\n", " 0.5702\n", " 0.6989\n", - " 1\n", - " NaN\n", " ID_1\n", " \n", " \n", " 2\n", - " Rif\n", " D516G\n", " C_noPhage\n", " 0.0926\n", " 0.6613\n", " 0.6474\n", - " 1\n", - " NaN\n", " ID_2\n", " \n", " \n", " 3\n", - " Rif\n", " D516G\n", " C_noPhage\n", " 0.1482\n", " 0.6465\n", " 0.7045\n", - " 1\n", - " NaN\n", " ID_3\n", " \n", " \n", " 4\n", - " Rif\n", " D516G\n", " C_noPhage\n", " 0.0978\n", " 0.6752\n", " 0.6700\n", - " 1\n", - " NaN\n", " ID_4\n", " \n", " \n", @@ -554,106 +338,75 @@ " ...\n", " ...\n", " ...\n", - " ...\n", - " ...\n", - " ...\n", " \n", " \n", " 949\n", - " sensitive\n", " MUT\n", " T7\n", " 0.0417\n", " 0.0402\n", " 0.3179\n", - " 1\n", - " 1.0\n", " ID_949\n", " \n", " \n", " 950\n", - " sensitive\n", " MUT\n", " T7\n", " 0.0789\n", " 0.0276\n", " 0.3601\n", - " 1\n", - " 1.0\n", " ID_950\n", " \n", " \n", " 951\n", - " sensitive\n", " MUT\n", " T7\n", " 0.0875\n", " 0.0216\n", " 0.3709\n", - " 1\n", - " 1.0\n", " ID_951\n", " \n", " \n", " 952\n", - " sensitive\n", " MUT\n", " T7\n", " 0.0755\n", " 0.0418\n", " 0.3628\n", - " 1\n", - " 1.0\n", " ID_952\n", " \n", " \n", " 953\n", - " sensitive\n", " MUT\n", " T7\n", " 0.0401\n", " 0.0345\n", " 0.3321\n", - " 1\n", - " 1.0\n", " ID_953\n", " \n", " \n", "\n", - "

954 rows × 9 columns

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954 rows × 6 columns

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" ], "text/plain": [ - " AB_r Bacterial_genotype Phage_t OD_0h OD_20h OD_72h \\\n", - "0 Rif D516G C_noPhage 0.1971 0.5960 0.6900 \n", - "1 Rif D516G C_noPhage 0.1593 0.5702 0.6989 \n", - "2 Rif D516G C_noPhage 0.0926 0.6613 0.6474 \n", - "3 Rif D516G C_noPhage 0.1482 0.6465 0.7045 \n", - "4 Rif D516G C_noPhage 0.0978 0.6752 0.6700 \n", - ".. ... ... ... ... ... ... \n", - "949 sensitive MUT T7 0.0417 0.0402 0.3179 \n", - "950 sensitive MUT T7 0.0789 0.0276 0.3601 \n", - "951 sensitive MUT T7 0.0875 0.0216 0.3709 \n", - "952 sensitive MUT T7 0.0755 0.0418 0.3628 \n", - "953 sensitive MUT T7 0.0401 0.0345 0.3321 \n", + " Bacterial_genotype Phage_t OD_0h OD_20h OD_72h experiment_ID\n", + "0 D516G C_noPhage 0.1971 0.5960 0.6900 ID_0\n", + "1 D516G C_noPhage 0.1593 0.5702 0.6989 ID_1\n", + "2 D516G C_noPhage 0.0926 0.6613 0.6474 ID_2\n", + "3 D516G C_noPhage 0.1482 0.6465 0.7045 ID_3\n", + "4 D516G C_noPhage 0.0978 0.6752 0.6700 ID_4\n", + ".. ... ... ... ... ... ...\n", + "949 MUT T7 0.0417 0.0402 0.3179 ID_949\n", + "950 MUT T7 0.0789 0.0276 0.3601 ID_950\n", + "951 MUT T7 0.0875 0.0216 0.3709 ID_951\n", + "952 MUT T7 0.0755 0.0418 0.3628 ID_952\n", + "953 MUT T7 0.0401 0.0345 0.3321 ID_953\n", "\n", - " Survival_72h PhageR_72h experiment_ID \n", - "0 1 NaN ID_0 \n", - "1 1 NaN ID_1 \n", - "2 1 NaN ID_2 \n", - "3 1 NaN ID_3 \n", - "4 1 NaN ID_4 \n", - ".. ... ... ... \n", - "949 1 1.0 ID_949 \n", - "950 1 1.0 ID_950 \n", - "951 1 1.0 ID_951 \n", - "952 1 1.0 ID_952 \n", - "953 1 1.0 ID_953 \n", - "\n", - "[954 rows x 9 columns]" + "[954 rows x 6 columns]" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -669,9 +422,9 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "**EXERCISE**:\n", "\n", - "Convert the columns `OD_0h`, `OD_20h` and `OD_72h` to a long format with the values stored in a column `optical_density` and the time in the experiment as `experiment_time_h`. Save the variable as tidy_experiment\n", + "Convert the columns `OD_0h`, `OD_20h` and `OD_72h` to a long format with the values stored in a column `optical_density` and the time in the experiment as `experiment_time_h`. Save the variable as `tidy_experiment`.\n", "\n", "
Hints\n", "\n", @@ -685,13 +438,12 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -715,11 +467,8 @@ " \n", " \n", " \n", - " AB_r\n", " Bacterial_genotype\n", " Phage_t\n", - " Survival_72h\n", - " PhageR_72h\n", " experiment_ID\n", " experiment_time_h\n", " optical_density\n", @@ -728,55 +477,40 @@ " \n", " \n", " 0\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_0\n", " OD_0h\n", " 0.1971\n", " \n", " \n", " 1\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_1\n", " OD_0h\n", " 0.1593\n", " \n", " \n", " 2\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_2\n", " OD_0h\n", " 0.0926\n", " \n", " \n", " 3\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_3\n", " OD_0h\n", " 0.1482\n", " \n", " \n", " 4\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_4\n", " OD_0h\n", " 0.0978\n", @@ -788,108 +522,89 @@ " ...\n", " ...\n", " ...\n", - " ...\n", - " ...\n", - " ...\n", " \n", " \n", " 2857\n", - " sensitive\n", " MUT\n", " T7\n", - " 1\n", - " 1.0\n", " ID_949\n", " OD_72h\n", " 0.3179\n", " \n", " \n", " 2858\n", - " sensitive\n", " MUT\n", " T7\n", - " 1\n", - " 1.0\n", " ID_950\n", " OD_72h\n", " 0.3601\n", " \n", " \n", " 2859\n", - " sensitive\n", " MUT\n", " T7\n", - " 1\n", - " 1.0\n", " ID_951\n", " OD_72h\n", " 0.3709\n", " \n", " \n", " 2860\n", - " sensitive\n", " MUT\n", " T7\n", - " 1\n", - " 1.0\n", " ID_952\n", " OD_72h\n", " 0.3628\n", " \n", " \n", " 2861\n", - " sensitive\n", " MUT\n", " T7\n", - " 1\n", - " 1.0\n", " ID_953\n", " OD_72h\n", " 0.3321\n", " \n", " \n", "\n", - "

2862 rows × 8 columns

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2862 rows × 5 columns

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" ], "text/plain": [ - " AB_r Bacterial_genotype Phage_t Survival_72h PhageR_72h \\\n", - "0 Rif D516G C_noPhage 1 NaN \n", - "1 Rif D516G C_noPhage 1 NaN \n", - "2 Rif D516G C_noPhage 1 NaN \n", - "3 Rif D516G C_noPhage 1 NaN \n", - "4 Rif D516G C_noPhage 1 NaN \n", - "... ... ... ... ... ... \n", - "2857 sensitive MUT T7 1 1.0 \n", - "2858 sensitive MUT T7 1 1.0 \n", - "2859 sensitive MUT T7 1 1.0 \n", - "2860 sensitive MUT T7 1 1.0 \n", - "2861 sensitive MUT T7 1 1.0 \n", + " Bacterial_genotype Phage_t experiment_ID experiment_time_h \\\n", + "0 D516G C_noPhage ID_0 OD_0h \n", + "1 D516G C_noPhage ID_1 OD_0h \n", + "2 D516G C_noPhage ID_2 OD_0h \n", + "3 D516G C_noPhage ID_3 OD_0h \n", + "4 D516G C_noPhage ID_4 OD_0h \n", + "... ... ... ... ... \n", + "2857 MUT T7 ID_949 OD_72h \n", + "2858 MUT T7 ID_950 OD_72h \n", + "2859 MUT T7 ID_951 OD_72h \n", + "2860 MUT T7 ID_952 OD_72h \n", + "2861 MUT T7 ID_953 OD_72h \n", "\n", - " experiment_ID experiment_time_h optical_density \n", - "0 ID_0 OD_0h 0.1971 \n", - "1 ID_1 OD_0h 0.1593 \n", - "2 ID_2 OD_0h 0.0926 \n", - "3 ID_3 OD_0h 0.1482 \n", - "4 ID_4 OD_0h 0.0978 \n", - "... ... ... ... \n", - "2857 ID_949 OD_72h 0.3179 \n", - "2858 ID_950 OD_72h 0.3601 \n", - "2859 ID_951 OD_72h 0.3709 \n", - "2860 ID_952 OD_72h 0.3628 \n", - "2861 ID_953 OD_72h 0.3321 \n", + " optical_density \n", + "0 0.1971 \n", + "1 0.1593 \n", + "2 0.0926 \n", + "3 0.1482 \n", + "4 0.0978 \n", + "... ... \n", + "2857 0.3179 \n", + "2858 0.3601 \n", + "2859 0.3709 \n", + "2860 0.3628 \n", + "2861 0.3321 \n", "\n", - "[2862 rows x 8 columns]" + "[2862 rows x 5 columns]" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "tidy_experiment = main_experiment.melt(id_vars=['AB_r', 'Bacterial_genotype', 'Phage_t',\n", - " 'Survival_72h', 'PhageR_72h', 'experiment_ID'],\n", + "tidy_experiment = main_experiment.melt(id_vars=['Bacterial_genotype', 'Phage_t', 'experiment_ID'],\n", " value_vars=['OD_0h', 'OD_20h', 'OD_72h'],\n", " var_name='experiment_time_h',\n", " value_name='optical_density', )\n", @@ -905,12 +620,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -934,11 +646,8 @@ " \n", " \n", " \n", - " AB_r\n", " Bacterial_genotype\n", " Phage_t\n", - " Survival_72h\n", - " PhageR_72h\n", " experiment_ID\n", " experiment_time_h\n", " optical_density\n", @@ -947,55 +656,40 @@ " \n", " \n", " 0\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_0\n", " OD_0h\n", " 0.1971\n", " \n", " \n", " 1\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_1\n", " OD_0h\n", " 0.1593\n", " \n", " \n", " 2\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_2\n", " OD_0h\n", " 0.0926\n", " \n", " \n", " 3\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_3\n", " OD_0h\n", " 0.1482\n", " \n", " \n", " 4\n", - " Rif\n", " D516G\n", " C_noPhage\n", - " 1\n", - " NaN\n", " ID_4\n", " OD_0h\n", " 0.0978\n", @@ -1005,22 +699,22 @@ "
" ], "text/plain": [ - " AB_r Bacterial_genotype Phage_t Survival_72h PhageR_72h experiment_ID \\\n", - "0 Rif D516G C_noPhage 1 NaN ID_0 \n", - "1 Rif D516G C_noPhage 1 NaN ID_1 \n", - "2 Rif D516G C_noPhage 1 NaN ID_2 \n", - "3 Rif D516G C_noPhage 1 NaN ID_3 \n", - "4 Rif D516G C_noPhage 1 NaN ID_4 \n", + " Bacterial_genotype Phage_t experiment_ID experiment_time_h \\\n", + "0 D516G C_noPhage ID_0 OD_0h \n", + "1 D516G C_noPhage ID_1 OD_0h \n", + "2 D516G C_noPhage ID_2 OD_0h \n", + "3 D516G C_noPhage ID_3 OD_0h \n", + "4 D516G C_noPhage ID_4 OD_0h \n", "\n", - " experiment_time_h optical_density \n", - "0 OD_0h 0.1971 \n", - "1 OD_0h 0.1593 \n", - "2 OD_0h 0.0926 \n", - "3 OD_0h 0.1482 \n", - "4 OD_0h 0.0978 " + " optical_density \n", + "0 0.1971 \n", + "1 0.1593 \n", + "2 0.0926 \n", + "3 0.1482 \n", + "4 0.0978 " ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1035,11 +729,16 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "**EXERCISE**:\n", "\n", "* Make a histogram using the [Seaborn package](https://seaborn.pydata.org/index.html) to visualize the distribution of the `optical_density`\n", "* Change the overall theme to any of the available Seaborn themes\n", "* Change the border color of the bars to `white` and the fill color of the bars to `grey`\n", + " \n", + "Using Matplotlib, further adjust the histogram:\n", + " \n", + "- Add a Figure title \"Optical density distribution\".\n", + "- Overwrite the y-axis label to \"Frequency\".\n", "\n", "
Hints\n", "\n", @@ -1047,37 +746,26 @@ "- There are five preset seaborn themes: `darkgrid`, `whitegrid`, `dark`, `white`, and `ticks`.\n", "- Make sure to set the theme before creating the graph.\n", "- Seaborn relies on Matplotlib to plot the individual bars, so the available parameters (`**kwargs`) to adjust the bars that can be passed (e.g. `color` and `edgecolor`) are enlisted in the [matplotlib.axes.Axes.bar](https://matplotlib.org/3.3.2/api/_as_gen/matplotlib.axes.Axes.bar.html) documentation.\n", + "- The output of a Seaborn plot is an object from which the Matplotlib `Figure` and `Axes` can be accessed, respectively `snsplot.fig` and `snsplot.axes`. Note that the `axes` are always returned as a 2x2 array of Axes (also if it only contains a single element).\n", "\n", "
\n", "\n", - "\n", "
" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 14, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1088,8 +776,11 @@ ], "source": [ "sns.set_style(\"white\")\n", - "sns.displot(tidy_experiment, x=\"optical_density\",\n", - " color='grey', edgecolor='white')" + "histplot = sns.displot(data=tidy_experiment, x=\"optical_density\",\n", + " color='grey', edgecolor='white')\n", + "\n", + "histplot.fig.suptitle(\"Optical density distribution\")\n", + "histplot.axes[0][0].set_ylabel(\"Frequency\");" ] }, { @@ -1112,28 +803,27 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 33, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -1167,28 +857,27 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 34, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1221,13 +910,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 35, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1342,7 +1030,7 @@ "WT 0.086394 0.326306 0.431576" ] }, - "execution_count": 10, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -1363,13 +1051,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 36, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1484,7 +1171,7 @@ "WT 0.086394 0.326306 0.431576" ] }, - "execution_count": 11, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -1503,7 +1190,7 @@ "**EXERCISE**\n", "\n", "- Calculate for each combination of `Bacterial_genotype`, `Phage_t` and `experiment_time_h` the mean `optical_density` and store the result as a DataFrame called `density_mean` (tip: use `reset_index()` to convert the resulting Series to a DataFrame).\n", - "- Based on `density_mean`, make a _barplot_ of the (mean) values for each `Bacterial_genotype`, with for each `Bacterial_genotype` an individual bar and with each `Phage_t` in a different color/hue (i.e. grouped bar chart).\n", + "- Based on `density_mean`, make a _barplot_ of the mean optical density for each `Bacterial_genotype`, with for each `Bacterial_genotype` an individual bar and with each `Phage_t` in a different color/hue (i.e. grouped bar chart).\n", "- Use the `experiment_time_h` to split into subplots. As we mainly want to compare the values within each subplot, make sure the scales in each of the subplots are adapted to its own data range, and put the subplots on different rows.\n", "- Adjust the size and aspect ratio of the Figure to your own preference.\n", "- Change the color scale of the bars to another Seaborn palette.\n", @@ -1521,9 +1208,11 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 37, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1534,30 +1223,29 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 38, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 13, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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PhageBacterial_genotypelog10 Mclog10 UBclog10 LBc
0T7RP4-6.908090-6.766699-7.086027
1T7RSF1010-6.839080-6.709209-6.999176
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4T7D516G-6.920474-6.722230-7.199283
\n", + "
" + ], + "text/plain": [ + " Phage Bacterial_genotype log10 Mc log10 UBc log10 LBc\n", + "0 T7 RP4 -6.908090 -6.766699 -7.086027\n", + "1 T7 RSF1010 -6.839080 -6.709209 -6.999176\n", + "2 T7 K43N -7.072899 -6.933264 -7.248105\n", + "3 T7 S512F -7.058820 -6.902430 -7.261299\n", + "4 T7 D516G -6.920474 -6.722230 -7.199283" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "falcor[\"Bacterial_genotype\"] = falcor[\"Bacterial_genotype\"].replace({'WT(2)': 'WT',\n", " 'MUT(2)': 'MUT'})\n", @@ -1731,28 +1505,27 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 39, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 16, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1802,9 +1575,11 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 29, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1814,9 +1589,11 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 40, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1827,28 +1604,27 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 41, "metadata": { - "clear_cell": true, "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 20, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1859,7 +1635,7 @@ ], "source": [ "sns.set_style(\"ticks\")\n", - "g = sns.FacetGrid(falcor, row=\"Phage\", aspect=3, height=3)\n", + "g = sns.FacetGrid(data=falcor, row=\"Phage\", aspect=3, height=3)\n", "g.map(errorbar,\n", " \"Bacterial_genotype\", \"log10 Mc\",\n", " \"log10 LBc\", \"log10 UBc\")" @@ -1875,8 +1651,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1890,7 +1669,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/_solved/case4_air_quality_analysis.ipynb b/_solved/case4_air_quality_analysis.ipynb index 7b44929..9fbe30f 100644 --- a/_solved/case4_air_quality_analysis.ipynb +++ b/_solved/case4_air_quality_analysis.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - air quality data of European monitoring stations (AirBase)

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -652,7 +649,9 @@ "cell_type": "code", "execution_count": 13, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -739,7 +738,9 @@ "cell_type": "code", "execution_count": 14, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -761,7 +762,9 @@ "cell_type": "code", "execution_count": 15, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -820,7 +823,9 @@ "cell_type": "code", "execution_count": 16, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -848,7 +853,9 @@ "cell_type": "code", "execution_count": 17, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -900,7 +907,9 @@ "cell_type": "code", "execution_count": 18, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -937,7 +946,9 @@ "cell_type": "code", "execution_count": 19, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -976,7 +987,9 @@ "cell_type": "code", "execution_count": 20, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1029,7 +1042,9 @@ "cell_type": "code", "execution_count": 21, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1085,7 +1100,9 @@ "cell_type": "code", "execution_count": 22, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1182,7 +1199,9 @@ "cell_type": "code", "execution_count": 23, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1261,7 +1280,9 @@ "cell_type": "code", "execution_count": 25, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1307,7 +1328,9 @@ "cell_type": "code", "execution_count": 26, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1358,7 +1381,9 @@ "cell_type": "code", "execution_count": 27, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1415,7 +1440,9 @@ "cell_type": "code", "execution_count": 28, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1428,7 +1455,9 @@ "cell_type": "code", "execution_count": 29, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1532,7 +1561,9 @@ "cell_type": "code", "execution_count": 30, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1568,7 +1599,9 @@ "cell_type": "code", "execution_count": 31, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1605,7 +1638,9 @@ "cell_type": "code", "execution_count": 32, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1701,7 +1736,9 @@ "cell_type": "code", "execution_count": 33, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1766,7 +1803,9 @@ "cell_type": "code", "execution_count": 35, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1873,7 +1912,9 @@ "cell_type": "code", "execution_count": 36, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1884,7 +1925,9 @@ "cell_type": "code", "execution_count": 37, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1896,7 +1939,9 @@ "cell_type": "code", "execution_count": 38, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1969,7 +2014,9 @@ "cell_type": "code", "execution_count": 40, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1981,7 +2028,9 @@ "cell_type": "code", "execution_count": 41, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1993,7 +2042,9 @@ "cell_type": "code", "execution_count": 42, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2048,7 +2099,9 @@ "cell_type": "code", "execution_count": 43, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2092,7 +2145,9 @@ "cell_type": "code", "execution_count": 44, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2153,7 +2208,9 @@ "cell_type": "code", "execution_count": 45, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2175,7 +2232,9 @@ "cell_type": "code", "execution_count": 46, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2186,7 +2245,9 @@ "cell_type": "code", "execution_count": 47, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2197,7 +2258,9 @@ "cell_type": "code", "execution_count": 48, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2253,7 +2316,9 @@ "cell_type": "code", "execution_count": 49, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2264,7 +2329,9 @@ "cell_type": "code", "execution_count": 50, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2315,7 +2382,9 @@ "cell_type": "code", "execution_count": 51, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2326,7 +2395,9 @@ "cell_type": "code", "execution_count": 52, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2442,7 +2513,9 @@ "cell_type": "code", "execution_count": 53, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2482,7 +2555,9 @@ "cell_type": "code", "execution_count": 56, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2510,7 +2585,9 @@ "cell_type": "code", "execution_count": 57, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2532,8 +2609,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2547,7 +2627,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/_solved/case4_air_quality_processing.ipynb b/_solved/case4_air_quality_processing.ipynb index a1c8bd8..9ae070a 100644 --- a/_solved/case4_air_quality_processing.ipynb +++ b/_solved/case4_air_quality_processing.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - air quality data of European monitoring stations (AirBase)

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -344,7 +341,9 @@ "cell_type": "code", "execution_count": 6, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -356,8 +355,10 @@ "cell_type": "code", "execution_count": 7, "metadata": { - "clear_cell": true, - "scrolled": true + "scrolled": true, + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -570,9 +571,11 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", - "

\n", - "Drop all 'flag' columns ('flag1', 'flag2', ...)" + "**EXERCISE**:\n", + "\n", + "Drop all 'flag' columns ('flag1', 'flag2', ...)\n", + "\n", + "
" ] }, { @@ -589,8 +592,10 @@ "cell_type": "code", "execution_count": 9, "metadata": { - "clear_cell": true, - "scrolled": true + "scrolled": true, + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -912,7 +917,9 @@ "cell_type": "code", "execution_count": 11, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1006,7 +1013,9 @@ "cell_type": "code", "execution_count": 12, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1038,7 +1047,9 @@ "cell_type": "code", "execution_count": 13, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1134,7 +1145,9 @@ "cell_type": "code", "execution_count": 14, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1146,7 +1159,9 @@ "cell_type": "code", "execution_count": 15, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1222,7 +1237,9 @@ "cell_type": "code", "execution_count": 16, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1433,7 +1450,9 @@ "cell_type": "code", "execution_count": 21, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1525,9 +1544,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "clear_cell": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1610,48 +1627,55 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "**EXERCISE**:\n", "\n", - "
    \n", - "
  • Use the glob.glob function to list all 4 AirBase data files that are included in the 'data' directory, and call the result data_files.
    • \n", - "
\n", + "Use the [pathlib module](https://docs.python.org/3/library/pathlib.html) `Path` class in combination with the `glob` method to list all 4 AirBase data files that are included in the 'data' directory, and call the result `data_files`.\n", + "\n", + "
Hints\n", + "\n", + "- The pathlib module provides a object oriented way to handle file paths. First, create a `Path` object of the data folder, `pathlib.Path(\"./data\")`. Next, apply the `glob` function to extract all the files containing `*0008001*` (use wildcard * to say \"any characters\"). The output is a Python generator, which you can collect as a `list()`.\n", + "\n", + "
\n", + "\n", + " \n", "
" ] }, { "cell_type": "code", - "execution_count": 26, - "metadata": { - "clear_cell": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [], "source": [ - "import glob" + "from pathlib import Path" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 10, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "['data/FR040120000800100hour.1-1-1999.31-12-2012',\n", - " 'data/FR040370000800100hour.1-1-1999.31-12-2012',\n", - " 'data/BETN0290000800100hour.1-1-1990.31-12-2012',\n", - " 'data/BETR8010000800100hour.1-1-1990.31-12-2012']" + "[PosixPath('data/BETN0290000800100hour.1-1-1990.31-12-2012'),\n", + " PosixPath('data/FR040120000800100hour.1-1-1999.31-12-2012'),\n", + " PosixPath('data/FR040370000800100hour.1-1-1999.31-12-2012'),\n", + " PosixPath('data/BETR8010000800100hour.1-1-1990.31-12-2012')]" ] }, - "execution_count": 27, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "data_files = glob.glob(\"data/*0008001*\")\n", + "data_folder = Path(\"./data\")\n", + "data_files = list(data_folder.glob(\"*0008001*\"))\n", "data_files" ] }, @@ -1675,7 +1699,9 @@ "cell_type": "code", "execution_count": 28, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1691,7 +1717,9 @@ "cell_type": "code", "execution_count": 29, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1816,8 +1844,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1831,7 +1862,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/_solved/pandas_01_data_structures.ipynb b/_solved/pandas_01_data_structures.ipynb index 01fc45c..845c166 100644 --- a/_solved/pandas_01_data_structures.ipynb +++ b/_solved/pandas_01_data_structures.ipynb @@ -7,9 +7,6 @@ "source": [ "

01 - Pandas: Data Structures

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -243,7 +240,7 @@ }, { "data": { - "image/png": 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hYmKC0U039bxtk6bG5ti8q87LGc1oay5obzZz9aZurj1XvmyAaR5roS/apk6uiFi23OucLRPAVcDt3cUeEau77vYKYHe/x5Ak9afOj/4XAK8FdkXEzmrsbcD6iFjD/LTMHuANNY4hSepDnbNl/gOIJVZ9qv84kqRB8B2qklQgy12SCmS5S1KBLHdJKpDlLkkFstwlqUCWuyQVyHKXpAJZ7pJUIMtdkgpkuUtSgSx3SSqQ5S5JBWrfp/1LOmY1+Yd3psbm2LDM/pv8IyHD4jN3SSqQ5S5JBbLcJalAlrskFchyl6QCWe6SVCDLXZIK1Nh57hGxDvgAcBzwd5l5ZVPHkqQ6mjy/fiXXrDuxkf028sw9Io4D/gp4KfBMYH1EPLOJY0mSHq+paZkLgLsy81uZ+X/ANHBxQ8eSJC0SmTn4nUb8NrAuM3+/Wn4t8NzMfFPXfTYCG6vFc4E7+zjUacD3asZtgrl619Zs5upNW3NBe7PVyfXzmXn6UiuamnOPJcYe81MkM7cAW2odJGJ7Zo7X2UcTzNW7tmYzV2/amgvam62pXE1Ny+wFzupaPhO4t6FjSZIWaarc/xs4JyLOjoifBi4BbmzoWJKkRRqZlsnMuYh4E/BZ5k+FvDozb2vgULWmdRpkrt61NZu5etPWXNDebI3kauQFVUnScPkOVUkqkOUuSQU6Kss9ItZFxJ0RcVdEbBpylqsj4kBE7O4aOzUibo6Ib1bXpwwh11kRcWtE3B4Rt0XEW9qQLSJ+JiK+FBFfrXK9uw25uvIdFxFfiYhtLcu1JyJ2RcTOiNjelmwRcXJEXBcRd1SPtecPO1dEnFt9nRYuD0XEW4edq8r2R9XjfndEbK3+PzSS66gr9xZ+tME1wLpFY5uAWzLzHOCWavlImwOmMvOXgOcBl1Vfp2Fnexh4UWY+G1gDrIuI57Ug14K3ALd3LbclF8BkZq7pOie6Ddk+AHwmM38ReDbzX7uh5srMO6uv0xpgLfAj4IZh54qIM4A/BMYz83zmTza5pLFcmXlUXYDnA5/tWr4cuHzImUaB3V3LdwKrq9urgTtb8HX7JPCSNmUDngx8GXhuG3Ix/36MW4AXAdva9L0E9gCnLRobajbgZ4F7qE7MaEuuRVl+HfjPNuQCzgC+A5zK/JmK26p8jeQ66p658+gXaMHeaqxNOpl5H0B1/bRhhomIUeA5wBdpQbZq6mMncAC4OTNbkQv4S+CPgZ90jbUhF8y/w/tzEbGj+uiONmR7BvBd4O+rqay/i4gTW5Cr2yXA1ur2UHNl5j7gvcC3gfuAg5n5uaZyHY3lvuJHG+hRETECXA+8NTMfGnYegMx8JOd/ZT4TuCAizh9yJCLiN4EDmblj2FmW8YLM/GXmpyMvi4gXDjsQ888+fxn4cGY+B/ghw522eozqDZQvB/5l2FkAqrn0i4GzgacDJ0bE7zZ1vKOx3I+GjzbYHxGrAarrA8MIERFPYr7Y/ykzP96mbACZ+X1ghvnXLIad6wXAyyNiD/OfYvqiiPhIC3IBkJn3VtcHmJ8/vqAF2fYCe6vfvACuY77sh51rwUuBL2fm/mp52LleDNyTmd/NzB8DHwd+palcR2O5Hw0fbXAjcGl1+1Lm57uPqIgI4Crg9sx8X1uyRcTpEXFydXsV8w/4O4adKzMvz8wzM3OU+cfUv2bm7w47F0BEnBgRT1m4zfw87e5hZ8vM/wW+ExHnVkMXAl8fdq4u63l0SgaGn+vbwPMi4snV/88LmX8Buplcw3qho+YLExcB3wDuBt4+5CxbmZ8/+zHzz2ReDzyV+RfmvlldnzqEXL/K/HTV14Cd1eWiYWcDngV8pcq1G3hHNT70r1lXxgkefUF16LmYn9v+anW5beEx35Jsa4Dt1ffzE8ApLcn1ZOB+4KSusTbkejfzT2Z2A/8InNBULj9+QJIKdDROy0iSVmC5S1KBLHdJKpDlLkkFstwlqUCWuyQVyHKXpAL9P8HwtFnO6Q7WAAAAAElFTkSuQmCC\n", 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\n", 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Zuq40HwF+LcmTAJI8cciaHwS+lOQxLJyh01v71Kq6o6peD9wHrE/y48CpqnorC78s/Yr6MCg9uniGritK7xecvwn4WJKHgE8DrxhY9ifAHcAXgM+wEHiAt/R+6BkW/mG4C9gD/EaSb7HwaX9/tuJfhLQIfygqSY3wkoskNcKgS1IjDLokNcKgS1IjDLokNcKgS1IjDLokNcKgS1Ij/h+2odF+GymItAAAAABJRU5ErkJggg==\n", + "image/png": 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"text/plain": [ "
" ] @@ -379,7 +376,7 @@ } ], "source": [ - "df.groupby('Pclass')['Survived'].aggregate(lambda x: x.sum() / len(x)).plot(kind='bar')" + "df.groupby('Pclass')['Survived'].aggregate(lambda x: x.sum() / len(x)).plot.bar()" ] }, { @@ -1098,7 +1095,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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+ "image/png": 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" ] @@ -1151,7 +1148,7 @@ } ], "source": [ - "countries['population'].plot(kind='barh')" + "countries['population'].plot.barh() # or .plot(kind='barh')" ] }, { @@ -1163,8 +1160,10 @@ "\n", "**EXERCISE**:\n", "\n", - "* You can play with the `kind` keyword of the `plot` function in the figure above: 'line', 'bar', 'hist', 'density', 'area', 'pie', 'scatter', 'hexbin', 'box'\n", + "* You can play with the `kind` keyword or accessor of the `plot` method in the figure above: 'line', 'bar', 'hist', 'density', 'area', 'pie', 'scatter', 'hexbin', 'box'\n", "\n", + "Note: doing `df.plot(kind=\"bar\", ...)` or `df.plot.bar(...)` is exactly equivalent. You will see both ways in the wild.\n", + " \n", "
" ] }, @@ -1299,7 +1298,9 @@ "execution_count": 24, "id": "d4d97581", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1325,7 +1326,9 @@ "execution_count": 25, "id": "0a9f577b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1499,7 +1502,9 @@ "execution_count": 26, "id": "fb5b5ee1", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1535,7 +1540,9 @@ "execution_count": 27, "id": "55994761", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1582,7 +1589,9 @@ "execution_count": 28, "id": "6ff00b82", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1597,7 +1606,7 @@ }, { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "
" ] @@ -1609,7 +1618,7 @@ } ], "source": [ - "df['Fare'].plot(kind='box')" + "df['Fare'].plot(kind='box') # or .plot.box()" ] }, { @@ -1631,7 +1640,9 @@ "execution_count": 29, "id": "c0e64aab", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1893,8 +1904,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1908,7 +1922,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/_solved/pandas_02_basic_operations.ipynb b/_solved/pandas_02_basic_operations.ipynb index 5423853..3bfc0fd 100644 --- a/_solved/pandas_02_basic_operations.ipynb +++ b/_solved/pandas_02_basic_operations.ipynb @@ -7,9 +7,7 @@ "source": [ "

02 - Pandas: Basic operations on Series and DataFrames

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -726,11 +724,10 @@ "metadata": {}, "source": [ "
\n", - "EXERCISE:\n", "\n", - "
    \n", - "
  • What is the average age of the passengers?
    • \n", - "
\n", + "**EXERCISE**\n", + "\n", + "What is the average age of the passengers?\n", "\n", "
" ] @@ -740,7 +737,9 @@ "execution_count": 17, "id": "a49adcdf", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -764,11 +763,11 @@ "metadata": {}, "source": [ "
\n", - "EXERCISE:\n", "\n", - "
    \n", - "
  • Plot the age distribution of the titanic passengers
    • \n", - "
\n", + "**EXERCISE**\n", + "\n", + "Plot the age distribution of the titanic passengers\n", + "\n", "
" ] }, @@ -777,7 +776,9 @@ "execution_count": 18, "id": "5127f39d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -813,14 +814,17 @@ "metadata": {}, "source": [ "
\n", - "EXERCISE:\n", "\n", - "
    \n", - "
  • What is the survival rate? (the relative number of people that survived)
    • \n", - "
\n", - "
\n", + "**EXERCISE**\n", + "\n", + "What is the survival rate? (the relative number of people that survived)\n", "\n", - "Note: the 'Survived' column indicates whether someone survived (1) or not (0).\n", + "
Hints\n", + "\n", + "- the 'Survived' column indicates whether someone survived (1) or not (0).\n", + "\n", + "
\n", + " \n", "
" ] }, @@ -829,7 +833,9 @@ "execution_count": 19, "id": "2a64e341", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -852,7 +858,9 @@ "execution_count": 20, "id": "2875859b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -876,11 +884,11 @@ "metadata": {}, "source": [ "
\n", - "EXERCISE:\n", "\n", - "
    \n", - "
  • What is the maximum Fare? And the median?
    • \n", - "
\n", + "**EXERCISE**\n", + "\n", + "What is the maximum Fare? And the median?\n", + "\n", "
" ] }, @@ -889,7 +897,9 @@ "execution_count": 21, "id": "458f4a30", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -912,7 +922,9 @@ "execution_count": 22, "id": "636facca", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -937,11 +949,16 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "**EXERCISE**\n", + " \n", + "Calculate the 75th percentile (`quantile`) of the Fare price \n", + " \n", + "
Hints\n", + "\n", + "- look in the 'docstring' how to specify the percentile, either range [0, 1] or [0, 100]\n", + "\n", + "
\n", "\n", - "
    \n", - "
  • Calculate the 75th percentile (`quantile`) of the Fare price (Tip: look in the docstring how to specify the percentile)
    • \n", - "
\n", "
" ] }, @@ -950,7 +967,9 @@ "execution_count": 23, "id": "bc9dfb6b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -974,11 +993,11 @@ "metadata": {}, "source": [ "
\n", - "EXERCISE:\n", "\n", - "
    \n", - "
  • Calculate the normalized Fares (normalized relative to its mean), and add this as a new column ('Fare_normalized') to the DataFrame.
    • \n", - "
\n", + "**EXERCISE**\n", + "\n", + "Calculate the normalized Fares (normalized relative to its mean), and add this as a new column ('Fare_normalized') to the DataFrame.\n", + "\n", "
" ] }, @@ -987,7 +1006,9 @@ "execution_count": 24, "id": "4a532ab5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1021,7 +1042,9 @@ "execution_count": 25, "id": "4173bb04", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1184,10 +1207,16 @@ "metadata": {}, "source": [ "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "* Calculate the log of the Fares. \n", " \n", - "**EXERCISE**:\n", + "
Hints\n", "\n", - "* Calculate the log of the Fares. Tip: check the `np.log` function.\n", + "- check the `np.log` function.\n", + "\n", + "
\n", "\n", "
" ] @@ -1197,7 +1226,9 @@ "execution_count": 26, "id": "2cf6819c", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1509,8 +1540,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1524,7 +1558,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/_solved/pandas_03a_selecting_data.ipynb b/_solved/pandas_03a_selecting_data.ipynb index 77e7968..734e1a9 100755 --- a/_solved/pandas_03a_selecting_data.ipynb +++ b/_solved/pandas_03a_selecting_data.ipynb @@ -7,9 +7,7 @@ "source": [ "

03 - Pandas: Indexing and selecting data - part I

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -17,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 14, "id": "bbac3865", "metadata": {}, "outputs": [], @@ -27,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 15, "id": "57c45168", "metadata": {}, "outputs": [ @@ -107,7 +105,7 @@ "4 United Kingdom 64.9 244820 London" ] }, - "execution_count": 2, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1087,7 +1085,9 @@ "execution_count": 18, "id": "e50cb2c4", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1099,7 +1099,9 @@ "execution_count": 19, "id": "c424a94d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1122,7 +1124,9 @@ "execution_count": 20, "id": "5cf61518", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1168,7 +1172,9 @@ "execution_count": 21, "id": "ae3c0cb0", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1191,7 +1197,9 @@ "execution_count": 22, "id": "1aa352c5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1229,7 +1237,9 @@ "execution_count": 23, "id": "3ce55041", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1492,75 +1502,42 @@ }, { "cell_type": "markdown", - "id": "3650db50", + "id": "6e55f240-02ea-4643-bd0f-e505fa923576", "metadata": {}, "source": [ "
\n", "\n", "EXERCISE:\n", "\n", - "Split the 'Name' column on the `,` extract the first part (the surname), and add this as new column 'Surname'.\n", + "For a single string `name = 'Braund, Mr. Owen Harris'`, split this string (check the `split()` method of a string) and get the first element of the resulting list.\n", + " \n", + "
Hints\n", "\n", - "* Get the first value of the 'Name' column.\n", - "* Split this string (check the `split()` method of a string) and get the first element of the resulting list.\n", - "* Write the previous step as a function, and 'apply' this function to each element of the 'Name' column (check the `apply()` method of a Series).\n", + "- No Pandas in this exercise, just standard Python.\n", + " \n", + "
\n", "\n", "
" ] }, { "cell_type": "code", - "execution_count": 24, - "id": "e32eb3f4", - "metadata": { - "clear_cell": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'Braund, Mr. Owen Harris'" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "name = df['Name'][0]\n", - "name" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "a674a798", - "metadata": { - "clear_cell": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['Braund', ' Mr. Owen Harris']" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": 31, + "id": "2982bedf-0f71-4f90-a705-8da6aa9bb3a1", + "metadata": {}, + "outputs": [], "source": [ - "name.split(\",\")" + "name = 'Braund, Mr. Owen Harris'" ] }, { "cell_type": "code", - "execution_count": 26, - "id": "32f648d8", + "execution_count": 32, + "id": "0a8b177f-9596-458a-a455-4c3e64b1e4dd", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1569,7 +1546,7 @@ "'Braund'" ] }, - "execution_count": 26, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1579,24 +1556,35 @@ ] }, { - "cell_type": "code", - "execution_count": 27, - "id": "cc6320be", - "metadata": { - "clear_cell": true - }, - "outputs": [], + "cell_type": "markdown", + "id": "3650db50", + "metadata": {}, "source": [ - "def get_surname(name):\n", - " return name.split(\",\")[0]" + "
\n", + "\n", + "EXERCISE:\n", + " \n", + "Convert the solution of the previous exercise to all strings of the `Name` column at once. Split the 'Name' column on the `,`, extract the first part (the surname), and add this as new column 'Surname'. \n", + " \n", + "
Hints\n", + "\n", + "- Pandas uses the `str` accessor to use the string methods such as `split`, e.g. `.str.split(...)`\n", + "- The [`.str.get()`](https://pandas.pydata.org/docs/reference/api/pandas.Series.str.get.html#pandas.Series.str.get) can be used to get the n-th element of a list, which is what the `str.split()` returns. This is the equivalent of selecting an element of a single list (`a_list[i]`) but then for all values of the Series.\n", + "- One can chain multiple `.str` methods, e.g. `str.SOMEMETHOD(...).str.SOMEOTHERMETHOD(...)`.\n", + " \n", + "
\n", + "\n", + "
" ] }, { "cell_type": "code", - "execution_count": 28, - "id": "eb7cf472", + "execution_count": 30, + "id": "1c33284b-86de-434c-9ac6-3ee4008afc3b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1613,54 +1601,17 @@ "888 Johnston\n", "889 Behr\n", "890 Dooley\n", - "Name: Name, Length: 891, dtype: object" + "Name: Surname, Length: 891, dtype: object" ] }, - "execution_count": 28, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "df['Name'].apply(get_surname)" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "b7a4fd64", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "df['Surname'] = df['Name'].apply(get_surname)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "04dde698", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# alternative using an \"inline\" lambda function\n", - "df['Surname'] = df['Name'].apply(lambda x: x.split(',')[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "8e47f04d", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# alternative solution with pandas' string methods\n", - "df['Surname'] = df['Name'].str.split(\",\").str.get(0)" + "df['Surname'] = df['Name'].str.split(\",\").str.get(0)\n", + "df['Surname']" ] }, { @@ -1683,7 +1634,9 @@ "execution_count": 32, "id": "d0769ddf", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1860,7 +1813,9 @@ "execution_count": 33, "id": "8653927c", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2067,7 +2022,7 @@ "id": "49d05bde", "metadata": {}, "source": [ - "For the quick ones among you, here are some more exercises with some larger dataframe with film data. These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so all credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKajNMa1pfSzN6Q3M) and [`cast.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKal9UYTJSR2ZhSW8) and put them in the `/notebooks/data` folder." + "For the quick ones among you, here are some more exercises with some larger dataframe with film data. These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so all credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/titles.csv) and [`cast.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/cast.csv) and put them in the `/notebooks/data` folder." ] }, { @@ -2275,7 +2230,9 @@ "execution_count": 38, "id": "101bc9c2", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2313,7 +2270,9 @@ "execution_count": 39, "id": "9a875b47", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2391,7 +2350,9 @@ "execution_count": 40, "id": "9083845a", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2429,7 +2390,9 @@ "execution_count": 41, "id": "973b11d5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2543,7 +2506,9 @@ "execution_count": 42, "id": "8d516c1e", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2566,7 +2531,9 @@ "execution_count": 43, "id": "2634393f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2604,7 +2571,9 @@ "execution_count": 44, "id": "bcabb630", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2616,7 +2585,9 @@ "execution_count": 45, "id": "6e0011f2", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2639,7 +2610,9 @@ "execution_count": 46, "id": "3ea078b8", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2677,7 +2650,9 @@ "execution_count": 47, "id": "bf63c5c4", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2715,7 +2690,9 @@ "execution_count": 48, "id": "a2b4032d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2913,7 +2890,9 @@ "execution_count": 49, "id": "84f1580b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -3038,6 +3017,9 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/_solved/pandas_03b_indexing.ipynb b/_solved/pandas_03b_indexing.ipynb index 48dcf2e..c76bdcb 100644 --- a/_solved/pandas_03b_indexing.ipynb +++ b/_solved/pandas_03b_indexing.ipynb @@ -7,9 +7,6 @@ "source": [ "

03 - Pandas: Indexing and selecting data - part II

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -17,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "a07d573c", "metadata": {}, "outputs": [], @@ -27,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "275d90de", "metadata": {}, "outputs": [ @@ -107,7 +104,7 @@ "4 United Kingdom 64.9 244820 London" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -160,7 +157,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "5c7b135c", "metadata": {}, "outputs": [ @@ -241,7 +238,7 @@ "United Kingdom 64.9 244820 London" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -261,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "2a593e16", "metadata": {}, "outputs": [ @@ -341,7 +338,7 @@ "4 United Kingdom 64.9 244820 London" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -407,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "add8d89a", "metadata": {}, "outputs": [ @@ -417,7 +414,7 @@ "357050" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -436,7 +433,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "c7f2b800", "metadata": {}, "outputs": [ @@ -492,7 +489,7 @@ "Germany 357050 81.3" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -525,7 +522,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "8c38b8cf", "metadata": {}, "outputs": [ @@ -581,7 +578,7 @@ "France 671308 Paris" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -602,7 +599,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "689ce562", "metadata": {}, "outputs": [], @@ -613,7 +610,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "bdee6f54", "metadata": {}, "outputs": [ @@ -694,7 +691,7 @@ "United Kingdom 64.9 244820 London" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -738,10 +735,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "e86eb675", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -764,10 +763,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "2ea77b99", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -822,7 +823,7 @@ "Netherlands Amsterdam 16.9" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -848,10 +849,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "d26f9a2d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -945,7 +948,7 @@ "United Kingdom 64.9 244820 London 265.092721 0.970382" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -972,10 +975,12 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "35eea480", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1069,7 +1074,7 @@ "United Kingdom 64.9 244820 Cambridge 265.092721 0.970382" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -1095,10 +1100,12 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "d2dc714d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1165,7 +1172,7 @@ "United Kingdom 64.9 244820 Cambridge 265.092721 0.970382" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1174,6 +1181,249 @@ "countries[(countries['density'] > 100) & (countries['density'] < 300)]" ] }, + { + "cell_type": "markdown", + "id": "b90acfd6", + "metadata": {}, + "source": [ + "The next exercise uses the titanic data set:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "ddfcaa02", + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"data/titanic.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "87877ee1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
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" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris male 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n", + "2 Heikkinen, Miss. Laina female 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n", + "4 Allen, Mr. William Henry male 35.0 0 \n", + "\n", + " Parch Ticket Fare Cabin Embarked \n", + "0 0 A/5 21171 7.2500 NaN S \n", + "1 0 PC 17599 71.2833 C85 C \n", + "2 0 STON/O2. 3101282 7.9250 NaN S \n", + "3 0 113803 53.1000 C123 S \n", + "4 0 373450 8.0500 NaN S " + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "markdown", + "id": "4e9e8655", + "metadata": {}, + "source": [ + "
\n", + "\n", + "EXERCISE:\n", + "\n", + "* Select all rows for male passengers and calculate the mean age of those passengers. Do the same for the female passengers. Do this now using `.loc`.\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "9a55e2ce", + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "30.72664459161148" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[df['Sex'] == 'male', 'Age'].mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "a351c467", + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "27.915708812260537" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[df['Sex'] == 'female', 'Age'].mean()" + ] + }, + { + "cell_type": "markdown", + "id": "31d49399", + "metadata": {}, + "source": [ + "We will later see an easier way to calculate both averages at the same time with `groupby`." + ] + }, { "cell_type": "markdown", "id": "7f26d7b3", @@ -1621,248 +1871,12 @@ "\n", "
" ] - }, - { - "cell_type": "markdown", - "id": "b90acfd6", - "metadata": {}, - "source": [ - "# Exercises using the Titanic dataset" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "ddfcaa02", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_csv(\"data/titanic.csv\")" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "87877ee1", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
\n", - "
" - ], - "text/plain": [ - " PassengerId Survived Pclass \\\n", - "0 1 0 3 \n", - "1 2 1 1 \n", - "2 3 1 3 \n", - "3 4 1 1 \n", - "4 5 0 3 \n", - "\n", - " Name Sex Age SibSp \\\n", - "0 Braund, Mr. Owen Harris male 22.0 1 \n", - "1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n", - "2 Heikkinen, Miss. Laina female 26.0 0 \n", - "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n", - "4 Allen, Mr. William Henry male 35.0 0 \n", - "\n", - " Parch Ticket Fare Cabin Embarked \n", - "0 0 A/5 21171 7.2500 NaN S \n", - "1 0 PC 17599 71.2833 C85 C \n", - "2 0 STON/O2. 3101282 7.9250 NaN S \n", - "3 0 113803 53.1000 C123 S \n", - "4 0 373450 8.0500 NaN S " - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.head()" - ] - }, - { - "cell_type": "markdown", - "id": "4e9e8655", - "metadata": {}, - "source": [ - "
\n", - "\n", - "EXERCISE:\n", - "\n", - "* Select all rows for male passengers and calculate the mean age of those passengers. Do the same for the female passengers. Do this now using `.loc`.\n", - "\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "9a55e2ce", - "metadata": { - "clear_cell": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "30.72664459161148" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.loc[df['Sex'] == 'male', 'Age'].mean()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "a351c467", - "metadata": { - "clear_cell": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "27.915708812260537" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.loc[df['Sex'] == 'female', 'Age'].mean()" - ] - }, - { - "cell_type": "markdown", - "id": "31d49399", - "metadata": {}, - "source": [ - "We will later see an easier way to calculate both averages at the same time with groupby." - ] } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/_solved/pandas_04_time_series_data.ipynb b/_solved/pandas_04_time_series_data.ipynb index a116d7c..14d992c 100644 --- a/_solved/pandas_04_time_series_data.ipynb +++ b/_solved/pandas_04_time_series_data.ipynb @@ -7,9 +7,6 @@ "source": [ "

04 - Pandas: Working with time series data

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -1553,7 +1550,9 @@ "execution_count": 37, "id": "1701f43d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1707,7 +1706,9 @@ "execution_count": 38, "id": "3d61b665", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1861,7 +1862,9 @@ "execution_count": 39, "id": "8e2cf035", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2015,7 +2018,9 @@ "execution_count": 40, "id": "760a4912", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2427,7 +2432,9 @@ "execution_count": 44, "id": "037f5b47", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2480,7 +2487,9 @@ "execution_count": 45, "id": "edf270bf", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2531,7 +2540,9 @@ "execution_count": 46, "id": "c0557860", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2543,7 +2554,9 @@ "execution_count": 47, "id": "20126280", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2593,7 +2606,9 @@ "execution_count": 48, "id": "e0a18e44", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2625,8 +2640,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2640,7 +2658,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/_solved/pandas_05_combining_datasets.ipynb b/_solved/pandas_05_combining_datasets.ipynb index 76f0418..cd19f1f 100644 --- a/_solved/pandas_05_combining_datasets.ipynb +++ b/_solved/pandas_05_combining_datasets.ipynb @@ -5,11 +5,9 @@ "id": "be5c9d31", "metadata": {}, "source": [ - "

05 - Pandas: Combining datasets Part I - concat

\n", + "

Pandas: Combining datasets Part I - concat

\n", + "\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -563,6 +561,102 @@ { "cell_type": "code", "execution_count": 10, + "id": "ce79b16e-ea96-4845-9104-9a18be4de526", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countrypopulationareacapital
0Belgium11.330510Brussels
1France64.3671308Paris
2Germany81.3357050Berlin
3Netherlands16.941526Amsterdam
4United Kingdom64.9244820London
\n", + "
" + ], + "text/plain": [ + " country population area capital\n", + "0 Belgium 11.3 30510 Brussels\n", + "1 France 64.3 671308 Paris\n", + "2 Germany 81.3 357050 Berlin\n", + "3 Netherlands 16.9 41526 Amsterdam\n", + "4 United Kingdom 64.9 244820 London" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = {'country': ['Belgium', 'France', 'Germany', 'Netherlands', 'United Kingdom'],\n", + " 'population': [11.3, 64.3, 81.3, 16.9, 64.9],\n", + " 'area': [30510, 671308, 357050, 41526, 244820],\n", + " 'capital': ['Brussels', 'Paris', 'Berlin', 'Amsterdam', 'London']}\n", + "countries = pd.DataFrame(data)\n", + "countries" + ] + }, + { + "cell_type": "code", + "execution_count": 11, "id": "160524db", "metadata": {}, "outputs": [ @@ -634,7 +728,7 @@ "3 Morocco 34.4 710850 Rabat" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -658,7 +752,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "e1ed5209", "metadata": {}, "outputs": [ @@ -687,9 +781,6 @@ " population\n", " area\n", " capital\n", - " pop_density\n", - " first\n", - " last\n", " \n", " \n", " \n", @@ -699,9 +790,6 @@ " 11.3\n", " 30510\n", " Brussels\n", - " 370.370370\n", - " Belgium\n", - " None\n", " \n", " \n", " 1\n", @@ -709,9 +797,6 @@ " 64.3\n", " 671308\n", " Paris\n", - " 95.783158\n", - " France\n", - " None\n", " \n", " \n", " 2\n", @@ -719,9 +804,6 @@ " 81.3\n", " 357050\n", " Berlin\n", - " 227.699202\n", - " Germany\n", - " None\n", " \n", " \n", " 3\n", @@ -729,9 +811,6 @@ " 16.9\n", " 41526\n", " Amsterdam\n", - " 406.973944\n", - " Netherlands\n", - " None\n", " \n", " \n", " 4\n", @@ -739,9 +818,6 @@ " 64.9\n", " 244820\n", " London\n", - " 265.092721\n", - " United\n", - " Kingdom\n", " \n", " \n", " 0\n", @@ -749,9 +825,6 @@ " 182.2\n", " 923768\n", " Abuja\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 1\n", @@ -759,9 +832,6 @@ " 11.3\n", " 26338\n", " Kigali\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 2\n", @@ -769,9 +839,6 @@ " 94.3\n", " 1010408\n", " Cairo\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 3\n", @@ -779,39 +846,25 @@ " 34.4\n", " 710850\n", " Rabat\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " country population area capital pop_density first \\\n", - "0 Belgium 11.3 30510 Brussels 370.370370 Belgium \n", - "1 France 64.3 671308 Paris 95.783158 France \n", - "2 Germany 81.3 357050 Berlin 227.699202 Germany \n", - "3 Netherlands 16.9 41526 Amsterdam 406.973944 Netherlands \n", - "4 United Kingdom 64.9 244820 London 265.092721 United \n", - "0 Nigeria 182.2 923768 Abuja NaN NaN \n", - "1 Rwanda 11.3 26338 Kigali NaN NaN \n", - "2 Egypt 94.3 1010408 Cairo NaN NaN \n", - "3 Morocco 34.4 710850 Rabat NaN NaN \n", - "\n", - " last \n", - "0 None \n", - "1 None \n", - "2 None \n", - "3 None \n", - "4 Kingdom \n", - "0 NaN \n", - "1 NaN \n", - "2 NaN \n", - "3 NaN " + " country population area capital\n", + "0 Belgium 11.3 30510 Brussels\n", + "1 France 64.3 671308 Paris\n", + "2 Germany 81.3 357050 Berlin\n", + "3 Netherlands 16.9 41526 Amsterdam\n", + "4 United Kingdom 64.9 244820 London\n", + "0 Nigeria 182.2 923768 Abuja\n", + "1 Rwanda 11.3 26338 Kigali\n", + "2 Egypt 94.3 1010408 Cairo\n", + "3 Morocco 34.4 710850 Rabat" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -830,7 +883,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "fbae6a1a", "metadata": {}, "outputs": [ @@ -859,9 +912,6 @@ " population\n", " area\n", " capital\n", - " pop_density\n", - " first\n", - " last\n", " \n", " \n", " \n", @@ -871,9 +921,6 @@ " 11.3\n", " 30510\n", " Brussels\n", - " 370.370370\n", - " Belgium\n", - " None\n", " \n", " \n", " 1\n", @@ -881,9 +928,6 @@ " 64.3\n", " 671308\n", " Paris\n", - " 95.783158\n", - " France\n", - " None\n", " \n", " \n", " 2\n", @@ -891,9 +935,6 @@ " 81.3\n", " 357050\n", " Berlin\n", - " 227.699202\n", - " Germany\n", - " None\n", " \n", " \n", " 3\n", @@ -901,9 +942,6 @@ " 16.9\n", " 41526\n", " Amsterdam\n", - " 406.973944\n", - " Netherlands\n", - " None\n", " \n", " \n", " 4\n", @@ -911,9 +949,6 @@ " 64.9\n", " 244820\n", " London\n", - " 265.092721\n", - " United\n", - " Kingdom\n", " \n", " \n", " 5\n", @@ -921,9 +956,6 @@ " 182.2\n", " 923768\n", " Abuja\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 6\n", @@ -931,9 +963,6 @@ " 11.3\n", " 26338\n", " Kigali\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 7\n", @@ -941,9 +970,6 @@ " 94.3\n", " 1010408\n", " Cairo\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 8\n", @@ -951,39 +977,25 @@ " 34.4\n", " 710850\n", " Rabat\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " country population area capital pop_density first \\\n", - "0 Belgium 11.3 30510 Brussels 370.370370 Belgium \n", - "1 France 64.3 671308 Paris 95.783158 France \n", - "2 Germany 81.3 357050 Berlin 227.699202 Germany \n", - "3 Netherlands 16.9 41526 Amsterdam 406.973944 Netherlands \n", - "4 United Kingdom 64.9 244820 London 265.092721 United \n", - "5 Nigeria 182.2 923768 Abuja NaN NaN \n", - "6 Rwanda 11.3 26338 Kigali NaN NaN \n", - "7 Egypt 94.3 1010408 Cairo NaN NaN \n", - "8 Morocco 34.4 710850 Rabat NaN NaN \n", - "\n", - " last \n", - "0 None \n", - "1 None \n", - "2 None \n", - "3 None \n", - "4 Kingdom \n", - "5 NaN \n", - "6 NaN \n", - "7 NaN \n", - "8 NaN " + " country population area capital\n", + "0 Belgium 11.3 30510 Brussels\n", + "1 France 64.3 671308 Paris\n", + "2 Germany 81.3 357050 Berlin\n", + "3 Netherlands 16.9 41526 Amsterdam\n", + "4 United Kingdom 64.9 244820 London\n", + "5 Nigeria 182.2 923768 Abuja\n", + "6 Rwanda 11.3 26338 Kigali\n", + "7 Egypt 94.3 1010408 Cairo\n", + "8 Morocco 34.4 710850 Rabat" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -1002,7 +1014,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "3115002f", "metadata": {}, "outputs": [ @@ -1031,9 +1043,6 @@ " population\n", " area\n", " capital\n", - " pop_density\n", - " first\n", - " last\n", " \n", " \n", " \n", @@ -1043,9 +1052,6 @@ " 11.3\n", " 30510.0\n", " Brussels\n", - " 370.370370\n", - " Belgium\n", - " None\n", " \n", " \n", " 1\n", @@ -1053,9 +1059,6 @@ " 64.3\n", " 671308.0\n", " Paris\n", - " 95.783158\n", - " France\n", - " None\n", " \n", " \n", " 2\n", @@ -1063,9 +1066,6 @@ " 81.3\n", " 357050.0\n", " Berlin\n", - " 227.699202\n", - " Germany\n", - " None\n", " \n", " \n", " 3\n", @@ -1073,9 +1073,6 @@ " 16.9\n", " 41526.0\n", " Amsterdam\n", - " 406.973944\n", - " Netherlands\n", - " None\n", " \n", " \n", " 4\n", @@ -1083,9 +1080,6 @@ " 64.9\n", " 244820.0\n", " London\n", - " 265.092721\n", - " United\n", - " Kingdom\n", " \n", " \n", " 5\n", @@ -1093,9 +1087,6 @@ " NaN\n", " NaN\n", " Abuja\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 6\n", @@ -1103,9 +1094,6 @@ " NaN\n", " NaN\n", " Kigali\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 7\n", @@ -1113,9 +1101,6 @@ " NaN\n", " NaN\n", " Cairo\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 8\n", @@ -1123,39 +1108,25 @@ " NaN\n", " NaN\n", " Rabat\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " country population area capital pop_density first \\\n", - "0 Belgium 11.3 30510.0 Brussels 370.370370 Belgium \n", - "1 France 64.3 671308.0 Paris 95.783158 France \n", - "2 Germany 81.3 357050.0 Berlin 227.699202 Germany \n", - "3 Netherlands 16.9 41526.0 Amsterdam 406.973944 Netherlands \n", - "4 United Kingdom 64.9 244820.0 London 265.092721 United \n", - "5 Nigeria NaN NaN Abuja NaN NaN \n", - "6 Rwanda NaN NaN Kigali NaN NaN \n", - "7 Egypt NaN NaN Cairo NaN NaN \n", - "8 Morocco NaN NaN Rabat NaN NaN \n", - "\n", - " last \n", - "0 None \n", - "1 None \n", - "2 None \n", - "3 None \n", - "4 Kingdom \n", - "5 NaN \n", - "6 NaN \n", - "7 NaN \n", - "8 NaN " + " country population area capital\n", + "0 Belgium 11.3 30510.0 Brussels\n", + "1 France 64.3 671308.0 Paris\n", + "2 Germany 81.3 357050.0 Berlin\n", + "3 Netherlands 16.9 41526.0 Amsterdam\n", + "4 United Kingdom 64.9 244820.0 London\n", + "5 Nigeria NaN NaN Abuja\n", + "6 Rwanda NaN NaN Kigali\n", + "7 Egypt NaN NaN Cairo\n", + "8 Morocco NaN NaN Rabat" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -1174,7 +1145,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "0061f065", "metadata": {}, "outputs": [ @@ -1204,9 +1175,6 @@ " population\n", " area\n", " capital\n", - " pop_density\n", - " first\n", - " last\n", " \n", " \n", " \n", @@ -1217,9 +1185,6 @@ " 11.3\n", " 30510\n", " Brussels\n", - " 370.370370\n", - " Belgium\n", - " None\n", " \n", " \n", " 1\n", @@ -1227,9 +1192,6 @@ " 64.3\n", " 671308\n", " Paris\n", - " 95.783158\n", - " France\n", - " None\n", " \n", " \n", " 2\n", @@ -1237,9 +1199,6 @@ " 81.3\n", " 357050\n", " Berlin\n", - " 227.699202\n", - " Germany\n", - " None\n", " \n", " \n", " 3\n", @@ -1247,9 +1206,6 @@ " 16.9\n", " 41526\n", " Amsterdam\n", - " 406.973944\n", - " Netherlands\n", - " None\n", " \n", " \n", " 4\n", @@ -1257,9 +1213,6 @@ " 64.9\n", " 244820\n", " London\n", - " 265.092721\n", - " United\n", - " Kingdom\n", " \n", " \n", " africa\n", @@ -1268,9 +1221,6 @@ " 182.2\n", " 923768\n", " Abuja\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 1\n", @@ -1278,9 +1228,6 @@ " 11.3\n", " 26338\n", " Kigali\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 2\n", @@ -1288,9 +1235,6 @@ " 94.3\n", " 1010408\n", " Cairo\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", " 3\n", @@ -1298,39 +1242,25 @@ " 34.4\n", " 710850\n", " Rabat\n", - " NaN\n", - " NaN\n", - " NaN\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " country population area capital pop_density \\\n", - "europe 0 Belgium 11.3 30510 Brussels 370.370370 \n", - " 1 France 64.3 671308 Paris 95.783158 \n", - " 2 Germany 81.3 357050 Berlin 227.699202 \n", - " 3 Netherlands 16.9 41526 Amsterdam 406.973944 \n", - " 4 United Kingdom 64.9 244820 London 265.092721 \n", - "africa 0 Nigeria 182.2 923768 Abuja NaN \n", - " 1 Rwanda 11.3 26338 Kigali NaN \n", - " 2 Egypt 94.3 1010408 Cairo NaN \n", - " 3 Morocco 34.4 710850 Rabat NaN \n", - "\n", - " first last \n", - "europe 0 Belgium None \n", - " 1 France None \n", - " 2 Germany None \n", - " 3 Netherlands None \n", - " 4 United Kingdom \n", - "africa 0 NaN NaN \n", - " 1 NaN NaN \n", - " 2 NaN NaN \n", - " 3 NaN NaN " + " country population area capital\n", + "europe 0 Belgium 11.3 30510 Brussels\n", + " 1 France 64.3 671308 Paris\n", + " 2 Germany 81.3 357050 Berlin\n", + " 3 Netherlands 16.9 41526 Amsterdam\n", + " 4 United Kingdom 64.9 244820 London\n", + "africa 0 Nigeria 182.2 923768 Abuja\n", + " 1 Rwanda 11.3 26338 Kigali\n", + " 2 Egypt 94.3 1010408 Cairo\n", + " 3 Morocco 34.4 710850 Rabat" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1341,32 +1271,69 @@ }, { "cell_type": "markdown", - "id": "b01819a6", + "id": "b361359f-e464-4094-b16f-fc6dbf22ee6b", "metadata": {}, "source": [ - "## Combining columns - ``pd.concat`` with ``axis=1``" - ] - }, + "
\n", + "\n", + "**NOTE**:\n", + "\n", + "A typical use case of `concat` is when you create (or read) multiple DataFrame with a similar structure in a loop, and then want to combine this list of DataFrames into a single DataFrame.\n", + "\n", + "For example, assume you have a folder of similar CSV files (eg the data per day) you want to read and combine, this would look like:\n", + "\n", + "```python\n", + "import pathlib\n", + "\n", + "data_files = pathlib.Path(\"data_directory\").glob(\"*.csv\")\n", + "\n", + "dfs = []\n", + "\n", + "for path in data_files:\n", + " temp = pd.read_csv(path)\n", + " dfs.append(temp)\n", + "\n", + "df = pd.concat(dfs)\n", + "```\n", + "
\n", + "Important: append to a list (not DataFrame), and concat this list at the end after the loop!\n", + "\n", + "
" + ] + }, { "cell_type": "markdown", - "id": "79eebe9b", + "id": "970012f2", "metadata": {}, "source": [ - "![](../img/pandas/schema-concat1.svg)" + "# Joining data with `pd.merge`" ] }, { "cell_type": "markdown", - "id": "5c855df6", + "id": "78e1b973", "metadata": {}, "source": [ - "Assume we have another DataFrame for the same countries, but with some additional statistics:" + "Using `pd.concat` above, we combined datasets that had the same columns. But, another typical case is where you want to add information of a second dataframe to a first one based on one of the columns they have in common. That can be done with [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html).\n", + "\n", + "Let's look again at the titanic passenger data, but taking a small subset of it to make the example easier to grasp:" ] }, { "cell_type": "code", - "execution_count": 15, - "id": "7f4613a7", + "execution_count": 16, + "id": "e00931e6", + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"data/titanic.csv\")\n", + "df = df.loc[:9, ['Survived', 'Pclass', 'Sex', 'Age', 'Fare', 'Embarked']]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "37dcebb7", "metadata": {}, "outputs": [ { @@ -1390,60 +1357,156 @@ " \n", " \n", " \n", - " GDP\n", - " area\n", - " \n", - " \n", - " country\n", - " \n", - " \n", + " Survived\n", + " Pclass\n", + " Sex\n", + " Age\n", + " Fare\n", + " Embarked\n", " \n", " \n", " \n", " \n", - " Belgium\n", - " 496477\n", - " 8.0\n", + " 0\n", + " 0\n", + " 3\n", + " male\n", + " 22.0\n", + " 7.2500\n", + " S\n", " \n", " \n", - " France\n", - " 2650823\n", - " 9.9\n", + " 1\n", + " 1\n", + " 1\n", + " female\n", + " 38.0\n", + " 71.2833\n", + " C\n", " \n", " \n", - " Netherlands\n", - " 820726\n", - " 5.7\n", + " 2\n", + " 1\n", + " 3\n", + " female\n", + " 26.0\n", + " 7.9250\n", + " S\n", + " \n", + " \n", + " 3\n", + " 1\n", + " 1\n", + " female\n", + " 35.0\n", + " 53.1000\n", + " S\n", + " \n", + " \n", + " 4\n", + " 0\n", + " 3\n", + " male\n", + " 35.0\n", + " 8.0500\n", + " S\n", + " \n", + " \n", + " 5\n", + " 0\n", + " 3\n", + " male\n", + " NaN\n", + " 8.4583\n", + " Q\n", + " \n", + " \n", + " 6\n", + " 0\n", + " 1\n", + " male\n", + " 54.0\n", + " 51.8625\n", + " S\n", + " \n", + " \n", + " 7\n", + " 0\n", + " 3\n", + " male\n", + " 2.0\n", + " 21.0750\n", + " S\n", + " \n", + " \n", + " 8\n", + " 1\n", + " 3\n", + " female\n", + " 27.0\n", + " 11.1333\n", + " S\n", + " \n", + " \n", + " 9\n", + " 1\n", + " 2\n", + " female\n", + " 14.0\n", + " 30.0708\n", + " C\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " GDP area\n", - "country \n", - "Belgium 496477 8.0\n", - "France 2650823 9.9\n", - "Netherlands 820726 5.7" + " Survived Pclass Sex Age Fare Embarked\n", + "0 0 3 male 22.0 7.2500 S\n", + "1 1 1 female 38.0 71.2833 C\n", + "2 1 3 female 26.0 7.9250 S\n", + "3 1 1 female 35.0 53.1000 S\n", + "4 0 3 male 35.0 8.0500 S\n", + "5 0 3 male NaN 8.4583 Q\n", + "6 0 1 male 54.0 51.8625 S\n", + "7 0 3 male 2.0 21.0750 S\n", + "8 1 3 female 27.0 11.1333 S\n", + "9 1 2 female 14.0 30.0708 C" ] }, - "execution_count": 15, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "data = {'country': ['Belgium', 'France', 'Netherlands'],\n", - " 'GDP': [496477, 2650823, 820726],\n", - " 'area': [8.0, 9.9, 5.7]}\n", - "country_economics = pd.DataFrame(data).set_index('country')\n", - "country_economics" + "df" + ] + }, + { + "cell_type": "markdown", + "id": "4ae11628", + "metadata": {}, + "source": [ + "Assume we have another dataframe with more information about the 'Embarked' locations:" ] }, { "cell_type": "code", - "execution_count": 16, - "id": "3105e789", + "execution_count": 18, + "id": "35e5b529", + "metadata": {}, + "outputs": [], + "source": [ + "locations = pd.DataFrame({'Embarked': ['S', 'C', 'N'],\n", + " 'City': ['Southampton', 'Cherbourg', 'New York City'],\n", + " 'Country': ['United Kindom', 'France', 'United States']})" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "94906138", "metadata": {}, "outputs": [ { @@ -1467,171 +1530,289 @@ " \n", " \n", " \n", - " country\n", - " population\n", - " area\n", - " capital\n", - " pop_density\n", - " first\n", - " last\n", - " GDP\n", - " area\n", + " Embarked\n", + " City\n", + " Country\n", " \n", " \n", " \n", " \n", " 0\n", - " Belgium\n", - " 11.3\n", - " 30510.0\n", - " Brussels\n", - " 370.370370\n", - " Belgium\n", - " None\n", - " NaN\n", - " NaN\n", + " S\n", + " Southampton\n", + " United Kindom\n", + " \n", + " \n", + " 1\n", + " C\n", + " Cherbourg\n", + " France\n", + " \n", + " \n", + " 2\n", + " N\n", + " New York City\n", + " United States\n", + " \n", + " \n", + "\n", + "
" + ], + "text/plain": [ + " Embarked City Country\n", + "0 S Southampton United Kindom\n", + "1 C Cherbourg France\n", + "2 N New York City United States" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "locations" + ] + }, + { + "cell_type": "markdown", + "id": "1ebb09a0", + "metadata": {}, + "source": [ + "We now want to add those columns to the titanic dataframe, for which we can use `pd.merge`, specifying the column on which we want to merge the two datasets:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "571b126f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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SurvivedPclassSexAgeFareEmbarkedCityCountry
003male22.07.2500SSouthamptonUnited Kindom
111female38.071.2833CCherbourgFrance64.3671308.0Paris95.783158FranceNoneNaNNaN
2Germany81.3357050.0Berlin227.699202GermanyNoneNaNNaN13female26.07.9250SSouthamptonUnited Kindom
3Netherlands16.941526.0Amsterdam406.973944NetherlandsNoneNaNNaN11female35.053.1000SSouthamptonUnited Kindom
4United Kingdom64.9244820.0London265.092721UnitedKingdomNaNNaN03male35.08.0500SSouthamptonUnited Kindom
BelgiumNaNNaNNaNNaN503maleNaN8.4583QNaNNaN496477.08.0
FranceNaNNaNNaNNaNNaNNaNNaN2650823.09.9601male54.051.8625SSouthamptonUnited Kindom
NetherlandsNaNNaNNaNNaNNaNNaNNaN820726.05.7703male2.021.0750SSouthamptonUnited Kindom
813female27.011.1333SSouthamptonUnited Kindom
912female14.030.0708CCherbourgFrance
\n", "
" ], "text/plain": [ - " country population area capital pop_density \\\n", - "0 Belgium 11.3 30510.0 Brussels 370.370370 \n", - "1 France 64.3 671308.0 Paris 95.783158 \n", - "2 Germany 81.3 357050.0 Berlin 227.699202 \n", - "3 Netherlands 16.9 41526.0 Amsterdam 406.973944 \n", - "4 United Kingdom 64.9 244820.0 London 265.092721 \n", - "Belgium NaN NaN NaN NaN NaN \n", - "France NaN NaN NaN NaN NaN \n", - "Netherlands NaN NaN NaN NaN NaN \n", + " Survived Pclass Sex Age Fare Embarked City \\\n", + "0 0 3 male 22.0 7.2500 S Southampton \n", + "1 1 1 female 38.0 71.2833 C Cherbourg \n", + "2 1 3 female 26.0 7.9250 S Southampton \n", + "3 1 1 female 35.0 53.1000 S Southampton \n", + "4 0 3 male 35.0 8.0500 S Southampton \n", + "5 0 3 male NaN 8.4583 Q NaN \n", + "6 0 1 male 54.0 51.8625 S Southampton \n", + "7 0 3 male 2.0 21.0750 S Southampton \n", + "8 1 3 female 27.0 11.1333 S Southampton \n", + "9 1 2 female 14.0 30.0708 C Cherbourg \n", "\n", - " first last GDP area \n", - "0 Belgium None NaN NaN \n", - "1 France None NaN NaN \n", - "2 Germany None NaN NaN \n", - "3 Netherlands None NaN NaN \n", - "4 United Kingdom NaN NaN \n", - "Belgium NaN NaN 496477.0 8.0 \n", - "France NaN NaN 2650823.0 9.9 \n", - "Netherlands NaN NaN 820726.0 5.7 " + " Country \n", + "0 United Kindom \n", + "1 France \n", + "2 United Kindom \n", + "3 United Kindom \n", + "4 United Kindom \n", + "5 NaN \n", + "6 United Kindom \n", + "7 United Kindom \n", + "8 United Kindom \n", + "9 France " ] }, - "execution_count": 16, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.concat([countries, country_economics], axis=1)" + "pd.merge(df, locations, on='Embarked', how='left')" + ] + }, + { + "cell_type": "markdown", + "id": "4b1df56c", + "metadata": {}, + "source": [ + "In this case we use `how='left` (a \"left join\") because we wanted to keep the original rows of `df` and only add matching values from `locations` to it. Other options are 'inner', 'outer' and 'right' (see the [docs](http://pandas.pydata.org/pandas-docs/stable/merging.html#brief-primer-on-merge-methods-relational-algebra) for more on this, or this visualization: https://joins.spathon.com/)." ] }, { "cell_type": "markdown", - "id": "64f7a2dc", + "id": "e3b5ad11-9387-46e9-a8f1-64fe61446358", "metadata": {}, "source": [ - "`pd.concat` matches the different objects based on the index:" + "## Combining columns - ``pd.concat`` with ``axis=1``" ] }, { - "cell_type": "code", - "execution_count": 17, - "id": "763667a5", + "cell_type": "markdown", + "id": "5b8e016e-5e29-42a6-bd30-26bdda19ec22", "metadata": {}, - "outputs": [], "source": [ - "countries2 = countries.set_index('country')" + "We can use `pd.merge` to combine the columns of two DataFrame based on a common column. If our two DataFrames already have equivalent rows, we can also achieve this basic case using `pd.concat` with specifying `axis=1` (or `axis=\"columns\"`)." + ] + }, + { + "cell_type": "markdown", + "id": "1e24ffc4-d651-4fbb-bdcf-5a42c6ddb1bd", + "metadata": {}, + "source": [ + "![](../img/pandas/schema-concat1.svg)" + ] + }, + { + "cell_type": "markdown", + "id": "fa045a3c-119a-4463-affe-b8282c415bd3", + "metadata": {}, + "source": [ + "Assume we have another DataFrame for the same countries, but with some additional statistics:" ] }, { "cell_type": "code", - "execution_count": 18, - "id": "6c3a72d7", + "execution_count": 21, + "id": "13cabbdd-51b3-47d6-b9f8-d0c60fd63fea", "metadata": {}, "outputs": [ { @@ -1655,104 +1836,79 @@ " \n", " \n", " \n", + " country\n", " population\n", " area\n", " capital\n", - " pop_density\n", - " first\n", - " last\n", - " \n", - " \n", - " country\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", " \n", " \n", " \n", " \n", - " Belgium\n", + " 0\n", + " Belgium\n", " 11.3\n", " 30510\n", " Brussels\n", - " 370.370370\n", - " Belgium\n", - " None\n", " \n", " \n", - " France\n", + " 1\n", + " France\n", " 64.3\n", " 671308\n", " Paris\n", - " 95.783158\n", - " France\n", - " None\n", " \n", " \n", - " Germany\n", + " 2\n", + " Germany\n", " 81.3\n", " 357050\n", " Berlin\n", - " 227.699202\n", - " Germany\n", - " None\n", " \n", " \n", - " Netherlands\n", + " 3\n", + " Netherlands\n", " 16.9\n", " 41526\n", " Amsterdam\n", - " 406.973944\n", - " Netherlands\n", - " None\n", " \n", " \n", - " United Kingdom\n", + " 4\n", + " United Kingdom\n", " 64.9\n", " 244820\n", " London\n", - " 265.092721\n", - " United\n", - " Kingdom\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " population area capital pop_density first \\\n", - "country \n", - "Belgium 11.3 30510 Brussels 370.370370 Belgium \n", - "France 64.3 671308 Paris 95.783158 France \n", - "Germany 81.3 357050 Berlin 227.699202 Germany \n", - "Netherlands 16.9 41526 Amsterdam 406.973944 Netherlands \n", - "United Kingdom 64.9 244820 London 265.092721 United \n", - "\n", - " last \n", - "country \n", - "Belgium None \n", - "France None \n", - "Germany None \n", - "Netherlands None \n", - "United Kingdom Kingdom " + " country population area capital\n", + "0 Belgium 11.3 30510 Brussels\n", + "1 France 64.3 671308 Paris\n", + "2 Germany 81.3 357050 Berlin\n", + "3 Netherlands 16.9 41526 Amsterdam\n", + "4 United Kingdom 64.9 244820 London" ] }, - "execution_count": 18, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "countries2" + "data = {'country': ['Belgium', 'France', 'Germany', 'Netherlands', 'United Kingdom'],\n", + " 'population': [11.3, 64.3, 81.3, 16.9, 64.9],\n", + " 'area': [30510, 671308, 357050, 41526, 244820],\n", + " 'capital': ['Brussels', 'Paris', 'Berlin', 'Amsterdam', 'London']}\n", + "countries = pd.DataFrame(data)\n", + "countries" ] }, { "cell_type": "code", - "execution_count": 19, - "id": "07814fa5", + "execution_count": 22, + "id": "7f4613a7", "metadata": {}, "outputs": [ { @@ -1776,12 +1932,6 @@ " \n", " \n", " \n", - " population\n", - " area\n", - " capital\n", - " pop_density\n", - " first\n", - " last\n", " GDP\n", " area\n", " \n", @@ -1789,134 +1939,53 @@ " country\n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", " \n", " \n", " \n", " \n", " Belgium\n", - " 11.3\n", - " 30510\n", - " Brussels\n", - " 370.370370\n", - " Belgium\n", - " None\n", - " 496477.0\n", + " 496477\n", " 8.0\n", " \n", " \n", " France\n", - " 64.3\n", - " 671308\n", - " Paris\n", - " 95.783158\n", - " France\n", - " None\n", - " 2650823.0\n", + " 2650823\n", " 9.9\n", " \n", " \n", - " Germany\n", - " 81.3\n", - " 357050\n", - " Berlin\n", - " 227.699202\n", - " Germany\n", - " None\n", - " NaN\n", - " NaN\n", - " \n", - " \n", " Netherlands\n", - " 16.9\n", - " 41526\n", - " Amsterdam\n", - " 406.973944\n", - " Netherlands\n", - " None\n", - " 820726.0\n", + " 820726\n", " 5.7\n", " \n", - " \n", - " United Kingdom\n", - " 64.9\n", - " 244820\n", - " London\n", - " 265.092721\n", - " United\n", - " Kingdom\n", - " NaN\n", - " NaN\n", - " \n", " \n", "\n", "
" ], "text/plain": [ - " population area capital pop_density first \\\n", - "country \n", - "Belgium 11.3 30510 Brussels 370.370370 Belgium \n", - "France 64.3 671308 Paris 95.783158 France \n", - "Germany 81.3 357050 Berlin 227.699202 Germany \n", - "Netherlands 16.9 41526 Amsterdam 406.973944 Netherlands \n", - "United Kingdom 64.9 244820 London 265.092721 United \n", - "\n", - " last GDP area \n", - "country \n", - "Belgium None 496477.0 8.0 \n", - "France None 2650823.0 9.9 \n", - "Germany None NaN NaN \n", - "Netherlands None 820726.0 5.7 \n", - "United Kingdom Kingdom NaN NaN " + " GDP area\n", + "country \n", + "Belgium 496477 8.0\n", + "France 2650823 9.9\n", + "Netherlands 820726 5.7" ] }, - "execution_count": 19, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.concat([countries2, country_economics], axis=1)" - ] - }, - { - "cell_type": "markdown", - "id": "970012f2", - "metadata": {}, - "source": [ - "# Joining data with `pd.merge`" - ] - }, - { - "cell_type": "markdown", - "id": "78e1b973", - "metadata": {}, - "source": [ - "Using `pd.concat` above, we combined datasets that had the same columns or the same index values. But, another typical case if where you want to add information of second dataframe to a first one based on one of the columns. That can be done with [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html).\n", - "\n", - "Let's look again at the titanic passenger data, but taking a small subset of it to make the example easier to grasp:" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "e00931e6", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_csv(\"data/titanic.csv\")\n", - "df = df.loc[:9, ['Survived', 'Pclass', 'Sex', 'Age', 'Fare', 'Embarked']]" + "data = {'country': ['Belgium', 'France', 'Netherlands'],\n", + " 'GDP': [496477, 2650823, 820726],\n", + " 'area': [8.0, 9.9, 5.7]}\n", + "country_economics = pd.DataFrame(data).set_index('country')\n", + "country_economics" ] }, { "cell_type": "code", - "execution_count": 21, - "id": "37dcebb7", + "execution_count": 23, + "id": "3105e789", "metadata": {}, "outputs": [ { @@ -1940,156 +2009,134 @@ " \n", " \n", " \n", - " Survived\n", - " Pclass\n", - " Sex\n", - " Age\n", - " Fare\n", - " Embarked\n", + " country\n", + " population\n", + " area\n", + " capital\n", + " GDP\n", + " area\n", " \n", " \n", " \n", " \n", " 0\n", - " 0\n", - " 3\n", - " male\n", - " 22.0\n", - " 7.2500\n", - " S\n", + " Belgium\n", + " 11.3\n", + " 30510.0\n", + " Brussels\n", + " NaN\n", + " NaN\n", " \n", " \n", " 1\n", - " 1\n", - " 1\n", - " female\n", - " 38.0\n", - " 71.2833\n", - " C\n", + " France\n", + " 64.3\n", + " 671308.0\n", + " Paris\n", + " NaN\n", + " NaN\n", " \n", " \n", " 2\n", - " 1\n", - " 3\n", - " female\n", - " 26.0\n", - " 7.9250\n", - " S\n", + " Germany\n", + " 81.3\n", + " 357050.0\n", + " Berlin\n", + " NaN\n", + " NaN\n", " \n", " \n", " 3\n", - " 1\n", - " 1\n", - " female\n", - " 35.0\n", - " 53.1000\n", - " S\n", + " Netherlands\n", + " 16.9\n", + " 41526.0\n", + " Amsterdam\n", + " NaN\n", + " NaN\n", " \n", " \n", " 4\n", - " 0\n", - " 3\n", - " male\n", - " 35.0\n", - " 8.0500\n", - " S\n", - " \n", - " \n", - " 5\n", - " 0\n", - " 3\n", - " male\n", + " United Kingdom\n", + " 64.9\n", + " 244820.0\n", + " London\n", + " NaN\n", " NaN\n", - " 8.4583\n", - " Q\n", - " \n", - " \n", - " 6\n", - " 0\n", - " 1\n", - " male\n", - " 54.0\n", - " 51.8625\n", - " S\n", " \n", " \n", - " 7\n", - " 0\n", - " 3\n", - " male\n", - " 2.0\n", - " 21.0750\n", - " S\n", + " Belgium\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 496477.0\n", + " 8.0\n", " \n", " \n", - " 8\n", - " 1\n", - " 3\n", - " female\n", - " 27.0\n", - " 11.1333\n", - " S\n", + " France\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 2650823.0\n", + " 9.9\n", " \n", " \n", - " 9\n", - " 1\n", - " 2\n", - " female\n", - " 14.0\n", - " 30.0708\n", - " C\n", + " Netherlands\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 820726.0\n", + " 5.7\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " Survived Pclass Sex Age Fare Embarked\n", - "0 0 3 male 22.0 7.2500 S\n", - "1 1 1 female 38.0 71.2833 C\n", - "2 1 3 female 26.0 7.9250 S\n", - "3 1 1 female 35.0 53.1000 S\n", - "4 0 3 male 35.0 8.0500 S\n", - "5 0 3 male NaN 8.4583 Q\n", - "6 0 1 male 54.0 51.8625 S\n", - "7 0 3 male 2.0 21.0750 S\n", - "8 1 3 female 27.0 11.1333 S\n", - "9 1 2 female 14.0 30.0708 C" + " country population area capital GDP area\n", + "0 Belgium 11.3 30510.0 Brussels NaN NaN\n", + "1 France 64.3 671308.0 Paris NaN NaN\n", + "2 Germany 81.3 357050.0 Berlin NaN NaN\n", + "3 Netherlands 16.9 41526.0 Amsterdam NaN NaN\n", + "4 United Kingdom 64.9 244820.0 London NaN NaN\n", + "Belgium NaN NaN NaN NaN 496477.0 8.0\n", + "France NaN NaN NaN NaN 2650823.0 9.9\n", + "Netherlands NaN NaN NaN NaN 820726.0 5.7" ] }, - "execution_count": 21, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "df" + "pd.concat([countries, country_economics], axis=1)" ] }, { "cell_type": "markdown", - "id": "4ae11628", + "id": "17e2c658-8343-4142-a995-3fb8de9ede08", "metadata": {}, "source": [ - "Assume we have another dataframe with more information about the 'Embarked' locations:" + "`pd.concat` matches the different objects based on the index:" ] }, { "cell_type": "code", - "execution_count": 22, - "id": "35e5b529", + "execution_count": 24, + "id": "763667a5", "metadata": {}, "outputs": [], "source": [ - "locations = pd.DataFrame({'Embarked': ['S', 'C', 'Q', 'N'],\n", - " 'City': ['Southampton', 'Cherbourg', 'Queenstown', 'New York City'],\n", - " 'Country': ['United Kindom', 'France', 'Ireland', 'United States']})" + "countries2 = countries.set_index('country')" ] }, { "cell_type": "code", - "execution_count": 23, - "id": "94906138", + "execution_count": 25, + "id": "6c3a72d7", "metadata": {}, "outputs": [ { @@ -2113,69 +2160,75 @@ " \n", " \n", " \n", - " Embarked\n", - " City\n", - " Country\n", + " population\n", + " area\n", + " capital\n", + " \n", + " \n", + " country\n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 0\n", - " S\n", - " Southampton\n", - " United Kindom\n", + " Belgium\n", + " 11.3\n", + " 30510\n", + " Brussels\n", " \n", " \n", - " 1\n", - " C\n", - " Cherbourg\n", - " France\n", + " France\n", + " 64.3\n", + " 671308\n", + " Paris\n", " \n", " \n", - " 2\n", - " Q\n", - " Queenstown\n", - " Ireland\n", + " Germany\n", + " 81.3\n", + " 357050\n", + " Berlin\n", " \n", " \n", - " 3\n", - " N\n", - " New York City\n", - " United States\n", + " Netherlands\n", + " 16.9\n", + " 41526\n", + " Amsterdam\n", + " \n", + " \n", + " United Kingdom\n", + " 64.9\n", + " 244820\n", + " London\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " Embarked City Country\n", - "0 S Southampton United Kindom\n", - "1 C Cherbourg France\n", - "2 Q Queenstown Ireland\n", - "3 N New York City United States" + " population area capital\n", + "country \n", + "Belgium 11.3 30510 Brussels\n", + "France 64.3 671308 Paris\n", + "Germany 81.3 357050 Berlin\n", + "Netherlands 16.9 41526 Amsterdam\n", + "United Kingdom 64.9 244820 London" ] }, - "execution_count": 23, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "locations" - ] - }, - { - "cell_type": "markdown", - "id": "1ebb09a0", - "metadata": {}, - "source": [ - "We now want to add those columns to the titanic dataframe, for which we can use `pd.merge`, specifying the column on which we want to merge the two datasets:" + "countries2" ] }, { "cell_type": "code", - "execution_count": 24, - "id": "571b126f", + "execution_count": 27, + "id": "07814fa5", "metadata": {}, "outputs": [ { @@ -2199,178 +2252,100 @@ " \n", " \n", " \n", - " Survived\n", - " Pclass\n", - " Sex\n", - " Age\n", - " Fare\n", - " Embarked\n", - " City\n", - " Country\n", - " \n", - " \n", - " \n", - " \n", - " 0\n", - " 0\n", - " 3\n", - " male\n", - " 22.0\n", - " 7.2500\n", - " S\n", - " Southampton\n", - " United Kindom\n", - " \n", - " \n", - " 1\n", - " 1\n", - " 1\n", - " female\n", - " 38.0\n", - " 71.2833\n", - " C\n", - " Cherbourg\n", - " France\n", + " population\n", + " area\n", + " capital\n", + " GDP\n", + " area\n", " \n", " \n", - " 2\n", - " 1\n", - " 3\n", - " female\n", - " 26.0\n", - " 7.9250\n", - " S\n", - " Southampton\n", - " United Kindom\n", + " country\n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", + " \n", + " \n", " \n", - " 3\n", - " 1\n", - " 1\n", - " female\n", - " 35.0\n", - " 53.1000\n", - " S\n", - " Southampton\n", - " United Kindom\n", + " Belgium\n", + " 11.3\n", + " 30510\n", + " Brussels\n", + " 496477.0\n", + " 8.0\n", " \n", " \n", - " 4\n", - " 0\n", - " 3\n", - " male\n", - " 35.0\n", - " 8.0500\n", - " S\n", - " Southampton\n", - " United Kindom\n", + " France\n", + " 64.3\n", + " 671308\n", + " Paris\n", + " 2650823.0\n", + " 9.9\n", " \n", " \n", - " 5\n", - " 0\n", - " 3\n", - " male\n", + " Germany\n", + " 81.3\n", + " 357050\n", + " Berlin\n", + " NaN\n", " NaN\n", - " 8.4583\n", - " Q\n", - " Queenstown\n", - " Ireland\n", - " \n", - " \n", - " 6\n", - " 0\n", - " 1\n", - " male\n", - " 54.0\n", - " 51.8625\n", - " S\n", - " Southampton\n", - " United Kindom\n", - " \n", - " \n", - " 7\n", - " 0\n", - " 3\n", - " male\n", - " 2.0\n", - " 21.0750\n", - " S\n", - " Southampton\n", - " United Kindom\n", " \n", " \n", - " 8\n", - " 1\n", - " 3\n", - " female\n", - " 27.0\n", - " 11.1333\n", - " S\n", - " Southampton\n", - " United Kindom\n", + " Netherlands\n", + " 16.9\n", + " 41526\n", + " Amsterdam\n", + " 820726.0\n", + " 5.7\n", " \n", " \n", - " 9\n", - " 1\n", - " 2\n", - " female\n", - " 14.0\n", - " 30.0708\n", - " C\n", - " Cherbourg\n", - " France\n", + " United Kingdom\n", + " 64.9\n", + " 244820\n", + " London\n", + " NaN\n", + " NaN\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " Survived Pclass Sex Age Fare Embarked City \\\n", - "0 0 3 male 22.0 7.2500 S Southampton \n", - "1 1 1 female 38.0 71.2833 C Cherbourg \n", - "2 1 3 female 26.0 7.9250 S Southampton \n", - "3 1 1 female 35.0 53.1000 S Southampton \n", - "4 0 3 male 35.0 8.0500 S Southampton \n", - "5 0 3 male NaN 8.4583 Q Queenstown \n", - "6 0 1 male 54.0 51.8625 S Southampton \n", - "7 0 3 male 2.0 21.0750 S Southampton \n", - "8 1 3 female 27.0 11.1333 S Southampton \n", - "9 1 2 female 14.0 30.0708 C Cherbourg \n", - "\n", - " Country \n", - "0 United Kindom \n", - "1 France \n", - "2 United Kindom \n", - "3 United Kindom \n", - "4 United Kindom \n", - "5 Ireland \n", - "6 United Kindom \n", - "7 United Kindom \n", - "8 United Kindom \n", - "9 France " + " population area capital GDP area\n", + "country \n", + "Belgium 11.3 30510 Brussels 496477.0 8.0\n", + "France 64.3 671308 Paris 2650823.0 9.9\n", + "Germany 81.3 357050 Berlin NaN NaN\n", + "Netherlands 16.9 41526 Amsterdam 820726.0 5.7\n", + "United Kingdom 64.9 244820 London NaN NaN" ] }, - "execution_count": 24, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.merge(df, locations, on='Embarked', how='left')" + "pd.concat([countries2, country_economics], axis=\"columns\")" ] }, { - "cell_type": "markdown", - "id": "4b1df56c", + "cell_type": "code", + "execution_count": null, + "id": "c420d1a6-5cf6-4efa-868d-0c591459e4e1", "metadata": {}, - "source": [ - "In this case we use `how='left` (a \"left join\") because we wanted to keep the original rows of `df` and only add matching values from `locations` to it. Other options are 'inner', 'outer' and 'right' (see the [docs](http://pandas.pydata.org/pandas-docs/stable/merging.html#brief-primer-on-merge-methods-relational-algebra) for more on this)." - ] + "outputs": [], + "source": [] } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2384,7 +2359,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/_solved/pandas_06_groupby_operations.ipynb b/_solved/pandas_06_groupby_operations.ipynb index b9151dd..b536309 100644 --- a/_solved/pandas_06_groupby_operations.ipynb +++ b/_solved/pandas_06_groupby_operations.ipynb @@ -7,9 +7,7 @@ "source": [ "

06 - Pandas: \"Group by\" operations

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -628,7 +626,9 @@ "execution_count": 10, "id": "613ddc81", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -669,7 +669,9 @@ "execution_count": 11, "id": "970c2e54", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -708,7 +710,9 @@ "execution_count": 12, "id": "6f8e4b59", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -747,7 +751,9 @@ "execution_count": 13, "id": "0ae49b3f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -788,7 +794,9 @@ "execution_count": 14, "id": "6daf3916", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -803,7 +811,7 @@ }, { "data": { - "image/png": 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\n", 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" ] @@ -834,9 +842,7 @@ "cell_type": "code", "execution_count": 15, "id": "bb9d51c0", - "metadata": { - "clear_cell": false - }, + "metadata": {}, "outputs": [], "source": [ "df['AgeClass'] = pd.cut(df['Age'], bins=np.arange(0,90,10))" @@ -847,7 +853,9 @@ "execution_count": 16, "id": "5baf6965", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -862,7 +870,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -1077,7 +1085,7 @@ "id": "7e3afc02", "metadata": {}, "source": [ - "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKajNMa1pfSzN6Q3M) and [`cast.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKal9UYTJSR2ZhSW8) and put them in the `/data` folder." + "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/titles.csv) and [`cast.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/cast.csv) and put them in the `/notebooks/data` folder." ] }, { @@ -1096,7 +1104,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "id": "57f07b5d", "metadata": {}, "outputs": [ @@ -1188,7 +1196,7 @@ "4 Stop Pepper Palmer 2014 Too $hort actor Himself NaN" ] }, - "execution_count": 22, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1211,7 +1219,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "id": "7b38d6e2", "metadata": {}, "outputs": [ @@ -1279,7 +1287,7 @@ "4 The 86 2015" ] }, - "execution_count": 23, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1306,10 +1314,12 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "id": "ffe929fb", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1318,10 +1328,12 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "id": "6afdc68a", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1330,13 +1342,13 @@ "" ] }, - "execution_count": 25, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1366,10 +1378,12 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "id": "37d8a053", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1378,13 +1392,13 @@ "" ] }, - "execution_count": 26, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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" ] @@ -1416,10 +1430,12 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "id": "265aabfe", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1428,13 +1444,13 @@ "" ] }, - "execution_count": 27, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -1466,10 +1482,12 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "id": "d47f2c0f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1489,7 +1507,7 @@ "dtype: int64" ] }, - "execution_count": 28, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -1502,10 +1520,12 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 30, "id": "a7f5a63b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1517,14 +1537,14 @@ "Jayaram 76\n", "Andy Lau 72\n", "Ajay Devgn 69\n", - "Eric Roberts 68\n", "Amitabh Bachchan 68\n", + "Eric Roberts 68\n", "Nagarjuna Akkineni 60\n", "Dilip 59\n", "Name: name, dtype: int64" ] }, - "execution_count": 29, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -1550,10 +1570,12 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "id": "651bce19", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1563,36 +1585,36 @@ "Hamlet (II) 5\n", "Hamlet (III) 2\n", "Han, hun og Hamlet 2\n", - "Harry, Hamlet and I 1\n", - "Hamlet (A Modern Adaptation) 1\n", + "Kitchen Hamlet 1\n", + "Hamlet 2 1\n", + "Kadin Hamlet 1\n", + "Hamlet in the Hamptons 1\n", + "H for Hamlet 1\n", "Predstava 'Hamleta' u Mrdusi Donjoj 1\n", + "Green Eggs and Hamlet 1\n", + "Hamlet A.D.D. 1\n", + "Hamlet (A Modern Adaptation) 1\n", + "Hamlet the Vampire Slayer 1\n", + "Harry, Hamlet and I 1\n", + "National Theatre Live: Hamlet 1\n", "Hamlet_X 1\n", - "Hamlet's Ghost 1\n", - "H for Hamlet 1\n", - "Fuck Hamlet 1\n", - "Hamlet, Son of a Kingpin 1\n", - "Hamlet liikemaailmassa 1\n", - "Kadin Hamlet 1\n", + "A Sagebrush Hamlet 1\n", + "Hamlet, Prince of Denmark 1\n", "The Tragedy of Hamlet Prince of Denmark 1\n", - "National Theatre Live: Hamlet 1\n", - "Hamlet: Prince of Denmark 1\n", - "Hamlet A.D.D. 1\n", "Hamlet: The Fall of a Sparrow 1\n", - "Zombie Hamlet 1\n", - "Dogg's Hamlet, Cahoot's Macbeth 1\n", - "A Sagebrush Hamlet 1\n", - "Hamlet in the Hamptons 1\n", - "Hamlet 2 1\n", "Hamlet Unbound 1\n", - "Kitchen Hamlet 1\n", - "Hamlet the Vampire Slayer 1\n", - "Green Eggs and Hamlet 1\n", - "Hamlet, Prince of Denmark 1\n", + "Hamlet: Prince of Denmark 1\n", + "Fuck Hamlet 1\n", "Hamlet X 1\n", + "Hamlet, Son of a Kingpin 1\n", + "Dogg's Hamlet, Cahoot's Macbeth 1\n", + "Zombie Hamlet 1\n", + "Hamlet liikemaailmassa 1\n", + "Hamlet's Ghost 1\n", "Name: title, dtype: int64" ] }, - "execution_count": 30, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1604,10 +1626,12 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 32, "id": "9cf43c6b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1616,24 +1640,24 @@ "Hamlet 19\n", "Hamlet (II) 5\n", "Hamlet (III) 2\n", - "Hamlet: Prince of Denmark 1\n", - "Hamlet: The Fall of a Sparrow 1\n", + "Hamlet 2 1\n", "Hamlet A.D.D. 1\n", - "Hamlet_X 1\n", "Hamlet's Ghost 1\n", - "Hamlet liikemaailmassa 1\n", - "Hamlet, Son of a Kingpin 1\n", + "Hamlet: The Fall of a Sparrow 1\n", + "Hamlet Unbound 1\n", + "Hamlet: Prince of Denmark 1\n", "Hamlet in the Hamptons 1\n", + "Hamlet, Son of a Kingpin 1\n", + "Hamlet_X 1\n", "Hamlet (A Modern Adaptation) 1\n", - "Hamlet 2 1\n", - "Hamlet Unbound 1\n", "Hamlet the Vampire Slayer 1\n", - "Hamlet, Prince of Denmark 1\n", + "Hamlet liikemaailmassa 1\n", "Hamlet X 1\n", + "Hamlet, Prince of Denmark 1\n", "Name: title, dtype: int64" ] }, - "execution_count": 31, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1660,10 +1684,12 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 33, "id": "5ab64a23", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1682,7 +1708,7 @@ "Name: title, dtype: int64" ] }, - "execution_count": 32, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -1694,10 +1720,12 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 34, "id": "2f51c366", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1817,7 +1845,7 @@ "187654 1935 1930 " ] }, - "execution_count": 33, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } @@ -1844,10 +1872,12 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 35, "id": "fd57aac5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1877,7 +1907,7 @@ "dtype: int64" ] }, - "execution_count": 34, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -1905,10 +1935,12 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 36, "id": "b97feb82", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1928,7 +1960,7 @@ "Name: character, dtype: int64" ] }, - "execution_count": 35, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -1954,10 +1986,12 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 37, "id": "4057c09f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1966,13 +2000,13 @@ "" ] }, - "execution_count": 36, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -2002,29 +2036,31 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 38, "id": "c3c80c4f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "The Life of Riley 3\n", - "The Life of the Party 3\n", - "The Life Coach 2\n", - "The Life and the Agony 1\n", - "The Life and Death of Peter Sellers 1\n", - "The Lifeguardsman 1\n", - "The Life Exchange 1\n", - "The Life of Buddha 1\n", - "The Life and Adventures of Nicholas Nickleby 1\n", - "The Life of a Jackeroo 1\n", + "The Life of Riley 3\n", + "The Life of the Party 3\n", + "The Life Coach 2\n", + "The Life Ballet 1\n", + "The Life of Buddha 1\n", + "The Life 1\n", + "The Life and Death of Peter Sellers 1\n", + "The Life of Lord Kitchener 1\n", + "The Life Zindagi 1\n", + "The Life Line 1\n", "Name: title, dtype: int64" ] }, - "execution_count": 37, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -2050,10 +2086,12 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 39, "id": "a38a3d15", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2061,18 +2099,18 @@ "text/plain": [ "Lloyd Kaufman 23\n", "Jagathi Sreekumar 20\n", - "Chris (II) Eddy 20\n", "Suraaj Venjarammoodu 20\n", + "Chris (II) Eddy 20\n", "Danny Trejo 17\n", "Matt Simpson Siegel 17\n", - "Ben (II) Bishop 15\n", "Joe Estevez 15\n", - "Kyle Rea 15\n", + "Ben (II) Bishop 15\n", "Brahmanandam 15\n", + "Kyle Rea 15\n", "Name: name, dtype: int64" ] }, - "execution_count": 38, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -2098,10 +2136,12 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 40, "id": "d80c0f2b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2152,7 +2192,7 @@ "2006 50.0" ] }, - "execution_count": 39, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -2179,10 +2219,12 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 41, "id": "2a8f6351", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2202,7 +2244,7 @@ "dtype: int64" ] }, - "execution_count": 40, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -2230,10 +2272,12 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 42, "id": "c38ff395", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2251,7 +2295,7 @@ "dtype: int64" ] }, - "execution_count": 41, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -2269,20 +2313,28 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "**EXERCISE**\n", + "\n", + "Add a new column to the `cast` DataFrame that indicates the number of roles for each movie. \n", + " \n", + "
Hints\n", + "\n", + "- [Transformation](https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#transformation) returns an object that is indexed the same (same size) as the one being grouped.\n", + "\n", + "
\n", + " \n", "\n", - "
    \n", - "
  • Add a new column to the `cast` DataFrame that indicates the number of roles for each movie. [Hint](http://pandas.pydata.org/pandas-docs/stable/groupby.html#transformation)
    • \n", - "
\n", "
" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 58, "id": "77eee4f6", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2324,7 +2376,7 @@ " actor\n", " Guests\n", " 22.0\n", - " 22.0\n", + " 24\n", " \n", " \n", " 1\n", @@ -2334,7 +2386,7 @@ " actor\n", " Himself\n", " NaN\n", - " NaN\n", + " 24\n", " \n", " \n", " 2\n", @@ -2344,7 +2396,7 @@ " actor\n", " Lew-Loc\n", " 27.0\n", - " 45.0\n", + " 47\n", " \n", " \n", " 3\n", @@ -2354,7 +2406,7 @@ " actor\n", " Bosco\n", " 3.0\n", - " 9.0\n", + " 34\n", " \n", " \n", " 4\n", @@ -2364,7 +2416,7 @@ " actor\n", " Himself\n", " NaN\n", - " NaN\n", + " 34\n", " \n", " \n", "\n", @@ -2379,20 +2431,20 @@ "4 Stop Pepper Palmer 2014 Too $hort actor Himself NaN \n", "\n", " n_total \n", - "0 22.0 \n", - "1 NaN \n", - "2 45.0 \n", - "3 9.0 \n", - "4 NaN " + "0 24 \n", + "1 24 \n", + "2 47 \n", + "3 34 \n", + "4 34 " ] }, - "execution_count": 42, + "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "cast['n_total'] = cast.groupby(['title', 'year'])['n'].transform('max') # transform will return an element for each row, so the max value is given to the whole group\n", + "cast['n_total'] = cast.groupby(['title', 'year'])['n'].transform('size') # transform will return an element for each row, so the size value is given to the whole group\n", "cast.head()" ] }, @@ -2418,7 +2470,9 @@ "execution_count": 43, "id": "708d707b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2470,7 +2524,9 @@ "execution_count": 44, "id": "ddbac330", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2522,7 +2578,9 @@ "execution_count": 45, "id": "7cf5a472", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2571,7 +2629,9 @@ "execution_count": 46, "id": "a5867953", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2613,7 +2673,9 @@ "execution_count": 47, "id": "1caad935", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2640,7 +2702,9 @@ "execution_count": 48, "id": "fe757699", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2664,6 +2728,9 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/_solved/pandas_07_reshaping_data.ipynb b/_solved/pandas_07_reshaping_data.ipynb index c3ffc5e..0b2a139 100644 --- a/_solved/pandas_07_reshaping_data.ipynb +++ b/_solved/pandas_07_reshaping_data.ipynb @@ -7,9 +7,7 @@ "source": [ "

07 - Pandas: Reshaping data

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -17,14 +15,15 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 13, "id": "270512af", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" ] }, { @@ -382,7 +381,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 20, "id": "f23c70b6", "metadata": {}, "outputs": [], @@ -395,7 +394,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 21, "id": "4435bd03", "metadata": {}, "outputs": [ @@ -483,7 +482,7 @@ "5 13.0000 2 male 1" ] }, - "execution_count": 8, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -494,7 +493,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 22, "id": "3a999ee9", "metadata": {}, "outputs": [ @@ -556,7 +555,7 @@ "3 7.8542 7.2500" ] }, - "execution_count": 9, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -567,7 +566,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 23, "id": "47c55cc9", "metadata": {}, "outputs": [ @@ -629,7 +628,7 @@ "3 0 0" ] }, - "execution_count": 10, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -656,7 +655,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 24, "id": "f5eeb481", "metadata": {}, "outputs": [], @@ -666,7 +665,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 25, "id": "3e902ec3", "metadata": {}, "outputs": [ @@ -808,7 +807,7 @@ "4 0 373450 8.0500 NaN S " ] }, - "execution_count": 12, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -827,7 +826,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 26, "id": "563610d4", "metadata": {}, "outputs": [ @@ -856,7 +855,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 27, "id": "2948f0eb", "metadata": {}, "outputs": [ @@ -909,7 +908,7 @@ "3 female 1 53.1000" ] }, - "execution_count": 14, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -949,12 +948,12 @@ "id": "a83de3ae", "metadata": {}, "source": [ - "# Pivot tables - aggregating while pivoting" + "## Pivot tables - aggregating while pivoting" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 28, "id": "ae2f767c", "metadata": {}, "outputs": [], @@ -964,7 +963,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 29, "id": "4109424e", "metadata": {}, "outputs": [ @@ -1024,7 +1023,7 @@ "male 67.226127 19.741782 12.661633" ] }, - "execution_count": 16, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -1049,7 +1048,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 30, "id": "56e3a68e", "metadata": {}, "outputs": [ @@ -1109,7 +1108,7 @@ "male 512.3292 73.5 69.55" ] }, - "execution_count": 17, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -1121,7 +1120,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 31, "id": "d648d80f", "metadata": {}, "outputs": [ @@ -1181,7 +1180,7 @@ "male 122 108 347" ] }, - "execution_count": 18, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1208,7 +1207,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 32, "id": "b9cf345c", "metadata": {}, "outputs": [ @@ -1268,7 +1267,7 @@ "male 122 108 347" ] }, - "execution_count": 19, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1277,6 +1276,14 @@ "pd.crosstab(index=df['Sex'], columns=df['Pclass'])" ] }, + { + "cell_type": "markdown", + "id": "20524f03-4971-465f-b610-73c39a89be49", + "metadata": {}, + "source": [ + "## Exercises" + ] + }, { "cell_type": "markdown", "id": "5916201b", @@ -1296,10 +1303,12 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 33, "id": "f1c056b4", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1360,7 +1369,7 @@ "3 0.500000 0.135447" ] }, - "execution_count": 20, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -1372,10 +1381,12 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 34, "id": "d2137b87", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1384,7 +1395,7 @@ "Text(0, 0.5, 'Survival ratio')" ] }, - "execution_count": 21, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, @@ -1429,10 +1440,12 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 35, "id": "a369f84c", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1441,10 +1454,12 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 36, "id": "a32d5f69", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -1499,7 +1514,7 @@ "True 20.2875 20.2500" ] }, - "execution_count": 23, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -1519,15 +1534,15 @@ }, { "cell_type": "markdown", - "id": "399ca374", + "id": "5251dca0-9e04-4f5b-91d4-f24b35443e2f", "metadata": {}, "source": [ - "The `melt` function performs the inverse operation of a `pivot`. This can be used to make your frame longer, i.e. to make a *tidy* version of your data." + "The `melt` function performs the inverse operation of a `pivot`." ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 37, "id": "0112108d", "metadata": {}, "outputs": [], @@ -1538,7 +1553,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 38, "id": "0a1c2d62", "metadata": {}, "outputs": [ @@ -1594,7 +1609,7 @@ "1 male 67.226127 19.741782 12.661633" ] }, - "execution_count": 25, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -1608,12 +1623,12 @@ "id": "850d7dbe", "metadata": {}, "source": [ - "Assume we have a DataFrame like the above. The observations (the average Fare people payed) are spread over different columns. In a tidy dataset, each observation is stored in one row. To obtain this, we can use the `melt` function:" + "Assume we have a DataFrame like the above. The observations (the average Fare people payed) are spread over different columns. To make sure each value is in its own row, we can use the `melt` function:" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 39, "id": "f4c39b5d", "metadata": {}, "outputs": [ @@ -1699,7 +1714,7 @@ "7 3 12.661633" ] }, - "execution_count": 26, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -1720,7 +1735,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 40, "id": "46fc91cd", "metadata": {}, "outputs": [ @@ -1801,7 +1816,7 @@ "5 male 3 12.661633" ] }, - "execution_count": 27, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -1810,6 +1825,308 @@ "pd.melt(pivoted, id_vars=['Sex']) #, var_name='Pclass', value_name='Fare')" ] }, + { + "cell_type": "markdown", + "id": "399ca374", + "metadata": {}, + "source": [ + "## Tidy data\n", + "\n", + "`melt `can be used to make a dataframe longer, i.e. to make a *tidy* version of your data. In a [tidy dataset](https://vita.had.co.nz/papers/tidy-data.pdf) (also sometimes called 'long-form' data or 'denormalized' data) each observation is stored in its own row and each column contains a single variable:\n", + "\n", + "![](../img/tidy_data_scheme.png)\n", + "\n", + "Consider the following example with measurements in different Waste Water Treatment Plants (WWTP):" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "0e50cec8-1244-43c6-b14e-f06e32deacc3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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WWTPTreatment ATreatment B
0Destelbergen8.06.3
1Landegem7.55.2
2Dendermonde8.36.2
3Eeklo6.57.2
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" + ], + "text/plain": [ + " WWTP Treatment A Treatment B\n", + "0 Destelbergen 8.0 6.3\n", + "1 Landegem 7.5 5.2\n", + "2 Dendermonde 8.3 6.2\n", + "3 Eeklo 6.5 7.2" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = pd.DataFrame({\n", + " 'WWTP': ['Destelbergen', 'Landegem', 'Dendermonde', 'Eeklo'],\n", + " 'Treatment A': [8.0, 7.5, 8.3, 6.5],\n", + " 'Treatment B': [6.3, 5.2, 6.2, 7.2]\n", + "})\n", + "data" + ] + }, + { + "cell_type": "markdown", + "id": "71ca855d-552a-4c04-9a07-fa5ea30bf3a2", + "metadata": {}, + "source": [ + "This data representation is not \"tidy\":\n", + "\n", + "- Each row contains two observations of pH (each from a different treatment)\n", + "- 'Treatment' (A or B) is a variable not in its own column, but used as column headers" + ] + }, + { + "cell_type": "markdown", + "id": "19252f37-e9c7-46b3-9e69-718312f4dabe", + "metadata": {}, + "source": [ + "We can `melt` the data set to tidy the data:" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "11ac8b4f-942a-4711-a689-8a66960fbbdc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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WWTPTreatmentpH
0DestelbergenTreatment A8.0
1LandegemTreatment A7.5
2DendermondeTreatment A8.3
3EekloTreatment A6.5
4DestelbergenTreatment B6.3
5LandegemTreatment B5.2
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" + ], + "text/plain": [ + " WWTP Treatment pH\n", + "0 Destelbergen Treatment A 8.0\n", + "1 Landegem Treatment A 7.5\n", + "2 Dendermonde Treatment A 8.3\n", + "3 Eeklo Treatment A 6.5\n", + "4 Destelbergen Treatment B 6.3\n", + "5 Landegem Treatment B 5.2\n", + "6 Dendermonde Treatment B 6.2\n", + "7 Eeklo Treatment B 7.2" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_long = pd.melt(data, id_vars=[\"WWTP\"], \n", + " value_name=\"pH\", var_name=\"Treatment\")\n", + "data_long" + ] + }, + { + "cell_type": "markdown", + "id": "09f947e8-70dd-485c-9c25-0125d22b3f9d", + "metadata": {}, + "source": [ + "The usage of the tidy data representation has some important benefits when working with `groupby` or data visualization libraries such as Seaborn:" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "93d18784-c36a-4845-9bf9-d8855e4a7d69", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Treatment\n", + "Treatment A 7.575\n", + "Treatment B 6.225\n", + "Name: pH, dtype: float64" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_long.groupby(\"Treatment\")[\"pH\"].mean() # switch to `WWTP`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dd2a72f7-695d-4411-9fec-989d358d76ab", + "metadata": {}, + "outputs": [], + "source": [ + "sns.catplot(data=data, x=\"WWTP\", y=\"...\", hue=\"...\", kind=\"bar\") # this doesn't work that easily" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "507af344-ec3d-40d2-a407-cfa732a5670e", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.catplot(data=data_long, x=\"WWTP\", y=\"pH\", \n", + " hue=\"Treatment\", kind=\"bar\") # switch `WWTP` and `Treatment`" + ] + }, { "cell_type": "markdown", "id": "5b2c8ee2", @@ -2345,6 +2662,14 @@ "df.head()" ] }, + { + "cell_type": "markdown", + "id": "43fe898c-8bf3-4819-ac2a-de07a948cec3", + "metadata": {}, + "source": [ + "## Exercises" + ] + }, { "cell_type": "code", "execution_count": 34, @@ -2441,7 +2766,9 @@ "execution_count": 35, "id": "0fee61fb", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2524,7 +2851,7 @@ "id": "45ce16c2", "metadata": {}, "source": [ - "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKajNMa1pfSzN6Q3M) and [`cast.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKal9UYTJSR2ZhSW8) and put them in the `/data` folder." + "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/titles.csv) and [`cast.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/cast.csv) and put them in the `/notebooks/data` folder." ] }, { @@ -2731,7 +3058,9 @@ "execution_count": 38, "id": "97cd998b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2768,7 +3097,9 @@ "execution_count": 39, "id": "165b1114", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2804,7 +3135,9 @@ "execution_count": 40, "id": "831a9220", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2854,7 +3187,9 @@ "execution_count": 41, "id": "6426434f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2904,7 +3239,9 @@ "execution_count": 42, "id": "391718f5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -2956,7 +3293,9 @@ "execution_count": 43, "id": "d49401d5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -3048,7 +3387,9 @@ "execution_count": 44, "id": "8c75667b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { @@ -3068,8 +3409,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -3083,7 +3427,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/_solved/pandas_08_missing_values.ipynb b/_solved/pandas_08_missing_values.ipynb index 1c04970..9300a45 100644 --- a/_solved/pandas_08_missing_values.ipynb +++ b/_solved/pandas_08_missing_values.ipynb @@ -7,9 +7,7 @@ "source": [ "

08 - Pandas: Working with missing data

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -755,8 +753,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -770,7 +771,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/_solved/visualization_01_matplotlib.ipynb b/_solved/visualization_01_matplotlib.ipynb index cb2d5c8..01ad3f9 100644 --- a/_solved/visualization_01_matplotlib.ipynb +++ b/_solved/visualization_01_matplotlib.ipynb @@ -6,12 +6,9 @@ "source": [ "

Visualization - Matplotlib

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", - "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", + "> *© 2021, Joris Van den Bossche and Stijn Van Hoey. Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", - "---\n" + "---" ] }, { @@ -43,15 +40,11 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", + "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, @@ -59,7 +52,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## - dry stuff - The matplotlib `Figure`, `axes` and `axis`\n", + "## - dry stuff - The matplotlib `Figure`, `Axes` and `Axis`\n", "\n", "At the heart of **every** plot is the figure object. The \"Figure\" object is the top level concept which can be drawn to one of the many output formats, or simply just to screen. Any object which can be drawn in this way is known as an \"Artist\" in matplotlib.\n", "\n", @@ -69,12 +62,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -107,16 +95,11 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "
" ] @@ -131,46 +114,6 @@ "ax = plt.axes()" ] }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "matplotlib.axes._subplots.AxesSubplot" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "type(ax)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(matplotlib.axis.XAxis, matplotlib.axis.YAxis)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "type(ax.xaxis), type(ax.yaxis)" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -196,13 +139,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 4, + "metadata": {}, "outputs": [], "source": [ "x = np.linspace(0, 5, 10)\n", @@ -220,32 +158,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**1. pyplot style: plt...** (you will see this a lot for code online!)" + "**1. pyplot style: plt.** (you will see this a lot for code online!)" ] }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", 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" ] @@ -257,39 +180,33 @@ } ], "source": [ - "plt.plot(x, y, '-')" + "ax = plt.plot(x, y, '-')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**2. creating objects**" + "**2. object oriented**" ] }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from matplotlib import ticker" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -301,8 +218,14 @@ } ], "source": [ + "x = np.linspace(0, 5, 10)\n", + "y = x ** 10\n", + "\n", "fig, ax = plt.subplots()\n", - "ax.plot(x, y, '-')" + "ax.plot(x, y, '-')\n", + "ax.set_title(\"My data\")\n", + "\n", + "ax.yaxis.set_major_formatter(ticker.FormatStrFormatter(\"%.1f\"))" ] }, { @@ -314,27 +237,22 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -355,6 +273,15 @@ "ax2.plot(x, y*2, 'r-')" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And also Matplotlib advices the object oriented style:\n", + "\n", + "![](../img/matplotlib_oo.png)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -364,7 +291,7 @@ "REMEMBER:\n", "\n", "
    \n", - "
  • Use the object oriented power of Matplotlib!
    • \n", + "
  • Use the object oriented power of Matplotlib
    • \n", "
  • Get yourself used to writing fig, ax = plt.subplots()
    • \n", "
\n", "
" @@ -372,27 +299,22 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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" ] @@ -418,27 +340,22 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -461,8 +378,10 @@ "ax.plot(x, x**3, color='0.8', linestyle='--', label='power 3')\n", "\n", "ax.vlines(x=-0.75, ymin=0., ymax=0.8, color='0.4', linestyle='-.') \n", + "ax.fill_between(x=x, y1=x**2, y2=1.1*x**2, color='0.85')\n", + "\n", "ax.axhline(y=0.1, color='0.4', linestyle='-.')\n", - "ax.fill_between(x=[-1, 1.1], y1=[0.65], y2=[0.75], color='0.85')\n", + "ax.axhspan(ymin=0.65, ymax=0.75, color='0.95')\n", "\n", "fig.suptitle('Figure title', fontsize=18, \n", " fontweight='bold')\n", @@ -477,11 +396,16 @@ "ax.text(0.5, 0.2, 'Text centered at (0.5, 0.2)\\nin data coordinates.',\n", " horizontalalignment='center', fontsize=14)\n", "\n", - "ax.text(0.5, 0.5, 'Text centered at (0.5, 0.5)\\nin Figure coordinates.',\n", + "ax.text(0.5, 0.5, 'Text centered at (0.5, 0.5)\\nin relative Axes coordinates.',\n", " horizontalalignment='center', fontsize=14, \n", " transform=ax.transAxes, color='grey')\n", "\n", - "ax.legend(loc='upper right', frameon=True, ncol=2, fontsize=14)" + "ax.annotate('Text pointing at (0.0, 0.75)', xy=(0.0, 0.75), xycoords=\"data\",\n", + " xytext=(20, 40), textcoords=\"offset points\",\n", + " horizontalalignment='left', fontsize=14,\n", + " arrowprops=dict(facecolor='black', shrink=0.05, width=1))\n", + "\n", + "ax.legend(loc='lower right', frameon=True, ncol=2, fontsize=14)" ] }, { @@ -500,6 +424,217 @@ "For more information on legend positioning, check [this post](http://stackoverflow.com/questions/4700614/how-to-put-the-legend-out-of-the-plot) on stackoverflow!" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exercises" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For these exercises we will use some random generated example data (as a Numpy array), representing daily measured values:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ -2, -1, -1, -1, 0, 2, 0, 0, -1, 1, 0, -2, -4,\n", + " -4, -2, 0, -2, -3, -4, -2, -2, -2, -3, -1, -2, -4,\n", + " -6, -5, -6, -8, -7, -9, -10, -10, -9, -7, -9, -7, -6,\n", + " -5, -4, -4, -4, -2, -3, -1, 0, 1, 1, 2, 4, 3,\n", + " 3, 5, 4, 3, 4, 5, 5, 5, 3, 2, 0, -1, -2,\n", + " -1, -2, 0, -2, -2, -3, -3, -4, -5, -4, -2, 0, -2,\n", + " -4, -4, -3, -1, -2, 0, 1, 1, 1, 0, 1, 3, 3,\n", + " 1, 0, 0, -2, -4, -5, -4, -2, -3])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = np.random.randint(-2, 3, 100).cumsum()\n", + "data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Make a line chart of the `data` using Matplotlib. The figure should be 12 (width) by 4 (height) in inches. Make the line color 'darkgrey' and provide an x-label ('days since start') and a y-label ('measured value').\n", + " \n", + "Use the object oriented approach to create the chart.\n", + "\n", + "
Hints\n", + "\n", + "- When Matplotlib only receives a single input variable, it will interpret this as the variable for the y-axis\n", + "- Check the cheat sheet above for the functions.\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(12, 4))\n", + "\n", + "ax.plot(data, color='darkgrey')\n", + "ax.set_xlabel('days since start');\n", + "ax.set_ylabel('measured value');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "The data represents each a day starting from Jan 1st 2021. Create an array (variable name `dates`) of the same length as the original data (length 100) with the corresponding dates ('2021-01-01', '2021-01-02',...). Create the same chart as in the previous exercise, but use the `dates` values for the x-axis data.\n", + " \n", + "Mark the region inside `[-5, 5]` with a green color to show that these values are within an acceptable range.\n", + "\n", + "
Hints\n", + "\n", + "- As seen in notebook `pandas_04_time_series_data`, Pandas provides a useful function `pd.date_range` to create a set of datetime values. In this case 100 values with `freq=\"D\"`.\n", + "- Make sure to understand the difference between `axhspan` and `fill_between`, which one do you need?\n", + "- When adding regions, adding an `alpha` level is mostly a good idea.\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "dates = pd.date_range(\"2021-01-01\", periods=100, freq=\"D\")\n", + "\n", + "fig, ax = plt.subplots(figsize=(12, 4))\n", + "\n", + "ax.plot(dates, data, color='darkgrey')\n", + "ax.axhspan(ymin=-5, ymax=5, color='green', alpha=0.2)\n", + "\n", + "ax.set_xlabel('days since start');\n", + "ax.set_ylabel('measured value');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Compare the __last ten days__ ('2021-04-01' till '2021-04-10') in a bar chart using darkgrey color. For the data on '2021-04-01', use an orange bar to highlight the measurement on this day.\n", + "\n", + "
Hints\n", + "\n", + "- Select the last 10 days from the `data` and `dates` variable, i.e. slice [-10:].\n", + "- Similar to a `plot` method, Matplotlib provides a `bar` method.\n", + "- By plotting a single orange bar on top of the grey bars with a second bar chart, that one is highlithed.\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(12, 4))\n", + "\n", + "ax.bar(dates[-10:], data[-10:], color='darkgrey')\n", + "ax.bar(dates[-6], data[-6], color='orange')" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -533,12 +668,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -583,18 +713,13 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -604,7 +729,7 @@ "source": [ "x = np.linspace(0, 10)\n", "\n", - "with plt.style.context('seaborn'): # 'seaborn', ggplot', 'bmh', 'grayscale', 'seaborn-whitegrid', 'seaborn-muted'\n", + "with plt.style.context('seaborn-whitegrid'): # 'seaborn', ggplot', 'bmh', 'grayscale', 'seaborn-whitegrid', 'seaborn-muted'\n", " fig, ax = plt.subplots()\n", " ax.plot(x, np.sin(x) + x + np.random.randn(50))\n", " ax.plot(x, np.sin(x) + 0.5 * x + np.random.randn(50))\n", @@ -615,43 +740,131 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We should not start discussing about colors and styles, just pick **your favorite style**!" + "We should not start discussing about colors and styles, just pick **your favorite style**!" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [], + "source": [ + "plt.style.use('seaborn')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "or go all the way and define your own custom style, see the [official documentation](https://matplotlib.org/3.1.1/tutorials/introductory/customizing.html) or [this tutorial](https://colcarroll.github.io/yourplotlib/#/)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "REMEMBER:\n", + "\n", + "* If you just want **quickly a good-looking plot**, use one of the available styles (`plt.style.use('...')`)\n", + "* Otherwise, creating `Figure` and `Axes` objects makes it possible to change everything!\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Advanced subplot configuration" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The function to setup a Matplotlib Figure we have seen up to now, `fig, ax = plt.subplots()`, supports creating both a single plot and multiple subplots with a regular number of rows/columns:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(2, 3, figsize=(5, 5))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A typical issue when plotting multiple elements in the same Figure is the overlap of the subplots. A straight-forward approach is using a larger Figure size, but this is not always possible and does not make the content independent from the Figure size. Matplotlib provides the usage of a [__constrained-layout__](https://matplotlib.org/stable/tutorials/intermediate/constrainedlayout_guide.html) to fit plots within your Figure cleanly." ] }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "plt.style.use('seaborn-whitegrid')" + "fig, ax = plt.subplots(2, 3, figsize=(5, 5), constrained_layout=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "or go all the way and define your own custom style, see the [official documentation](https://matplotlib.org/3.1.1/tutorials/introductory/customizing.html) or [this tutorial](https://colcarroll.github.io/yourplotlib/#/)." + "When more advanced layout configurations are required, the usage of the [gridspec](https://matplotlib.org/stable/api/gridspec_api.html#module-matplotlib.gridspec) module is a good reference. See [gridspec demo](https://matplotlib.org/stable/gallery/userdemo/demo_gridspec03.html#sphx-glr-gallery-userdemo-demo-gridspec03-py) for more information. A useful shortcut to know about is the [__string-shorthand__](https://matplotlib.org/stable/tutorials/provisional/mosaic.html#string-short-hand) to setup subplot layouts in a more intuitive way, e.g." ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 17, "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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7IjCRpaSkaPjw4f2OxeP1o5/oJ2CwIhZwL/4FtAaw/DuRhZqfJK1bt05fffWVqqqq1NLSolOnTsW6xKiJx+tHP9FPwGBFLOBMX/4dan6S9OGHH8rpdCo1NVXz58/XL7/8Eo8yoyIerx/9RD8BgxWxgDN9+Xeo+fX09GjFihV6/PixJOncuXOaOHFi3GqNtHi8fvQT/QQMVsSe6G33SPktW7Zow4YNkqR3331XBQUFkfrRMWE3v9///vdyu91KS0vTlClT9Kc//SneJb+S5uZm7dixQzdu3FBKSopqampUVFSk/Pz8uLx+9BP9BAxWWJ+DA4Chjs/BDV0Dfe144CkAwEgEHADASAQcAMBIBBwAwEgEHADASAQcAMBIBBwAwEgEHADASAQcAMBIBBwAwEgEHADASAQcAMBIBBwAwEhhBdzly5dVXFys77///qWx2tpaLV68WG63W/v37494gQAADIRtwD148EDbtm3TnDlz+h2vqKjQ3r17dfjwYZ09e1ZtbW0RLxIAgFdlG3BpaWk6ePCgcnJyXhq7du2aRowYoby8PCUlJWnevHmqq6uLSqEAALwK24BLSUnR8OHD+x3r7u5WZmZm8Dg7O1vd3d2Rqw4AgAFKGcx/3N/DwB0Ox0t/1tjYOJgfA8Agpj5VG4lnUAGXm5srv98fPO7s7NTIkSP7/V6Tmtqkx8ObNBeJ+SQ6/rGLWBrUxwTy8/MVCAR0/fp1PXnyRKdPn1ZhYWGkagMAYMBs38E1Nzdrx44dunHjhlJSUlRTU6OioiLl5+erpKREW7Zs0YYNGyRJ7777rgoKCqJeNAAAdmwDburUqaqqqvrN8bfeekvV1dURLQoAgMFiJxMAgJEIOACAkQg4AICRCDgAQ4LX65Xb7ZbH49GFCxf6/Z5du3bpo48+inFlSFSD+hwcAMRCQ0ODOjo6VF1drba2Nm3atEnHjh3r8z1tbW06d+6cUlNT41QlEg3v4AAkvLq6OhUXF0uSJkyYoHv37ikQCPT5nsrKSq1bty4e5SFBEXAAEp7f71dGRkbwOCsrq8++tz6fT7Nnz9aYMWPiUR4SFLcoASS8F/e9tSwruO/t3bt35fP59O2336qzszPkeVpbW6NWYzz19vYaO7fBIOAAJLwX973t6upSdna2JKm+vl49PT1asmSJ/vOf/+hf//qXvF6vysrKXjqPSft6/pppe5a+aKB7mHKLEkDCKywsVE1NjSSppaVFOTk5cjqdkqQFCxboxIkTOnr0qPbt2yeXy9VvuOH1wzs4AAlv5syZcrlc8ng8cjgcKi8vl8/nU3p6ukpKSuJdHhIUAQdgSNi4cWOf40mTJr30Pfn5+SH3zsXrhVuUAAAjEXAAACMRcAAAI4X1Oziv16umpiY5HA6VlZVp2rRpwbFDhw7pxx9/VFJSkqZOnaovvvgiasUCABAu24ALtQdcIBDQN998o1OnTiklJUXLli3T+fPnNX369GjXDQBASLa3KEPtAZeamqrU1FQ9ePBAT5480cOHDzVixIjoVgwAQBhs38H5/X65XK7g8fM94JxOp4YNG6bVq1eruLhYw4cP13vvvaeCgoJ+z2PSNjImbYtj0lwk5gPgf2wDLtQecIFAQAcOHNDJkyfldDq1dOlSXbp0qd/Pp5i0jYxJ2+KYNBeJ+SS6gW65BAyE7S3KUHvAtbe3a+zYscrMzFRaWppmzZql5ubm6FULAECYbAMu1B5wY8aMUXt7u3p7e2VZlpqbmzV+/PioFgwAQDhsb1Ha7QG3fPlyffzxx0pOTtaMGTM0a9asWNQNAEBIYX0OLtQecB6PRx6PJ7JVAQAwSOxkAgAwEgEHADASAQcAMBIBBwAwEgEHADASAQcAMBIBBwAwEgEHADASAQcAMBIBBwAwEgEHADASAQcAMBIBBwAwEgEHADBSWI/L8Xq9ampqksPhUFlZmaZNmxYcu3XrltavX6/Hjx9rypQp2rp1a9SKBQAgXLbv4BoaGtTR0aHq6mpVVFRo27ZtfcYrKyu1bNkyHT9+XMnJybp582bUigUAIFy2AVdXV6fi4mJJ0oQJE3Tv3j0FAgFJ0rNnz9TY2KiioiJJUnl5uUaPHh3FcgEACI9twPn9fmVkZASPs7Ky1N3dLUnq6emR0+nUnj17VFpaql27dsmyrOhVCwBAmGx/B/diYFmWJYfDEfy6s7NTixYt0po1a7Ry5UqdOXNG8+fPf+k8ra2tkak4AfT29hozH5PmIjEfAP9jG3C5ubny+/3B466uLmVnZ0uSMjIylJeXp3HjxkmS5syZoytXrvQbcJMnT45QyfHX2tpqzHxMmovEfBJdY2NjvEvAa8T2FmVhYaFqamokSS0tLcrJyZHT6ZQkpaSkaOzYsbp69aok6eLFiyooKIhetQAAhMn2HdzMmTPlcrnk8XjkcDhUXl4un8+n9PR0lZSUqKysTOXl5Xr06JEmTpwYXHACAEA8hfU5uI0bN/Y5njRpUvDrN954Q999911EiwIAYLDYyQQAYCQCDgBgJAIOAGAkAg4AYCQCDgBgJAIOAGAkAg4AYCQCDgBgJAIOAGCksHYyAYB483q9ampqksPhUFlZmaZNmxYcq6+v1+7du5WUlKSCggJt375dSUn8+/11RwcASHgNDQ3q6OhQdXW1KioqtG3btj7jmzdv1p49e3TkyBHdv39fZ8+ejVOlSCQEHICEV1dXp+LiYknShAkTdO/ePQUCgeC4z+fTqFGjJEmZmZm6c+dOXOpEYuEWJYCE5/f75XK5gsdZWVnq7u4OPrrr+f92dXWptrZWa9eu7fc8pj48lgfj9o+AA5DwLMt66djhcPT5s9u3b2vVqlXavHmzMjIy+j2PSQ+P/TXTHoz7ooE+KJdblAASXm5urvx+f/C4q6tL2dnZweNAIKAVK1Zo7dq1mjt3bjxKRAIKK+C8Xq/cbrc8Ho8uXLjQ7/fs2rVLH330UUSLAwBJKiwsVE1NjSSppaVFOTk5wduSklRZWamlS5dq3rx58SoRCcj2FuWvVy+1tbVp06ZNOnbsWJ/vaWtr07lz55Samhq1QgG8vmbOnCmXyyWPxyOHw6Hy8nL5fD6lp6dr7ty5+uGHH9TR0aHjx49LkhYuXCi32x3nqhFvtgH3W6uXXvzX07p167Rv377oVQrgtbZx48Y+x5MmTQp+3dzcHOtyMATYBpzd6iWfz6fZs2drzJgxIc9j0gofk1YsmTQXifkA+B/bgAu1eunu3bvy+Xz69ttv1dnZGfI8Jq3wMWnFkklzkZhPohvoajhgIGwXmYRavVRfX6+enh4tWbJEn3/+uS5evCiv1xu9agEACJNtwIVavbRgwQKdOHFCR48e1b59++RyuVRWVhbdigEACIPtLcpQq5dKSkpiUSMAAK8srJ1MQq1eei4/P19VVVWRqQoAgEFiJxMAgJEIOACAkQg4AICRCDgAgJEIOACAkQg4AICRCDgAgJEIOACAkQg4AICRCDgAgJEIOACAkQg4AICRCDgAgJEIOACAkcJ6XI7X61VTU5McDofKyso0bdq04Fh9fb12796tpKQkFRQUaPv27UpKIjcBAPFlm0QNDQ3q6OhQdXW1KioqtG3btj7jmzdv1p49e3TkyBHdv39fZ8+ejVqxAACEyzbg6urqVFxcLEmaMGGC7t27p0AgEBz3+XwaNWqUJCkzM1N37tyJUqkAAITPNuD8fr8yMjKCx1lZWeru7g4eO51OSVJXV5dqa2s1b968KJQJAMCrsf0dnGVZLx07HI4+f3b79m2tWrVKmzdv7hOGv9ba2jqIMhNLb2+vMfMxaS4S8wHwP7YBl5ubK7/fHzzu6upSdnZ28DgQCGjFihVau3at5s6d+5vnmTx58iBLTRytra3GzMekuUjMJ9E1NjbGuwS8RmxvURYWFqqmpkaS1NLSopycnOBtSUmqrKzU0qVLuTUJAEgotu/gZs6cKZfLJY/HI4fDofLycvl8PqWnp2vu3Ln64Ycf1NHRoePHj0uSFi5cKLfbHfXCAQAIJazPwW3cuLHP8aRJk4JfNzc3R7YiAAAigE9kAwCMRMABAIxEwAEAjETAAQCMRMABAIxEwAEAjETAAQCMRMABAIxEwAEAjETAAQCMRMABAIxEwAEAjETAAQCMRMABAIxEwAEAjBRWwHm9Xrndbnk8Hl24cKHPWG1trRYvXiy32639+/dHpUgA4DqEV2UbcA0NDero6FB1dbUqKiq0bdu2PuMVFRXau3evDh8+rLNnz6qtrS1qxQJ4PXEdwkDYBlxdXZ2Ki4slSRMmTNC9e/cUCAQkSdeuXdOIESOUl5enpKQkzZs3T3V1ddGtGMBrh+sQBiLF7hv8fr9cLlfwOCsrS93d3XI6neru7lZmZmZwLDs7W9euXev3PI2NjREoN3GYNB+T5iIxHxNxHbJn8twGyjbgLMt66djhcPQ7Jik49mtvvvnmQOsDAK5DGBDbW5S5ubny+/3B466uLmVnZ/c71tnZqZEjR0ahTACvM65DGAjbgCssLFRNTY0kqaWlRTk5OXI6nZKk/Px8BQIBXb9+XU+ePNHp06dVWFgY3YoBvHa4DmEgHFZ/7+9fsHPnTv38889yOBwqLy9XS0uL0tPTVVJSonPnzmnnzp2SpOTkZD19+lQOh0NlZWWaNm1a8By1tbXavXu3kpOT9fbbb2v16tXRm1WEeL1eNTU19Tuf+vp67d69W0lJSSooKND27duVlJTYHysMNZ/ndu3apfPnz6uqqioOFb6aUPO5deuW1q9fr8ePH2vKlCnaunVrHCsNT6j5HDp0SD/++KOSkpI0depUffHFF3GsNDyXL1/WZ599pk8++USlpaV9xgZyPXhdr0MvCtUnH3zwgdLT04PHO3fuVG5ubjzKHLCI9o0VIT/99JO1cuVKy7Is68qVK9bixYv7jL/zzjvWzZs3radPn1put9u6cuVKpH50VNjNp6SkxLp165ZlWZb1l7/8xfrHP/4R8xpfhd18nv+52+22SktLY13eK7Obz5o1a6xTp05ZlmVZW7ZssW7cuBHzGl9FqPn8+9//tv7whz9Yjx8/tizLsj799FPrn//8ZzzKDNv9+/et0tJS68svv7SqqqpeGo/W9cC069CL7Ob3/vvvx6GqyIl030TsLYdpy3hDzUeSfD6fRo0aJUnKzMzUnTt34lJnuOzmI0mVlZVat25dPMp7ZaHm8+zZMzU2NqqoqEiSVF5ertGjR8et1nCEmk9qaqpSU1P14MEDPXnyRA8fPtSIESPiWa6ttLQ0HTx4UDk5OS+NRfN6YNp16EV2f4/v378fr9IiItJ9E7GA8/v9ysjICB4/X8Yrqd9lvM/HElWo+UgK3v/v6upSbW2t5s2bF/MaX4XdfHw+n2bPnq0xY8bEo7xXFmo+PT09cjqd2rNnj0pLS7Vr165+V9olklDzGTZsmFavXq3i4mIVFRVp+vTpKigoiFepYUlJSdHw4cP7HYvm9cC069CL7P4e3717Vxs2bJDH49HXX3+d8H3/okj3TcQC7sX/I60BLONNJKHm89zt27e1atUqbd68uU/TJaJQ87l79658Pp8+/fTTeJQ2IHb91tnZqUWLFun//u//1NLSojNnzsSjzLCFmk8gENCBAwd08uRJ/f3vf9f58+d16dKleJQZEdG8Hph2HXqR3XVp3bp1+uqrr1RVVaWWlhadOnUq1iVGzUBev4gFnGnLeEPNR/rvRWfFihVau3at5s6dG48SX0mo+dTX16unp0dLlizR559/rosXL8rr9car1LCEmk9GRoby8vI0btw4JScna86cObpy5Uq8Sg1LqPm0t7dr7NixyszMVFpammbNmqXm5uZ4lTpo0bwemHYdepHddenDDz+U0+lUamqq5s+fr19++SUeZUbFQF6/iAWcact4Q81H+u/vq5YuXZrwtyafCzWfBQsW6MSJEzp69Kj27dsnl8ulsrKyeJZrK9R8UlJSNHbsWF29elWSdPHixYS/pRdqPmPGjFF7e7t6e3tlWZaam5s1fvz4OFY7ONG8Hph2HXpRqPn19PRoxYoVevz4sSTp3LlzmjhxYtxqjbSBvH5hfUwgXOEu4/3jH/+o5cuXR+rHRs1vzWfu3Ll66623NGPGjOD3Lly4UG63O47V2gv1+jx3/fp1bdq0aUh8TCDUfDo6OlReXq5Hjx5p4sSJ2rJlS8J/jCPUfI4cOSKfz6fk5GTNmDFDf/3rX+NdbkjNzc3asWOHbty4oZSUFOXm5qqoqEj5+flRvx6Ydh16Uaj5/e1vf9OJEyeUlpamKVOm6Msvv0z4vv+1SPdNRAMOAIBEMXSiHQCAV0DAAQCMRMABAIxEwAEAjETAAQCMRMABAIxEwAEAjETAAQCM9P/vaynKPmB65QAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "
\n", - "\n", - "REMEMBER:\n", - "\n", - "
    \n", - "
  • If you just want quickly a good-looking plot, use one of the available styles (plt.style.use('...'))
    • \n", - "
  • Otherwise, the object-oriented way of working makes it possible to change everything!
    • \n", - "
\n", - "
" + "axd = plt.figure(constrained_layout=True).subplot_mosaic(\n", + " \"\"\"\n", + " ABD\n", + " CCD\n", + " \"\"\"\n", + ")\n", + "axd;" ] }, { @@ -663,25 +876,15 @@ }, { "cell_type": "markdown", - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "source": [ "What we have been doing while plotting with Pandas:" ] }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 18, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd" @@ -689,13 +892,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 19, + "metadata": {}, "outputs": [], "source": [ "flowdata = pd.read_csv('data/vmm_flowdata.csv', \n", @@ -705,27 +903,34 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 49, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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" + "" ] }, + "execution_count": 49, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "out = flowdata.plot() # print type()" + "flowdata.plot.line() # remark default plot() is a line plot" ] }, { @@ -751,27 +956,22 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 18, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -781,7 +981,7 @@ } ], "source": [ - "flowdata.plot(figsize=(16, 6)) # SHIFT + TAB this!" + "flowdata.plot(figsize=(16, 6), ylabel=\"Discharge m3/s\") # SHIFT + TAB this!" ] }, { @@ -793,21 +993,16 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 19, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, @@ -844,17 +1039,12 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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DMHr0aCxZsgRGo9FTSSEiInIJZ2kmIiJqGzwS8O7ZsweTJk1CQkJCvdeOHDmC+fPn45FHHsHhw4exdOlSbNmyBR9++KEnkkJEROQya8DrQ7M063V65F8q9HYyiIiI/IpHAt7y8nKsXbsW48ePr/fa2rVrMWLECIwbNw5yuRz9+vXD9OnTsWbNGo6VIiIin+JLLbxrX9mAqYmPozS/zNtJISIi8hseCXgnTpyIxMREh6+lpaVh4MCBNtsGDhyI8vJyXLp0yRPJISIiahZfCnj3bzwMAKgqq/ZySoiIiPyHtLVPWFpaioiICJttUVFR1tccBcoKhaJV0kZEtTQaDfMetVtanRYAUFBQ0Or5wFne02rNabp44SJUqGrVNBG1B3zuEXmHRqPx6PFbPeAFasdGNVVycrKHUkJEzigUCuY9arcCAwMBAHGxca2eD5zlPblMBgDo1bsXuiV1btU0EbUHfO4ReYdCoYBKpfLY8Vt9WaLY2FiUldmOP7L8HhcX19rJISIicsqHejRbuVhnTERE1K61esA7ZMgQnDhxwmZbamoq4uLi0K1bN7ecozC7GNWVnqslICKi9sGXxvBa+GCSiIiIfFarB7wPPvggDhw4gB07dkCn0yE9PR2rVq3CjBkzXO7q7MyU7rPx+PD5bjkWERG1P764LJEl0PXFIJyIiMhXeWQM75gxY5CXl2d9KI8dOxYikQjjx4/Hq6++isWLF+Ojjz7C888/j/j4eEydOhUPPfSQW9OQe+6qW49HRETtjy8Fl0JtxOvdhBAREfkRjwS8u3fvbvD10aNHY/To0Z44NRERUcvVdDjypRZeC5MPponIl+VfKkR89zi39SQkIv/S6l2aPc2XauOJiMg/Wbs0+9IzpSYtvhiEE/mqEz+fxtTEx7Hv6wPeTgoReUmbC3hP/nLG20kgIiI/54tjeE1GEwAfC8KJfNyZQ5kAgAsnLns5JUTkLW0u4DXoDd5OAhERtRFGo9HbSbCydGX2pSCcyNdZKojEkjZX5CWiJmpzuV8kbnMfiYiozTm+Nx3bPt7j7WQ0ypeCS0taTCaTl1NCRETkPzwyaZU3icWckICIyNc9N+oVAMDdj97p5ZQ4ZmkVsnQj9gWWQJc9momIiJquzTWHihjwEhFRC1kDXh9s4RXYwktERNRkbS7gFbNLMxERtZRlyVsfCi5NJt8Lwsl/5F3IR0VxpbeT0eo4yRsRtbkuzWzhJSKilvLFLs2W4NuXxhWT/3iwzxMICg3Elso13k5Kqzr+U7q3k0BEXtbmmkO5qDgREbXE4e2pyEq/AsC3WlOtszSzxYqaSa3UeDsJre7Ez6cBACweErVfbS/gZQsvERG1wAt/+T/rz77UmipwWSIi8jKTyYQvX/sOVWVKbyeFqMnaXMDryizNOq0eP325HzqNzoMp8l2CIODApsNcu5iIyAmjD3VpVpZXAwB++eagl1NCRO3V0V1pWP2fdVj+5EpvJ4X80OtT3sW+db+1+nnbXMDrio/nfY7/m/o+ZvZ/2ttJ8YpjP57EyxPexur/rPN2UoiIfJIvTVplsXv1Pm8ngYjaKaPBCACorlR5OSXkj/Z9/Rtef+DdVj+v1yatmjJlCtLS0urNqrxlyxb07Nmz2cd1ZWhT1inzGK38rMJmn8+fVVeYb1Z5F/K9nBIiIt/ki92HfTFNRNQ+WMrtvA+RP/FawFtRUYFnn30W06dPd+txXZrMo53nVanc/OfX69ilmYi8w2Qy+fRycr7UpdnClybSIqL2xTJXDu9D5E+8VsooLy9HZGSk24/rSo1Te5/pUiIx//mNBt8r0BFZCIKAD55ahXPHLno7KeQBvrTsjyO+2IrRLbmzt5NA5He4iod7WObK8cXhHuTbvBl3eS3graiowK5duzBmzBikpKTgb3/7G37++ecWH9eVDNjeA16RtVsKb1rku1RVamx6fwfm3bbI20khD/D1gNck+E76Egd1BwCMfOAWL6eEiNorS9nR1+/d5HtyMvO8dm6vdGnW6XTo06cPunfvjtdffx1yuRxr1qzB7NmzsW7dOgwaNMhmf4VC0eRjX7p0qcnvU1XXDrh35RxtRU5ONgCgqkrZLj8/NUyj0fjEdaGuMq8baTSafCI95F5nTp1BQEhAg/scWH8USTf2QmzX6FZKVa2y0vJWv+6c5T2tVgsAyMu7yrxAzdZer53i4uJGP7uvPPd8WU5uTdmxkmVHcs2F1EvWn+2vHY3Gs2uEeyXglcvl2Lhxo8222bNn44cffsD69evrBbzJyclNPrausLbGqbH3BQYGNuscbUV1tnk5ppDg4Hb5+alhCoXCJ66LypIq8w+C4BPpoVomkwn/+8f7mPDUXUi6rk+zjtG7dx+ERoY4fV2n1ePJV15EdKcorM/9pLlJbbbwsLBWv+6c5b2goCAAQHRkNPMCNVt7vXbi4uIa/ey+8tzzZdp88yzNwSw7koskKrn1Z/trR6FQQKXy3MzfPjVTSLdu3VBQUNCiY7g2hrdFp/J7luEs7f17IN9mWSfaF8dStncleWX4ed1veHnC280+RlO7xZUXVjT7HK6wLLlh4UsTs1iG4Rj1xkb2JCJ7X772HXQanbeT4fcsY6FNHA5HfsQrAe+VK1fw8ssvQ6lU2mw/d+4cunfv3qJjt/dxua6w3LT4nZEvs0yq5kuBB5m5Y7ZO+wDTniUgbq3xYv/7x3sOz98URoMR376zFepq93TN0qq1uHqxthLY8l1xZn2i5inNL290n5xzV5G654TnE+OnLPf99r7SCbnOm+O+vdKlOSYmBnv27IFSqcTzzz8PmUyGzz77DFeuXMGyZctadGyXWoHae6DHJl7yA7UtvKxN9jWW2Tpb8hBrLOBt7b/7L98cavb596z5FZ88+wXUVWpMe+n+FqfllYnv4MiO4/jB+A1EIpH1ezbqGfASNcXlM9k2vzeljDij35MAgD2mbz2SJn9nve/zmUwu8uaqMF5p4Q0JCcHq1atRWVmJMWPG4MYbb8Thw4fx5ZdfIjExsUXHdqWlIbCRiVLaOuvU8ox3yYdZum/yOvU9lr9JS4LSxoJl+3u6IAitWtBy5ZmiUZpbdq3jzlvoyI7j5jRYAt2awoKBXZqJmuTha//l7SS0ObUrfPChTK7xZguv18bw9u7dGx9//DEOHz6MEydO4Kuvvqo3WVVzuNI9d/jYIQCAa27o2+Lz+iMRa+nID1haANn13vdYuxu3qEtzw/cf+0LVB0+twhjppGafz1WuPKClcnOnKYObuhxbhp1YejlY8oK7ju/M4e2pbgvaiXyJvz5HSvPLkHPuKorzSr2dFLcMZaH2qW6Prj1rfmnVc/vUpFXu4EqNk6UwER4T5qnk+DTrIuy8Z5EPY2uW77IEg1Wlykb2dK7RMbx2FXLfL91pfp+xda4LV54ploBX76DL8emDGbhTPBFXs5o+MaPlFm2pFLAGvB7ME+pqDV74y/9hwbjXPHYO8ozFsz7CzhU/eTsZPs1fg7Qp3WdjRr8n8fcujyLr1BWvpsXaO5CNJeSius/7Nx9c5tLzsKXaYMDb9AxoufH5a41fS3HSKvIHDHh9lzu6JxkbOYazgLO1ZipuLCCvS2YJeLX6eq/9WFObbemm3CQ192hLGqxdmg0ebOGteR6cP3bRc+cgj9i54icsnvWRw9f4nDfzZpfKlqj7HLyQdsl7CUHdWZp5TZFr7POfTt16s6a3uYDXlQxoCY7b64Ogds6q9vn5yT+4EnBQ62osWG0KU6MtvLb3J0vrQmtVhGhdeCBbuvo56nIslZmDYVcK3Paf1fJeTbW2ycdwleX7ZmG2beFz3qwtPE+8/Rms1xKvKXKR/RAmy+8Fl4uQvu+sR8/d5gJeV27qtROueD7T/vHDCZz5PdPj53GJpYWXBZt2L/f8VRRmF3s7GQ5xzVHf1TotvLavWyZMMbg4U3FOZh7OH89yLXEA1MqmLzFk+T4cLRskErt+v7V81toWXvP/v2060uRjuKpu+k78ctpj56HWxYDXrLHniT+0AHs7jZZLyR0VntS+2F+7jw5+BjnnrmJOyr/x6dyvPHruthfwulCYMLViC++Csa/inzc+7/HzNAcfhP5HrVRj+T9XQqNyT0vP9L5PYkr32QAAVZUaWnXLj6vX6XFZkdPi47ga2FDrcUvA28ikVc5aeF2tCJmR9E/MHvYc7hRPxKnf6tckF2YXQ6ep35qrcSHgta6Tq61/zTZnKQ9LL5zCy0U2x/ekuul75vaXfGKSHGo5VmybNZaHtr77YyulpPm8HfBa8JoiVznKfxuXbGuVSRLbTMCbe/4qdq74ybVuWDW7trTr1mt/X4Lfvm9ajXvGHxdadC63qgl0edPyP9++vRXfL92Jzct2uf3Y4yOmYXrfJ1t8nOVPrsLD/Z9GaX5Zi47jzXXbqGHuCXgbW4fXLuCVWFp4mx/8/fhF/dkhp3Sfjefver3edle6NFuuVVWlqt5rzVnKQ1zznn/e9AIAwFQnL3gs+LVLnqpS7ZnzUKtiF3WzudcvaPCZlLantleDr65g4e2A19JIwsYScpWja7e1rqM2E/A+ddMLWDzrI5vxYI19idabWQu/7J/XH8RL973VpH1fcFCg8pbaYRi8afkba9dJB5PjuMpRa25xbstbdU4dUAAAKoqbX3OnOHwOGUfPtzgt5BnuKHg1ug6v3ev2S/U0RlWlrnePc9YVL21f/S68Ok3T81hDywaJm7GUh3066wa5rgTirrAv5BvZw6LFdFo9Vv9nndt65DQHZ9StteieN52+JpFKrD97e6ysM17vSuwHjSVXLxagoKZnDHmPVq21eaY4y1OWimxPajMBb3lRJQDYPFAaK0gJbpicw9UaQEs6fUFtLV3D+105m8ug2MdYbg7uCDg8taantIEZa5vqyRsWYvV/1rkrSeRmdQtezW0NaXRMXb0xvE3v0lxWUI7xEdPw4vg3bM9pt6RRQ/c3V2aRtI61dZAvRc1YysM+7xiNJsgCZAAATXXTu1q7wr4Qy1nSW27HJz/iy9e+w7r/bfJaGtjCW+vCicsOt5cXVaAwq3YuC2+3pDrj7XQJbuod6Yr3H/8MC8a92uT9p/Wei3/0nOPBFFFdGUfPQ1Vl2xtIEATcHfIPvD/nM+s2Rz32BAEICg30eBrbRMBbt0CkVdUWThrtKleTa1syLXZzCgO+MnlVU7qlZBw9j5nXPIWN725vrWS55OCWo1j3xvfeTkarqxvwvj/nU3w07/NmH8vRBDvuYFmipbkBtaPxlORb6gZvzQ2MGmuptQ/ARC7M0lyYXQIA+H1bqs12k91Dt6ECpCvXoeW4jo5n6dLc3EKiIAgwGU2I6RQJwPZZ50726fPkjNDtheUaaq172p3iidj60Q8223y5Nc5TnK3VrdfqsWvVvnqT2NlXSFRX1B+aYFGUU+K1iR69H/CaryV39DBrqq0f7sYfu080ad+WDqMi1+i0esy9fgGeHfkyLp6srUyy3O+2f7IHAFBWWIEtH9Qfhrf9kz0N5jV38euAd+tHP6C8qAJVpUrrtro1DE1d3/HMocxmT9LTnO5eix/+sFnncjtLLV0D39PVi+ZFoX0lSLe36J43sWLBl95ORquzBLxGgxFbP/oB3y3Z5nRf+1o3e55q4bW0RGnVOlRXqlzKYxqVFj+u3V9vu64VH7DUuLr3DlfvhZZr2NEETzbnsCuoSyRNn6V5+8d7HG6v11XYyT3wtkk3wqA3Nrn7tKWS1VFwIW7GLM115Z7PBwAEhwcD8GQLr+13cXDzUY+cpz1qzY5Sa1/51vbc7bBL8+oXnPcOemfmB5g97Dmbbfb3mh/X/Or0/Q90e8w60WNra+ye2VqKc0q8nQSHJiU84u0ktCuWio/MPy7g0cHPoLqiGkD9ytKVC7/C2SPeG6LmtwFvzrmreH/Op3ht8hKbmoHUPbU1QI3VGNRt2fzk2TXNSkdzWjUun2n5zLXupCyrdvqaZbwc+Rbrwu9OCuonfjmNM79nIiv9MsZHTMPP639zeqy613BZYYX1Z1eWY3HE0qVZrdTgoaR/Ymri48hMvdCk7vFP3rAQSx75qN52d9UC6rR63CmeiI3vea/nwrljF/2+Fbvu9efsXliYXYxfvj1Ub7tUZh4r11grgbNliZoymZmz25d97x9H+UgqkyBlzGAAtRV/FneKJ5pne64Zp25/XMctvA3nWQD49N9r8c1bmx2+drBmYsRuyZ0BAIrfzwEAju46jg2Lt2LD4q1Y8/K3WPfG943msd++P4L93/3u8DX79CX0im/wWNT6TCZTo7Oa1rvG22EL7/ZPXZtxedP7O2x+rzue15lzxy66dA57JpMJWz/c7VKFcJG3A82a+wuHO/imN6cvw0v3OR+n7m6nDtiuelBWWDPE1C7gzc7IbbU0OeK3Aa8lw129WGhTCNbWGcObn1Xo8K1GgxEfPLUKBVdqB7Rv+WA3AOCyIgcXTlxqcjL8OcNbCkUVxY2PK27OGN6rFwug9lArRFtTWVqF7Z/safI4SEuhtO5A//xL5uvdaDTimdtfwj9vfB7balq4GppFvG4L76VTV6w/F15suLuWqkqNO8UT8d7sTxy+LgswB7wapQal+eUoK6jA48PnY+dnPzV4XADISr/icHvd9LlKo9Jar/XygnIAwIdPr2728VpCXa3BnJR/45WJ77TaOYtySvDe7E/c2kpubELA+9b0ZXh10mJUlSlttltmIG5sUij7grqlIqUpywUlDurh+JjGxrs0G/RG9Li2GwDg0mnHlZRPj3jRZuktSxDu6DNZx946mbjowolL+Oatzfj032ut2/oM7Wn9+bP55p4sPa7ths59OmFfTSXWKxPfwcfPfIGPn/kCX7z8DVYs+LLRStWX7nvL6bVn/3c8vu9Ug8ci1/z2/REc3XW8RcfY9N4OTIh7CGU19zGg/jPa/ppuj12a6/b+635NF/Qa3MOl9xc1ocvynJR/AzAP/5o97DlUO5ih3RmtWovft6bi/cc/w2f/brinmjxQZv3Z8qxvDUaDsV45zlLZBrhn0tPC7GIU55ZAp9W7fWZsS/oUh8/hTvFE7Fq1z63H90V7vvgFv33fej1zXrj7fza/K2ue9fa9kOwrqS2V3q3FawGvWq3GSy+9hDvuuAPDhg3DpEmT8Ntvzluh7FlaBZTl1TYBb92M+PQt/3FYC5px9Dw2vb8DP9l1mcz44wIe7v80HhvyrNOxH/aO7DhWmyad44KboxtCU29YlaVV9QqKrvps/lqc/PVMve2WgmSDY7Rqmkj2b/jdpeBVEARM6z0X//nL/zX5Pa898C6W/3Nlk/f3JYIgtOjG/9VrG/HuY58gfb+i8Z0Ba5eRupUzUxMfBwAc3l57TVoqchqaHbRuAfeNaUutP585cM7R7lb7vj4AANag2pyGOXh18mIAQFhUKID6PRpWPv8Vflz7a7O+r+dGvdJg3qwqUzptuXrm9kX4W4eZuFM8EVN7zXX53O5kqZhzNibJE12317z8LbZ9vAe/OmhtbS6bLs1O5kywBIv292LLNdlYC6/NOYxGdOzZAYB5Mr3GaJ1c979tOgJ1tcaaprya7sJ1PfjyJHRL7gypTIIfPt/ntDU+u046LF2fC68Uo7qiGnu/2o+8C+ZjBwYHAABKrjqeAf3y6Wzrz7s+/Nn6c8qYQQBqnyNXFDm47f4bkbb3FNb+dwM01VpMeX4Cvi//HB8eM9fq725ioa7u30xx+BwWz/qo3ne2f8PvUBxu+F7QVmhUWqx743u3z85bt6fUS/e9hYV/btlqDbtW7gUAlNfpkWMf4NoXLtvyxJPVFdXIaqQytPRqGZYf+T/8+eGRNttNJhP0Oj0Ks4utec3iu3e345dvDjZ6/vxLhVj94jqcP56FeyIfbPTeZDKZsOWD3bgn8kFrxVPOubwG3xMYUjupz9Gdx5tcRm3M3q8P4Kcv6w8fsnh18hL8NWwqjAYjju46jr1fH8Anz9X2iHx9ynstTsOU7rPx966P4a6gB/Dpc2sbf4MLzh27iOyMXDx5w0IAwBeL1rv1+P5KEASc/PWMR+4LlpU56vYSrCpT2lRSb6n8Aju16/BdUW2ZPzgiyO1pqUvq0aM34JVXXsGZM2ewYsUKJCQkYNOmTXjsscewefNmJCYm2uwrCAJMJhMkEnNtQGVplXVJhuoKVYNTzE+Iewj3P/NX9E3pBcDcZXPV81/b7HPvk3/Gpvd3YO51863bxsomOz1mTEIUho4aiDEzbsfbD31g3f7nwAcAAL0G98Ddj45Gn2GJUFep8eqkxdZ9xBIxTEaTNThJHNQd140binPHLqJrvwQk9OqIgOAAaJQaXHNjXywc9xqqyqrxycl30LOmtUEQBKiVGohEQFCo+QIpL6qAPFAOsUSM/KxC9OjfFYC5ALb+zc1Y/+Zm7NKvs36HgiDYTNaVdyEfIpEIgiAgoVdHh59bcSgTVy8W4LZJNyIkIqTe69++sxWfPPsFdunWWQsMJ34+jcrSKug0eoSEB0Gn0cNoMCK6Y1S99/+8zlzhMfXFiVBVqdGxRweH6RAEoUldrcsKKxAcFoiAoIBG920uZXk1xBIxHh38DPKzCtG1XwJWKpr+ABAEAWv/u8E6BrfgUhFMt5isrV+CIKAouxgmk2D9Pkrzy/DtO1sBAEd3pdkcb+GfX6u3DQB+35qK1S+uw8Rn/oqQmjGAluPXvSmV5Jkne+jcpxN2Lt+HAHEgeg3uiaGjBqD0ahn6De8NkUgEo8Fosz7nneKJ+DR9MfIvFSH/UhH+/PBJ60P0q9c32qSlorgKb0xbiiuKHIz8xwh06tkBYokYIpEIZYUV1sDAniXvjJVNRnTHSDz5wSxEd4pCWHQoAoLkCI8JxftzPsXP6w9i7tKZ6NAtFmKxCEajCR17dEDG0do1sOsWDu8UTwQArM36AFEdIyGTS63XV865qzAajOie3AWA+aYtlUshD5Ah70I+uvbr7DCtjbG0qjsqWJ/45TSeuf0lLNn/X1x7U1K917VqLcQSMWRyWb3XGhIYYv5ej+9NR8qYQYiMi2jS+wRBgNFghFRW/3Fh06W55jNlHD0Pg96IIzuO4S9zxiAgSA7A+dCJzD8uIGXsYEgkYkjlUmtFiUXdgHj3yn2I6xINwDweaOSUWxAcVv8heeZQBqI7RSH/kvNlKf4aNhUAsPzo/2Gl3TPh+ruG4h//+RsAYPp//47P5q/FXcFTMHr6bQiPDrPZ94N/rkKHbrHoltzFWnkoCAImd37UGtS/um2BtXfBT2v3I+98PhIH9kDhlSIMvLU/Bo5Ixh8/1FZ+7Fi2FzuWmYOasQ/dgYjYMGsh4rpxQzHotmuwc8VP+Lym8BYYEoCQ8GD0GtQD0Z2isHnZToRGhuCGv6agKKcEaXtPIflPfdClb4JNd8ixcvNzTh4os7ZK71xRvwfGv0b8B0PvHIhR/7gV19zQF6X55agoqkSnXvEICg1EUGggQiND8Ma0pRg55RYMHzsEJpMJueeuonOfThCLxagsrcIv6w/iz7NGNdpV9OCWo+iUGG995tVVmF2M2M7R1ntkY8oKyhESGQJ5QG1+0Wn1KC+swL/vfAUvrP8XetX0BFj3v0348rXvENkhAmNn3G7dPzsjF9+8uRmPL53p9P7UFHVbPARBgF5nsLnfNMRkMkEkEkEkEkEsrd87wn4cuqpKjZKrZYjpZH7W1s2ryvJqhEbWf4bb06q1KM0vR6ee8dY0H/vxJIaMHFCnh4YOsgCZ089QXVGNrR/+gNOHMvDMijmIiA1v9LyuMOgNmJPyb+RdKMC26rWQB8rx2t+XYNzMkRg+drD1eRiTEA2JVIKnP3kM8kA5vl+2EwAwRjqpweO/OnkJSvPLcev9NzgstwC1lc0Wr/19Cf67+d+4mlWIQbf2t6bTcg/9Y/cJLJ37mc17Un84icuKHASFBCC2S4zN9W00GOtVGP5rxIu4+9HR+NNfhiE4LKhJ3a/tVZZW4X81Aeub05fh+/LPERgcgN2rf8ZXr32HvimJOLDxMIDae4W9n9f9Zi27AcCqs++hU2I80vcrMOi2/tbrQhAEaKo11jKrMxsWb8XDb0yBYBIgloihVWmx5NGP6+330b9Wo7JUaR0q4szZw+dtvuuinBIU5ZSYy6GdomzuC/7MZDJh9rDnMGzUQIevF+eVIjYhGhvf3Y7Bd1yLTe9tx65V+3DntFvx3OqmNQBYguO6ed1RGeaFu/+H6+8aipTRg63b7ouZYbOPpcdTeEwYvs7+CGUFFSgorV/x7E4iwQvVfhUVFbjpppvw7rvvYtSoUdbt99xzD6677josXLjQui01NRXzhzetlfDrnI+x/o3vcdM91yGhd8cmTShw4/jheHnTc3h18mL88o255WPC03fj+6U73V7L++Tyh3H3Y6Px79H/xfGf0t16bHeSB8pwzY39UFlShYtOpu9vqZH/uAVGgwmVxZUozS+Hsqy63tqvA0Yko0ufBJTml+GKIhdqpcZaoz3glmSEx4bht02Ou+qOmX47dq82t3Jc9+chiO4YZa0V/9Pdw3DpdDbiu8fhzMEM9BrSE3FdY7B/g7llcPL8e6FVabHj0x9t1rrs0b8rkq7rjV2r9qHPsERUlSoddpu/bdKNiOkUBYPeiFO/ncUVRS7+/PBISOVSqKvU0Kp1iO4YCUEw39ztiSViDByRjPLCSlyq0+rToVssOvbsgJK8MuSeu2rznvjucfXWnJv873uczmAtEokQFBpoM6HV23tfwuJZHyIoLAj//nwuHh38rMPav7DoUFSXVzdpTNjwcUOgUWpw7thF3P/sePyxOw2aaq3NTH7OjJ5+G5766BGIxWLoNDoIAnB/x4c9tv5oQ2669zpcPp2NnEzb7z04LAg9ru2KngO6QywRQyIRo7pKhb1fHoDRYIRYLMJN912PTj06wGg0waAzwKAzYOfKvdYC6LiZI1FwpQidesajqkzpsAV25JRbIAuQQa/VWysSJs77C7RqHa6czUXigO4IiQiGyWTC6d/OIm3fadz96J2Iio9E4ZVi7FnzS70WoAdfnmTumWASrD0UJBIJRGIRBJMArVoLrUqHnSt+glatw033DEfXfp1RXalGVZkSXfp0Qtq+U9bxO70G90C/lF7Y4aTLescecbjjgVuw/7vfkZ3hvDUjcVB33DT+OlxW5ODQlj8abQHu0rcTul/TBfHdO0AiFUNVqXY6ds9SqVe3IOzIe7+9imtu6Gf9ff93v2PJox/bdJFMGTMInXt3wubl5lknJVIJjAYj4rrEYOqiiVg8q/4Y9MZ0TeqMJb++gonxD0MiFUMileCZlXOQdH0f/G/Ke5i/5kl0SjQHH0aDES/e8waO7DiOZYf/h37DewMAzh/Pwovj32jxOL8P/ngDnft0QsbR83hu1CstOpa96E5RCIkIRkhEMErySiGYBMR1jUFoVCiqSpU4W9OifNO916GsoAIBQXKERARDMJmsXfXumjUKgaGBKCsoh0gsglFvxOnfMhCTEIVeg3vCaDBCr9Nbe3J17BGHyPhICCaTTeUXYM5Leq0BP321H1WlSsjkUox7eCSMBhNCIoKx4Z0tMJkEdO2XgD7DEiEPkCGyQwSqSpX47fsjKC+qxNA7B6JDlxik/ngSRdklmPTceOi1Bug0OlxMv4IzBzPqfQelV80VjGKJGEnX9wEEAYNu628tDFoK/SajCd++swX9hvdG8p/6Yt3/mWcTThkzCEnX9YFBb4RRb7BWhNY14em7AaDexIb3PDEOYrEY8kAZxBIxDHojzh27iG5JnREaGQJBEKyVlZP/fQ/kgXLsWrUXhVeKERgSgMG3XwujwYi0fafR49qu6DWwO6RyKc4cysTFk5cRFBqIP88aZXPe6I6RGPG3GyALkKK6QoWq8mpoqrUw6g0wmQRUl1fDaDQhMi4cUrkUR3YcR3SnKMR1iYaqUg1VlRo9ru2G6goVcs9dtcmPADB01ACU5JXZ9Crq3KcTXlj/NCI7RCA2wVxZZjQacXRnGi6duoIVC7+yOcYdM27Ck0segbKsGh8/8zn2f3fY5vXu13RBXNcY/LH7BDr27IDhY4dg64e7633vdQUGB0Cj0iJxYHd0TUpA4ZVim96I9sQSMQKC5OjQLRbhsWEoL6hAdkYexj50B+Z9NhtbP9yN9x//zOF7+wztiQtpl3DtLckozi1F/5v6If+iuZwSGhVi/ftdPp2DgGC5tZK7OdbnfYLXH3gPJ36uv365vbCoEOh1Btw1axRENc/0qjIlJFJJg5OD2ZNIJZDJpTa91jp0i7X+XJxT4tJ49ZvuGQ6xRGyudBeLERIWBLFEDKPBiKKcEsR3j0NwzTbAUgFsgslogtFgtP3fWLvd8nNweBASEjuay1KC+doTTOYZ901GE0yWn03m362vmQQIJhMEATAJ5u2Cydz4Z3lmm2q2CSYTdFoDju60HSpx/V1DERkXgYw/zuPSqWyEx4Q57PXao39XhEaFQK/VQ6vWQavSIb57LERiMS6fzkbHnh0glUtxLvUiNNVa9BmWiMCQAMgCZNBpdEj/1dwzceb/piA3M69et/GAILm13Hbj+OEYM+N23PjX4fXSoVAooFKpMGzYsCb//VzhlYD34MGDmDFjBn799VfEx9dOiPHiiy8iIyMD69fXdjloKODt0CMG3Qd2wdnfzuO5DbMR0aF+zaFBZ0Du2XwIEKCt1iEvswBhMaHoPrAL4rpFO02jpQCoLFXh942p6JzUCWd/O48Lxy4jL6MA198zBIe+S0V4XBgWbpmL4PAg5J0rwNVzhdj67h5I5VKb9dxGzbwZf557h3X8mSAIuJB6GWsXbERst2hk/t6yiQ+aoufgrii8XILqssbHmMR1i0bRldoANDQ6BMpS55NbUa2AYLnDJUPEEjFkAVIERwSh7GqFg3fWCokKrvd36n9rX2iqtTBoDbicnospr92L6IRIXDqZg9um3YCLxy7jcnou/nTvUITH2raSleSW4ULqZRz5/jhMJgFisQgapRbxveIQGhWC6IRIjJhyvU3NnUajweXjuTi69QREYhEuHruCQaOSoVFqzS0MAnDt7f3QK6UHFAfO4cIflyESAbdOvQEHv/0DfYb3RO/rekAsFkOv1VsLcYC5NjLnzFWse3kLTAYTojpFQK/RI7ZbDKRyCYJCA/GnCUMR09m2Rl0QBGiUWmSfzsO5I1m4nJ6DoPAgxHSOhKpCDWWZCmKJGHc+MsL8IDCakL7vLNL3nkXX/gkYdtdAJN/UG6pKNQJDAmDQGfD1i5tRWaxEjuIq+lzXE/JgObKOX0FJTm1BICwmBFUlzq//sJgQmIzmh1FAsBzl+bbj4mUBUnNALJOYW9Ura1t6QqKCoVFqERwe2OA57MkCZZAFSKGqaHgW7uaSyCQwGUw2lR4SqQSyQCk0ytrCRmBoAIbdNRDpe8+isqjhiXTszVg8Cav+1bQuZi9sfxJpP5zGpRM5GDAyGapyFa6eL8SF1MuQyiUou1oBQTDPhlw3//X9UyLumz8OBp0R3fonWLerKtQ4s/8cKourIA+SI6pTBPqP6Ov0/CaTCQatAWX5lQgKDUB4nLmlt6KoCuePZCHnbD5UFWrcPHk4ul6TAHWVBhqlFuoqDc7sz0Tm4SyMmnkzegzqiu3v/4T4xDjcMGEoju8+jcqiKnTsFYeu1yQgJDIYGo0GgYGBTe7NYs9oMCJHkY/i7FKExYQgIDgAYokIB7/9A4e+O4a5K6ejd0oP6NQ6qCo1yErLRly3aCT0i0dlkRISqRhhMbX3EKPeiDP7zyEvMx8/rjgArUqHu54cCYlUjKqSauz7/CBu/cef8Mva+sMJYrtGo6pECXmQDFKZFBHxYQiPNX931eUqZJ/Jg06tR8decRCJRSjNLbf+/SQyiXW9ZZFYZC6I1vweGh0CjVJr7VkgC5BaZ68NiwkxF2LFYpTl195rLZU59mSBMkjlEkAA1FXmvGm5XxsNJus5gsODrD1bxFLz8Rua5V4eJAcgQKd23xAFkUgEkUQEk8EEsVRs/V8wOh5WY6nksRcQbO55YdAZrYVom3OIRU1e/kYkEiG8Qxh0ap3Nva3u3wQAgsLM3XINeiNkcilCo4MRUNPzRCQSQVlWbQ0SjAYTCi6aK3GDw4OgrtJAEAR06t0BskAZyq5WWK8ry/cb3TkSpbnl1vN17BWH6+8ZgpEP3ew07VqVDhdSLyEkMgQdesRAJAMCA2u7D6urNDj5owIXj1/BH9tPokP3GGhUWnRJ6oT75o9DVMcI5F8ogjxIhuiESADA1fOFOPz9cexd5XiYXkCwHPIgOf72/J/Ra1gPBIbIkfbDGZz6OQMdesTg6vlC5Jy5io6946DXGswV1OGBmPjC3Yioue9cOZULxYFzOPGjAjmKqwgICYC2Wotu/RNw5XQexFJz0CyVSyEPliE4PAjaai2qSqsR1y0GWpUWUZ0iER4TCnmwHIe/P47QqGBoqrVQV2oQHB6E8LhQ9P1TIv769J2QB8lRnF0KvdaAyuIq9BneE2KJGIIgYP1LW8zfd+8O2Ph/Oxu8ViQyCSRSCcQScxlEHiR3eWnQuuWjvz1/F0Y8cH3t30upwat/fg86jQE3/m0Yiq6U4tS+sxh210Dc8+wYKEurcWxnOvZ8uh8hUcGIiAszB5qCAIPOCJ3aPI7YqDdCo9QiKDwQeo3B7jkott5fzPcBEUQ1Fd4iicj8v9i8vfBSSb3GM0uPNrFEBJFYXHNvq+m9Uec1iEQQ1+RFkVhkzZeWn8U1PwPme1vu2doW0oBgOWK7RUNZpoJGqYW2WouEvvEoulKKzkkdcSU9FwHBcnTtn4DAkACoqzTWz3LxeDYS+nSAAECn0iEw1JxHs0/nwWQS0Dulu3n1Ap0RRoMRAcFyTH5pPOJ71lY8lOaVI/9CIQx6IwbcntSk55hGo4HJZGpbAe+2bdswb948nDx5EgEBtd2DlixZgu3bt+PHH2tr51NTUz324dsCdbUGBp2hXjfAhhgNRmutsVgihslkgk6jR1CdMSJNUZxXau0uVfdibuihW1Fcici4CHN3Lq0e8kC5dX1JS5ecopwSxHaOhiAIEIvNN1TLWO3YztEQS8SoKK5CSEQwpDIJtCotZAEyqJUaSKQSmIwmVFeoEBEXbr7RCAKqK1QIiwmDPEAGiVQCrVqL/EtFCAwOgFQutd7wLLVWlkmTQsKDoNcaoKnWQCqXIjQqFKpKFfRaA6I7RkIqlyIiNgzyQDmMRiMkEom1645Bb4S6Sg1ZoByBwXIEhgTadO/R6wzIPXcVCb3iPdrturkUCgWSk5O9nYw2yVHXIFf2tw+EjEajtbujpeujJf84O55gEmofopZZv2sKviKxyJr3LMeqezz7Nbwt241GI8RisfU99p+v7vvqHsvZ99DcgM/fMe+1DndfX5Z8UjdPOcu7DeUPy8Q9dfez39fyWt38bhmy1Ny0101nXZb7S917QlvFvEfuZCnfQgTrs5Ec83QLr1fG8DZ0Y+XF4JqgkECg8aE4NiyBpfV/iQRBIa4/KC3dg+w5+xuKRCLruEGRSAR5oNz6c93xJ3FdYmyOIxKJEBYVahPUR3WoHX9oGRNS93X78Un2Y44DggKs4zIdueZPzlt6nLEUNszdheunqS6RSAR5gMzhGDVq+1y9zzkq7NZVt6DblEKvSCRyOGWhWCy22V43D9Y9Z93tztLR0P3d0bGcppPIQ9x9fTkLTB393lD+aGrgKhKJWhTkOjq3I43layJyzL58S97jlVmaY2PNzd5lZbZjB8rKyqyvEREREREREbWEVwLea6+9FnK5HGlpaTbbjx07hpSUFG8kiYiIiIiIiNoYrwS8YWFhmDBhApYuXYqsrCyo1WqsWLECubm5mDzZ+XJARERERERERE3llUmrAECn0+HNN9/E3r17UVlZiaSkJDz99NP1BiunpqZ6I3lERERERETUStrULM1EREREREREnuaVLs1EREREREREnsaAl4iIiIiIiNokBrxERERERETUJjHgJSIiIiIiojaJAS8RERERERG1SQx4iYiIiIiIqE1iwEtERERERERtEgNeIiIiIiIiapMY8BIREREREVGbxICXiIiIiIiI2iQGvERERERERNQmMeAlIiIiIiKiNokBLxEREREREbVJDHiJiIiIiIioTWLAS0RERERERG0SA14iIiIiIiJqkxjwEhERERERUZvEgJeIiIiIiIjaJAa8RERERERE1CYx4CUiIiIiIqI2iQEvERERERERtUkMeImIiIiIiKhNYsBLREREREREbRIDXiIiIiIiImqTpN5OQGNSU1O9nQQiIiIiIiLyoGHDhnnkuD4f8AKe+/BE5JxCoUBycrK3k0HU7jDvEXkH8x6RdygUCqhUKo8dn12aiYiIiIiIqE1iwEtERERERERtEgNeIiIiIiIiapM8EvCWlJRgwYIFuPnmmzF06FDcf//9OHToEABgw4YNSEpKwoABA2z+vfvuu55IChERkcs+O/YHEt9/BwaTydtJISIiohbwyKRVc+bMQWhoKDZt2oTw8HAsW7YMc+bMwa5du1BRUYG+fftiy5Ytnjg1ERFRi71/xFxJq9LrEB4Q6OXUEBERUXO5vYW3qqoKvXr1wsKFCxEXF4eAgADMmjULKpUKJ0+eREVFBaKiotx9WiIiIreRiyUAAL2RLbxERET+zO0Bb1hYGF5//XX06tXLui07OxsA0LFjR5SXl6OkpARTpkzB8OHDMWrUKLzzzjvQarXuTgoREVGzSCXmx6PeZPRySoiIiKglPL4Or1KpxIIFCzBy5EgMGDAAe/bsQXx8PJ566ikkJSUhLS0NTz/9NJRKJRYtWuTwGAqFwtPJJCI7Go2GeY/aLaPBHOieO3cOZYFBrXpu5j0i72DeI/IOjUbj0eOLBEEQPHXw3NxcPPbYY4iNjcXy5csRHBzscL8vvvgCb775JtLS0iCV2sbgqampGDZsmKeSSEROKBQKJCcnezsZRF5x44qPkV+txIEZs5AQFt6q52beI/IO5j0i71AoFFCpVB6L+Ty2LNHJkycxceJEDBs2DJ988onTYBcAunfvDr1ej7KyMk8lh4iIqMlEIvP/HqsRJiIiaoacnBzcd999NtuUSiWefPJJTJkyBZMnT8bs2bNRWVkJANiyZQsmTJiAiRMnYsOGDdb3rFixAuPHj8eECROQnp7u9HwmkwkvvfQSJk+ejIkTJ+Lbb7+1eT0zMxP9+/dHTk4OCgoKMHXqVOu/2267DVu3bnXjp28ej3RpzszMxKxZszB79mxMnz7d5rXly5fj2muvxa233mrdlpGRgeDgYMTGxnoiOURERM3DiJeIiBzYqDiNb8+ccusxJ15zLe5L7u/y+1avXo2BAwfi4YcfBgB88MEH2Lp1K+69914sX74cGzZsgEwmwz333INRo0ahqKgI27dvx3fffYeMjAz89NNPGDBggMNjHzt2DFKpFOvWrUN1dTVGjRqFCRMmQCwWQxAEvPHGG+jevTsAID4+HmvWrAEAGAwGTJ06FXfccUczvw33cXvAazQaMX/+fEycOLFesAsApaWlWLRoEZYvX45+/fohNTUVK1euxIwZMyCyVKkTERH5AIERLxER+bjKykro9Xrr73PmzAEAHDp0CAMGDEBYWBgAICUlBceOHcP58+cxbtw4SKVS9O/fH/37Ow+yU1JSkJKSAsAcx0VEREAsNncS/u6773DDDTfgl19+qfe+TZs2YcyYMQgJCXHb52wutwe8x48fx+nTp5GZmYnPP//c5rXx48fjxRdfRHBwMJ544gkUFRUhLi4Ojz76KKZNm+bupBAREbWI52a5ICIif3Zfcv9mtcZ6wpQpU/DQQw/h119/xc0334y77roLSUlJKC4uRnR0tHW/2NhYFBUVITc3F8HBwXj88cetEwwnJSU1eI4nn3wSx44dw1tvvQUAKCsrw+bNm7Fq1SqHAe+3336LlStXuveDNpPbA96UlBRkZGQ0uM+8efMwb948d5+aiIjITcw9jkyMeImIyMd1794du3btwuHDh3HgwAE8+OCDePbZZyGXy232EwQBIpEIgiBArVZj2bJlSE1NxfPPP4/vvvuuwXO8//77yM3NxcyZM7Fhwwa8/fbb+Oc//1lvwmHA3ACamJiI0NBQt37O5vL4skRERET+il2aiYjI12k0GgQGBuLmm2/GzTffjDvuuANLly7F3Llz8fPPP1v3KywsxODBgxEbG4vExESIRCKkpKQgNzfX6bEvXLgAAOjVqxc6d+6Mrl274uLFizh06BDOnTsHADh//jzmzp2L1atXIzIyEj///DNuuOEGj35mV3hslmYiIiJ/x3CXiIh83YwZM3Dw4EHr7/n5+ejatSsGDRqE9PR0VFZWorq6GseOHUNKSgpGjBiB/fv3AzAHtJ06dXJ67IsXL2Lx4sUAALVajaysLHTp0gV79+7FN998g2+++Qb9+/fHsmXLEBkZCQBIT09vtIt0a2ILLxERkR3rskTs0kxERD4mKysLU6dOtf4+f/58vPfee/jggw8gEokQERGBl156CYGBgZg3bx5mzpwJkUiExx9/HGFhYRg8eDD279+PqVOnQqfT4cUXX3R6rlGjRuH333/H5MmTodPp8Mgjj9iMC3akqKgIMTExbvu8LSUSfPxpnpqa6rFFiInIOYVCgeTkZG8ng8grbl71CfKqqrDnH9PRK7p1H9rMe0TewbxH5B0KhQIqlcpjMR9beImIiJzw6RphIiIiN1m2bBkOHz5cb/vrr7+Orl27eiFF7sOAl4iIyI6IszQTEVE7MnfuXMydO9fbyfAITlpFRETkBMNdIiIi/8aAl4iIyAkfn+aCiIiIGsGAl4iIyA5naSYiImobGPASERE5wXCXiIjIvzHgJSIicoItvERERP6NAS8REZETJm8ngIiIiFrEIwFvSUkJFixYgJtvvhlDhw7F/fffj0OHDllf37ZtG+69914MGTIEo0ePxpIlS2A0Gj2RFCIiIpdZliViCy8REZF/80jAO2fOHBQWFmLTpk04dOgQrr/+esyZMwcFBQU4cuQI5s+fj0ceeQSHDx/G0qVLsWXLFnz44YeeSAoREZHLauas4hheIiIiP+f2gLeqqgq9evXCwoULERcXh4CAAMyaNQsqlQonT57E2rVrMWLECIwbNw5yuRz9+vXD9OnTsWbNGphM7DxGREQ+hC28REREfk3q7gOGhYXh9ddft9mWnZ0NAOjYsSPS0tLwwAMP2Lw+cOBAlJeX49KlS0hMTKx3TIVC4e5kElEjNBoN8x61W3q9HgBwMSsL8rLyVj038x6RdzDvEXmHRqPx6PHdHvDaUyqVWLBgAUaOHIkBAwagtLQUERERNvtERUUBAEpLSx0GvMnJyZ5OJhHZUSgUzHvUbsmPHATUKnTv0QPJnRJa9dzMe0TewbxH5B0KhQIqlcpjx/foLM25ubn4+9//jpiYGLz99tvW7SKRqIF3ERER+QaBo3iJiIj8mscC3pMnT2LixIkYNmwYPvnkEwQHBwMAYmNjUVZWZrOv5fe4uDhPJYeIiMhlJo7hJSIi8mse6dKcmZmJWbNmYfbs2Zg+fbrNa0OGDMGJEydstqWmpiIuLg7dunXzRHKIiIiahfEuERGRf3N7C6/RaMT8+fMxceLEesEuADz44IM4cOAAduzYAZ1Oh/T0dKxatQozZsxgV2ciIiIiIiJyG7e38B4/fhynT59GZmYmPv/8c5vXxo8fj1dffRWLFy/GRx99hOeffx7x8fGYOnUqHnroIXcnhYiIqFksFbDs0kxEROTf3B7wpqSkICMjo8F9Ro8ejdGjR7v71ERERG4lMOAlIiLyax6dpZmIiMifMdwlIiLybwx4iYiI7FhmlGCXZiIiIv/GgJeIiMgJrsNLRETk3xjwEhEROcN4l4iIyK8x4CUiInKC8S4REZF/Y8BLRERkx7IsPMfwEhER+TcGvERERE5wDC8REZF/Y8BLRETkBBt4iYiI/BsDXiIiIjuimoWJBEa8REREfo0BLxERkRPs0kxEROTfGPASERE5wQZeIiIi/+axgDc7OxtTp05Fv379kJOTY92+YcMGJCUlYcCAATb/3n33XU8lhYiIyCU1kzTDxBZeIiIivyb1xEH37NmDRYsW4ZZbbqn3WkVFBfr27YstW7Z44tRERERuwxZeIiIi/+aRFt7y8nKsXbsW48ePr/daRUUFoqKiPHFaIiIit+IYXiIiIv/mkRbeiRMnAgDy8/PrvVZeXo6SkhJMmTIFmZmZiIiIwLhx4zB37lwEBAR4IjlEREQuEYk4SzMREVFb4JGAtyGRkZGIj4/HU089haSkJKSlpeHpp5+GUqnEokWLHL5HoVC0ciqJSKPRMO9Ru6XVagEAOTm5UBhMrXpu5j0i72DeI/IOjUbj0eO3esD7r3/9y+b34cOH45FHHsGbb76J559/HlJp/SQlJye3VvKIqIZCoWDeo3YrIPUwUK1EQucEJPdNatVzM+8ReQfzHpF3KBQKqFQqjx3fJ5Yl6t69O/R6PcrKyrydFCIiIit2aCYiIvJvrR7wLl++HL/88ovNtoyMDAQHByM2Nra1k0NERFSPdVkijuElIiLya60e8JaWlmLRokU4ffo0DAYDDh8+jJUrV2LGjBnWSUKIiIh8AeNdIiIi/+aRMbxjxoxBXl6edXbLsWPHQiQSYfz48XjxxRcRHByMJ554AkVFRYiLi8Ojjz6KadOmeSIpRERELcCIl4iIyJ95JODdvXt3g6/PmzcP8+bN88SpiYiIWq6mxxG7NBMREfk3n5i0ioiIyBcx3CUiIvJvDHiJiIicENjCS0RE5NcY8BIREdnhLM1ERERtAwNeIiIiJxjuEhER+TcGvERERM6whZeIiMivMeAlIiKyY1kX3uTldBAREVHLMOAlIiJygpNWERER+TcGvERERE4w3CUiIvJvDHiJiIicYAsvERGRf2PAS0REZIfLEhEREbUNDHiJiIiIiIioTWLAS0RE5ITAUbxERER+zWMBb3Z2NqZOnYp+/fohJyfH5rVt27bh3nvvxZAhQzB69GgsWbIERqPRU0khIiJySW2XZq8mg4iIiFrIIwHvnj17MGnSJCQkJNR77ciRI5g/fz4eeeQRHD58GEuXLsWWLVvw4YcfeiIpREREzeZLk1YJggCjiSsDExERucIjAW95eTnWrl2L8ePH13tt7dq1GDFiBMaNGwe5XI5+/fph+vTpWLNmDUx8kBMRkQ/xnXAX+PrUSfRZtgQFSqW3k0JEROQ3PBLwTpw4EYmJiQ5fS0tLw8CBA222DRw4EOXl5bh06ZInkkNEROQSkcjcqdmXWng3Kk4DALIrK7ycEiIiIv8hbe0TlpaWIiIiwmZbVFSU9TVHgbJCoWiVtBFRLY1Gw7xH7ZZGowEA5BcUtHo+cJb3lCoVACD78mWEVFS2apqI2gM+94i8w/LM9ZRWD3iB2przpkpOTvZQSojIGYVCwbxH7VZg2h9AVSU6dOjQ6vnAWd6Tn0gFKiuQmJiI5PiOrZomovaAzz0i71AoFFDVVOp6QqsvSxQbG4uysjKbbZbf4+Li3HKO3ksXY/6Pu91yLCIian9qZ2n2nS7NlnkuJC5WGhMREbVnrR7wDhkyBCdOnLDZlpqairi4OHTr1s0t5zAJAr45c8otxyIiovbLl9bhNdYE3wx4iYiImq7VA94HH3wQBw4cwI4dO6DT6ZCeno5Vq1ZhxowZLnd1JiIi8iQfauC1tjaLxa3+6CYiIvJbHhnDO2bMGOTl5Vlntxw7dixEIhHGjx+PV199FYsXL8ZHH32E559/HvHx8Zg6dSoeeughTySFiIio2XyrhdfcpZlVw0RERE3nkYB39+6Gx8+OHj0ao0eP9sSpcaIg3yPHJSKidsS6LJGX01GH0WROjA8liYiIyOe1uX5RlVrPTmtNRERtny9OWmXpNeVLawMTERH5ujYX8Io5DpiIiFrIMqeELwW8JjDgJWqOwmqlt5NARF7U9gJejm4iIqIWsgSVPhXw+mCaiHzdsat5+NOKj/H92TPeTgoReUnbC3jZwktE5PP+uWs7Bnz4vreT4ZQlpPSl4NLEMbxELjtTVAgAOJqX6+WUEJG3eGTSKm/i0kZERL5va+ZZbyehYT7Ymmrp0uxLaSLydZbcwvIhUfvV5lp4eT8jIqKWqm3hNXk1HXVZAl2Gu0RERE3X5gJedmkmIqKW8sUxvJylmch1lvzC0iFR+9XmAl4Rb2lERNRCtS28Xk2GDU5aRdR8LB0StV9tLuB1pYVXEIR2X3BQ6nTeTgIRkU+ZtXUTFMVFAHytS7P5f4GdmomazJJfOIaXqP1qcwGvKze0b86cQu+li/HWwf0eTJHvyigpxsCPlmKTglP1ExFZ/JR10fqzL1WKGmuCb19KE5Gvs2QXhrtE3lel1UJvNLb6edtcwAsXCgKWQO/DP454KjU+7XxJCQDgp6wLXk4JEZFv8qXg0jIWUWto/cICkb/ac/E8ALbwEvmCQR8vw5wdW1r9vG0u4HWlaNLeu4XJJOY/v84LNS1ERP7A6EMBb7VeDwB487dfvZwSIv9xKCcbAFt4iXxF3V5UrcVr6/BOmTIFaWlpEIttY+4tW7agZ8+ezT6uK7XxvlOM8Q6pWAIA0JsY8BIROeKLMyJfKCv1dhKIqB3bnpmBUYm9ECD1WhhB5BKvXakVFRV49tlnMX36dLce16WA1wcLMq3JMsFXO/8ayA9Yl5Vgl7Q2xyQIPr2cnC91abbwpZmjifyGD99n/MnhnGw8sWsbpg0cjJduG+nt5BA1ide6NJeXlyMyMtLtx23v3ZRdYbn18zsjX6YzGtFr6WIs/v03byeFPMBg8p1ZkB3xpS7NFu29spaoORjuukeVTgsAyKms9HJKyN94swLZqy28u3btwocffoiSkhL06NEDc+fOxW233VZvX4VC0eTjXqrT1aux91WrVM06R1uRXbPshlJZ3S4/PzVMo9H4xHWhMpjHLa489gf+HBnj5dSQu51WKBAokXg7GU6Vl5e3ej5oLO8NiIr2ibxJ5E/KSksbzTe+8tzzZblFhQCASmUVvytyydnyMuvP9teORqPx6Lm9EvDqdDr06dMH3bt3x+uvvw65XI41a9Zg9uzZWLduHQYNGmSzf3JycpOPXZmTDfzxe5PeF5R+HKgod/kcbUXxlSDg+FEEhwS3y89PDVMoFD5xXVRqNcC+PYBI5BPpITfZswMA0KdvX4TK5U53MwkCbl39GebdcBPuSbqmVdMGAGHh4a1+3TnLe/2OHUFGSTFGJSUxLxA1VU1+jomJaTTf+Mpzz5cVBAUCaX8gODiE3xW5RJmXAxw9BKB+3KVQKKCq0xDpbl7p0iyXy7Fx40YsWLAA0dHRCA0NxezZs5GUlIT169e36NiujeFt0an8nqimgw/Hg5Ev0xsta496OSFUj9Fkwswtm3A0L6dFx2iI3mhEblUl/v3j7mafoyV8qUuzZayzJU8QUdOxS7N7SESWsqPv3BvJP4TInFdue5pPLUvUrVs3FBQUtOgYJhfGo7qyb1tUO1FM+/4eyLcZBXPhnuMWfU9hdTX2XbqIf+7c3uxjWP6+je/XOn//fGWVze++eN1xZn0i8hbL5JG+VBlI/sGbc3Z4JeC9cuUKXn75ZSiVSpvt586dQ/fu3Vt0bFfyn6Sdz9hnDXd5zyIfpq+5QTY1MKLWY6k0a0nlobGRpntLK0JrtSbc/vlKh+dviqLqaoxZuxpZdcYpuZOlgMkWXiLXcZZ/95BYV/hg4ZFc481eAV4JeGNiYrBnzx68/PLLKC8vR3V1Nd577z1cuXIF//jHP1p0bFcy4PCEzgAAuQ9PmOJJInZLIT9gqCnc8yr1PZbyY0vuIY3V+Lb2/UlrNNj87korxrZzGThXWoIvThx3S1q+Sj+BoZ8stz7XLN2/2cJL5LpPj/0BvZF5p6XELDtSM7W7Ft6QkBCsXr0alZWVGDNmDG688UYcPnwYX375JRITE1t0bFeyX2xwCADghi7dWnROf2Vdh5ehBPkwS8suH66+x/InMbVggHVjf1f718s1aqRezW32+VzlSiWqu8e2vbDvR5RrNNbjWQoLvr6UE5GvKqyubnSfI7k5+PzEsVZIjX8SuaFnD7VPjc3Z4UleW5aod+/e+Pjjj91+XFcKGrX7tu9My0CCfJmehXufZa2MaME9tLHgzb5CbtqmDThVVIgLT/yrVboounJ/tPQWctSKZBIEZJQUIzk2rsnHE8H8dDKYTJCIxdbvW+fhVqp8ZRVigoIha6e9n/yVzmiERCSCROxT07N41X/2/Wi7oQm3jMnfmSdPfXDQUA+kyP+J2aWZmqluj6kpG7/B6vETWu050+buii7N0ozWHRvmazichSwEQfDZh5eBXdB8luWSKW/B+nmNjc22H+N7qmYNyNZq5XSlS7Plwe0oIP0y/QTu+uoLHMq+0uTjWQJ66zh2k21LrydoDQbcuPITLPjpB4+dgzwjafm7mLppg7eT4VO+TD9h87uvPuca88qv+5D4/jtIfP8d5FVVejUt7NJMzVW3hfdQTjayKyta7dxtLuB1pXtua0+G4mssyxL56wOgPdMZjVhxPNVtBd8hnyzHfd98BcBc4PV0C5IrDLw+fZY7JhJr6qRV9lor4DW4MF5WWtOy5ij/nC8tAQBklhY3+XiWgqXRbuI2T45DtATXmzMUHjsHec7vudneToJP86VnmytWp9V2sT6S23pDOhxhwEvNZV+B3JrDc9pewOtSl+aa93goLXUdv5qHlE8+wN6si61wNtfwluV/VqWl4rX9P+Mru9rr5qrUanGiIB8AkPzBexizdrVbjusOrgQc1LrcsSyFoZGg2b67tNiu1dPTVHq9y+/RObhmawuJTT+OGPYtvOb/1QaD0/e0lHWCLBZmqQ1qrILNH3j7mWjpHMh7BLnKfgyvpXfYvksXseS0e8qzzrSZgLdSq8HJgnwXa5zM+7ZGC+eEb79GqUaN5/bs8vi5XMV7lv+p1pkL4ZVabYuPpTHUL9Bfrihv8XHdxcAlWHyWyQ1BZ2OTWNjfn+1bPZtqx7lMfJl+AmeKCl2656tdCHitsyg7uGabNSt+TcnSUsA11BTWj+bmNP0YLqrbS+qKD90HiNzB28GiO3hz4h8A1vFw7B1IrrLvFTb5u/XYfeEcZm7ZhB/zPNtzoc0EvA9t3oh71n9pU+PU1Nk/W9qknllS3OTAw5cm4LGOYWYbr9+xFvrd0KXUU2t6XiwrxX9/3dfibk+NtQCS97ijhr+xY9hfP5Zr39X79tydW/GffT/i7q/X4OtTJ+u9viVDgeyK+uOJql0IeC1psl/aCGje2pWWz1qkUgGoLeiWatRNPoar6n7ft32+AiU15yZqCxobInOqrLSVUtJ8Xh/m086HA1LzGRz0sDhw5XKrnLtNBLyCIOBY/lUA5vGHFo23HJj/17ZwTMfYLz/HPzZ926R9q3RaZJY0fQyXJ1k+f0MFsCJVNfouW4JjV/NaKVWuyamswImav317IhFbWrkEfHD0sMMCfFO5I2h2ZM6OrViVdgxZLSxAsIXXd7kl4HVxHd7aLs3Nv2+fKiyot+2p3Ttw59pV9bbrHASvzli+D6VOV++15ox7s7znvvVfArCt/PFUK4+jZaCI2orGJkFcfKq2W6WvtmB6u4XX8q0w4CVXmRyUN1vrKmoTAW+VrrZ1te54q6a28GpaMB7KckN0VIByZsbmjc0+nyc0dFM/nJMNg8mEVWmprZiiphux+jPcWzPZUntSt4X37UMH8PzePc0+lqMaN3ewjPNpySQh963/CjO2+FZ+oVp1uzQ3t3DYWIWL/WFdbeH96eIFFFYrbbY56zXg6Fp15flgsBtrW1dzujRb9rUE0nXXO/bUOF7724Ev9UoiaqkJ336NfGWV09ctlcmA745R9Xa6LPd6X60QAIBd589h3yXfmzOnvTmck41SdW0vIWflTbnY80sT+W3Aq9Lrce2H7+OnixdQd2G1gjoFm6au75hZUozL5eXNSkdzbjwtaZlwJ+tNq0n7ejYt5JragLfxP0xxI10SndUWt7T21rpESwsKzGkF7a/13p/Uvf6aWwhrrAW/Xgsvmh7wZpWXYda273H75ytsj2n30G3oWnelB1DtbMr1j2dJtyv5yj7YrhuouzK22BX2hdjWnEWzrVLqdHh69w6UqVuntTyzpNimtxvZenzHVofbBUFAXp3npbdbUp3xdrq80cJbrlGjqLq6yfvP2bEFM7ds8mCKqK6PU4/gol1vPpMg4O8bv8GUjbU9YB1VcCt1WocTPbqb3wa8OZUVUOn1eOO3X20yf92+4CoHk/HUVTevvrp/X7PS0ZwJEOwLW95W1cD4Y1FTVmmnVicRmbOus0mDNAY9tAYD0gsLcN1nH+I7xWmnx6pbiK47Xq+lLUhy6xItzTtOkar+w83bD3qyVbfA09zJYBprQawX8IqbPkuzpYBkfy3bt/A2dF25EjhYW2IdBbyWMbzN7MBlEgSYBAHdwiMANG/26Kaep67GKsyocV+ln8DmDAU+/ONwq5xv7Jef47kfd7fKufzRcSfDoOyX4nI0NKHuvhsbeK56UkuH4bWU5R7Wmi3N1332Ea5f8VGT9j3owlrn1HJqvR5v/LYfo9aswmfH/rDZDgAZNcM4TxcW4FkHE/duyTjbKun024DX0nqkN5lsCi/hAQHWnxsK5ADbB3tz821zJvzxlUl4LB+5sYoB8j2SmmDS2QOn/wfv46aVn+BCzdqf+69ccnqsuoX9tDoFgaoWXhdyiRQAoNYbkJZ/1aWx1udKSvB/B36tt92VCYQaYzSZfLpLlj+oW1vr6r1Q1sQKEWfLEjU2Fg8A3jq43/Exm9jCOzvlOhgFoV5wmVVeVq+bNFCblxxVRDVlDK/WYHC6xu7Pl7IAAKFyOQBApXdeGG8J+/Qdz/fN+RuoYb/ncD3ehnpBjFm7ul4FxOmiQpvflx455PT9T+/egWe8tOpG3WF83mC5RVR76B7kiCs9TZo6p05bVaXVolKrabXz1e21+vqBX6wVzfaxxVsHD7Ramhzx24DX0j1MZzTYFF4K63R5cDZzss5oxFO7tyOrvMy6rbimj3luVaVL3Zub092rsUC8tVgK+56apVdj0LNFrokqNBqsP3WyyQGYxEHh2XLdGkzmEKFUo0Z2pXnW2Ya6jda9hut2oSxQN9yyo9TpkPj+O3j1158dvi6TmG8v1Xod7vvmK9z7zVfYlnm2SXlmzJersensmXrbc6sqG31vU2gNBvRZtgTLj7ZOi4s9QRDwvwO/+MwEds1Vd01LZ3/XI7k5+PePu+td2xJrwNtw4GofPFr6nDTlOrq9R6LD7fbvdVZxdG2HeADABbuuWiO/WIk/rfgYT+zcavO5DA10aa7Jsk4DXoPJhGs/fB9//269w9cVxUUAgF7RMQCAjJKSevucLS7Ccz/uavQ7/dfuHU67ddp3OYsKDGrwWNR07qpeK1WrsONcRoPPCz57gRf2/ej0tXOlJfUK4GtOptn83jk8vNFzWHoiCYLQrLKdwWTC8qO/N9iaDNRWEAJApab1ghlHLC28pa3URd9dLpaVtouu/sM+/QCDP17eauf7tE6rLlC7tq5KZxvwtmYFiSNeC3jVajVeeukl3HHHHRg2bBgmTZqE3377rcnvt3Sf0xqMNktA1K11v+QkcE3Lv4otGWex83ymddvJgnwAwC2rPsXtX6xw+D7H6Wj8oWL/UGrtNqWLZaUOb6aWdDSly+mO85kut4Zd88H7mP/TD03ef/2pk/jx4nmXztFWfJR6BAv27sHRJq5D5mgtUst1W7eVdsnvBwE0PG68btCSUScAO9vIGpxbarp/rawzodmPF89b85K8phdG3YqnJ3dtx0d/HGnwuA1pyWzhJwvysTlDgUqtBkfyzOuYLv696fccd6rUavHpsT8w2Ulw4wkXy0oxe/sWt1a42XRpdtJzZd4PO/HtmVP1usZarmGtoZGA1+62E1LTwlnehEJfiFzmcLv9/dBZENq3Jrh0VjGx/VymTZ61BIuOWmCCZea0OKuIPZqbA2PNigNXawrRN3TpZn39/cPmvNwlPByhcjn2OLhXXqkox4Yzp3G6kUkUv89Q2Dz/APOzc3OGol6w/Mqv+zw2XtjXCIJgrVjwlK/STzQ4xKQp3j54AHN3bsOVOsto2V/DvtKTzJvqVpomxcZZK7Ccsb/2y9SN32Ou/8zczfbL9BMY9PEya0+MprhYVoov09PwzqHf8Pr+nxvcN1gmt/6cV+V80i130xuNNs8MkyDgzd/MPWcMbuoldbWqCgXK+j1m3MES4H5+4hhGrVmFl37Z65Hz+JLWnnfBvuGgoqZ12b6Ft266JvcfgEW33o7eUdGeT2ANrwW8r7zyCo4fP44VK1bg4MGDuPfee/HYY4/h4sWmzapmGb+lNRpsxh2W1Klx+tcPOxw+vCwFcQAIlcmtXcTqTmxy/Gqew0KQ/Q3x49Sj1p9/uHDOYVod1fbvudC0wO7AlcstGo8gCAJGrVmF8evW1nutodYIC1GdIbz2rRz21Hq9ddC65diuPNgX7N2DR7ZtbvL+vuRSeRnylVXNXrPyXE1rTVO7ofx48QIAYG36CZvtJkHABw7GiSl1zgusdcdeLjv6u/Xnn6/mNXjjrJuPLIHoI9s24571X0IQBOs4429Op9u8b/Hvv2HIx8tdbt3sFBqGdw4dwLbMsw3OsunMPeu/xNO7d2Dwx8vx4PffWbd/ceI4Drdy9z/LfcRR8KM1GLAq7ZjTrq3NtensGey+cA7bz2W47Zh1WwOd9SKwfNYKu2vb0k3Y0Zq1zs6h1uvRIyIKAHCyML/R9Dm77g9kX8aak2nYf/kSAOC37PrrAK6bMAndI6MQExSM1/f/7LQge7XOtWjpLVOsUiGzpBjP7tllvddb8oOlJ4ZJEGxaG65U1gYvD//2C/ZmXURRtRK390hE3+gY6zPvSkU5Zg4Zhp3nMzHyi5U2FVz948wF+veP/N6ke8m+SxfxW/ZlFFVX44md2/D07h1Yb5dfAeDV/T83acKl41fzUOGG1ied0dgqLZRp+VdtnvPfnjmFu776wnpdWAiCgEt1eoS5qu5z9IV9Pzocx+YKyzKMdQuU9t+Xr7TwCoIApU7n0oRDripQKvFLnfyZVV4GjV1hu1qnw4q/3Is7E3vZbLeMjdcaDLi7bz+b1z5KPdKkstrFslL8WnPNPLRlI3Y0co+t1ukwe/sWjFqzCi//sq/mGA1fX3XvnwdzruB8af0eHs2x4cwpfJx6xGml1j93bcegj5dBEARklZfhcE42UutUPFu6zmsNhmZPYnXTqk9ww8qPMX7dWmzPbNnzyX4ZtRMF+dibddH6PbfWmq+tTaipiMip8xxpiEqvx9sHD3hkLojTRQUoU6ttrqmvT520uWZfvPV2PDhoKHZOedC6bWSnzm5PS11Sjx7diYqKCmzduhXvvvsuevbsCQCYPHky1q1bh3Xr1mHhwoU2+5sEAWVqNaKDgiASiZBbWWmtoa/W6zFr6/cAzON3LQXIu/r0xfZzmbjrqy8wqf8AXBPXAYIg4FxpCb6sEyQo9TqkzpqDYZ9+gMt1WrQmfPu19ed+MbE2LV/94zrAYDJh6sDBNq1bj23fYv35z7374qZu3VGsqra2ss274WZc37kL7t+wDo9u32xzfL3JiDsTeyNfqUTfmBicLizEiO49rC2k/719FCYkXwOTYA5QLK0lPSOjIBKJoCgqRHhAIIJkUqQXFODWHubv1TJZS1Z5Gap1OmvrSKlaZQ1OdUYj9mZdRKBUCqNgwi3deljTVvf+lVFcjJ3nM/G35GvRKSzM/P3rdAiWySASifDCvh+x6ewZnHh0rk0rdoFSiWq9DqFyOaq0WmiNRlwT1wHOnC8tQUG1Ejd17V7vtSJVNQIkEoQHBNpsFwQBIpEIRapqhMrkCJLJkFlSjNjgYEQHBVvTqjYYEBsc7PC8Kr0eBpOx3rEbcq6kBBKxCKPW1K7feeGJf9VbgkQscjz5l85oxF/XrbUGf9mVldAY9AiUyqzvP1tcBL3RiEEdO5mPX1qCAw4K6ADQe+lih9sP5VzBQ1s24pXbRiImKBgyiQRSsRgGkwn5Nb0iekRGWQt1L916B176ZS9uXvUJbunWA3qTEXqjCZP7D4BREHBVWYXvzpyyHv9v336N0b16W3+/YeXH1uEFjiYIqdBq8OevvsCt3XsiISwMMrEYUrEYpWo1ZBIJgqRSqA0GXJfQBV0jIhAVGIjJ1w7EnO1b8OSu7ZCJxRgY3xFdwyMQGRSEcHkAIgIDER4QgMTIKAzplFD72bOv4Pdc5wGtpcZ3QnJ/JISFIT4kFB1DwyARibDs6O8Ilcvx39tHQSaW4KesC+gaHoHEqGh8dvwPTB04GGHyAMQGB1v/5oD54X+pohxdwsIhFYsRILW91Vq+c5MgwGAyoVhVjY6h5jy15mQaXj/wC4wmEwZ0iEfXiAgkhIXDYDLBJAg4mH0FHUJCnOYhrcGAEwX5uK5zF+u2EpXKet9buHcPgmUy/LVfstPvpK4SlQrfnEnHQ4OH1fscdYeT5Cur0CksDJ+fOAalToc9Fy/g8ZTrESA1V4xYa331epuuTcuO/g6xSISOoWFQG/QYFN/R+l2UqlU2raXzf/oBhTWtn0t+P4gekVEY1bMXgmS2LbmfHjuK3tExNbP4O7bo558AAI8OG16vK+OE5P7W72/puLvx6LbNeGjLRsSHhCIy0Pb+8PTuHcitrMQ1cR1wqsjcshosk2Hsl58DMFf6TRs42Bow7710EYnvv4OYoGAodTqEyGQYn5RsLUTGBAWhRK3Gw1vNM4ze0LUbpg0cbF2e66nrb0SPyCgczsnB77nZuO+br/D1fffj+i5dkRAWhlu6dccvl7Mw9JMPcE1sHGJDQqAzGhEbHAyJSIysOgVrR7OYWrqnJUZFQRDMz46vT53Ed4rT6BMdg7iQEFRptQgLCECITIbwgECEBQRAJhZba/oX3DwCeqMJVTotDCYT4kNCkVFSjPSCfEy+diBigoMRKJEiOjgIUpEYEIkgF4thFARIxGLc9dUXuK1HT3z2l3shQu2SToIgYIPiNEYn9kZEYP379In8q4gPDUVUYJD1Wv3ixHH0iY7BtR3iIRKJoDMasDfrIub/9ANMgoB5N9yEx4f/CQBwpmYM5+HcHNzSvYf1uF+dOon/7PsRm+5/AAPjO9rkdcB8TRtNJoQFBODL9BPQGAyYOWRYvfR9W+eeWanV4NfLlyCTSDCwQ0dEB5m7jtvnMYszRYXoEh6B8IAA65AWTQPLMFbr9fjp4gWMrAnwyjVqXFUqkVFcjO4RETb3SIt8ZRXiQ0Ktn88S4Ey+diAAc8XuHV+sxJbJ/0C/mFhIxWKkXs1DYlSU9TmbWVKMS+VlkIoluKVbd3xxMg2v7f8ZALD+b5MwPKGLzTmVOh1K1SoIgnlcepBMZp0sUywSwSCYECCRwCQI0JtM0BuN0BuNMJhM0JmMUOp01uv46MOzYRIEjPxiJUb2TMQdPRKxt2ZpmpSEzogLCcHHd9+D1/b/jBXHzWW3m1Z+YrO6h71Ht2/GX/sloWdkFDqHhSM6KBhRdtde3ec/AMzduQ3dDx7A5Ypy3Jt0DUYl9sLqtGN4/Y47ESiTYWvGWey2ayA5kpeD5/fuQVRgECICAxAuD0B4zTPNUlkGAFMGDMKOcxkY9+XnuK5zV/SIjERscDBigsz/ooOCECiVQiIWI1gmg1QstpbHRDXfqSAAUrEY50tLrJObvfHbfnx411/RKyoa/3fgV+v3ZtHLSdlixpaN6BkZhYySYvSP64B/3XATdEYjjuTm4J6kaxAbFIwgmRRBUhlkEolNWchoMtlUqqcXFuCJXdugNxnRISQUUYGBiAwMwgMbv7HuU6SqRpVWi8+O/YF+sbF4cNBQm/RM+OZrm9+/OHEcO+r0ZsmtqsRGxWlU6/W4qWs3JDbQwmgSBKdlN3cwCQKMJpN1TqK61p86iS4REQ7LwY7oTSZ8dvwPbFDU3mMs5WK1Xo/lRw9jxuCheGbPTozt1QcLapay/OCPw/h95qMIDwiAzmi05rOowCBIRCJcLCtFQk055nxZKSo1GiTHdUCgVAqZWOxw+MzLv+zDy7/sw71J11i32S+dKatZhkgiFuPik/MgCALOKBTQeLCbvEjwwqwtBw8exIwZM/Drr78iPr62i8mLL76IjIwMrF9f280vNTUVkw7+Yr2Z1w1q6wqWyZA6aw52nj+HwR3ND4/BHy9Ht/AIm5pzexOS++OtO8fiSG4OXtv/M5Q6Hf43cjQW/fyTTZDbEIlIhHF9+mJbIzVT/719FKYMGISVx1Px6v6fm3TslogJCkaVTmu9IMUiEYKkUkQHBVvHdjrSKTQMYXI5qvV6p2MmwwMC0DE0zBqodQ2PsDlmmDygwYkVro3rAElNAadKq0WQTIazdq3xSbFxMBiNUBsM0JuMiA0Kxpmafa6reWhauqZeExuHQKnUWvM9tGMn68/DEzpDAPBHTdfDgfEdkVdViejAIIQFBJhvOoJg7Yo7OL4T0gvz0SU8oqawFoLcqioYTCZ0CQ+HWCQy1wgbjfXSDAB9omMQGRgIndGIEzXHTI6NQ5g8wGaGVq3RaD2nvd5R0ZBJJDY9FEQA4kNCUabR1GsVG92rN36wq4n+3x13Wm9q9oKkUohEIpvave0PTMPHqUcghgjvjB6HT3/ehyNVFThVVGAzNr6uyMBATLzmWnx67A90DgtHuUaNUYm9caG0BKeKCvHVffejY2gojuTm4K4+/RAilyOjpBilKhW2nctAal4uilUqc0HGZG7VCZBKodLr8fwtt2HGYNuHmVqvx8azZ3AkNwd5VZXIVypRodXYdFGViERIe3SutXJn7ck0vPzLXmtPhpduvQO5VZW4tkM83jl4wHp/6BASgqLq6mYNORCLRNZ/EpHI4QzXYpEIUYFBMAkmlDloBYsJCkKwTN5g3qzr2rgOQM05RTDPqC4W1bb+yMUSXNvBHBQfc1DpMLRjJ4hEIvO/mm0CzA9JtV4PmUSCwmolrtbpapYUG4dgqRQlajVig4NxuqjQOu5bBKBbRKRNxaG9gfEdnV7z9mk7VVRo8zCNCAis10psESSVokt4BCRiMZQ6LXIqbe9bCWFhEARgZM9EnCjIxzM33IwHN39X7zgdQkIgFYuxYeLfrUE3YF4V4M2D+7EtMwMdQ0KRX63EV/fdj1C5HI9u22zTyjs4vhPeGDUG//5xN86VFttMtCaXSGw+0w1duuFQTm0Pnrv79sP7Y+/G3tQ/oAkPh6K4EPcl90fPyChr4aWu3MpKXKkox9BOCdZASRAEHM3LxcHsKzicm41KrRZBUimKVSqUatSo1ukw+dqBuKFLVxzMvoKMkmLEBYcgMSoaI7r3gEkQUKpW4c99+lnvdbvOn8Ph3GzkVFaiqFqJyxUVUBv06BoegSqdFpUazy4rIRaJECyVwSiYrHmrS3g4gmVylKiqIQjmwKm5aegcFg4Bgk1X0cjAQJgEAYFSqc39Ty6WIEQug1gkgkwsgUEwWSugY4ODrT93DY+ACOY81dQ8DQADOsRb/5YmkwkSsRgmQbBWiFzbIR6narqsRwQEIjEqCvqarqX2ky4BQN+YWAD1u+V3CAmBTGyu+BTXFIrzq5WQiyXoERWFKq3Gmvf7RMcgSCbD6cIC633U8tks6n72ut+V/d8kVC6HRCSGUTBBZzS2aJ32pugbHYMP7x6PmKBg66SmlorkC2Wl2HEu0xp8ikUivDp0OCbfdAsAcwD2aepRHMvPw9WqqnrPhrG9+mDm0GH4+I+jOJqXi0n9r0WxSgW1wVBvyIAzSbFxCJRIYYKA7IpyVGq1TnvdLR79Z9yTlIzCaiVWpx3Hr5ezUFCtRKla3epD5W7o0hUv3ToSnx3/w6YipzEysRgiiKA3Gd2S5hCZDGFyc7AWJJO5PM9HkFQKiUgMsdj8LLVcnwaTCQXVSnQOC0ewTGatZBIAa+Wz5X+jYILRZIJREGA0WX43/x8mD0DXiAgINYGk1mCAxmCA1mBAfrUSEpEIQzslQAQRBAjWgNPynHxw0BAsuvWOJn2W8evWIr3OcBa5WIKY4CCbZ7g72d8Dtj8wDcWqarz0815klZdZK1ie+tNNeOfQAfSOisbDQ1MwsmcvxDhoeFIoFFCpVBg2rH5loVvS642Ad9u2bZg3bx5OnjyJgDqzKi9ZsgTbt2/Hjz/WTjSQmpqKb/OyESyRIqOiHHKJGL8XFuL2Tgm4oUM8pCIxtCYjUmLirJOg1CUIAsp1OmiMBqiMRhSq1QiXydAzLAzBUsfju+xpjAYIAnBVrcKJ0mJ0CAyGXCyGoqIMQ2Pi0L+mldVgMkFtNGBnzhWUaLXYdzUX1QYDburQEaMSOmNYbAdrpgGAPFU1vrt0ER2DgpGrqsaf4uKx8fJF9AwLR251NfLU1RjVqQt25WajRKtB3/AIZFZWICEoGB2DgxElD0ChRg2jIOBMeRkSgoOREBSCP0qKMDAqBkbBhMSwcBRrNIgOCIBULEaxRgO9yYSMinJU1LSyTOiRiO8uXbQWbm7sEA8BQJVOD7XRAJlYjE7BwdhX88CNDQhEbGAgwmVyHCk2P2BTYuJgFAQcLy3GtZHR0AsmXFZWoVNQMFQGAwpqupkES6UQBCA5MhKAuTu1pRatXKvF5To1rSmxcQgQSxAgkaBKr0O1wYAzNS2QA2pq5XKrq1Gp12NwdAwMgglpNV0mBkfHIK20BKFS899aBBEuVFWg2mDAkOhYnCgtRv+oaHOQAhFEIiCjohzVBgMGRcegSq+HXCzG2YpyDIqOsX5vXUJCAAA6owlFWjUKamqjxDUtFBqjEYOiY2ASBMjEYhyrKWQkRURaJ52whBcCBFxRKq1/hy7BIZCIRJCKxYgNDIQgAJerq6znGN+tB9QGA7QmIzIrKvB48rWIlMuRq6rGDR064rKyCucqK3BTh44ItWvx0hiNSC0uNH8nMhk0BiMMggmRcjlkYjG6hoThBrvxTRqNBoE1NdlqgwEXqioh1HyuQIkEEIkQKZcjUh4Ad7LckuwL9w0xCgJUBj2Uej1kYgli7WrgK3U6lOt06BQcbDP5hz2DyYQynRYlGg125FyBWCRCj9AwhEjN958f8nIwODoWFTWVOcPjOkBlMCBQIoGA2ut58+UsmAAESSTQmky4IS4eqSVF6BUWDolIDI3RgMzKCtzdtTvKdVocLSrEbZ06Q1/TanGspBhxgYG4rFQiOSIKigrb7m4hUimuiYwyP2yE2pmMBQGoNuiRWVmBlNg4GEwmiCBCmU6LSzVBWaRcjnCZHDEBgRBqqmBM1kKsOS/IRGIYBBMMJgGnys09QbqEhCAhKAQ6kxFikQh6kwlikQjhMjkm9EjE74UFyFVVQ2s0Iqdaias1k54Ni41DZs1Yw15h4cisNOez/pFRmJt8LZacPonMygoMjYnFZaUS1QY9kiOiUK7TIktZhcSwcFxSVmHjHaNxqaoKZyvKcU1kFAIkEpyvrMCpslLIxBIUatQQIEAqEiNfrUKwVAq9yYTRnbtiVKfOMEGw1ipbVOi00BiNMAlAoESCqADXr2VBEFCl1+NCVSWUej1SYuMQVKeVziQIyFJWQVFeils7JiBMJkdGRTk6BgUjQi5HqVaLQIkYQRKp9Zqvm/f8hc5orGmNk6JMq7EW4KRiMWQisbmC02SCymhAtV4PncmEipqKKgEC9Cbzc+CSshJrL5zDmM5dEVtzjRoEAQVqFVQGA44WFyExLBzdQkKhMhhwsaoSRkHAbR0TUKbTIkwmQ4hUBhMEiCHCkeJCpMTGIbhm1vhKvQ4iiJBZWY70slLc2CEeQTWvCQDSy0oQExCIXmHhENVc50ESCc5XVqJbaGhNC5k531jyQIlGg0q9Dt1CQ3G0qAhikQiDasZ/A+ZKuGMlxSjTadE5OAQCBIggQm5Nb4UQqRTqmtYVy/sEwdwV2vL/idISdAkJQYfAIARJpCjSqBEul0NvMkEqElufOZerqxAlN7e4X6iqRFJEJACgWKNBlV6Pfw8YjAOF+eYVLmoK6ZZK398K83FDTbf4QKkExRoN0stKkRITB8B8nzlWUowb4uKRp6pGTGAg5GIJIuRyiAAUatTWZ158UBAGREWj2mDAkaJC9IuIRFJEpDkoEATzs05kfpaU67ToERqGUJkMhppeIwIE6Ewm6/1VLjZfQzKRGFKxCBKRGLKa/yv1OhwpKkRMYCCyqioRIpWhY5D5Xj84OgZJkVFNvo6d5T29yYhijQYVej0qdTqEyWToGxFpU6arS2s04kx5GfLVKoTJZFCUlyE+KBgBYgnkEjFiAwIxoM41YiEIAtRGI5R6PZQGPapr/peJxRgWE+fwuWgUBFTpdaioec6pDQaIRObnvk0FRc2zQlTznlCZDAlBwQiWyszXjrIKRVoNjCYTEoJD0C00FEESKQJqWiCdtXhaKuOq9HpkVyuhNxlRptVBLALUBiM0JoM5LSYBuppAVyoS15R3RDAJ5mNLxCIYTQLy1SpEBQTU5D0pzpSXoWdNr8JgqRQXa/7GluuiuqY7tbHmXnyushwjE7rgxg4dka1UIq20GBN6JKJXWDgMggBFeRl+LyqARCSyPv8sgabWZIQgmPN2WmkxhsbE1VsGSlKncrvu//bbRAByVNXQGU0QicyfWS4WQy4RQy6WIF+tQnpZqbU8a/47iaz5HQAm9kjE9D5JDq8xe6fKSvFLfh4uK6twTWQUTDA/40wCcLa8DLd36gy5RAypSAyRCOgdFoFKvR6lWg2qDQZr2hXlZegRGgYB5msxpOZ5dlmphAhA7/CImkYK8yo5QRIp/tK1O0Lsyp3mXhgmBDvptWJPo9HAZDK1rYB369ateOaZZ5Ceng65vHYg/pIlS7Bjxw7s2VPbKpWamuqxD09EzikUCiQnN63bKxG5D/MekXcw7xF5h6dbeL0yaVVsrLmLTZndIP2ysjLra0REREREREQt4ZWA99prr4VcLkdaWprN9mPHjiElJcUbSSIiIiIiIqI2xisBb1hYGCZMmIClS5ciKysLarUaK1asQG5uLiZPnuyNJBEREREREVEb45VliQBg4cKFePPNNzFz5kxUVlYiKSkJn332GTp39uw6TERERERERNQ+eGXSKlekpqY2vhMRERERERH5rTY1SzMRERERERGRp3llDC8RERERERGRpzHgJSIiIiIiojaJAS8RERERERG1SQx4iYiIiIiIqE1iwEtERERERERtEgNeIiIiIiIiapMY8BIREREREVGbxICXiIiIiIiI2iQGvERERERERNQmMeAlIiIiIiKiNokBLxEREREREbVJDHiJiIiIiIioTWLAS0RERERERG0SA14iIiIiIiJqkxjwEhERERERUZvEgJeIiIiIiIjaJAa8RERERERE1CYx4CUiIiIiIqI2iQEvERERERERtUkMeImIiIiIiKhNYsBLREREREREbRIDXiIiIiIiImqTGPASERERERFRmyT1dgIak5qa6u0kEBERERERkQcNGzbMI8f1+YAX8NyHJyLnFAoFkpOTvZ0MonaHeY/IO5j3iLxDoVBApVJ57Pjs0kxERERERERtEgNeIiIiIiIiapMY8BIREREREVGbxICXiIjIjqA7CkF3wtvJICIiohbyi0mriIiIWpNQOgUAIOqY6eWUEBERUUuwhZeIiIiIiIjaJAa8RERERERE1CY1qUtzdnY2Fi5ciCNHjuCnn35Cly5dnO67c+dOfPLJJ7h06RLCwsJw55134plnnkFQUBAA4LbbbkNxcTFEIpHN+1JTUyGXy1vwUYiIiIiIiIhqNRrw7tmzB4sWLcItt9zS6MF+/fVXPPvss3j77bcxatQoZGVl4eGHH4ZEIsHChQsBABUVFViyZAnuvPPOlqeeiIiIiIiIyIlGuzSXl5dj7dq1GD9+fKMHq6iowNy5czF27FhIpVL06dMHo0ePxu+//w4A0Ol0UKlUiIqKannKiYiIiIiI2pGcnBzcd999NtuUSiWefPJJTJkyBZMnT8bs2bNRWVkJANiyZQsmTJiAiRMnYsOGDdb3rFixAuPHj8eECROQnp7u9HwmkwkvvfQSJk+ejIkTJ+Lbb7+1eT0zMxP9+/dHTk4OAODLL7/EpEmT8Pe//x2vvfaauz52izTawjtx4kQAQH5+fqMH+8tf/lJvW3Z2Njp16gTAHDwDwBdffIHnnnsOVVVVSEpKwrx58zB48GAXkk1ERERERESrV6/GwIED8fDDDwMAPvjgA2zduhX33nsvli9fjg0bNkAmk+Gee+7BqFGjUFRUhO3bt+O7775DRkYGfvrpJwwYMMDhsY8dOwapVIp169ahuroao0aNwoQJEyAWiyEIAt544w10794dgDnwXrFiBX744QdIpVI89NBDSEtL83qc59FliTZt2oQDBw7gyy+/BGBu4e3fvz+Sk5Px+uuvQ6/X47333sP06dOxfft2dO7c2eFxFAqFJ5NJRA5oNBrmPWq3+tV0RPJGHmDeI/IO5j1yRbh8LyLkP7n1mBW6kajU3dHgPgUFBfWu1UuXLiEwMNC67fbbbwcAbN26Fd27d7e2vvbu3RubN29GTk4Ohg0bhnPnzkEsFuPOO+90eu2HhIRgwoQJUCgUyM/PR1BQEDIyMgAAP/74I3r16oWysjKcP38eUVFREAQBx48fR1BQEEpLS1FcXNxovtJoNE37gprJYwHvihUrsGzZMrz77rsYNGgQAKBLly7YuHGjzX4vvPACfvjhB3z//fd4/PHHHR4rOTnZU8kkIicUCgXzHrVbpppOTd7IA8x7RN7BvEeuENRnIaiC3XrMkNgEdA5q+BoMCwtDYGCgzbX6xBNP4KGHHsLp06dx880346677kJSUhLOnz+PHj16WPft3bs3AgMDodPpEBwcjGXLlkGpVGLBggVISkpq8LxPPvkkjh07hrfeegvJyckoKyvDkSNHsGrVKsyYMQO9e/dGly5d8PTTT+Pxxx9HYGAg7rrrLowaNarRz61QKKBSqZrwDTWP2wNek8mE//znP/j111/x+eefY+DAgQ0nQCpFQkICCgoK3J0UIiIiIiIitxMF3QtR0L3eTgYAoHv37ti1axcOHz6MAwcO4MEHH8Szzz5bbwUcQRAgEokgCALUajWWLVuG1NRUPP/88/juu+8aPMf777+P3NxczJw5Exs2bMDbb7+Nf/7zn5BKa8NJpVKJjz/+GLt27UJoaCgefPBBnD17ttFg2tPcvg7viy++iBMnTmDDhg31gt2TJ0/itddegyAI1m1arRaXL1+29v0mIiIiIiKiptFoNJDJZLj55psxf/58LF26FJs3b0Z8fDyKi4ut+xUWFiIuLg6xsbFISUmBSCRCSkoKcnNznR77woULuHDhAgCgc+fO6Nq1Ky5evIhDhw7hzTffxP3334/Tp09j7ty5uHDhArp27Yro6GjI5XKkpKTg1KlTHv/8jWlRwHvy5EmMHTsWeXl5AMxLGP3www9YsWIF4uPj6+0fExODDRs24K233kJ1dTUqKirwyiuvQCwW4957faOGhIiIiIiIyF/MmDEDBw8etP6en5+Prl27YtCgQUhPT0dlZSWqq6tx7NgxpKSkYMSIEdi/fz8Ac0BrmWDYkYsXL2Lx4sUAALVajaysLHTp0gV79+7FN998g2+++Qb9+/fHsmXL0LlzZ1y4cAEajQaCIODUqVPo0aOHRz97UzTapXnMmDHIy8uztsqOHTsWIpEI48ePx1/+8hdkZWVBr9cDME9DXVVV5bCv9q5du9C5c2esWLECS5YswW233QaDwYCUlBR89dVXiI6OdvNHIyIiIiIialuysrIwdepU6+/z58/He++9hw8++AAikQgRERF46aWXEBgYiHnz5mHmzJkQiUR4/PHHERYWhsGDB2P//v2YOnUqdDodXnzxRafnGjVqFH7//XdMnjwZOp0OjzzyiNO4LTY2FjNnzsS0adMgkUgwZMgQpKSkuP3zu0ok1O1f7INSU1MxbNgwbyeDqN3h5B3Unpny+wIAxB0zW/3czHtE3sG8R+QdlkmrPBXzeXRZIiIiIn8mCFqIRAHeTgYREZFHLVu2DIcPH663/fXXX0fXrl29kCL3YcBLRETklMnbCSAiIvK4uXPnYu7cud5Ohke4fZZmIiKitkPk7QQQERFRCzDgJSIiIiIiojaJAS8REZFTbOElIiLyZwx4iYiIiIiIqE1iwEtEROSUT6/cR0RERI1gwEtERERERERtEgNeIiIip9jCS0RE5M8Y8BIREREREVGbxICXiIjIGYEtvERERP6sSQFvdnY2pk6din79+iEnJ6fBfX/77TdMnjwZKSkpuOOOO7Bo0SKo1Wrr66WlpZg3bx5GjBiB6667DtOmTcOpU6da9imIiIiIiIiI7DQa8O7ZsweTJk1CQkJCowe7dOkSHnvsMdx1113Yv38/Pv/8c6Snp+OVV16x7vPUU0+htLQU33zzDfbt24ehQ4di5syZKCsra9knISIicju28BIREfmzRgPe8vJyrF27FuPHj2/0YOvXr0diYiKmTp2KoKAgdO3aFXPmzMGWLVtQWlqKzMxMHD58GM899xw6duyIkJAQzJ07FyKRCFu2bHHLByIiIiIiIiICAGljO0ycOBEAkJ+f3+jB0tLSMHDgQJttAwcOhMFgwOnTp5Gfnw+ZTIakpKTaBEil6N+/P06cOOFq2omIiDyMLbxERET+rNGA1xWlpaWIiIiw2RYVFQUAKCkpsb4uEols9omMjERxcbHT4yoUCncmk4iaQKPRMO9Ru9XP/OhCRkYGBAS36rmZ94i8g3mPyDs0Go1Hj+/WgBdAvWDW8rtIJIIgCPVed/a+upKTk92XQCJqEoVCwbxH7ZapplNTv379IBKHtuq5mfeIvIN5j8g7FAoFVCqVx47v1oA3Nja23uRTpaWlAIC4uDjo9XqUl5fXC3zLy8sRGxvrzqQQERERERFRO+fWdXiHDBlSbyxuamoq5HI5BgwYgCFDhkCv1+P06dPW13U6HdLT05GSkuLOpBAREbkBx/ASERH5sxYFvCdPnsTYsWORl5cHAJg8eTKys7OxevVqaDQaXLx4EUuXLsXEiRMRFhaGXr16YcSIEXjjjTdQUFAApVKJt99+GwEBAbj77rvd8oGIiIjchwEvERGRP2u0S/OYMWOQl5cHQTA/9MeOHQuRSITx48fjL3/5C7KysqDX6wEAXbp0waeffoolS5Zg6dKliIyMxJ133ol//etf1uO98847eO211/C3v/0NOp0OAwYMwKpVqxAa2rpjpIiIiIiIiKhtazTg3b17d4OvZ2Rk2Pw+fPhwfPXVV073Dw8PxxtvvNHE5BEREXkTW3iJiIj8mVvH8BIRERERERH5Cga8RERETrGFl4iIyJ8x4CUiIiIiIqI2iQEvERGRU2zhJSIi8mcMeImIiIiIiKhNYsBLRETkFFt4iYiI/BkDXiIiIiIiImqTGPASERERERFRm8SAl4iIiIiIiNokBrxERETOCBzDS0RE5M8Y8BIREREREVGbJG3KTmq1Gm+88QZ+/fVXVFRUoHfv3njyySdx00031dv3oYcewtGjR222CYIAvV6PvXv3onPnzrjttttQXFwMkUhks19qairkcnkLPg4REZE7sYWXiIjInzUp4H3llVdw5swZrFixAgkJCdi0aRMee+wxbN68GYmJiTb7rly5st7733nnHZw8eRIJCQkAgIqKCixZsgR33nmnGz4CERERERERUX2NdmmuqKjA1q1b8cQTT6Bnz54ICAjA5MmT0atXL6xbt67RE6Snp+Prr7/Gq6++CpFIBJ1OB5VKhaioKLd8ACIiIs9hCy8REZE/azTgPX36NPR6PQYMGGCzfeDAgThx4kSD7xUEAYsWLcKsWbPQtWtXAEB5eTkA4IsvvsAdd9yB4cOHY+rUqUhLS2veJyAiIr8jmCohmEq9nQwiIiJq4xrt0lxaai6QREZG2myPiopCSUlJg+/duXMnCgoKMG3aNOs2nU6H/v37Izk5Ga+//jr0ej3ee+89TJ8+Hdu3b0fnzp3rHUehUDTlsxCRG2k0GuY98ph+UeMBAGfLNns5JY71q+mEdO5cJoxCcauem3mPyDuY94i8Q6PRePT4jQa8Qs2SDPYTTDnbVtcHH3yABx98EEFBQdZtXbp0wcaNG232e+GFF/DDDz/g+++/x+OPP17vOMnJyY0lk4jcTKFQMO+Rx5jyzf/76jVmSV+fPn0gknRo1XMz7xF5B/MekXcoFAqoVCqPHb/RLs2xsbEAgLKyMpvtZWVl1tccUSgUOHfuHMaNG9doIqRSKRISElBQUNDovkRERK2HY3iJiIj8WaMB77XXXgu5XF5vjO2xY8eQkpLi9H07d+5Ev379rGN3LU6ePInXXnvN2nIMAFqtFpcvX0b37t1dTD4RERERERGRY40GvGFhYZgwYQKWLl2KrKwsqNVqrFixArm5uZg8eTJOnjyJsWPHIi8vz+Z9aWlpuOaaa+odLyYmBhs2bMBbb72F6upqVFRU4JVXXoFYLMa9997rvk9GRETUYmzhJSIi8meNBrwAsHDhQvzpT3/CzJkzccstt2Dfvn347LPP0LlzZ6jVamRlZUGv19u8p7CwENHR0fWO1blzZ6xYsQLp6em47bbbcNttt6GwsBBfffWVw/2JiIiIiJrDVPoQTBUveDsZRORFIqFu32IflJqaimHDhnk7GUTtDifvIE8y5fcFAIg7Zno5JY5Z0ieK+xUiScdWPTfzHpH7uHKvYd4j8g7LpFWeivma1MJLRETkiKD9GYKg9XYyiIiIiBxiwEtERM0i6E9DKHsEQuWr3k6KB/l0JygiIiJqRJsLeAXDFZjy+0LQp3s7KUREbZupwvy/8bJ300FERETkRJsLeKH9GQAgqDd5Nx1ERG1ee2j9bA+fkYiIqO1qewEvEREREREREdp0wMtaeSIiaik+S4iIiPxZGwx4RTX/s5BCRORZosZ3ISIiIvKiNhzwEhGRZ7WDikXfXqqeiJpIMOR4OwlE5CVtMOCtofrK2ynweYIx3zyjte6ot5NCRH6NFY1E5OMMCm+ngIi8pO0GvNQ43REAgKD62ssJISLyVWzhJWobDN5OABF5CQNeIiJqoTYcFArV3k4BEbmDwICXqL1qUsCrVqvx0ksv4Y477sCwYcMwadIk/Pbbbw73PXToEPr164cBAwbY/Hvuuees+5SWlmLevHkYMWIErrvuOkybNg2nTp1yzycSsWud6/idERE5IlQs9HYSiIiIqAWkTdnplVdewZkzZ7BixQokJCRg06ZNeOyxx7B582YkJiba7FtRUYHQ0FCkpqY6Pd5TTz0FiUSCb775BmFhYfj0008xc+ZM7Pr/9s48TKri6v/f6p7u2RhmBoYlgCCCLLJlBETFICICvj81+OKC8QVZIxp3XFCJGBQTFIN5SfJGEcUFl2gUFJGgMREBQRbZR1Rkh5lhenrW3vue3x/Vt/d1pteZ83meeXr63rpVdW/fqjrn1KlT69ejuLi4eXfEMAzDJJkWbDRzHk11DRiGYRiGaQYRZ3hra2vx8ccf4+6770bPnj2RnZ2NyZMno1evXnjnnXeCpg+ntH7//ffYtm0bHn74YXTu3Bn5+fm46667IITARx991Ly7YRiGYRiGYRiGYRgXERXeAwcOwG63Y9CgQT7HBw8ejD179gSkr6mpgc1mw+zZszFixAiMHj0aTzzxBOrq6gAAe/bsgU6nQ79+/dzXZGVlYcCAAUHzixneQqIJ8DNjGIZhmEyGLP8GOU+nuhppDMs6DNNaiejSXF1dDQAoKiryOV5cXAyDwRCQPi8vD926dcOMGTMwfPhw/PDDD3jggQfw0EMP4cUXX0R1dTUKCwsh/NbaFhUVoaqqKmgdysqiDyVflF2OTnmxX9caKdCdRpc2QF1dHc6c4WfF+GKxWLgNMWHJyzqOcwqAxsZGnKyI7V3p63IEStd3TK2fU1FwKMl15LbHNIW+xbfDqeTjx1reltEbtS2fOn0K9bbw7YrbHsMkEkLH3OUwWCbDSW19zlgsloSWHFHhJdeMqb+CGurYlClTMGXKFPf3/v3748EHH8Sdd96JM2fOgIiCXhcqPzWPaKHGHaD62K9rjZD5R1At0LZtWxR152fF+FJWVsZtiAkLWatBRiA/Px/9z4ntXVHK5We6vmNq/bQaTdLryG2PaQpKOaDVNPK744falrt26QqRG/7ZcNtjmMRB5k9AtZ+gOOcTaDp/73OurKwMJpMpYWVHdGkuKSkBABiNRp/jRqPRfS4SPXr0AABUVFSgpKQENTU1bkVapaamJur8mHjB7j0MwzAMwzAMwyQYJdAzOFlEVHgHDhwIvV6P3bt3+xzftWsXhg0bFpB+1apVWLNmjc+x77+XWnz37t1RWloKu92OAwcOuM/bbDbs27cvaH5MMmjBEVYZhmFihCzrU10FhmEYhmHiRESFt6CgAJMmTcKyZctw5MgRmM1mrFixAqdOncLkyZOxd+9eTJgwAadPy0AJVqsVCxcuxNatW+FwOHDw4EEsXboUEydORLt27dCrVy+MGjUKixcvRkVFBRoaGrBkyRJkZ2fjmmuuSfgNM8HgmV6GYRgVqrkn1VVgGCbusKzDMK2VqPbhfeyxx/Dss89i5syZqKurQ79+/fDyyy+ja9euOHnyJI4cOQK73Q4AmD59OhRFwYIFC1BeXu5WmO+88053fs8//zwWLVqEG264ATabDYMGDcKrr76KNm3aJOYuQ0DmD0C18yA67YcQ+qSWnR7wzC7DMPGA+xKGYRiGYcKROqNTVAqvXq/H/PnzMX/+/IBzI0aMwKFDh9zfhRCYNWsWZs2aFTK/tm3bYvHixU2objRE/zCp/nn5j2IEtJ0SVB+GYZiWTmIHMSILgOyQgQ0TC88KMQzDMEzzUVJWckSX5paNKjyxQMMw6QoR8d6SrRhyGkAVg4HGl1NdFYZhGIZhmkzq9K0WqPCy8sowLQrTm6Czo0H2g6muCZMKlAoAAFnWprgiDMMwDMM0HVZ4UwTP8Epa+/0z6QzZtst/HEdTWg8mHLyGl2EYhmGYMBC7NKcIl5DmPJnaajAMEwYLAIDs36S4HkxqYIMcwzBNgyz/THUVGIZxwwpvHIlBOFLK5RXGXyeoLpkCz84waYzjR/lpeiu19WDCkAyllPsphmFig2ru9v6WsnowDAOQfXfKym7dCq/7ElP8q8EwTJxogd0UwzAMw0SJUrcIimFyqqvBMM1DFKSsaJYkAbDVLzxEjlRXgWnVaFNdASYiPPvKMEx6Q7UPp7oKTcf0GmDflepaMEzz0BS6/yWyJbfopJaWdrCQJgmt8JNtB6jiAk/gIIZJNoIV3tYNGyQZhokPck9vhmFSg2cNL1UMBCl1SSu5lSu8rfz2o1H4bV8DAMi6JcF1YZhQsMKbviRTGWUDJcMwzYSskZNYvgCZ3k1CZRimdSGyLvA9oBiSVnZW0kpKGrEIYBoAzkRVpIXAQiaTalq7Yaq1k9wZXqV6elLLYxgmmUSOEks1cwAAIu/mRFeGYVoXwl+eS974zpJkqyaaF433KmZSDXdT6UsyDWJJKsu22e9A9H0f2Q9AOTsB5Dwd3zoxDBMnWJZhmNSRuvYX1Qyv2WzG4sWLsXHjRtTW1qJ379645557MHLkyKDpP/30U7z00ks4evQoCgoKcNVVV+HBBx9Ebm4uAGD06NGoqqqCEL4CzM6dO6HX65t5S0zsRCNI8iDBpAp+95jmo9T9HhB6aArmxnYh2aNPal4DOH8CrBuBvMyMqEqkgOr/AJF/G4S2a6qrwzQBcvwIaHtCcPyDQCh1+4DGA8V4J0TRUgiRneqqMEzskL88l2YzvAsXLsS3336LFStWYMuWLbj++usxZ84c/PTTTwFpN27ciIceegi33347tm/fjhUrVuDzzz/H0qVL3Wlqa2uxdOlS7Nu3z+cvLsquyIkhMQvSknDPgWd4mVTD7176kkG/jelVoPHFJlwYi4DsUo6THH0yrtj3AaaVoJoYDQNM2kBV/wVq+N9UVyNNyWyFF9bP3bFVGCbzSF37i6jw1tbW4uOPP8bdd9+Nnj17Ijs7G5MnT0avXr3wzjvvBE1/1113YcKECcjKysL555+PcePGYevWrQAAm80Gk8mE4uLi+N8NAGhc+Ypo8s8gYS0hRDOzywovk2r43Ut/kufaTEotyHEsaeUh739iSKw6TWW4UA3ArbwzGQH5z5zYv01NRdKeFtA2A2bJGCZT8Ht3LeuSVnJEhffAgQOw2+0YNGiQz/HBgwdjz549AemvvfZazJkzx+fYiRMn8LOf/QwAUFNTAwB4/fXXMWbMGAwfPhxTpkzB7t27m3gLfqgdgSY/msTxKZNhmMShv0h+iraprQeTInz7aTJcD6q6KnnFx+Q6qA6pGSxUq0FFWKjOcPj3C05LeC4Z3L8kAWr4P5B5baqrwQTF992lhmVJKzniGt7q6moAQFFRkc/x4uJiGAyRw0l/+OGH2LRpE1atWgVAzvAOGDAA/fv3xzPPPAO73Y4//elPmDZtGj755BN07Rq4ZqisrCyaewEAFOhOoksbWc6RCNf1KSKoy4hjKaOlUKA7hS5tgLq6Opw5E/z+2+WcRYdcwFBVhaqTre8ZtWYsFktatIu2+kL8LB9osJ2PU2lQH8ZDXtZxnFMANDY24GRFbL9NX5cTTqR3LEd7FD3aAmaLBcfLytC3+GRU1zW1vL5+zkEGQ/R9X4dcI9rlABUV5TBam/6uprLtZWuP4dy2gMViwjFubxmE4vPumhobcSLGNtkS8W/PP/74PRxKTcj0Fotnn950GP9UvO/j5MnjaLCnT93Sjb7Fcgnld0d7pbgmjD+F+jPo7DcfqbYz77aXCCIqvKqbjH+AqVDHvFmxYgX+/Oc/44UXXsCQIUMAAN26dcMHH3zgk27+/PnYsGEDVq9ejd/85jcB+fTv3z9SNT31NR8G1QJ6vT7idUq5x9IXSxktBfVZtW3bFkXdg98/NXQENQDtS9qhQ0Hre0atAXIcB1WNhWj7lM82DGVlZWnRLsh0EFQHtMnPQ/9zUl8fxgNZDSAjkJ+fH/Nvo5TLz0jvGNntIAOQm5OD/t36R31dqPL6nVcBkT06YjqV9u2j7/uU+g5AI9CpYwd0btP0dzWVbY/sBDIAOTl69O/G7S1TIFJAFZ7veXm53F8isD337nUeRNY5IdN7K7npMP6peN9Ht25dIHLSp27phqevr4LI/kVqK8P4QKZvQXW+x9R2VlZWBpPJlLCyI7o0l5SUAACMRqPPcaPR6D7nj6IoePzxx7Fy5Uq89tprGDt2bNgysrKy0KVLF1RUVIRNFxPsjhUn0nsfXrJ/B3IcTnU1MhvHAQAA1f02xRUJhdqWHSmtBROO9O4nvCHjr0HWjTFcEMtYoj6HTN7fXRULeAzNLPx/L3Z7DU7491orqpNUj+bAbTMayDgz1VVgAgh8d4kUkNIIrTAGSR8/Iiq8AwcOhF6vD1hju2vXLgwbNizoNU888QT27NmD999/H4MHD/Y5t3fvXixatMgnwILVasWxY8fQo0ePJtyCPzF0BLpS+antFodymVRAhutAVVenuhoZTiyRzVOB2qZZgGPihPNswCFqXAFyngqSOBbhUt0GJpMFUlUsyGSlncnsdzCBWMKv7exe8GiSKtIc+LdlMpRg24KZ/wEyTkXvomkJLTqiwltQUIBJkyZh2bJlOHLkCMxmM1asWIFTp05h8uTJ2Lt3LyZMmIDTp08DAD777DNs2LABK1asQKdOnQLya9++Pd5//30899xzaGxsRG1tLRYuXAiNRoPrr78+DrdEfp9hUBVe/aVxKDc81Pg6yJqJoeQzZ+amNUGKCWR6NzAyZ1OIaSuvVOC6R2IBvFWSEG8d33eJnBWg+sWg6mAzArEYWhIftIpM74CcVQnL3xO0itsb0/KghhfCntdry8OeTwsyfC9hpmVBSj2U8j5RBgoLMsPrPC23w0swEdfwAsBjjz2GZ599FjNnzkRdXR369euHl19+GV27dsXJkydx5MgR2O1yC4NVq1ahvr4+qBvz+vXr0bVrV6xYsQJLly7F6NGj4XA4MGzYMLz11lto165dHG8tGiEpeTNHVP80AEB0/j7hZcUX3pYoHaH6PwDmdyC0XYHsy5qXmaZNfCqVcFgAb9U49scxsxB9PtVHnzYoan+ZmDGFlAZQ3RMQBVYg/7aElMEuzZmK/+/Fv18ogzCRE0Jog57LDPi3ZdII5wkAANU+AKp/FpqOniVD5CwHNCUQQlU3g727yTHgRKXw6vV6zJ8/H/Pnzw84N2LECBw6dMj9feXKlRHzu/DCC/HGG29EX8uYiG6Gl8iBZCq87nIdxyGyuietvGajBibjNdHpheJaZ0SNIPMnQFZPCN0FTcwsMb8tOQ4D1s0Q+VObnIdSeRmgVLq+8RretMW2ucmXElHEAIjxx994ogq/QcYCin4/WiE0IMg1SQm5I6F31cmciNxduBRe51GQ6V2fQHZMJsFjdmgc8LR5X4gEhEj3Z8czvEw6ofP86xVdjZRq0NlRQN6tEG0XqEeDXJ+cyYyILs2ZAinVLmue+jBDCylkPwiquACwfuk60LyHTaa/SytGNGlrH25WWYkhltnwBNbCcQQUZrsAxhuP6yTV3g8yTPQ5S2QGkS26rPyMGWQ/CHJWhkgcPWS4CVT/NKiJ7YuIvJRdsItliyVC3xJiJiYad36yfw+ldgHI3wXQ/10K68ZrjViOh0S7NOsACBDFUqdY8TxXqvttfJZNMG6o8VWQ5d+JyDkBeWY6IZ5JCCMWkZIByi7ACi+TTpBlje93ck1OmFb5fgIIblRmhTdqyHkGVHkx0Pg3eNb7hdnPyb5HfjqPuA40vfMgpRpUNx9knB3lFZnWUSVv5oWqxoOqrk1aefGGLBtAjYnyXPDDPfMe/H2iiiEgwyRPxxMWP4XXMBF0tplu0oCXe2gTZ2Ytq/3yS+webUxiIKVBrtEJnSJSDvJD5PodjzxIkvF2wPw2EFB+qGuDvKsxKZeJ9RoSQsg19wltC/6/B3tWxBOq/z2o5vZklJSEMtKdEM9ACbEGvvFviatKXOHflkkjGl/y/e4aM0kJtkQoyLtrSo7c3CIUXrhmo6hhqcdSEHZ2y/+2m2FdUBWOaGfEnKcz1GKepDorcdyaKslQzV2g+qeSVFoUa6sdh0AVF0CpuS9Ex6OS4N82BpdQ9yWOwyDbN34HG+NUISZ+RDHLWn0z6OzoZuShGjH936MolErVMOT/Lvlf6+6Tg4wFMSi8Hm+GBBs2/TcXjSus8MYbIhvIvDrBYz9vSxSAbWvQw1Q1LvhxdTIk3clIGZJpPcgxU+h9d/IhpQEUNDhVlN6IzaRlKLzCsxSZbF+5/gsnZPu5yDXLPUwVcKLsgJTKQGtIRsAdbHoROrAMWTf5HrCsA0xvhcnLIxhRE5TT0Kiz0LHPRlHV1YD5H34HWeFNP6LoFxw/NC8Pt3Dnr3hFY6iUfT1ZPvTL0/9aVxsI5hERYnwgsgVRYFTlPIFKIpkByyeJy9//90jkvbQSqOGvcjmTdUMSC+Uxm4zTY7wiU0RiNmaEghpfTnUVGHXMFIXyUye3p6XauVIeTRGZ0rqDQo7DLoHDK/ZWNOsWhd9tW/8VwuoQDaowEP0sMVn/1cSyEkU4t2Xeligaws+gRkap/5MM6x61whm4VpBs2+U/9r3BSgiTl5dgZHrX63j4d5psO2SdQ65HcwUyIJPnmuY8J698mNghy6dQyvuDEhrwqClEOcMbcDgaoS/UEOf/boeL/RA4ppB5LahiIKiir996WjXflqQkxtMI1kpRXPs+e8WoIMsGKLW/bVJ2pBibIbMwAKDUPQNyHPE7Gr28Q/bvQI7j8a1U1LDCGwqqfzb4cacBFGT/9ZaIUj0VSk0K4wW5x0TVkOwaF4PKpskjYxVesh+Qs0CmV+B7G9F0BIFBUMjcRKuD2/odutzAgCmZJHCywhsNVDm0eRmYVroyitXbwEvhrZkrP4POhEap8FKt+9/crANhSybLp65yPevRyLxORmcGvCLKmkDWTaCGF0GVQ0FN7vSUwLbERA3V/xGAE1R5Mci6MWL6KHMNfpQIZN8fcCw4kYyFoa6L5l1w9V+OnyJcGyavIB4KVPuA16U1XmfUJTWJV3gT5h7rny/P8MaBQI8cqrkLML8bPHkEqPpWkGFSpFRNyrvVYFoJqp7md9BXJA4XA4MM14GqxoJc/QNZN0Opvi2BY1S21/8cwDFW6OwloLMjU12N5GDbGhgDJZm4x0y1LajtKLVbgWWswutet2v9Gj6N32uGl5SGEBcHe+hNHRxU63e46/06J8XQxLJSAe/Dmxyaun+nVxMm1/vuDLYOOkqF1+f/SJ1ToDGEau+ThijAZwsVMs4ANTwvv9t2R8g3DBnVdtIUMoNqH4tTXiHeK8snIMN/+xkSPf2gj1Co1EUqJMTxKGYenS5FV/G17McUOTzSO+dtpHLfVzLWJCUqcJXf83YZtpjmEOfo3Y4fAfi/x7wPb8yQf9/j9/tEMd5Q3dPys+ZewPa1j9E4qirYf5CeUo6j4ROKHK961cRUBuPB7QmXoZDjBCiojJcaghpeA2Z4VYU3tSpn5iq8qjANO8jyT89xxauzcZ4McXGQ23YclJfX/wnUsDz6eqguqGEFKH+FN0SEwCAo5QOgGP4n+vr4QeSAUjURpG7B1PScmnk9Ex5VuYx2NkX9PbyUTlXhDRKoI6zV2avDIq+1vlrRVEVEJdClWX5vxpr5sNF+meiJ1yxEiCjhrhlV8lm/6/Vue8+aNlXhbZbQF+0MrwCcFRHaj7fHjquvV/fJTgDu/QxDGnSbBln/A2p8Bf7Pm5ypctsMDjmOZmDgx/BR9ZtM2L40tmdEzkpXgMNWtHTE33vD+rnv92gMrOa/y09XLBmqHBFmsiVYFT6W/0Ra2+gVpZ7ibPglpS7KHR0yH6qdH33aNHwmVHUl6OwvUl0NL4I8I/f4p/Z3TpDzjE9/JUrWQXTcBdH2yURX0E0GK7yqMO2AyDrfc9zh5UbnPBbi2iAzV6qS0PgXUMNzUVeD1M4unItJkEYT/YBtB+z+EUZjQDEAjoOg2kebmEEMa1rIHPV+xC2J+AhfqkAUxVYrpACW9b7XqeecBt+9a6PCq/5exhi95lT016n18kZTII83/J9fuqa79FP94iZfm04Q2aDU3Otx//Y+5zwLpe530e+j3CQSq/AKdx/rdd57fbrZK4ga1cgP67YQa6z825er7w8j9JF9H0gJE+QswCgUvA2LNg8CsIdXYH0MOq58Is3WNAftOa4yvo9rtmT8Naj+Dwh4FgHbQaUOsu2REXZNb6a6KrEhQnvwUOPrIOu2JmbsrbD5/W6OMigR3Z69rq5/XipdrWpGP8J4qxijyiUglkzEQH0ehGvmlsIEdyRnlW9k9mh3BYkCcpwAVQ6TQdWCnVdqM1quI8dJkMsjAkDUO4GQ6R+gigtAzkhyUPoQiyxKihFK/ZLmK/VB4s6Q7Ws5C63KhNQAOns5QF7tSdsTQtMGyPl/zSs/BjJX4XXPiNlB9h1BzguQWynwP+XlGqIpAbL6AADI4gkmRRFnHVy4N1QO89KYPwg85gi/PjL+hFFc7QejuC6a7Uemgc6OiqlWLYPmrach62a30B/sPSLHEV+ru/k9qO6cVDvXN+3ZS4IXooQL1hBEadGUIDfruzDX+NWRCAEuppou8tPfYGNaCaXqmvAKnRrdzx/7DqnUZzr2fYDl06CGKKpfJPsV67+hGG6AUjM3SAZNwNsAGLeZpsB8lNpHQe4+z7tteN4PH5csl5JLxikh1iV6eSCQA9B2c2UXvA8lMss9qGvuCV1t+y6/70GUx5yrAZ0cG2B+O2RWvuuhXffrPJa4mTLdUAD6oOMbKY0gy78jCj7K2SuhVM+KrrzGl9In2Itrtpn8f78EQ2RpZoCi0KIW1T8NMk6JMT/V4B/BrT2WwFYiVi+j9IGcZ0C2bz3fg3l/ZI+DKA6+3ydZ/i09+1yyoPu4cXp07qPOU15eh0BUwVNVRLZaiTD5H/X9bv1X3LwcqOpK+Y9lrTtPpWYulIqL5PmzVwWV64LFaUhLbN+Aqv7L8z3K4JekzrjHYLyIJ2TbGfUYQkoDlHJXEMVQeo//NZWXyB1jrKGCjkZLkKVFppWuWWjV4ynQq1U1igtNIQCpkzXahzSzLuHJYIXXyzfcbe31mrnNnSTXkfkNUuSsAhlne2VTBVH8qjxXc4cnXeWIkDNR5DghLc1+L2Ow2RpADmgAgPxZEO1kkAoy/DfIy0pHSkNigh2oHa9yNlDBUGfJ1c9wmN4AkUPWM1SkXfu3wY/D5YbW8LcMdEULDzlPgyouaF4e3lsn+FnLiAhUNR5UM8dzsCnukm5PBO+ivne9wy4BJ6uv52T2aLTRbweFKUtoe3jyqnsC3tsGUcOLgC1EYCRqkLNTQbbncrcBTQmg7QbR9kmINnMh2v0dyJ0s0xj+O2SdMgb3+mY7yH5IRgxV24a3xdW+F1Bd3uJKdH0NKbURAlwFycf8D8B5IvC8z7vt9b/i5aaulIMsfm6F3sY2678ArTSkkO3rEJV2Pb+AvXf9klm3uoVZqn/G92TWBRBtnwL0lwAiX24r4wq2FtBPe3sVue9RSZigJDT5QO71gPld19o/rzHO/q0MIhfJPdJ5ArBtBCk1UM6OA5ne9zoZ5De1746qbmQ/ENv66JiJ81rYKKGaua4ARU2NWB3nerv7jzAzvCFQKoYHeN1IVPmp+b8f2Q+BbB6jBJESdixpdnlnx4Cqb5b/Ow6DKi8CmfwCgjmPQGSPgOjku9cukQNUc7v07AvmNWH+KHL55vd8l9BF2EKPiEC23XJvZnXCIayS7PXb6oYDsAP+W63FAzLK9mv52GOEdxvj/TC9JuVYr4midITq5sV+jfOUxyjajP5Mej3GPhtPTgOo+hZQ7cMhtr/zw74batwIMgfKC2TdBKV2HojMUtZQGqD2RVTzQED62Crr9d7m3eZ7yvRaVFloOu+F6HQAJxt+17y6RConmkRmsxlPPvkkxowZg6FDh+Lmm2/G5s2bQ6bfvHkzJk+ejGHDhmHMmDFYsGABzGaP8lhdXY25c+di1KhRuOiiizB16lTs3x+jpUh9ibyEDVG01PVPIUS+tF5T1VgpFDS8CKX2t6C6hQFZCW0HQNPRvwBQxRAo5X2gVF4G5ewYKLULQNbN0oe++saA/b6o6mqQ5QuQs0JGpHX86POiCk0nCH2pW7Ggs5dBKe8Hpe73oMoLQRX9oNQtApFTDhDeAbj8Xnhq+D9QYzQvk9can1CuGWHXRXrNrtQvkvWMEJHY30WCzGtAVeNADX8McEMkx4+ycYfpNIlszd72xyc/pUY+v3gIZrY4zzSQGWT3FpRddbRt9RhYvD0UYkCpuVcaasgi/wzXSEXa5c0gCh5ypxU542R1Ki+GUnVtwLtM9jJfRcj8LqjyYs95NUCVF6LgMYiCR7zS/K9sX4Yb5Gd5H9kGjHcAzsOAbjBE3q8g2twOof+5XOuhaQcoZ5p0/2mFW2lygoyzZJTumF3Rw2TvOBJ+Vi4gWEuIZDX3goyz5G9jelu+Q96GvkhtyHvbD29lwet/aQjzCmhVc6dfJRxe5+4GbK6xx/pv12ymvxKh5h1+rTgZp4LO/gLkOBYgbIqccRCathBCD9F+NQAnyHADqOEvoOpbPQmzxwHWL6EYbgZZt3j60rwpQFYPJArR5i7PfVSNBVldLtq6AfJY7f0gy3oQWWX/6uXe7fN/5UWA8yiozhPEjNQ9fjUlQNZAeazmN1Cq/iusQkuOH0GG62U/H+y80uAR7puKOgsZqg7mD0BRuqEGvZ7MIHOQPY5trr3Nm7CnuKSpQQlDoCpUZAGZP/SNYxLqEsdhkP0AQLWghqVBqhj+2YbM134wwBBAhmtB1ZM9BxpfktHh4+iK6y7L9AHUcZKI3MY2svjteawbBAAQIheijcdrhmofDJKrZxKALGtB5o9BzsrQikej37Kdmjkg61ehK235FFR9k3QjVg2a9t2h8/fqn0S7NwDdUFDtPCiGyWFdoSMRUEelFtTwF8/XihGe//23ucmdKPPwmihy56uYQOZPkjbBQUQg09tRy4kUxDuIyOL27KSzV3sZLZqh8FZPB529LPR5x48hPEdcv7ftK1DFQKBRxhXyXhuueG+/5C0TWj8LLMc4AzB/ICciTCtBtd5GgAjjpHWzW6Yn+w+ghpf8xgBP2xcFD0LT+XsgzzVG2kIs1ci5LuCQEDokeleYrMhJgIULF+LgwYNYsWIFunTpgg8//BBz5szBmjVrcN555/mkPXr0KObMmYOHH34YN9xwA6qqqnDvvfdi4cKF+P3vfw8AuO+++6DVavH3v/8dBQUFWL58OWbOnIn169ejuLg4oHyldl5wt2B/ssdDlKwDNB0hNG1BedPc270EE8CRfSVE/gwAgOjwhZwp1nQE9MNAhlsAxaUgqoKo+W2Qt2tb4589/2f1Bhw/+s7E+ZVJzlMQAES710CGX7kiiCqA6VVPItNrQa0iVNE3qP2W6hcB2VdIAVIdlLPOB/QXy5fNy2JJVeNlHqIIyDrPy4LVCKXuaTmYm/8OZPWFyLkOgOL73Nzu2wCZVwO6gS73QgHfSKUWEPJBDUshciaAaj2KFNXOBUEHUfg0AJ2vq4mapvF1IPcaSDcHO6j2EcD6BdDpEABACCEboF/ADtkZ2OT9QQBkBBwnIPRDPB2v5SOQ6W3Avgsiqx9IN8A1Y2oDtOcBIg+yg3MAyIZw7dlMZIMQelc+TgBaCCGCrm9TjHdAFD7jqocCIbQg6xaQcRpEwaMgpU4aZEQeQL4dNBmulZ/5t0NoOoLqn/Kcq5sPtLk/Knd7UTAfyPsfwPEdYN0k15pbPnVvJeTGthWkrmfUngtR+IJUKPWj0GAbjjb67YDjkPt3oqz+gKPMt6ySz0FVY73Kfly+lwBE4RL5Llo2AHk3y04tbwZg2+KZ2fbfpsi1T7XI6udbjtBAdNyakLWt5DgGqroW7jVxmvZA7i0QWd0AIkDXH9AUAaJA/m6KUc6m2fcDcEDk/waAAoh8yHazFCJ7FIT+Ik8ZpLjfJ08UX/KsKSKvY0BY5YBs22U71bQNPGc/ADJcDwAQnaNb5ym9U3QQWd09ZWtKfLbzoToZLIm0vUBKBUTOVfAO2ETOSgitn+HQe89x2yaQ+IV0dfeefaU6UEWp3z3sdbUPZ6D7sXc615ZYBAC5kyCy+oBCuWhpSiAKHgHZdsp09dL4SVVX+abLGijbjguR1QMo+jOo5i5Qw598korCP4Aq/yPfBeM0T1Ftm7a/arQIbSegwxbQ2UsBAGR+FyL7YghNMVD4R1DtAwEu3SSK4bOGKhQu4UoU/QVCXyoFHuN0Ob653quwYmzjciiWf8nxTTcIIvdXAMitVJOmC0Sbe0COHyCyLwa058p2oxhkzqrLuvO0NMxou8h2R40eg4J9P4jsEEIn90GmRsBZLgU53TCI9m+5FIFs2U9HCdUtkmOg84iPUUEqQGZpZAEgcqXARk4DoMkHGlcCog1Evm+ASSJyrb2UdZBrpMOUTzbIMSPH8930rly2ZfkUyJ4AUfSC1wUWOT4CEB13hs9bjZ6vfnf8CEAjPWmEHu4Z3mhdPq0bAVEIqr4RyJsO0TZ4nBAiAlm/kF8cPwGuPoLIIvs8VVh3npBjMMhr3HVAiOBiqhTCCdTwv56DzpMgdRcAr3FKFL8m5SL1e5vbgbwbXQqAl/wF4Kx5Cjr1/K10k65bAFj/47N0iEShp876SyByfumeRRRtHgDZ90iXY+NMOV46zwB5N0LkjAc0HQBNO1AwbzjHQV85TxQDOWMhtD3cy/ZEwcPy2RQ+B6oaA9h3gSoGe67RDYHInSw9ADQlUj7RFALUAJACZJ0j5TyRL8/5TXZQ1Xi/h+zVX1hWQylfD01nOV4LTRFQvBxw+MbKIbKCKn8uv9QvAtrcAyh1IMcBiLyprnGrTeD9NwfHftdvtSWq5GS4HiTypBFdew6g7SYNz45DrjHTy4hA9rDvoTsZkbuvUeVFdezyHfu9rnHJVSHHadf4SqY3INr82lf2anwZlD8LQtMOCBF5OmBMbvyr/LT6GoPI8hmQ1RdkegOABlAqIAqfBUzvSA9V3XAgZ4wnhorpbaDdSikTuQyoovA5CJd7vih4AtCeK40nuf8PmrYLpHJf9xREzi8h8lLjpScoggmmtrYWI0eOxAsvvICxYz1C7cSJE3HRRRfhscd8t7dYvHgxtmzZgjVr1riPff7557j33nvx1VdfoaqqCtdeey1Wr16N/v37AwAcDgcuu+wy3HHHHbjtNt8p8Z07d6K06y2hK5g3BTC9AdHuXTl76gc5fpJCClmlH7lLuBbt3oPQR/YXl+4dnwCKEWTbAVgDLalqXmT+KIS10JWuw38gXO54gEtBs/5brhWwbpKdKNVKgcsR44w306oRHbcC5g9BjS+7BNULfc4TkXTbDOpiIgBtd2g6+FoGy8rK0K9PkewE/bwZ3OTPgabgASnY2b4BNEUQur4yyIYmHyJCwBuy7QJZ/yM7bW0XQNsD0HYAoJEDapIgywa5L2baooM0tLSsfYhF8au+Lv3h0nb4UnroWP8FZI8FsnoBjS9Gd23HnYDQuwdkQM5ukHEW3Opb9miIohdDKkhEVlDD34BGOQMiOu13GcEc0nBknA3ACeTeDE3hU0HziJaysjL3+BgJUhoAofVpa0Q2wLpRzrY6fgR0FwFZ3XwNx/m/kctQyAbYdwDQQbSdLwVH/UiI4le8BDinnBkwrwYch5p1bylF28MvmGUO3MKtKEJI900myegRv629BDSdQ7+z5DwtZ7+cZyDyZ+G7Hyw+bY+clVKpDrIsSLRfDaG7AKTUAiLXZTgASKkH1T0V3V6oumEQ+TPlDgm2MLPC0ECUrIfIOleW4TgGalgGWCK7XMcNUQxNp/AB1qhxRfjgknm/giYOkXmJnKCK6PpIFdF+rSuIa/AAXSlF21MaIkLJ/sJluEjTPZhF0Z/dnoFNpaysDCaTCUOHhvcibSoRFd4tW7Zg+vTp2LhxIzp16uQ+/sQTT+DQoUN4913fdRK33HILevfujaee8gz4lZWV+MUvfoGXX34Z5eXl+N3vfod9+/b5CBYzZ85EYWEh/vhHX3eonTt34sILB0mF1fwPQORIq0X2pYDuwqBWk2ThbdHxHFPk+qnskYAoiGgVCp+/E9LamSWtoUo1YN8DaLtLqxSZAfMaAHZ5TOgB6GWAA5EtLZqiCBAaiKxecu1xwx9lx6w9B9C0lUEadEOlEOP4DmTbJq1+ihHQlUJofyajqJEZZFkrZyQdh+XscdYFsg7OI6FvQtPFd41eOLTnAtpO0m011kiRmo5xdQmNmqw+zY+Wqj0XcB6FKFwst4+yfAEphFvlzIam2PUbNALWr+Tzzp8N0ebBmGYvANWqbpVRZJUqQD886Cwh4Ct0SzdWG4SmCETmiIpsJkOOYyDTO9K6bf0yuq0pRFtE6ybc4si9WfYDQQUvDaDtKo0ZQdybRMddADWCGv4kjYEiV65BcvjNbuf8FzRFL0jDChmlgQQuxc5eJmeJLevkO239Esi5BiL7CgBaIGdcs/rhaJGzeRUQ2s7NzisWhTcWiCwyQrX+cp++QxUDYpoNJXJ5x5BLqe4DOA7L5SmWdYD2Z0BWfwj9MJDpTQBZEAX3yBkhxSg9S2yb5FjmXvMdAe25rqieNoDsbg+uQHSIap/mVKG/RO7ZGoBA2PnzaPqZ7DEySGFWf7mMSV0CoJJ1vmd9uW6QXGJlfj8wn1jQ9gwvB4g8OXurCvP6UTIAWfbl0gir6ST7CHXmM6uva3ZLK2UZh18ARZErxzFvA6C2p5SBHIfkc9J2BcgGUfQChK4voiVS2yOyy6VMuoFyPX0YyFkJqrkf0P8cgEa2C5ELkBki9waINoHuwIBrvHUclPfhdjnNgdCdHzyt8ycZa6D+OfmsyArA6RfvIxsB7qs510oFOnuMlOcc34Ea/irl69xJkO1I8Yq6HxlSqkH1z0PoR7i8aXrJujnKAMcRiIK5ELrmxT0BXEb8ijC/a/Z4iLaPy2U1SjWQPdJtRCeyAI2vBnft15T4BVnKQkyB3EQhYt2LOe5oe0Lkz5DeBub3pRyubS89pvTDIL05CKLgQcB+EGT9F4SmEwAbyHlSertqz4PInQSyfSX7aJEHiGwI/QipDzS+DOh+DggdhCgE8qe6PVOaSsoV3rVr12Lu3LnYu3cvsrM91vGlS5fik08+weef+wYYGT9+PK666io8+KBnptNut2PgwIFYvHgxKioq8PrrrwesAZ47dy6qqqrw2mu+M1A7d+5EXl5ek2+QaUmQ12c4QwdFkcY/z3CCnuI6r8A3sEeoQYAi5JcZWCwW5OQ0rwNjVBQI2EDIdn/3vD8K1HdVwAKNMEOhNiBo4Pu+aeB5XzUQsEGnKYdDaQ+CBhphhhAOgLRwUBEEHBDCBq1oAKCBQykGQeuqCwA4kKWpg0MpBEGunxFwABAgaKAVjXBSPgTsAAQ0ohFOKoQGVijIhoDDVUedu47yHnMQv/e/ZbSlWOG2F0/U/huuT/U9zYVsC3YA5NU2BQRs0Ih6VzvMhoAJBD2k8Kv2/QQpCGsh26bD1eakcKxQnuu401WuQGzvcrTvPkEjGqBQDrzXnjYfBQJOV9+g1sfpOpYd5rpoxtT0hdteJuH7rmlgAkHn9c7GL2+Jt4eVJkw6wNNPOL3akQKtqIFW1MOhdISCPMj22+hqv+TX5jwygoDFNbZ6l+vdR2Rme/PGYrFAUZSEKbwRzd7hLL+hrMH+x9Xvcu1l4KxopPwSYelmGCY8iZplYuJJYsP4M6mB2x7DpAZuewyTGtQZ3kQRcQqspKQEAGA0+ga7MBqN7nP+6f3TVldLt4oOHTqgpKQENTU1AdHbampqgubHMAzDMAzDMAzDME0hosI7cOBA6PV67N692+f4rl27MGzYsID0paWl2LPHd5+znTt3Qq/XY9CgQSgtLYXdbseBA56w4DabDfv27QuaH8MwDMMwDMMwDMM0hYgKb0FBASZNmoRly5bhyJEjMJvNWLFiBU6dOoXJkydj7969mDBhAk6floGJJk+ejBMnTmDlypWwWCz46aefsGzZMtx4440oKChAr169MGrUKPd63oaGBixZsgTZ2dm45pprEn7DDMMwDMMwDMMwTOsgYtAqQM7APvvss/jiiy9QV1eHfv364f7778fQoUOxbds2TJ06FRs2bECPHj0AANu3b8fSpUtx6NAhFBUV4aqrrsIDDzwAvV6GbK+rq8OiRYuwZcsW2Gw2DBo0CPPmzUPv3r0Dyt65M/zecgzDMAzDMAzDMExmk7IozQzDMAzDMAzDMAyTiaRuE1uGYRiGYRiGYRiGSSCs8DIMwzAMwzAMwzAtElZ4GYZhGIZhGIZhmBYJK7wMwzAMwzAMwzBMiyQpCq/BYMCjjz6Kyy67DBdeeCFuuukmfP311+7za9euxfXXX4/S0lKMGzcOS5cuhdPpdJ8/ceIE5syZg0svvRSXXHIJ5syZgxMnTrjP19TU4Mknn8QVV1yBIUOG4KabbgrYC5hhWiPNbXsAsHXrVowZMwZjxowJyN/pdGLp0qUYP348SktLMXHiRHz88ccJvy+GSXcS3fYAoLq6Gvfccw/69u2Lbdu2JfR+GCZTSHTba2xsxDPPPIMrrrgCpaWluO6667Bu3bqE3xfDpDuJbntnzpzBAw88gEsuuQSlpaW49tpr8d5770VXOUoCN910E82YMYMqKyvJYrHQkiVL6Oc//zmVl5fTtm3baMCAAbRu3TqyWq303Xff0ejRo2nZsmVERGSz2Wj8+PH00EMPkcFgoJqaGpo3bx6NGzeObDYbERHNmjWLrrvuOjpy5AhZLBZatWoVDR06lM6ePZuM22OYtKU5bY+I6Pnnn6cxY8bQrFmz6IorrgjIf9myZTRq1Cjav38/Wa1W+uyzz2jAgAG0devWZN4mw6QdiW57O3bsoJEjR9Ljjz9Offr04TbHMC4S3fbuv/9+mjhxIh07doxsNhu9+eab1K9fPzpw4EAyb5Nh0o5Et72rr76a7rvvPjIYDGSz2ejDDz+kPn360FdffRWxbgmf4a2vr0evXr3w2GOPoUOHDsjOzsbs2bNhMpmwd+9evPnmmxg1ahSuvvpq6PV69O3bF9OmTcMbb7wBRVGwadMmHDt2DI8++ijatWuHwsJCPPLIIzh+/Di+/PJLmEwmfPXVV5g9ezbOPfdcZGdn41e/+hV69+6NDz/8MNG3xzBpS3PbHgDk5uZizZo1uOCCCwLyJyKsWrUK06dPx4ABA6DX6zF27FhcfvnleP3115N9uwyTNiS67QHSkv6Xv/wFs2fPTuatMUxak4xxr7CwEI899hi6d+8OnU6HW2+9Ffn5+fjmm2+SfbsMkzYkuu2ZzWbMmDEDjz/+ONq1awedToeJEyeibdu2KCsri1i/hCu8BQUFeOaZZ9CrVy/3MdUduXPnzti9ezcGDx7sc83gwYNRU1ODo0ePYvfu3ejevTuKi4vd54uKitC9e3e327IQwv2wvNPs27cvUbfFMGlPc9seANxxxx1o06ZN0PyPHz+O6urqoHnwkgKmNZPotgcA48aNw5AhQ+JfeYbJYBLd9oQQWLBgAYYPH+4+ZjAYYDab0blz5zjfDcNkDolue7m5ubjhhhtQUlICAGhoaMCrr74KIsLYsWMj1i/pQasaGhrw6KOP4sorr8SgQYNQXV2NwsJCnzSqcltdXQ2j0RhwXk1jMBiQl5eHyy67DMuXL8fhw4dhs9nw6aefYteuXTAajUm5J4bJBGJte5FQ0wTLI5rrGaa1EO+2xzBMdCS67dlsNjz88MPo27dvVEI3w7QWEtn2xo8fj6FDh+Ldd9/F8uXL0bNnz4jXJFXhPXXqFG655Ra0b98eS5YscR8XQoS8hohCnlePL168GP369cOUKVNwxRVX4JtvvsE111wDnU4X3xtgmAylKW0vEkTU7DwYpqWTiLbHMExkEt32ampqMHPmTBgMBixfvhxZWVlxyZdhMp1Et71//vOf2LFjB6ZMmYJZs2Zhx44dEa9JmsK7d+9e3HjjjRg6dCheeukl5OXlAQBKSkoCZmLV7x06dAh6Xk2jTmu3a9cOzz33HLZs2YLNmzdjwYIFqKqqQpcuXRJ8VwyT/jS17UVCTRMsD7VtMkxrJlFtj2GY8CS67R0/fhw33XQTCgsLsWrVKrRv3z5+lWeYDCZZ415BQQFuvfVWXHTRRVi5cmXE9ElReL///nvMnj0bv/71r/Hkk0/6zLyWlpYGrPfbuXMnOnTogO7du6O0tBQnTpyAwWBwn6+qqsLx48cxbNgwAMDGjRuxd+9e93mLxYJt27ZhxIgRCb4zhklvmtP2ItGtWzd06NAhaB5q22SY1koi2x7DMKFJdNurqKjAtGnTMGbMGCxbtgz5+flxrT/DZCqJbHv79+/H5ZdfjpMnT/oct9ls0Gq1Ea9PuMLrdDoxb9483HjjjZg2bVrA+dtuuw2bNm3CunXrYLPZsG/fPrz66quYPn06hBAYOXIkevfujUWLFsFoNKK6uhpPP/00+vTpg0svvRQA8MUXX+CRRx5BeXk5TCaTO6Lz+PHjE317DJO2NLftRUIIgdtuuw2vvPIK9u/fD5vNhrVr12LLli1By2OY1kKi2x7DMMFJRtt78sknMWTIEMybN4/bK8O4SHTb69OnD3Jzc/HUU0+hoqICdrsdn376Kb7++mtMmDAh4vWC1IV4CWLHjh249dZbodPpAm7ol7/8JZ5++mls2LABf/vb33DkyBF06tQJEydOxO233+5Of+bMGSxatAi7du2CEAJDhw7F448/jk6dOgGQm4AvWLAAX375JZxOJ0aMGIHf/va37NLMtGqa2/ZOnTrl7kScTiecTif0ej0A4KmnnsLEiRNBRPjrX/+Kjz76CJWVlejVqxfuuOMOXHnllUm/X4ZJF5LR9mbMmIHt27eDiGC3291lDR8+HK+88krS75lh0oFEt72LL74Yl19+edD8ue0xrZlkjHunT5/Gs88+i02bNsHpdOKcc87BbbfdhkmTJkWsX8IVXoZhGIZhGIZhGIZJBUnflohhGIZhGIZhGIZhkgErvAzDMAzDMAzDMEyLhBVehmEYhmEYhmEYpkXCCi/DMAzDMAzDMAzTImGFl2EYhmEYhmEYhmmRsMLLMAzDMAzDMAzDtEiyUl0BhmEYhmkN/OEPf8CBAwdw9uxZmM1mdO/eHdu3b8fbb7+N0tLSVFePYRiGYVokvA8vwzAMwySRDz74AD/88AMeeeSRVFeFYRiGYVo8PMPLMAzDMCli3rx5GD9+PIxGI7Zv3w6j0YgffvgB999/P9auXYvDhw9jyZIlGDJkCFatWoWPP/4YGo0GY8eOxYwZM1JdfYZhGIZJe1jhZRiGYZg04OjRo3jrrbfw3nvv4cUXX8Tq1avxwQcfYO3atWjXrh3Wr1+Pt99+GwBwyy23YMKECejSpUuKa80wDMMw6Q0rvAzDMAyTBgwcOBBCCHTo0AF9+/aFVqtFSUkJdu3ahX379uHYsWOYOnUqAKCxsRGnTp1ihZdhGIZhIsAKL8MwDMOkAVlZWUH/JyLodDqMHj0aCxcuTEXVGIZhGCZj4W2JGIZhGCbNGTBgALZt2waz2QwiwtNPPw2LxZLqajEMwzBM2sMzvAzDMAyT5nTp0gVTp07FrbfeCq1Wi7FjxyInJyfV1WIYhmGYtIe3JWIYhmEYhmEYhmFaJOzSzDAMwzAMwzAMw7RIWOFlGIZhGIZhGIZhWiSs8DIMwzAMwzAMwzAtElZ4GYZhGIZhGIZhmBYJK7wMwzAMwzAMwzBMi4QVXoZhGIZhGIZhGKZFwgovwzAMwzAMwzAM0yL5/+1kr25h/68+AAAAAElFTkSuQmCC\n", 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\n", 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" ] @@ -866,7 +1056,8 @@ "source": [ "axs = flowdata.plot(subplots=True, sharex=True,\n", " figsize=(16, 8), colormap='viridis', # Dark2\n", - " fontsize=15, rot=0)" + " fontsize=15, rot=0)\n", + "axs[0].set_title(\"EXAMPLE\");" ] }, { @@ -878,13 +1069,8 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 24, + "metadata": {}, "outputs": [ { "data": { @@ -922,7 +1108,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Is already a bit harder ;-)" + "Is already a bit harder ;-). Pandas provides as set of default configurations on top of Matplotlib." ] }, { @@ -934,7 +1120,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -943,36 +1129,33 @@ "" ] }, - "execution_count": 22, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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VGYUQQtRBrYHdm2HDhnHRRRfRsWNH3n33XWbMmMGkSZOqTJeRkRFwAYWLxWKR+qxGWULQ1/qRugwuqc+Gx6/AftNNN3n8P3nyZK/TSQ4+eDIyMqQ+a+Fr/UhdBpfUZ3Clp6cHvAy/ujs+8cQTnDhxAoC0tDQuvvjigAsihBAiOGptse/atYs333yTzMxMDAYDq1atYvjw4Tz11FPExMQQHR3NlClT6qOsQgghfFBrYL/00ktZsGBBlfdvueWWkBRICCFEYOTOUyGE0BgJ7EIIoTES2IUQQmMksAshhMZIYBdCCI2RwC6EEBojgV0IITRGArsQQmiMBHYhhNAYCexCCKExEtiFEEJjJLALIYTGSGAXQgiNkcAuhBAaI4FdCCE0RgK7EEJojAR2IYTQGAnsQgihMRLYhRBCYySwCyGExkhgF0IIjZHALoQQGiOBXQghNEYCuxBCaIwEdiGE0BgJ7EIIoTES2IUQQmMksAshhMZIYBdCCI2RwC6arDNFJeSbbOEuhhBB51Ng37dvH8nJyXz88ccAnDx5kpEjRzJixAjGjh2L1WoNaSGFCIUhry/g1lcXhLsYQgRdrYHdZDLx6quv0qdPH/d777zzDiNGjOCTTz7hvPPOIzU1NaSFFMIXqtNZp+nXRT7Dhsi/hag0QoRPrYHdaDQyZ84c2rRp434vLS2NAQMGADBgwAA2btwYuhIKIYSoE0OtExgMGAyek5nNZoxGIwAJCQlkZ2d7nTcjIyMIRRQAFotF6rMaXUv/ZmRkoOhqzy6W1WXF+YT/ZN9seGoN7N4oiuL+X1XVaqfr2rVrtZ+JusnIyJD6rEWXLl3Q6fW1Tle5LqVeAyP7ZnClp6cHvAy/esVER0djsVgAOHXqlEeaRgghRHj5Fdj79u3LqlWrAFi9ejX9+vULaqGEEEL4r9ZUzK5du3jzzTfJzMzEYDCwatUq3nrrLcaNG8eiRYtISkrizjvvrH1NeUfh7O/QUQ4CIjRqSgsK0ZTUGtgvvfRSFiyo2tf3gw8+qNuapl/m+js5v27zCSGEqBO581QIITRGArvQDFWt2w1KQmiVBHYhhNAYCexCCKExEtiFZkivGCFcJLALIYTGSGAXmiEt9tD7cnsml760CqtdLlQ3ZBLYhRA+e+3rDIpK7Jw1yTMYGjIJ7EIIn8lJUeMggV1ohvRjr0dK7ZOI8JHALoTwWX9nGj9GjgGHPCu2IZPALoTw2Xjnf2mn5KA354W7KKIGEthFg5D2zki2/OvegJYhvWKEcPHrCUpCBNsfc5eHuwiiDlTJsTdo0mIXQvhMwXVWpEhgb9AksAvtkFRMPZLI3pBJYBdCCI2RwC6Expw1WUN2y787FROSpYtgkcAuNEN6xbj0fOVbHv3ol5AsuzzHLqGjIZNvRwgN+mFfdkiW6yw7dsrV0wZNArsQQmiMBHbRqB3aleb+X8aKCT3JsTcO4QvsqybAy61Ct/wNb8OMK0K3fNEg2CzF4S5CExWe0L7i1xMcOF0YlnU3JvUf2MsucG2cCaoTnCFqZa15Gc4cCM2yRYOh6OSksyl56tNtJL/9Q7iLEXS/79se1OWFL7CXkYswIiDl+4/0igm91koRID/bYNq+5jPO/6Q/6V+/H7RlhqG54/njk7yoCIQiESYsVMmyB435+A4ArJm/Bm2Z4W+xCxEICexCVBH+FrtTAr0IDknFiMZICcFuKy120ahJKiY8wpWKeVC/kp6KVjtFBK9O/RqPfdeuXTz55JN06NABgM6dOzNp0iQf567UYkcCvRCNTbiujU2O+Kj0v7FhWX9j4VdgN5lMDBw4kAkTJtR9Zmmx14vs4/tRFB3x53UKd1FCTHrFhIPUdCgEr1b9CuzFxYHcFFI5xy69YkIh4f3ern8m54e3IEKT5BgaPKF4GpVfOXaTyUR6ejqPPvoo9913H5s2bfJ9ZtkjRBBJjj08pJtyw+ZXi71Lly6MGjWKAQMGcPjwYR566CFWr16N0Wj0mC4jI8P9f9fSv3v27kE1RFd4vRe9IcKfYtSobPkVy9CYWSyWOm1LY9t+f8ubfSKTsmTTgf37iWrWotZ5yuqysdVRXYViu8rq7NDBg+TkFgB13zeDsX4tfWfFRa6bvswmc9C2y6/A3qlTJzp1cv2cOnbsSHx8PKdOnaJ9+/Ye03Xt2rXKvF06d4bIWPfrSy7pTIQxyp9i+MRbGRqjjIwMv7alsW1/WXm3fbsQRdHTM3lYjdMb7eWppk4XXUSLlufUuo7KddnY6qh2h4DQbteFF3Yk4VzX793ffTMQWvrO8tNiIRuiY2Lo2rUr6enpAS/Tr1RMamoqH33kujqdnZ3NmTNnSExM9GleOYUTB7OLcNZy/8LlPz1Jzx8fr6cSiTqTlGqD5ldgv+mmm9iwYQP33XcfTz75JJMnT66Shqme3KDUlO09forD79zKx9+sDfqypVdM/ZGqDoEgVqpfqZi4uDjmzJnj1wpVp4wy0ZRZ9n1Psn4bv+6eCrcOCHh5cvE0PA7lFNImKdyl0Ab9WVfqrM/Jj4AZQVlmvd95WvmGJFV11HcRhIaY8rLCXYQm6b11B8NdBM1wRLUGIIuEoC2z/gN7ldSLnNMJ/1303SPlLyqcyh7cuYk9m78NQ4maivK63pFlxmKTBpq/lFbnA3D0nGuCtkwZBEyER5DyiVGKzev7nZYOpMs3d3v9bPtJMxeM+zoo62+qlNLv70hOMc+vOskLn+8Mc4k0QAleOK7/FnvlH7T0kmlSlFBeYfFxX9qXsZ3fIh8KXTmagHOcOQAUWuwA7M2Sx9UFLIixMOyB3SlDCjQpDWHQt+Si5cQoJeEuRqP2l+L3wl0EDQl+YycMgd0zkEtgb2rqthMfzQj8Zg0RHF67kzptzIl4iwsdh+q/QKJaYc+xOyUV08TULbB3WHQj+WdO+TRtqPqxn8w3h2S5jY3H5bDS/6NyM7hJv5WxRdPDUiYtiS4+HrRlhb9XjLTYRS3MxQUBzb97XSoWU5Ff867ceZLHpr7Pur2nAypDqFlMRTjs9pCuw6l6iex+2pWZzwXjvubpz7YFVigtKL0X4zLLL0FbZNhb7KpTukk1RfG2E/WynsO7NtFt3SPsnPNY+Zt1uKnJvv1TVkROxPzr5yEoXfBEpZzH9n8PCek6KqZNlQAD+6btOzgSNYJHf3swwFJpgSZy7HLx1Gf5mZCzP9ylCK7SA/l5jsygL9pbKsZUkAtAs+Lf/VpmvPkwAC1NR/wuV325omhdSJfv+ewEV137e+dvt1PLAbhUdyTAUmlACO6eDvszT5v8oGAH10LBSe+f/esPMLN3/ZYnxPz5tn3dRxyOGlIRfubf1bK+xTI4isfZdaAtdhkIoiItBHbq2CvGYYMsDd/8sGAwzLmx5mm+fqZ+ylIPlBAGSKeXwB74WDJl8zeOwB7KgdCcFQK7rtLBtu6BXkJ7mYr7aE6Wf2eWlYX94mmtrbEP/wSzr4VcDXenKqwl37zl/fopRz0I5Rmaw26t9jN/W5hK44rrIeUMYos9FOmHRqvCHafxs7sHZZFhGASs0uvaWuzH0lx/i3NCUh5RvwJtUKpOJzt/+NzrfuOweRleoDSA1BSIam7luuYvtFR/0GhIQpkx8rx46ln/Mmar/0IxQmn9BPYDa8r/r5xj97VXjL97rORGG5i6fx8Vv8Itn0+n+9oH2fb2HVWm85ZjL/vReK7V84fkcNTUuHBNm5i1zrfCaljFg2lZSm3TwTOuz5r6tbIAqI02sH98l/tf/+88lQBd2antqzi+bl64i1EnlVt6deXIPQJAr6IfsFktHp85Hd4HBKui0sHeZquhNV76o+uh03Aq0Eeqlxb74fTVAOgcdRyiQVIxIRX27o5VWvDFZ2ByHPlbPqtxujqs0PU3c2vDvhnKj+1L/OJe2q37WwgKEzrOGlvHvigPCOnvj/Fctr36wF4xjBgsZzw+s9mqD0qNLcUQyuZPxbNrh8P1/6SIjwE4H9/uDhbeNNYWewVV+7F7pmL2/7YVgFPfet6inL/+P36uzwmHf4A5N8CmWXVfgLUYdizxa9118sO00K+jQfAj9FRz0IvN3+vx2uElsHsbTbKt6nkXqdfcvHsBjSuwh1LFs2tdleSW9IrxX/APx2G/87TyUJXO0i+88sWxuEMr/Fqbw6lC3lHXi9O/1X0B3zwHyx6F39P8Wr/P0ucHbVGWE35sZz3RxcYHtoAK+0vl1nSNqZgKB4fK89lraLGHO/wcyzUx/+cjPk8fyu6OFZ921kHneXCsHOhrowtDxZZYTFhLLLVPWM9C0QW43gO74qzcYq98al7WiyE4aRPP8S382JsKSgfmsfo31kiN6vKF1mHasx8O9aMw9SO2RSsAjtPG53nKglWJxUSfE9UfAL31Y/fW4q4S2GtI4YQ7tP95bhovLd/NWVP4e+UE86E4ShAfKuGN06myeneWx4Eucmpb8qd0Cel668JaYuGXf96FPftA0Jcd+sD+n6s9XqqVArZizvWcPsinvhUPHH6NBV62Y4TilLwugyo5fR/gqcTe8K8l6Pyoz4wfv6z0TqUWew392Gtit9Z+8TRcmhUf51H91w2ic1fltGlFOqVuBVR1+kCLU6OFm3/nsQXpLEn3HDExgbyQrtcXpqJ8tn/7CfvT19K7cE3pQ6yDK/SBPTvD42XlU8X4n1/xeK340O+4LpxOB4eyXU932X+67q3u8kZK8H/gFXsI2Z1OsFth5XgwV935FKePPT5cUwehdKFR9v37c0ZWuWts5W5iag1DCtS0PzntDe/0vMwcXmZixEJ0Ft8CUnZmCB8yXenB86cLA6g3nSHAwtSsMPt3lhlfpCA7+GMSBWr3nEfp+dNfKTy6PWTrCMPF00pvVP4xuk/RghTYHTbOFLtaZHmmugRHlyM5roPBwZzioJSnoooHudxiK+xc7LrAu+aVKtPq6hDYOziPBaV8oVT5lnRfqFXOWlyBfUWzGNbGRHtPxeh0pVNWPHPzVGMqRglty7I2zXCNBe/rofrwugUhK4vN7hnYb5y2tur6P/wLhxc+XfvCQhzYL89KpZfuAN2yvgDKe/E0BM2LXb/PFoe/Cdk6GtzFU13ZDzFI556uMar9X5bZ5goWxSXBT29UDOyt1Tz4cpTrhZeLgGpd+wk3WGUtdt+/k7KWetUcryvcvdAmnrGJCV5b7LrSAKJU2M8cimdQcdbQK8Ye0czncjYEobxR6JO0ox6vr7RvrTJNxyOL6bj/g9oXpo8IVrFqVLaf/brm03pZX138wRq6MbDqPbBXPnJWvShUtYUV2AorLr/uKQp3AApJir08UBkqbK/VS47cYTFVu5wd8//u/r/E7Fu6aeP+kxw+HdgDLPxR1ttJV4fvt3wMmJrncdhK2PTJa5iLyx+srNO7Wtx61RX08/NysCqRnvM5qs+xOxpKYPe1oRPCXHxRoef+8oHR/y66ashDj+cdx84aej4Fy76t67HXdLNbPar3wG5zOFx9w8teV7p7UGdwtab0anBOnRx2O3W8ruPJfe00CFXldIC1PEBXdzF3R2Z+lfccltIf1Zb3YXKcx81Wlx2ei730xp8jv22pNKP31mifhV04NuMWn4t+evc6CrKCl78tC+xbvpzF4cplrqTsx1L5O6jSft+9lKv3TUNJ6Vj+Xuk8Olz7U9z0TvzBuc9jvrW7Mnlr1n/YuNY1RnjR2WwKXm7HkV/X4TSUB/ZaxzUKJZ8bFqGL7Ff+Pjeg+b/bsoMtGaV38Ia4V0xVob36fODXH+m8/Ha2zH++1mnPtYc+VVrvgb3E5oT1b7pft3dmwuY57td6fempc4AtdpvqaqlVPD2vchfhkR99eJBFYA8U8PDFX+GNtuVLrqb7mLdhFuzm0mBfNoRvpQusX3/0luufyj+YkkKqc53e91PBNkvuoMXsXj5NeyzXhLOabVMrpWKu3DaejouTMSkK5mrq2FHa2lJ0lbat0vTRVlcPqyil/GBWdlakVx2UVHPW88OeTK45+TG6da8DcGDLt7RQCzm7cioGQ3naxmoNw7NPS6vRW/90i7kYJseRtmhq5clD4mZdzQfgilZ/PI3CAs99NPnrflz22VVAGAYIqVB/m2Y/yYFffwzq4ovPuHrfRJ+p/R6SloSg63Ql9RbYTxj0HDUYsJsLOHyi0vMjv3m2wovS7nD+5gpVFVQVZ+mmqRVOsxOslcY6/vBPng+yMOXC/5539U4pVZ6KCUJg37HIs6jVHLy8rclafNbjddH2ZR6vLz82v3Rez7lNhZ7zqXYr+7+YUntZ/XQ4Mwvrv3uxZPkXXj9XnU6+iG2GtdJp1B8vaM81Hdp5ncd9Gl3pQqZT8czT6tSqOfay/LweB6bCqmdCAAmcJZs4zo8o/dx9wdVBjFp+MLCeCn5/Y19tm1713oSifNfQCBdn+HdXdl1FKTbWxESzpHnt6ambD7xGxrwn3a9tpdcxIksPumUpMqDaRkBFv58xcSan5mELth49wyebDlFid1T5vVY8MF6dtZCLPv9Trev0R7B68wWq3gL7wPbncWv7JPIObyerqPpuac7SHHx7te7PxFQLs+DllhT9/D4rYmN4uk08Tmf5xdNOph01zp/9xXhIm01uxXFq3DtEEJPspcusrsXu7WzFYfYMSrHfPuvx+nzncddyK+3QBSdd6ROr3YnV7uTXL//NxdunEirFhzfTSXeSS3972+vnW4t+Y1LCOcxtFVXlM1t1LfZqeq2olXpWXGLfW2Wa/BOu93SqA4vJ+zWFdkoOWWprWjvOgKq6L+Cfaz3GFdtecE936H/Tvc4fCPvMq7H/q0et012v/7XKe+VpJifHDXrXGU+IO7w/nZjAK/Hn+DTtVWfLe31snnG/x2dKhbNSSzVnUit+PcHpAleq9sC/B1Eyo/yeGG9nMPq5yYxYeTkTP9ngZWkN+N4O4FBEcHsJ1XsqpveOl0AxsLBFLM8meO4gVruTMz965vF+UaveKZa5awMH37rRfYpe5sBeV2rh9PezeblNHGuaxaA6bHgLyts3VB2i4MhpV/A8kHXW/Z7iRyrm2MHf+Hnlp9Xe3l128DIXeu+brLNXPeVXLd5bmxXlHtiEPtLVmloTE81uYwQnvpsBQLeXVtJ36lqsuZ75PbWOT6cyZe3n2LuDUa3ef4w6g+vCpN5L6xmgyOGaL69yWqWSNTHR/BztCv72snRSpesuvYrWc7aW5fTe4joAGrBjNXk/BX4+4jNOqa2IxIpqzgODa72JDs9HFhpLKtxMl/EVFPj/QG5H/glKDm/EkJOBIf+I69rLmbpdw9CV3uSjQ2VQ+/MYk+jHcA32Eq/3TVS0fOVK/vP2ZIoiyn+v3r7dElv1DbZrCjy79qlOu/u7yz2+r8r0RSYTt33elfXvPEqJ3cGN+u0kKeX1/9WvmVV+X2UjcP75QIWB8UonMVirT0kGzOmkxw+Pe6xw4wfPs//VK3ya/e9t4rmjXRIpN43j2H0/BKVIfgf2N954g6FDhzJs2DB27Ki5JVxZz1NLmXpOa1bFVjilmxyH8bVWXJlVnq4YPyWF3soe9+sXJ4xh5tr9RCz5M52K0j0uullsDiw211H5Qnv5KfNPuw5xDBPdO57P9kgjRRYbOzcsp+eaP7uncTjV0tNBV/B2OqoG5Cr53Rq0X9CHvpueYNPy/3r93OawoaoqBxa/4PXzXkXrAdilb01O6XpjTmyk8Ped7HV6T1cAONe/RavfXHexPZ2YwLDz2tKraD22Az9gc6jkFJWgL/I8nVVmX4s1+xC5i8dAYRbO41s9Lm5XdvTj0bQ/tZY9G7/y+rkhMgaALjbvucayuxeN2EmfdluVzy2lwffpxAQeP7cNm6MiMZ90tbqt+9dRrCiktG5JUemBdmyFYFaxXf95bDNSK6QM4jlLh0VVH0FYpLqCeGxpf/GM9x8lcsu77s9NisKMlnHYgK5535P97dvYD22ARfdxdtZNqA4b+z57AVOuK8g7Tu6CyXFY962psi7Adc1DVdH/qyuR8//P/XbOvHthRq/yi+L5x2HP1x43YVV38baso8Gm6Ggcqh09Dnf/d/e85rOYvn8b0zeTPGd+rQ28eUGNz0W4fdNQRhX8izy1vHGxspnrey5SFJLbJ7Et0siObVXHU3L8sxv86pmCRFX5zXaMfh3aMaV1K7Z9U/Wi7O6drq6U99hXYH6tQ5XPb/uiGxPe/ZSSkqqNoB66QxSddF07SzqyjAdeeIPLd77GuuhoTMFIqdrMHunaiifeRnsR2SeO0OfobC52+Ja6+7a0Lhcc+IR2F10WePkARfVj1KDNmzczd+5c3nvvPQ4cOMD48eNZssRzBMT09HR++vwd7o5awf+axfDv1q4xQnYc/p1cnY7rS/OpW44cI1Itv6xpB2a2iuPP+YXEO508k3AOq2Obsf7ocVpX2LGdlB+VctQWxCsFFKuRNFNcrfjuHc8HYOfh3xkT25vvE04zIr+QQTmtOEw7Bus8j4xzjCOJKdnP2VYZPHE2ny1Dd3By0xLO5M5ienwzJp/6A0UFDkxJV3OeLg/nZUO55YpL2LpiFj1uuBulRRJREXrWrF5O97QHWdCiOX31/YnpdgeXXHsnBzO20u6Lm8jWG0gpHs1/jf9CBW5r15ajERG8kZ3DCwnxDCg2Me10Di/ZHmFF52/d5dt52HV94IRBzx6jkR6WEn6OieKU3sCPhbfxd/uPXKY7igokt0/idOlFv7L5CtQYJtoe5h3jTN++5DHbccy8CnvCpUTe8Tb893oA8pSWtFLPAlBkTCDWms2uv/xOG8shir6aQKTi4HfTNi622Yif5GoJqk4HyiutOdOiKwsuHsDc3OVcUmJlbtZpfoiOomeJlVvaJ7nLu7HdwzwW8Z27KGlHjrGv7ywu3Pgk13Ro735/2ukc/tGmPLD/ePQYM1q1ZFCRiQeTEj22v6JP7DdQgpHiu25k8d5Urt11GVcOfoqbV/zRvf+Umd4qjvdbxhFT0py0E7trrLJFxsEMtX4OQGbEBWRFtONi0zaM/9hD4ZxbsbfvS9ud79a4DMvjaWxM38YNvzwBQI5Ox+IWzbErcG9BEYfb/YWrH5hC1rH9ZH/6V5o7fqWV1UC/C11j77yafYY7i1wHZssLOZxa8x+KTcX8YWeKex0HjV2IP7cdcb+X17F55P8o3r6MqIwlnGlxKR1yfySjZX9M+hZcccZ1drslKpKH2yZ61Pe1pd9HF4uN90/kUxhRglVRMKoqSXaHR8vRrCjoVZW9zgv4tpWJD1q7Dqo7D//Or84LKdbHkXPudURFRxN34Av+qNtDbc6ozfmL9Rn+9Zdb6PDRVdVOt6JZDC+U7isLTmRxWYmV3ZGX0338OgrzcykxFxF/7vlVvw9TEVExsa7eZZnpcP7Vrl5pgPOlPBxOBw6njqjXW7Mj0silJVaPbf41+ipM8T1QSvLpfmo5v7W8nq8Nm1naIpaHzhZwPMLAj9FRmCs0HD+89EOuuMK31n51/Ars06dPJykpiXvuuQeAgQMHsnTpUmJjY93TpKen89XPQ0ht0dxj3sssJeyI8uxH3FoXTZeiXGyKwpbo8tzrzUXFrK7Qqr/abEYBNkZHu9ZbVEzLCsE+y2BgfUy0x7LvKixiWfPyct1QbKK508ny5rH0N5lZHxPNuXY7PSwl7jOI82x2bio2oUNlXkvXl3iV2UJnqxUVhbN6HQU6HR1sNvSATnWlbBSgQKdjSek2d7DZ6G8y4wQiVPigZQsA7i0oZHGleqlIr6p0tNk4YDS637vc5OBcp4X/xVZ/4apPkYPMSCe/R5RfVIzJvIV/m3/gAl0W/3NcxV61PYN0mzn1f+/xz9XfkNT6f1yuO4CC60DpwNV7KFp1XX7Wl25bWT1EO53unfDBswUoQL4ai0FfzMboKNrYHaSXfoc35OtooajYdUWsbBZDgsOBHYUcQ813c15ptnjsBzcVmyhRFH6o9N36Iv3w7xgrvbf7np+4pMsf6L+4HwXWAvq07UNSbBLfH/yNkrMWonQm8iKLcUZ4pm6Ugs5coOZjUJ10UHI4RylAr4JdcdWdQXX1znbiul6wqPQ7HpFfyEFjBO1tNpo7VRRUVBT0qBwq/a4MqsoBo5HrTa5UlRMFpwIfxbXwKMPVZjOdrTZsKJwy6Flb2tqrqLfZQr5exyVWG1/FNqODzUZysQkHCnYFThgMtHY42B4VSaLdgVFVOd9enkZRSrfJpijYFIXvY6Ip1Omw19La7V1g5JcWnv247y4oJEpV+S3SyNYo13eaXODkh1gFa+kQjxcUnMMfOEmcWoK+NJVRsf4AdKrK5ZYYsHTiqCGb+We3MbNVHDGqSrTTyfCCIo9tKHPcoOfdlnEsrxADygwpKEKvKiyOc/2mRp4tolDXAhUDCg5UCsiM0NPOGgm6YsyKwvl2O5/Hxrr2YVUBRcVh6oQ+xnsabUhBEdGqE1tpr68IFZa2qFqWisIW2CdNmkT//v1JTk4GYMSIEbz++ut07Fjefzg9PZ2//zqS3ApXv9tGtqV5RHPOWvM4bc12v99M34ykqCQKbflkWV09ZmL0MbSwmsgqnb19VDtiVRWn6uRYyUlMCiTY7VgVBR2uJEqJolBcKWWSYLdjUXQU6uuWdYpyOrErisfOrFNVmjlV97IMqopedf1I1dLJKl8AjHY6UdFhqbB6g6rW+CNJxMgpPH8g50TEY1WtFNq9XwBsH90eu1PFoFM4Znbl0ROMCTzU4SEuj7uCLcdNdD83mugIhYISJy2j9GzO28zcI/MwmYsAlWaKBbOiYNbpMDj0RCg2VMBR+gP3JkJVcZQGoVBJtDs45eVgYNQZsTpd9XRFyyvIKcnhqNl1d6QOhRh9M2Z1n4mzpITImOburrQWi4WoqCjOWs8y6/AszA4znWM7s7doL4X2QqwOG2dsVZ+xG2+Mx6mqOHFiddgx2RyoONHprOiIwu50oFMcxGBFVQ2Y9K5GR3OH073PGJ1qWTzAobjqtiKdqqLHdXDXASYvKcCY0saMt88qqrifufZVVz7e7GU+nVOPgitD7EQhUnVgVyNB1eOI8G04Db2jFQ69Z75etTdDr5Tg1JcHXZ0jDr3OgU0pIlIXSbQSR67FjKKzo1CWElJB73nRvIWhBcPaDWN3wW7OVfuyNG8aqAoGRwTXnu1G29wYkiJLOF4STbySTzslh1+bWfmsrffnJbdwRmBS7NhLe2gZna5YreL6fmxBuAIZqepRVBWdosekeO8EUKZNZBtOl5wOSmD361Js5WOBqqpeLy6uf7jhjgtekdOpoqs0QLTTqeJQVSIqHBBsDid6RUGnUygqsdPMqEdVocBio3lUBArlnVIURcHpVCm02ImLiXDfTWo0+Le3ZGRk0LVrV7/mBbi0W9X3utKVB/o+4PcyK6puH2iIKtZlnx59wlyaxi/QfdNfk7m/1mluBSaEvihBlZ6eHvAy/ArsiYmJ5OSUHwVPnz5NfHyAD1AIo8pBvew9XaXeNBWDfGxk6Y1UCrSMqXyyX76MuBjXqba/Ab2xaCxBXYimwK9oc80117Bq1SoAfvvtN9q0aeORXxdCCBE+frXYe/XqRbdu3Rg2bBiKovDSSy8Fu1xCCCH85PftTs8++2ztEwkhhKh32k78CiFEEySBXQghNEYCuxBCaIwEdiGE0Bi/7jz1RTA62QshRFMUliEFhBBCNFySihFCCI2RwC6EEBpT5xuUUlJSSE9Px2638/jjj9O9e3eee+45HA4HCQkJTJs2DaPRyPLly5k/fz46nY6hQ4dy9913YzKZGDduHDk5OURHRzN16lQSEhJCsV2Nhq/1mZ+fz9///neaNWvGO++8A7ieIzlu3DhOnDiBXq9nypQptG/fvpY1alcgdQmu5wyMHTuWN954gxtuuCGMW9IwBFKfdrudCRMmcOzYMex2O8899xy9e/euZY3aFkh9njlzhueff56SkhJsNhvjx4+nR48aHqmo1sHGjRvVRx99VFVVVc3NzVX79++vjhs3Tv3mm29UVVXVN998U124cKFaXFys3nzzzWpBQYFqNpvVgQMHqnl5eeoHH3ygpqSkqKqqqlu2bFEnTpxYl9Vrjq/1qaqqOnbsWHXWrFnqU0895Z5/2bJl6uTJk1VVVdV169apY8eOrd8NaEACrcujR4+qTzzxhDpq1Ch17dq19b8BDUyg9Zmamqq+9NJLqqqq6r59+9QhQ4bU7wY0MIHW57x589Tly5erqqqqaWlp6kMPPVTj+uoU2O12u1pcXKyqqqo6HA71qquuUm+44Qa1pKREVVVV/eWXX9TRo0erP//8s/rMM8+455swYYK6Zs0a9aWXXlJXrlzpfn/QoEF1Wb3m+FqfqqqqhYWF6qZNmzy+7H/84x/qTz/95F7WtddeW89b0HAEWpcmk0m12+3q888/L4FdDbw+rVararFYVFVV1ZycHHXAgAH1vAUNS6D1WdEXX3yhjhs3rsb11SnHrtfriYlxPbFlyZIlXHfddZjNZoylT/pJSEggOzubnJwcWrdu7Z4vPj6e7OxsOnfuzPr1rud5bt68mRMn/H8YsBb4Wp+A19EzK9azXq9Hp9NhtVqrTNcUBFqX0dHR6PU1P9mpKQm0PiMiIoiMdD0pbf78+dx66631VPKGKdD6BMjOzmbIkCG8++67PP300zWuz6+Lp9999x2pqam8+OKLHuNwq6U9J9VqHsRx9913ExERwfDhw/npp588gn9TVlt9Vqe6em7K/K1L4V2g9blw4UJ2797NqFGjQlXERiWQ+kxISGDp0qWMHz+e8ePH1zhtnQP7hg0bmD17NnPmzKF58+ZER0djsVgAOHXqFG3atPH6II6EhASMRiMvv/wyn376KY899pj7CNaU+VKf1UlMTHQf5W02G6qqElHheadNTSB1KaoKtD6XLFnC2rVrmTVrVpPeL8sEUp+bN28mPz8fgP79+7N7d80PVq9TYC8sLCQlJYX33nuPli1bAtC3b1/3QzdWr15Nv3796NGjBzt37qSgoIDi4mK2bt1K7969Wb9+Pf/+978BWL58Of369avL6jXH1/qszjXXXMPKlSsB+P777/njH/8Y8jI3VIHWpfAUaH0eO3aMzz77jJkzZ7pTMk1ZoPW5evVqPv/8cwD27t1L27Zta1xfne48XbRoETNmzPB4aPXUqVOZOHEiJSUlJCUlMWXKFCIiIli5ciVz585FURT+/Oc/c/vtt2OxWBgzZgyFhYW0adOGKVOmNOlWu6/1qdPpePDBBykoKODUqVNcfPHFPPnkk1x11VVMnDiRI0eOYDQamTp1aq1fuFYFWpclJSXMnTuXQ4cO0bp1axISEpg3b14Ytyi8Aq3PjRs38vXXX5OUlOSef+7cue6cclMTaH1ecskljBs3juLiYqxWKxMmTKBnz57Vrk+GFBBCCI2RO0+FEEJjJLALIYTGSGAXQgiNkcAuhBAaI4FdCCE0ps6jOwrRUE2dOpXdu3eTnZ2N2Wzm/PPPZ8uWLXz66adcfvnl4S6eEPVGujsKzVm2bBn79+/n+eefD3dRhAgLabELTRs3bhwDBw4kLy+PLVu2kJeXx/79+/nb3/7GV199xcGDB3nrrbfo0aMHCxcuZMWKFeh0OpKTk3n44YfDXXwh/CKBXTQZR44c4ZNPPmHJkiW89957fPHFFyxbtoyvvvqK1q1bs3LlSj799FMAhg8fzv/93/953DkpRGMhgV00GZdeeimKopCQkMAll1yCXq8nPj6erVu3snPnTo4ePcr9998PQHFxMZmZmRLYRaMkgV00GQaDwev/ZaNiXn/99bzyyivhKJoQQSXdHYUAunXrRlpaGmazGVVVee2119xDqgrR2EiLXQggKSmJ+++/n/vuuw+9Xk9ycjJRUVHhLpYQfpHujkIIoTGSihFCCI2RwC6EEBojgV0IITRGArsQQmiMBHYhhNAYCexCCKExEtiFEEJjJLALIYTG/D/41eVFCHsr3gAAAABJRU5ErkJggg==\n", 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\n", 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" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "fig, ax = plt.subplots() #prepare a Matplotlib figure\n", + "fig, (ax0, ax1) = plt.subplots(2, 1) #prepare a Matplotlib figure\n", "\n", - "flowdata.plot(ax=ax) # use Pandas for the plotting" + "flowdata.plot(ax=ax0) # use Pandas for the plotting" ] }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "data": { @@ -980,18 +1163,20 @@ "Text(0.5, 0.98, 'Flow station time series')" ] }, - "execution_count": 23, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -1008,68 +1193,58 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 24, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(16, 6)) #provide with matplotlib 2 axis\n", + "fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(16, 6)) #provide with matplotlib 2 axis\n", "\n", - "flowdata[[\"L06_347\", \"LS06_347\"]].plot(ax=ax1) # plot the two timeseries of the same location on the first plot\n", - "flowdata[\"LS06_348\"].plot(ax=ax2, color='0.2') # plot the other station on the second plot\n", + "flowdata[[\"L06_347\", \"LS06_347\"]].plot(ax=ax0) # plot the two timeseries of the same location on the first plot\n", + "flowdata[\"LS06_348\"].plot(ax=ax1, color='0.7') # plot the other station on the second plot\n", "\n", "# further adapt with matplotlib\n", - "ax1.set_ylabel(\"L06_347\")\n", - "ax2.set_ylabel(\"LS06_348\")\n", - "ax2.legend()" + "ax0.set_ylabel(\"L06_347\")\n", + "ax1.set_ylabel(\"LS06_348\")\n", + "ax1.legend()" ] }, { "cell_type": "markdown", - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "source": [ "
\n", "\n", " Remember: \n", "\n", - "
    \n", - "
  • You can do anything with matplotlib, but at a cost... stackoverflow
    • \n", - " \n", - "
  • The preformatting of Pandas provides mostly enough flexibility for quick analysis and draft reporting. It is not for paper-proof figures or customization
    • \n", - "
\n", - "
\n", + "* You can do anything with matplotlib, but at a cost... stackoverflow\n", + "* The preformatting of Pandas provides mostly enough flexibility for quick analysis and draft reporting. It is not for paper-proof figures or customization\n", "\n", "If you take the time to make your perfect/spot-on/greatest-ever matplotlib-figure: Make it a reusable function!\n", + " \n", + "`fig.savefig()` to save your Figure object! \n", "\n", "
" ] @@ -1078,134 +1253,309 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "An example of such a reusable function to plot data:" + "## Exercise" ] }, { "cell_type": "code", - "execution_count": 25, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "flowdata = pd.read_csv('data/vmm_flowdata.csv', \n", + " index_col='Time', \n", + " parse_dates=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Overwriting plotter.py\n" - ] + "data": { + "text/html": [ + "
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L06_347LS06_347LS06_348
Time
2009-01-01 00:00:000.1374170.0975000.016833
2009-01-01 03:00:000.1312500.0888330.016417
2009-01-01 06:00:000.1135000.0912500.016750
2009-01-01 09:00:000.1357500.0915000.016250
2009-01-01 12:00:000.1409170.0961670.017000
\n", + "
" + ], + "text/plain": [ + " L06_347 LS06_347 LS06_348\n", + "Time \n", + "2009-01-01 00:00:00 0.137417 0.097500 0.016833\n", + "2009-01-01 03:00:00 0.131250 0.088833 0.016417\n", + "2009-01-01 06:00:00 0.113500 0.091250 0.016750\n", + "2009-01-01 09:00:00 0.135750 0.091500 0.016250\n", + "2009-01-01 12:00:00 0.140917 0.096167 0.017000" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "%%file plotter.py \n", - "#this writes a file in your directory, check it(!)\n", + "flowdata.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", "\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.dates as mdates\n", + "**EXERCISE**\n", "\n", - "from matplotlib import cm\n", - "from matplotlib.ticker import MaxNLocator\n", + "Pandas supports different types of charts besides line plots, all available from `.plot.xxx`, e.g. `.plot.scatter`, `.plot.bar`,... Make a bar chart to compare the mean discharge in the three measurement stations L06_347, LS06_347, LS06_348. Add a y-label 'mean discharge'. To do so, prepare a Figure and Axes with Matplotlib and add the chart to the created Axes.\n", "\n", - "def vmm_station_plotter(flowdata, label=\"flow (m$^3$s$^{-1}$)\"):\n", - " colors = [cm.viridis(x) for x in np.linspace(0.0, 1.0, len(flowdata.columns))] # list comprehension to set up the color sequence\n", + "
Hints\n", "\n", - " fig, axs = plt.subplots(3, 1, figsize=(16, 8))\n", + "* You can either use Pandas `ylabel` parameter to set the label or add it with Matploltib `ax.set_ylabel()`\n", + "* To link an Axes object with Pandas output, pass the Axes created by `fig, ax = plt.subplots()` as parameter to the Pandas plot function.\n", + "
\n", "\n", - " for ax, col, station in zip(axs, colors, flowdata.columns):\n", - " ax.plot(flowdata.index, flowdata[station], label=station, color=col) # this plots the data itself\n", - " \n", - " ax.legend(fontsize=15)\n", - " ax.set_ylabel(label, size=15)\n", - " ax.yaxis.set_major_locator(MaxNLocator(4)) # smaller set of y-ticks for clarity\n", - " \n", - " if not ax.get_subplotspec().is_last_row(): # hide the xticklabels from the none-lower row x-axis\n", - " ax.xaxis.set_ticklabels([])\n", - " ax.xaxis.set_major_locator(mdates.YearLocator())\n", - " else: # yearly xticklabels from the lower x-axis in the subplots\n", - " ax.xaxis.set_major_locator(mdates.YearLocator())\n", - " ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))\n", - " ax.tick_params(axis='both', labelsize=15, pad=8) # enlarge the ticklabels and increase distance to axis (otherwise overlap)\n", - " return fig, axs" + "
" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 33, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } + "tags": [ + "nbtutor-solution" + ] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "flowdata.mean().plot.bar(ylabel=\"mean discharge\", ax=ax)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ - "from plotter import vmm_station_plotter\n", - "# fig, axs = vmm_station_plotter(flowdata)" + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "To compare the stations data, make two subplots next to each other:\n", + " \n", + "- In the left subplot, make a bar chart of the minimal measured value for each of the station.\n", + "- In the right subplot, make a bar chart of the maximal measured value for each of the station. \n", + "\n", + "Add a title to the Figure containing 'Minimal and maximal discharge from 2009-01-01 till 2013-01-02'. Extract these dates from the data itself instead of hardcoding it.\n", + "\n", + "
Hints\n", + "\n", + "- One can directly unpack the result of multiple axes, e.g. `fig, (ax0, ax1) = plt.subplots(1, 2,..` and link each of them to a Pands plot function.\n", + "- Remember the remark about `constrained_layout=True` to overcome overlap with subplots?\n", + "- A Figure title is called `suptitle` (which is different from an Axes title)\n", + "- f-strings ([_formatted string literals_](https://docs.python.org/3/tutorial/inputoutput.html#formatted-string-literals)) is a powerful Python feature (since Python 3.6) to use variables inside a string, e.g. `f\"some text with a {variable:HOWTOFORMAT}\"` (with the format being optional).\n", + "
\n", + "\n", + "
" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 47, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "image/png": 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\n", 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XZ2arJic4M2ubqh88Vb18vc5VlGYVJWmkpN9LukPS7ZI+mfufIOl+STfnv73LjtWsHXwGZ1Zdy4BPR8SNktYFZkm6Og/7XkR8u8TYzNrOCc6soiJiAbAgf14i6Q5gRLlRmXWOqyjNVgGSRgM7ADfkXhMkzZY0WdIG5UVm1j5OcGYVJ2kd4H+B4yLiUeB04BXA9qQzvO80mO4oSTMlzVy0aFGnwjVrGSc4swqTtAYpuZ0XERcDRMQDEfFMRDwLnAnsXG/aiJgUEWMjYuywYV37qjqzhpzgzCpKkoCzgTsi4ruF/sMLo70LuK3TsZl1ghuZmFXXG4APArdKujn3+y/gYEnbAwHcDXy0jODM2s0JzqyiIuI6QHUGTet0LGZlcBWlmZlVkhOcmZlVkhOcmZlVUqkJTtI4SXdJmiNpYp3hknRKHj5b0o65/1qS/izplvyMva92PnozM+tmpSU4SUOA04DxwNakll1b14w2HhiT/44i3aAK8DSwe0RsR7pZdZykXTsRt5mZ9YYyz+B2BuZExNyIWApcCOxXM85+wLmRXA+sL2l47n4sj7NG/ouORW5mZl2vzAQ3Ariv0D2PFz4ItuE4kobke3sWAldHxA2YmZllZSa4evfn1J6FNRwnP2poe2AzYGdJ29RdiJ+nZ2a2Siozwc0DRha6NwPmr+g4EfEIcA0wrt5C/Dw9M7NVU5kJbgYwRtIWkoYCBwFTa8aZChyaW1PuCiyOiAWShklaH0DS2sDbgDs7GLuZmXW50h7VFRHLJE0ArgSGAJMj4nZJR+fhZ5AeKbQ3MAd4Ajg8Tz4cmJJbYq4GXBQRv+50GczMrHuV+izKiJhGzXPxcmLr+xzAx+tMN5v08kYzM7O6/CQTMzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4MzOrJCc4s4qSNFLS7yXdIel2SZ/M/TeUdLWkv+X/G5Qdq1k7OMGZVdcy4NMR8WpgV+DjkrYGJgLTI2IMMD13m1WOE5xZRUXEgoi4MX9eAtwBjAD2A6bk0aYA+5cSoFmbOcGZrQIkjQZ2AG4ANomIBZCSILBxg2mOkjRT0sxFixZ1LFazVnGCM6s4SesA/wscFxGPNjtdREyKiLERMXbYsGHtC9CsTZzgzCpM0hqk5HZeRFycez8gaXgePhxYWFZ8Zu3kBGdWUZIEnA3cERHfLQyaChyWPx8GXNrp2Mw6YfWyAzCztnkD8EHgVkk3537/BZwMXCTpSOBe4IBywjNrLyc4s4qKiOsANRi8RydjMStDqVWUksZJukvSHEkvuBdHySl5+GxJO+b+dW9gNTMz61NagpM0BDgNGA9sDRycb0ItGg+MyX9HAafn/o1uYDUzMwPKPYPbGZgTEXMjYilwIekG1KL9gHMjuR5YX9Lwfm5gNTMzA8pNcCOA+wrd83hhkhpwnJobWF/AN6uama2aykxw9S5+x4qM08wNrL5Z1cxs1VRmgpsHjCx0bwbMb3acBjewmpmZAeUmuBnAGElbSBoKHES6AbVoKnBobk25K7A4Ihb0cwOrmZkZUOJ9cBGxTNIE4EpgCDA5Im6XdHQefgYwDdgbmAM8ARyeJ697A2tETOtgEczMrIuVeqN3TkjTavqdUfgcwMfrTNffDaxmZmZ+FqVZL5C0tqStyo7DrJc0leAkvVHS4fnzMElbtDcsM+sjaV/gZuA3uXt7SbXXq82sxoAJTtJXgM8DX8i91gB+1s6gzOx5TiA9GOERgIi4GRhdWjRmPaKZM7h3Ae8EHgeIiPnAuu0MysyeZ1lELC47CLNe00yCW5obewSApBe3NyQzq3GbpEOAIZLGSPoh8MeygzLrds0kuIsk/Zj0HMiPAL8FzmxvWGZW8AngNcDTwAXAo8BxZQZk1gsGvE0gIr4taU/STrUV8OWIuLrtkZkZABHxBHB8/jOzJjV1H1xOaE5qZiWQdBkvfE7rYmAm8OOIeKrzUZl1v2ZaUS6R9GjN332SLpH08k4EabaKmws8Rro0cCapNuUBYEt8ucCsoWbO4L5LesDx+aSnhxwEvAy4C5gM7Nau4MwMgB0i4s2F7sskXRsRb5Z0e2lRmXW5ZhqZjIuIH0fEkoh4NCImAXtHxM+BDdocn5nBMEmj+jry541y59JyQjLrfs2cwT0r6UDgl7n7vYVhtdcFzKz1PgVcJ+nvpFqULYBj8i07U0qNzKyLNZPg3g/8APgRKaFdD3xA0trAhDbGZrbKk7Qa6cEKY4BXkRLcnYWGJd8vKTSzrtdvgpM0BPhYROzbYJTrWh+SmfWJiGclTYiIi4Bbyo7HrJf0ew0uIp4BdupQLGZW39WSPiNppKQN+/7KDsqs2zVTRXlTfnL5L8jPowSIiIvbFpWZFR2R/xffjRiAb9Mx60czCW5D4EFg90K/AJzgzDogIvx6KrOV0Myjug7vRCBm1pikbYCtgbX6+kXEueVFZNb9BkxwktYCjiQ97LW4cx3RcCIza5n8TsbdSAluGjCe1MDLCc6sH83c6P1T0pNL3g78AdgMWNLOoMzsed4L7AH8M9eobAesWW5IZt2vmQT3yoj4EvB4REwB9gFe296wzKzgyYh4FlgmaT1gIU00MJE0WdJCSbcV+p0g6X5JN+e/vdsYt1mpmklw/87/H8nXAV4CjG5bRGZWa6ak9UkPVp4F3Aj8uYnpzgHG1en/vYjYPv9Na1mUZl2mmVaUkyRtAHwJmAqsA3y5rVGZ2XMi4pj88QxJvwHWi4jZTUx3raTRbQ3OrIs104ryrPzxD/i+G7NSSBoBbE7eZyW9OSKuXcnZTZB0KOl9cp+OiIdbFKZZV2mmFeWawHtI1ZLPjR8RX2tfWGbWR9I3gfcBfwGeyb0DWJkEdzpwYp7+ROA7LL+RvHa5RwFHAYwaNareKGZdrZkqyktJbw+eBTzd3nDMrI79ga0iYtD7X0Q80PdZ0pnAr/sZdxIwCWDs2LF+c4j1nGYS3GYRUe9C9aBJGkd6U8EQ4KyIOLlmuPLwvYEngA9FxI152GTgHcDCiNimHfGZdYm5wBq04ABT0vCIWJA73wXc1t/4Zr2smQT3R0mvjYhbW7ng/KaC04A9gXnADElTI+IvhdHGk14TMgbYhVS9sksedg5wKr7Z1SpK0g9JVYlPADdLmk4hyUXEsQNMfwHpBvGNJM0DvgLsJmn7PN+7gY+2I3azbtAwwUm6lbQTrA4cLmkuaecSEBGx7SCXvTMwJyLm5uVdCOxHus7QZz/g3IgI4HpJ6/cdgbqFmK0CZub/s0gtmFdIRBxcp/fZg4rIrIf0dwb3jjYvewRwX6F7HsvPzvobZwSwALOKyw9WIL+5+6n8+qq+2g8/ycRsAA1v9I6IeyLiHmA48FCh+yHSo7sGS/UWuxLj9L8Q6ShJMyXNXLRo0YpMatYtpgNrF7rXBn5bUixmPaOZJ5mcDjxW6H489xusecDIQvdmwPyVGKdfETEpIsZGxNhhw4atVKBmJVsrIp7bB/PnF5UYj1lPaCbBKV8DAyA/E6+ZxikDmQGMkbSFpKHAQbzwOsNU4FAluwKLCy3AzFYVj0vasa9D0k7AkyXGY9YTmklUcyUdy/KztmNIzZYHJSKWSZoAXEm6TWByRNwu6eg8/AzSq0H2BuaQWpI99266ei3EIsIX0K2KjgN+Iamv9mI46cZvM+tHMwnuaOAU4Iuk61/TyU83GKz8oNdpNf3OKHwO4OMNpq3XQsysciJihqRXAVuRrkvfGRH/HmAys1XegFWUEbEwIg6KiI0jYpOIOCQiFnYiODMDSQeQrsPdRrp15ufFKkszq2/ABCfpW5LWk7SGpOmS/iXpA50IzswA+FJELJH0RtKLh6fQmoZeZpXWTCOTvSLiUdJ9cfOALYHPtjUqMyvqe8DyPsDpEXEpMLTEeMx6QjMJbo38f2/ggoh4qI3xmNkL3S/px8CBwLT8ho9m9l2zVVozO8llku4ExgLTJQ0DnmpvWGZWcCCptfG4iHgE2BDXopgNqJlGJhOB1wNjc8utx0kXus2sjSStlz+uBVwDPChpQ9IzYWc2ms7Mkv4etrx7RPxO0rsL/YqjXNzOwMyM80nXvmeRbtEp7oABvLyMoMx6RX/3wb0F+B2wb51hgROcWVtFxDvy/y3KjsWsFzVMcBHxlfz/8EbjmFn7DHSvW9/Lf82svv6qKD/V34QR8d3Wh2NmBd/J/9ciNfK6hVRNuS1wA/DGkuIy6wn9NTJZN/+NBT5Geg/bCNKju7Zuf2hmq7aIeGtEvBW4B9gxvxVjJ2AH0vNZzawf/VVRfhVA0lWknWtJ7j4B+EVHojMzgFdFxK19HRFxm6TtS4zHrCc087DlUcDSQvdSYHRbojGzeu6QdBbwM1IDrw8Ad5Qbkln3aybB/RT4s6RLSDvXu0jPwjOzzjicdJngk7n7WvwsSrMBDZjgIuIkSVcAb8q9Do+Im9oblpn1iYingO/lPzNrUlNv5s7Nkd0k2czMeoYf2GpmZpXkBGfW5SStVaffRmXEYtZLnODMut8MSbv2dUh6D/DHEuMx6wkDXoPLD1v+JrAx6SkKAiIi1ut3QjNrlUOAyZKuATYFXgrsXmpEZj2gmUYm3wL2jQjfd2NWgoi4VdJJpFt2lgBvjoh5JYdl1vWaSXAPOLmZlUfS2cArSM+g3JL0EuJTI+K0ciMz627NJLiZkn4O/Ir0okUAIsKvyzHrjNuAD0dEAP/I1+P8sHOzATST4NYDngD2KvTz++CsJ4yeeHlHl3f3yfu0fJ4R8b2a7sXAkS1fkFnFNPMkE78PzqxEksYA3yC9xeO5WwYiot83ekuaTHoj+MKI2Cb32xD4Oel5sncDB0bEw20J3KxkDW8TkPS5/P+Hkk6p/etciGarvJ+Qnj25DHgrcC6pwclAzgHG1fSbCEyPiDHA9NxtVkn93QfX17BkJjCrzt+gSRon6S5JcyS9YEdTckoePrv4huOBpjWrkLUjYjqgiLgnIk6gidsEIuJa4KGa3vux/GHpU4D9WxinWVfp731wl+X/bXlzgKQhwGnAnsA80s2sUyPiL4XRxgNj8t8upKPYXZqc1qwqnpK0GvA3SROA+0n3pa6MTSJiAUBELJDUcD6SjgKOAhg1atRKLs6sPAM+yUTSWEmXSLoxn0XNljS7BcveGZgTEXMjYilwIenosmg/4NxIrgfWlzS8yWnNquI44EXAscBOwAeBw9q90IiYlN8iPnbYsGHtXpxZyzXTivI84LPArcCzLVz2COC+Qvc80lnaQOOMaHJas0qIiBn542Okd8MNxgOShuezt+HAwkHOz6xrNZPgFkXE1DYsW3X6RZPjNDNtmkELqlmq0NS8m5bXSVUom6SxwPHA5hT22YjYdiVmN5V09ndy/n9pK2I060bNJLivSDqL1OKqlTd6zwNGFro3A+Y3Oc7QJqbti3MSMAlg7NixdZOgWZdbqVoUSRcAuwEbSZoHfIWU2C6SdCRwL3BAy6M16xLNJLjDgVcBa7B852rFjd4zgDGStiBdND+I9FDZoqnABEkXkqogF+eqlUVNTGtWFStVixIRBzcYtMcg4zHrCc0kuO0i4rWtXnBELMstwq4EhgCTI+J2SUfn4WcA04C9gTmkp6kc3t+0rY7RrEu0qxbFrNKaSXDXS9q6HU3wI2IaKYkV+51R+BzAx5ud1qyi2lWLYlZpzSS4NwKHSfoH6eix731wK3OB28xWXFtqUcyqrpkEV/uoHzPrrLbVophVWTMPW76nE4GYWUOuRTFbCc2cwZlZuVyLYrYSnODMupxrUcxWzoDPojQzM+tFTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJTnBmZlZJpSQ4SRtKulrS3/L/DRqMN07SXZLmSJpY6H+ApNslPStpbOciN6sGSXdLulXSzZJmlh2PWTuUdQY3EZgeEWOA6bn7eSQNAU4DxgNbAwdL2joPvg14N3BtZ8I1q6S3RsT2EeGDRKukshLcfsCU/HkKsH+dcXYG5kTE3IhYClyYpyMi7oiIuzoRqJmZ9aayEtwmEbEAIP/fuM44I4D7Ct3zcr8VIukoSTMlzVy0aNFKBWtWQQFcJWmWpKPKDsasHVZv14wl/RZ4WZ1Bxzc7izr9YkXjiIhJwCSAsWPHrvD0ZhX1hoiYL2lj4GpJd0bE86r8c+I7CmDUqFFlxGg2KG1LcBHxtkbDJD0gaXhELJA0HFhYZ7R5wMhC92bA/BaHabZKioj5+f9CSZeQLglcWzOODw6tp5VVRTkVOCx/Pgy4tM44M4AxkraQNBQ4KE9nZoMg6cWS1u37DOxFarhlVillJbiTgT0l/Q3YM3cjaVNJ0wAiYhkwAbgSuAO4KCJuz+O9S9I84PXA5ZKuLKEMZr1qE+A6SbcAfwYuj4jflByTWcu1rYqyPxHxILBHnf7zgb0L3dOAaXXGuwS4pJ0xmlVVRMwFtis7DrN285NMzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMyskpzgzMysklYvOwAzM+s+oyde3tHl3X3yPi2fpxNcE9rxxZuZWXu5itLMzCqplAQnaUNJV0v6W/6/QYPxxkm6S9IcSRML/f9H0p2SZku6RNL6HQvezMx6QllncBOB6RExBpieu59H0hDgNGA8sDVwsKSt8+CrgW0iYlvgr8AXOhK1mZn1jLIS3H7AlPx5CrB/nXF2BuZExNyIWApcmKcjIq6KiGV5vOuBzdobrpmZ9ZqyEtwmEbEAIP/fuM44I4D7Ct3zcr9aRwBXtDxCMzPraW1rRSnpt8DL6gw6vtlZ1OkXNcs4HlgGnNdPHEcBRwGMGjWqyUWbVZukccAPgCHAWRFxcskhmbVc2xJcRLyt0TBJD0gaHhELJA0HFtYZbR4wstC9GTC/MI/DgHcAe0RE0EBETAImAYwdO7bheGarisL17T1J+9kMSVMj4i/lRmbWWmVVUU4FDsufDwMurTPODGCMpC0kDQUOytP1HX1+HnhnRDzRgXjNqqTh9W2zKlE/Jz/tW6j0UuAiYBRwL3BARDwkaVNSdcneeby9ge+TqlEmR8RJuf8cYE3gwTzL6yPi6CaWuwi4p8XF6c9GwL86uLxOq3L5Ol22zSNiWCcWJOm9wLiI+HDu/iCwS0RMqBnvuep9YCvgrk7El1V524Jql69r9p1SEtyqQtLMiBhbdhztUuXyVbxsBwBvr0lwO0fEJ8qNbLkqf/9Q7fJ1U9n8JBOzVU+/17fNqsIJzmzV0/D6tlmV+GHL7TWp7ADarMrlq2zZImKZpAnAlSy/vn17yWHVquz3n1W5fF1TNl+DMzOzSnIVpZmZVZITnJmZVZITnJmZVZITnJmZVZITXItIOlbSyIHH7E2SLpb0AUnrlB1LO0h6uaTJkr4uaR1JZ0q6TdIvJI0uO74q877T27p533GCa50TgRsk/Z+kYyR15LFLHbQL6b1990q6SNK78j1UVXEO6f6wx0jvGLyT9LLd3wCTywtrleB9p7edQ5fuO75NoEUk3QTsBLwNeB/wTmAWcAFwcUQsKTG8QZN0U0TsIGld0s56MPA64NfABRFxVZnxDVZf+fLneyNiVL1h1nred7zvtIvP4FonIuLZ/LbxI4FNgR8B44C55YbWEgEQEUsi4qf5gdhbATcAE0uNrDWelbSlpNcBL5I0FkDSK0k3Q1v7eN/pbV277/gMrkX6O1KRtHZEPNnpmFpJ0rUR8eay42gXSXuQflSfBT4C/CewHbAe8JGIqPdKJ2sB7zu9rZv3HSe4FpG0ZUT8tew4rHUkbQQ8HBHPlB1LlXnfqZ5u2XdcRdki9XZQSe8sI5ZOkfTfZcfQZp8qewddFXjfqaSu2Hf8sOUWkfTu2l7AaZJWB4iIizsfVetIOqW2F/DBvqbPEXFs56NqnaqXr5t53+ntbauby+cE1zoXkZrFLiStYIAXA/uSLjL39E4KvBu4BriK5eU7iNTarQqqXr5u5n2nt3Vt+XwNrkVyC6KTgV8CZ0RESPpHRGxRcmgtkZs4nwhsDHw2Iu6XNDciXl5yaC1R9fJ1M+87va2by+czuBaJiBmS9gQ+AfxO0ufJzYOrIN+LdJyknYCfSbqcCl3DrXr5upn3nd7WzeXriiCqIt/L8wPg/cBnyo6nHSJiFrA78CRwXcnhtFzVy9etvO/0vm4sn6sozcysknwG1yKSXiTpc5I+K2ktSYdJmirpW1V4yKqkV0m6QtLlkl4h6RxJj0j6s6RXlx3fYFW9fN3M+05v6+byOcG1zjnAJsAWwOWkZ819m9Sq6PTywmqZSaSnFfwM+B2p1dsGpIvLp5YYV6tUvXzd7By87/Syri2fqyhbRNLNEbG9JAELgOG5NZiAWyJi25JDHJSaB6rOiYhXFobdGBE7lhfd4FW9fN3M+05vb1vdXD6fwbVYpCOGafl/X3cVjiKKD039bs2wKrz6o+rl63red3pW15bPCa51Zhbu3D+ir6ekVwA9/bqP7LRC+X7U1zM/Mfy3pUXVOlUvXzfzvtPburZ8rqLsAEnqOyqVtGdEXF12TO0i6QsR8Y2y42iXqpev23jfqY4yyuczuA6I5x9FfLO0QDrjgLIDaLOql6+reN+plI6Xzwmu8zTwKD3N5bN2qfp37/K1mBNc51W9Ttjls3ap+nfv8rWYE5y1mo9CzVZO1bctn8GtAu4uO4A2+0XZAbRZ1cvXze4uO4A2q/q21fHyuRVli0gaBSyMiKfyDaofAnYE/gKcGRHLyoxvsCS9C/hDRDwkaRjwHWAHUvk+HRHzSg1wkKpevm7mfae3t61uLp/P4FpnGsu/z5OBfYAbSI8dmlRWUC10UkQ8lD+fCtwEjAeuAH5SWlStU/XydTPvO72ta8vnM7gWkfSXiNg6f54FvC4ins3dt0TEdqUGOEiS7oqIrfLnWRGxU2HYzRGxfWnBtUDVy9fNvO/09rbVzeXzGVzr3Cdp9/z5bmAkgKSXlhZRa10j6WuS1s6f9weQ9FZgcamRtUbVy9fNvO/0tq4tn8/gWkTSSOBc0nPZFgNvJJ2qbwB8JiKmlxjeoElaAzge6HuU0mbA48BlwMSIuLes2Fqh6uXrZt53envb6ubyOcG1WH7/0ZbA6sA8YEZfdUtVSHoJsHpEPFh2LO1Q9fJ1K+87va/byucE1waSNiQ9ZejhsmNppdzCbWdgBOmmzfnAn6MiG1HVy9cLvO/0pm4tnxNci+Smzt8C9gAeId3UuB7pBYATI+Lu0oJrAUl7kV5q+Dfg/tx7M+CVwDERcVVZsbVC1cvXzbzv9Pa21c3lc4JrEUl/Ar4P/DIinsn9hpAeMHpcROxaYniDJukOYHztj42kLUjv8Cr11fSDVfXydTPvO729bXVz+dyKsnU2ioif9+2gABHxTERcCFShNVjfdZFa9wNrdDiWdqh6+bqZ953e1rXlW73MhVfMLEk/AqYA9+V+I4HDSC3Cet1kYIakC1levlHA+4CzS4uqdapevm7mfae3dW35XEXZIpKGAkcC+5EutIq0si8DzoqIpSWG1xK5lVuxfPOAqRHxl1IDa5Gql69bed/pfd1aPie4DpB0XER8v+w4Win/KL0GuD8iFpYdT6tVvXy9wvtO7+mm8vkaXGd8quwABkvSGZJekz+/BLiZdHPuTZIOLjO2Vqh6+XqY950u183lc4LrjCq85+lNEXF7/nw48NeIeC2wE/C58sJqmaqXr1d53+l+XVs+J7jOqEI9cPE6yJ7ArwAi4p+lRNN6VS9fr/K+0/26tnxuRdkikpZQf2cUsHaHw2mHRyS9g9T09w2kRgFIWh2XzwbB+07P69ryOcG1SESsW3YMbfZR4BTgZaSbb/uOzvYALi8tqtapevm6lvednte15XMrShu0KrZ0K6p6+aw8Vd+2yi6fE5wNmqR7I2JU2XG0S9XLZ+Wp+rZVdvncyMRaoQot3fpT9fJZeaq+bZVaPic4a4WqVwNUvXxWnqpvW6WWz41MrClVb+lW9fJZeaq+bXVz+XwNzszMKslVlGZmVklOcGZmVklOcGZmVklOcGZmVklOcGZmVkn/HwOTnJQ73YsGAAAAAElFTkSuQmCC\n", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "fig, axs = vmm_station_plotter(flowdata, \n", - " label=\"NO$_3$ (mg/l)\")\n", - "fig.suptitle('Ammonium concentrations in the Maarkebeek', fontsize='17')\n", - "fig.savefig('ammonium_concentration.pdf')" + "fig, (ax0, ax1) = plt.subplots(1, 2, constrained_layout=True)\n", + "\n", + "flowdata.min().plot.bar(ylabel=\"min discharge\", ax=ax0)\n", + "flowdata.max().plot.bar(ylabel=\"max discharge\", ax=ax1)\n", + "\n", + "fig.suptitle(f\"Minimal and maximal discharge from {flowdata.index[0]:%Y-%m-%d} till {flowdata.index[-1]:%Y-%m-%d}\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", + "
\n", + "\n", + "**EXERCISE**\n", + "\n", + "Make a line plot of the discharge measurements in station `LS06_347`. \n", + " \n", + "The main event on November 13th caused a flood event. To support the reader in the interpretation of the graph, add the following elements:\n", + " \n", + "- Add an horizontal red line at 20 m3/s to define the alarm level.\n", + "- Add the text 'Alarm level' in red just above the alarm levl line.\n", + "- Add an arrow pointing to the main peak in the data (event on November 13th) with the text 'Flood event on 2020-11-13'\n", + " \n", + "Check the Matplotlib documentation on [annotations](https://matplotlib.org/stable/gallery/text_labels_and_annotations/annotation_demo.html#annotating-plots) for the text annotation\n", "\n", - "**NOTE**\n", + "
Hints\n", "\n", - "- Let your hard work pay off, write your own custom functions!\n", + "- The horizontal line is explained in the cheat sheet in this notebook.\n", + "- Whereas `ax.text` would work as well for the 'alarm level' text, the `annotate` method provides easier options to shift the text slightly relative to a data point.\n", + "- Extract the main peak event by filtering the data on the maximum value. Different approaches are possible, but the `max()` and `idxmax()` methods are a convenient option in this case.\n", + "\n", + "
\n", "\n", "
" ] }, { - "cell_type": "markdown", - "metadata": {}, + "cell_type": "code", + "execution_count": 79, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(-30, -30, 'Flood event on 2010-11-13')" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "
\n", - "\n", - "**Remember** \n", + "alarm_level = 20\n", + "max_datetime, max_value = flowdata[\"LS06_347\"].idxmax(), flowdata[\"LS06_347\"].max()\n", "\n", - "`fig.savefig()` to save your Figure object!\n", + "fig, ax = plt.subplots(figsize=(18, 4))\n", + "flowdata[\"LS06_347\"].plot(ax=ax)\n", "\n", - "
" + "ax.axhline(y=alarm_level, color='red', linestyle='-', alpha=0.8)\n", + "ax.annotate('Alarm level', xy=(flowdata.index[0], alarm_level), \n", + " xycoords=\"data\", xytext=(10, 10), textcoords=\"offset points\",\n", + " color=\"red\", fontsize=12)\n", + "ax.annotate(f\"Flood event on {max_datetime:%Y-%m-%d}\",\n", + " xy=(max_datetime, max_value), xycoords='data',\n", + " xytext=(-30, -30), textcoords='offset points',\n", + " arrowprops=dict(facecolor='black', shrink=0.05),\n", + " horizontalalignment='right', verticalalignment='bottom',\n", + " fontsize=12)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "# Need more matplotlib inspiration? " + "# Need more matplotlib inspiration?" ] }, { @@ -1224,18 +1574,31 @@ "source": [ "
\n", "\n", - "**Remember**\n", + "**Galleries!**\n", "\n", - "- matplotlib gallery is an important resource to start from\n", - "- Matplotlib has some great [cheat sheets](https://github.com/matplotlib/cheatsheets) available\n", + "Galleries are great to get inspiration, see the plot you want, and check the code how it is created:\n", + " \n", + "* [matplotlib gallery](https://matplotlib.org/stable/gallery/index.html)\n", + "* [seaborn gallery](https://seaborn.pydata.org/examples/index.html)\n", + "* [python Graph Gallery](https://python-graph-gallery.com/)\n", "\n", "
" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1249,7 +1612,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { @@ -1267,6 +1630,13 @@ "right": "1657px", "top": "106px", "width": "212px" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } } }, "nbformat": 4, diff --git a/_solved/visualization_02_plotnine.ipynb b/_solved/visualization_02_plotnine.ipynb new file mode 100644 index 0000000..7bd4e82 --- /dev/null +++ b/_solved/visualization_02_plotnine.ipynb @@ -0,0 +1,1585 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Plotnine: Introduction

\n", + "\n", + "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", + "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plotnine\n", + "\n", + "http://plotnine.readthedocs.io/en/stable/" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Built on top of Matplotlib, but providing\n", + " 1. High level functions\n", + " 2. Implementation of the [Grammar of Graphics](https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448), which became famous due to the `ggplot2` R package \n", + " 3. The syntax is highly similar to the `ggplot2` R package\n", + "* Works well with Pandas" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "import plotnine as p9" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will use the Titanic example data set:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "titanic = pd.read_csv('../data/titanic.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
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" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris male 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n", + "2 Heikkinen, Miss. Laina female 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n", + "4 Allen, Mr. William Henry male 35.0 0 \n", + "\n", + " Parch Ticket Fare Cabin Embarked \n", + "0 0 A/5 21171 7.2500 NaN S \n", + "1 0 PC 17599 71.2833 C85 C \n", + "2 0 STON/O2. 3101282 7.9250 NaN S \n", + "3 0 113803 53.1000 C123 S \n", + "4 0 373450 8.0500 NaN S " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "titanic.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's consider following question:\n", + ">*For each class at the Titanic, how many people survived and how many died?*" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Hence, we should define the *size* of respectively the zeros (died) and ones (survived) groups of column `Survived`, also grouped by the `Pclass`. In Pandas terminology:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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PclassSurvivedcount
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\n", + "
" + ], + "text/plain": [ + " Pclass Survived count\n", + "0 1 0 80\n", + "1 1 1 136\n", + "2 2 0 97\n", + "3 2 1 87\n", + "4 3 0 372\n", + "5 3 1 119" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "survived_stat = titanic.groupby([\"Pclass\", \"Survived\"]).size().rename('count').reset_index()\n", + "survived_stat\n", + "# Remark: the `rename` syntax is to provide the count column a column name " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Providing this data in a bar chart with pure Pandas is still partly supported:" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "survived_stat.plot(x='Survived', y='count', kind='bar')\n", + "## A possible other way of plotting this could be using groupby again: \n", + "#survived_stat.groupby('Pclass').plot(x='Survived', y='count', kind='bar') # (try yourself by uncommenting)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "but with mixed results..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plotting libraries focussing on the **grammar of graphics** are really targeting these *grouped* plots. For example, the plotting of the resulting counts can be expressed in the grammar of graphics:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(survived_stat, \n", + " p9.aes(x='Survived', y='count', fill='factor(Survived)'))\n", + " + p9.geom_bar(stat='identity', position='dodge')\n", + " + p9.facet_wrap(facets='Pclass'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Moreover, these `count` operations are embedded in the typical Grammar of Graphics packages and we can do these operations directly on the original `titanic` data set in a single coding step:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='Survived', fill='factor(Survived)'))\n", + " + p9.geom_bar(stat='count', position='dodge')\n", + " + p9.facet_wrap(facets='Pclass'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + " Remember: \n", + "\n", + "
    \n", + "
  • The Grammar of Graphics is especially suitbale for these so-called tidy dataframe representations (check here for more about `tidy` data)
    • \n", + "
  • plotnine is a library that supports the Grammar of graphics
    • \n", + "
\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Building a plotnine graph" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Building plots with plotnine is typically an iterative process. As illustrated in the introduction, a graph is setup by layering different elements on top of each other using the `+` operator. putting everything together in brackets `()` provides Python-compatible syntax." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Bind the plot to a specific data frame using the data argument:" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(data=titanic))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We haven 't defined anything else, so just an empty *figure* is available." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### aesthestics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Define aesthetics (**aes**), by **selecting variables** used in the plot and linking them to presentation such as plotting size, shape color, etc. You can interpret this as: **how** the variable will influence the plotted objects/geometries:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The most important `aes` are: `x`, `y`, `alpha`, `color`, `colour`, `fill`, `linetype`, `shape`, `size` and `stroke`" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Q1q1bNWfOnKh9o0ePVk1NzZceDgAA4FJ1O24OHTqk22677TP3eTwenTx5sttDAQAAdFe34yYzM1P79+//zH01NTXy+XzdHgoAAKC7uh033/rWt7Ro0SK9/vrrkW0Oh0P79u3TihUrVF5e3iMDAgAAXIp+3X3ikiVLVFNTo+LiYg0ePFiSdNttt+nDDz9UaWmpHnnkkR4bEgAAoKu6HTdJSUl65ZVX9Nprr+m1116T3+9Xenq6brzxRpWWlvbkjAAAAF3Wrbhpa2vTmjVrNGnSJN1000266aabenouAACAbunWe26SkpL0ox/9SB999FFPzwMAAPCldPsNxVdffbVqa2t7chYAAIAvrdvvuXn22Wc1a9YsZWVlqbS0VImJiT05FwAAQLd0O25KS0vV2tqqadOmSZJSU1PlcDgi+x0Oh06cOPHlJwQAALgE3Y6befPmRcUMAABAPOh23Cxbtqwn5wAAAOgR3X5DMQAAQDzq9pUbSaqrq9OGDRu0f/9+tba2XrB/27ZtX+blAQAALlm34+YPf/iDrr/+emVnZ+vw4cPKzc3VyZMn9cEHH+iyyy5TTk5OT84JAADQJd2+LfXQQw9p+vTpqq2tlWVZevHFF9XY2Kjf/OY3cjqdWrhwYU/OCQAA0CXdvnLz9ttv6+GHH5bTea6POm9LXX/99Vq0aJEWLFigP/7xjz0zZQ9LTExUUlKS3WP0GZ2fqvN4PLIsy+ZpYDLWGmKFtRbfuh03DodDiYmJcjgcGjx4sBobG1VQUCBJuuKKK+L624vb29vV3t5u9xh9hsvlUmJiolpaWhQKheweBwZjrSFWWGv26OqFiW7flho1apQOHz4sSbr22mv1zDPPqLa2VocOHdJTTz2l4cOHd/elAQAAuq3bV25mz56txsZGSdLy5cv1D//wD8rNzZUkpaSkaMuWLT0zIQAAwCVwWD10s/DUqVPas2ePgsGgCgoKlJWV1RMv2yv8fr/dI/QpLpdLaWlpam5u5vItehVrDbHCWrOH1+vt0nGXdFvqqquuUk1NTdS2TZs26eTJk0pNTdXNN9+s6dOnx3XYAAAAs11S3NTW1ioYDEYeh0Ih3XXXXZH33gAAANjtS//vF/gIHAAAiCf8v6UAAIBRLjluOr+46GLbAAAA7HDJHwUvLi6OfCtxp4kTJ16wzeFw6OOPP/5y0wEAAFyiS4qbRYsW9dYcAAAAPYK4AQAARuENxQAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjNLP7gE6Ojq0Zs0avfPOOzp9+rS8Xq/uuOMO3XDDDZKkhoYGrVq1SvX19crKytLcuXOVm5sbef727du1ZcsWBYNB5eXlqbKyUm6326azAQAAdrP9yk0oFFJ6erqWLVumqqoqzZs3T2vWrFFtba3Onj2rZcuWKT8/X1VVVSorK9Py5ct15swZSdLevXu1efNmLVy4UOvXr1dHR4fWrl1r8xkBAAA72R43ycnJKi8vV1ZWlpxOp6666iqNGjVK+/btU01Njdra2jRt2jQlJCSouLhYmZmZqq6uliTt3LlTkyZN0vDhw+V2u1VeXq7du3erra3N5rMCAAB2sT1uPq21tVUHDx6Uz+dTY2OjfD6fnM5PxszJyVFjY6Okc7escnJyIvt8Pp/C4bCamppiPjcAAIgPtr/n5nyWZem5557TlVdeqXHjxmn//v3yeDxRx3g8HgUCAUnnQuj8/Q6HQ263W8FgMOo5fr9ffr8/8tjpdCojI6MXzwTnc7lcUb8CvYW1hlhhrcW3uIkby7L005/+VCdOnNDSpUvlcDiUkpISCZlOgUBAKSkpks7d0vqi/Z22bt2qdevWRR5XVFSosrKyl84Enyc1NdXuEdBHsNYQK6y1+BQXcWNZltasWaPDhw/rxz/+sZKTkyVJQ4cO1bZt2xQOhyO3purq6lRaWirp3G2ouro6FRUVSTp3m8rpdCo7Ozvq9cvKyiLHSOeu3DQ3N8fi1KBzf7NJTU3VqVOnFAqF7B4HBmOtIVZYa/ZIS0vr0nFxETdr167Ve++9p2XLlkV9jHvMmDFKSEjQyy+/rClTpqi6ulpHjx5Vfn6+JKmkpETPPPOMioqKlJmZqY0bN6qwsFBJSUlRr+/1euX1eiOP/X4/i9EGoVCInztigrWGWGGtxSeHZVmWnQMcO3ZMs2fPVkJCQtS9yxkzZmjmzJmqr6/X6tWrVV9fr8zMTM2dO1ejR4+OHNf5PTeBQEB5eXmaP3/+Rb/n5vz336D3uVwupaWlqbm5mT8E0KtYa4gV1po9zr9Q8UVsjxs7EDexxR8CiBXWGmKFtWaPrsZN3H0UHAAA4MsgbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGKWf3QPYITExUUlJSXaP0Wc4HA5JksfjkWVZNk8Dk7HWECustfjWJ+Omvb1d7e3tdo/RZ7hcLiUmJqqlpUWhUMjucWAw1hpihbVmj65emOC2FAAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjNLP7gEkafv27dq5c6fq6+uVn5+vhx56KLKvoaFBq1atUn19vbKysjR37lzl5uZGPXfLli0KBoPKy8tTZWWl3G63HacBAADiQFxcuUlPT9fMmTM1efLkqO1nz57VsmXLlJ+fr6qqKpWVlWn58uU6c+aMJGnv3r3avHmzFi5cqPXr16ujo0Nr16614xQAAECciIu4KSgo0LXXXqvU1NSo7TU1NWpra9O0adOUkJCg4uJiZWZmqrq6WpK0c+dOTZo0ScOHD5fb7VZ5ebl2796ttrY2O04DAADEgbiIm8/T2Ngon88np/OTMXNyctTY2Cjp3C2rnJycyD6fz6dwOKympqaYzwoAAOJDXLzn5vMEg0F5PJ6obR6PR4FAQJLU2toatd/hcMjtdisYDEY9x+/3y+/3Rx47nU5lZGT04uQ4n8vlivoV6C2sNcQKay2+xXXcpKSkREKmUyAQUEpKiiQpOTn5C/d32rp1q9atWxd5XFFRocrKyl6aGp/n07cdgd7CWkOssNbiU1zHzdChQ7Vt2zaFw+HIram6ujqVlpZKOncbqq6uTkVFRZLO3aZyOp3Kzs6Oep2ysrLIMdK5KzfNzc0xOgu4XC6lpqbq1KlTCoVCdo8Dg7HWECusNXukpaV16bi4iJtQKKRQKKRwOKxwOKz29nY5nU6NGTNGCQkJevnllzVlyhRVV1fr6NGjys/PlySVlJTomWeeUVFRkTIzM7Vx40YVFhYqKSkp6vW9Xq+8Xm/ksd/vZzHaoPO/M9DbWGuIFdZafHJYlmXZPcSmTZu0efPmqG0lJSV68MEHVV9fr9WrV6u+vl6ZmZmaO3euRo8eHTmu83tuAoGA8vLyNH/+/It+z835779B73O5XEpLS1NzczN/CKBXsdYQK6w1e5x/oeKLxEXcxBpxE1v8IYBYYa0hVlhr9uhq3MT1R8EBAAAuFXEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACj9LN7ADskJiYqKSnJ7jH6DIfDIUnyeDyyLMvmaWAy1hpihbUW3/pk3LS3t6u9vd3uMfoMl8ulxMREtbS0KBQK2T0ODMZaQ6yw1uzR1QsT3JYCAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBR+tk9wJd15swZPf/88/rjH/+olJQUzZw5U7fccovdYwEAAJt85eNm7dq1CoVCWr9+vY4cOaKFCxfq8ssv19/93d/ZPRoAALDBV/q2VGtrq/bs2aNvf/vbcrvdGjFihEpKSvS///u/do8GAABs8pWOm7/+9a+SpKFDh0a2DR8+XA0NDXaNBAAAbPaVvi3V2tqqlJSUqG0ej0fBYDBqm9/vl9/vjzx2Op3KyMiIyYyQXC5X1K9Ab2GtIVZYa/HtKx03ycnJF4RMS0vLBcGzdetWrVu3LvK4oqJClZWVMZkRn0hNTbV7BPQRrDXECmstPn2l4+ayyy6TJL3//vu64oorJEl1dXXy+XxRx5WVlamoqCjy2Ol0qrm5OXaD9nEul0upqak6deqUQqGQ3ePAYKw1xAprzR5paWldOu4rHTfJycm67rrrtHHjRj3wwAP68MMPtWPHDi1YsCDqOK/XK6/XG3ns9/tZjDYIhUL83BETrDXECmstPn2l40aSvvvd72r16tWqqKiQ2+1WeXm5rr76arvHAgAANvnKx03//v31wx/+0O4xAABAnPhKfxQcAADg04gbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARnFYlmXZPQTM5vf7tXXrVpWVlcnr9do9DgzGWkOssNbiG1du0Ov8fr/WrVsnv99v9ygwHGsNscJai2/EDQAAMApxAwAAjOJavHjxYruHgPlSUlI0YcIEud1uu0eB4VhriBXWWvziDcUAAMAo3JYCAABGIW4AAIBR+tk9AMy2fft27dy5U/X19crPz9dDDz1k90gwUEdHh9asWaN33nlHp0+fltfr1R133KEbbrjB7tFgoNWrV+utt95SMBjUgAEDNHnyZM2cOdPusXAe4ga9Kj09XTNnztTbb7+t06dP2z0ODBUKhZSenq5ly5Zp8ODBqq2t1dKlS5WVlaWvf/3rdo8Hw0ydOlX33XefkpKSdPz4cS1evFjZ2dkqLCy0ezT8f8QNelVBQYEk6fDhw8QNek1ycrLKy8sjj6+66iqNGjVK+/btI27Q44YOHRr12OFwqKmpyaZp8FmIGwDGaW1t1cGDBzVlyhS7R4GhNmzYoO3bt6utrU2DBw9WcXGx3SPhPMQNAKNYlqXnnntOV155pcaNG2f3ODDU3XffrVmzZungwYP6/e9/L4/HY/dIOA+flgJgDMuy9NOf/lQnTpzQggUL5HA47B4JBnM4HLryyivVr18/VVVV2T0OzsOVGwBGsCxLa9as0eHDh/XjH/9YycnJdo+EPiIcDuvIkSN2j4HzcOUGvSoUCqm9vV3hcFjhcFjt7e06e/as3WPBQGvXrtV7772nJUuW8HX46DUtLS3atWuXAoGAwuGw3n33Xb366qsaO3as3aPhPPzvF9CrNm3apM2bN0dtKykp0YMPPmjTRDDRsWPHNHv2bCUkJMjlckW2z5gxg+8fQY8KBAJ6/PHHdejQIYXDYaWnp+vGG2/U9OnTuQ0aR4gbAABgFG5LAQAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQN0Af8a//+q8aOnSoXC6Xbr/99h55zbfffluLFy9WIBDokdf7tGuuuUYrV66MPK6oqJDD4Yj8k52dralTp6qmpuaSXnfYsGGqrKzs6XG/UH19vTwej+rq6mL6+wJ9EXED9OJLEigAAAjBSURBVAG1tbX653/+Z5WXl+uNN97QU0891SOv+/bbb2vJkiW9Ejfbtm1TQ0OD7rvvvqjtw4cP129/+1tVV1frJz/5iWpqanT99dfr6NGjPT5DTxo2bJimT5+uRYsW2T0KYDziBugDamtrJUn33XefCgoK9Ld/+7c2T/TZgsFg5N+fffZZ3XnnnUpJSYk6JiUlRddee63y8/N111136ec//7lOnjypf/u3f4v1uJfsnnvuUVVVlY4dO2b3KIDRiBvAcBUVFZo2bZokacSIEXI4HHr++edVWVmpkSNHyu12a9iwYZozZ44+/vjjC57/85//XOPGjVNycrK8Xq9uueUWNTQ06MUXX9R3vvMdSVJGRoYcDoeGDRsWed6f//xnlZaWqn///kpNTdU3v/lNHTx4MOq1HQ6HnnzyST388MPKyspSRkaGJOnw4cN64403NGPGjIueX15eniRF3e7Zt2+fpk+frvT0dLndbl199dWqqqr63Nf47W9/q6lTpyo7O1sej0djx47VL37xi6hjOjo69NBDD8nn8ykpKUlDhgzRlClTIj+zi+2XpKKiIqWnp2vTpk0XPS8A3dfP7gEA9K5/+Zd/0ciRI/XII49o27ZtGjJkiEaMGKGFCxdq+fLlysjI0Pvvv6/ly5dr2rRp2rlzZ+S5K1as0IIFC3Tvvfdq+fLl6ujo0M6dO3X8+HHdeuuteuyxx7Rs2TL993//twYOHKikpCRJ0vvvv6+JEydq2LBh2rBhg0KhkBYtWqSJEyfqT3/6UyRiJOm5555TQUGBXnjhBbW3t0uSduzYoYSEBF1zzTUXPb/OqMnOzpYkHThwQPn5+briiiu0cuVKZWVl6c9//rMaGxs/9zUaGhp03XXXac6cOUpOTtaePXt07733yrIszZo1S5L0xBNPaM2aNfrJT36i3Nxc+f1+/frXv1ZbW1uX9kuS0+nUtddeq9dee00PPvhgl/77AegGC4DxXnrpJUuSVVdX95n7Ozo6rN27d1uSrPfee8+yLMs6efKk5Xa7rfvvv/9zX3f9+vWWJOv48eNR27/3ve9ZbrfbOnbsWGRbfX29lZCQYC1atCiyTZKVm5trhcPhqOfff//9Vm5u7gW/3913323l5uZaHR0dVnt7u7Vv3z5r4sSJVkJCglVTU2NZlmXdeeedVkZGhvXxxx9/7tw+n8+aN2/eZ+4Lh8NWR0eHdf/991v5+fmR7bfeeqs1ffr0z33Ni+3vtHDhQmvQoEEXPQ5A93FbCuijfvGLX2jcuHHq37+/EhISVFhYKEnav3+/pHO3agKBgO69995Lfu033nhDJSUlUVdofD6fCgoK9MYbb0Qde/PNN8vhcERtO3LkSNRzz/eXv/xFCQkJSkxM1KhRo3To0CFt3LhRo0ePlnTuqs+MGTOUmpra5Xmbm5v1wAMPyOfzKSEhQQkJCfrZz34W+VlI0vjx4/Vf//VfWrx4sd58802Fw+Go17jY/k5er1cnTpxQR0dHl+cDcGmIG6AP+tWvfqVZs2bpG9/4hv793/9dv/vd7/SrX/1KktTa2ipJOnHihKRPbvdciubmZmVlZV2wPSsrSx999FHUtsGDB19wXGtra+QW16eNGDFCb775pt566y399a9/1QcffKA77rgjsv/EiROXPHNFRYWqqqr0gx/8QL/+9a/15ptv6p577on8LCTp0Ucf1cMPP6wNGzboG9/4hrKysrRkyRJZltWl/Z2Sk5Mj5wigdxA3QB/00ksvaezYsVq7dq1uueUW/f3f/73S0tKijhk0aJAkqamp6ZJfPz09XR9++OEF248ePar09PSobZ++atP5/JMnT37maycnJ2vChAnKy8tTdnb2Bc8fNGjQJc3c2tqqV155RY899pjmz5+vkpISTZgw4YIrL0lJSVq8eLHq6up04MABzZ49W4sXL458Suti+zs1NzcrMTFRAwYM6PKMAC4NcQP0QcFgUImJiVHbNm7cGPU4Pz9fbrdb69ev/9zX6XyNT1+FKCws1I4dOyJXf6RzbzKurq7WxIkTLzrfyJEju/1ldzfeeKO2bNmi06dPd+n4trY2hUKhqJ/H6dOn9R//8R+f+5yvfe1revzxx5Wenq59+/Zd0v66urq4/Sg+YAo+LQX0QTfddJPmzZunpUuXqqCgQK+++qp27NgRdczAgQO1aNEiPfzwwwqFQrr99tsVDoe1a9cufetb39KECRM0atQoSdLzzz+v22+/XW63W2PGjNH3vvc9rV+/XpMnT9ajjz4a+bRUenq65s2bd9H5rrvuOi1dulQffPCBLr/88ks6t0WLFmn79u0qLCzUggULNGTIEL377rsKBAJasGDBBccPHDhQ11xzjZ588kllZGSoX79+evLJJzVw4MCo76O5/fbblZeXp3Hjxsnj8eg///M/9dFHH6mkpKRL+zu9+eabXQo8AF+C3e9oBtD7Pv1pqbNnz1rf//73rYyMDGvAgAHWjBkzrN/97neWJOull16Keu4LL7xgjRkzxkpMTLQGDRpk3XbbbVZDQ0Nk/+LFi63LL7/ccjqdls/ni2z/05/+ZE2ePNlyu91W//79rSlTplj79++Pem1J1ooVKy6Yt62tzfJ6vdbPfvazqO2dn5a6mL/85S/W1KlTrdTUVMvtdltjx461Nm/eHNn/6U9LHThwwCouLrbcbrd1xRVXWCtWrLAWLVpkeTyeyDFPPfWUNWHCBGvgwIGWx+Oxxo8fb23atKnL+y3Lso4cOWI5nU5rx44dFz0HAN3nsKxPvdsNAOLA97//fe3duzfqe3e+6lauXKmVK1fqwIEDn/leIwA9g7gBEJeOHj2qESNGaPfu3Ro3bpzd43xpoVBII0eO1MKFCyNfDAigd/CGYgBxKSsrSy+++KKOHz9u9yg9oqmpSffcc4++/e1v2z0KYDyu3AAAAKNw5QYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABglP8HRNLNtuH2ctUAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare')))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### geometry" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Still nothing plotted yet, as we have to define what kind of [**geometry**](http://plotnine.readthedocs.io/en/stable/api.html#geoms) will be used for the plot. The easiest is probably using points:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare'))\n", + " + p9.geom_point()\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "EXERCISE:\n", + "\n", + "
    \n", + "
  • Starting from the code of the last figure, adapt the code in such a way that the Sex variable defines the color of the points in the graph.
    • \n", + "
  • As both sex categories overlap, use an alternative geometry, so called geom_jitter
    • \n", + "
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare', color='Sex'))\n", + " + p9.geom_jitter()\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These are the basic elements to have a graph, but other elements can be added to the graph:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### labels" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Change the [**labels**](http://plotnine.readthedocs.io/en/stable/api.html#Labels):" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare'))\n", + " + p9.geom_point()\n", + " + p9.xlab(\"Cabin class\")\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### facets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Use the power of `groupby` and define [**facets**](http://plotnine.readthedocs.io/en/stable/api.html#facets) to group the plot by a grouping variable:" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare'))\n", + " + p9.geom_point()\n", + " + p9.xlab(\"Cabin class\")\n", + " + p9.facet_wrap('Sex')#, dir='v')\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### scales" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Defining [**scale**](http://plotnine.readthedocs.io/en/stable/api.html#scales) for colors, axes,...\n", + "\n", + "For example, a log-version of the y-axis could support the interpretation of the lower numbers:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/stijnvanhoey/miniconda3/envs/DS-python-data-analysis/lib/python3.7/site-packages/pandas/core/series.py:856: RuntimeWarning: divide by zero encountered in log10\n", + " result = getattr(ufunc, method)(*inputs, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare'))\n", + " + p9.geom_point() \n", + " + p9.xlab(\"Cabin class\")\n", + " + p9.facet_wrap('Sex')\n", + " + p9.scale_y_log10()\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### theme" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Changing [**theme** ](http://plotnine.readthedocs.io/en/stable/api.html#themes):" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/stijnvanhoey/miniconda3/envs/DS-python-data-analysis/lib/python3.7/site-packages/pandas/core/series.py:856: RuntimeWarning: divide by zero encountered in log10\n", + " result = getattr(ufunc, method)(*inputs, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare'))\n", + " + p9.geom_point() \n", + " + p9.xlab(\"Cabin class\")\n", + " + p9.facet_wrap('Sex')\n", + " + p9.scale_y_log10()\n", + " + p9.theme_bw()\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "or changing specific [theming elements](http://plotnine.readthedocs.io/en/stable/api.html#Themeables), e.g. text size:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/stijnvanhoey/miniconda3/envs/DS-python-data-analysis/lib/python3.7/site-packages/pandas/core/series.py:856: RuntimeWarning: divide by zero encountered in log10\n", + " result = getattr(ufunc, method)(*inputs, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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Da75oqxFC+TIdrzmjrUbMiMetRu7F49LwLFG+TMNjvqS01ci9eHwvWKJ8mY7HnNFWI2bE21Yj9+J1aXhWKF+m4TVfUtpqRIvX94IVypfpeM0ZbTViRjxuP6DF69LwrFC+TMNrvqS01YgWr+8FK5Qv0/GaM9pqhBBCCCGkhahAIoQQQghphAokQgghhJBGqEAihBBCCGmECiRCCCGEkEaoQCKEEEIIaYQKJEIIIYSQRqhAIoQQQghphAokQgghhJBGaCXtFqDNaq0H5cs0vOaLNqsllC/T8Zoz2qzWjGizWutC+TINj/mizWoJQPlqCR5zRpvVmhFtVms9KF+m4TVftFktoXyZjtec0Wa1ZkQbWFoPypdpeM0XbVZLKF+m4zVntFktIYQQQkgLUYFECCGEENIIFUiEEEIIIY1QgUQIIYQQ0ggVSIQQQgghjYiyi626uhpbtmzBX3/9hRs3bqC6uhpubm4ICAjAuHHjMHjwYIMZ8xUVFdi0aRNSUlJQXV0Nb29vREZGYvLkybC1tTX4HUqlEr/88guOHj2KkpISuLi4oH///nj++eebvUYCIYQQQqRJlFeQqqqqkJCQAAcHBwwaNAgTJ05Ev379kJubi88//xz//ve/9Z5fUVGBefPmISEhAcHBwZgwYQLc3d2xZcsWLF261GABK7VajSVLlmDLli1wcXHBhAkT0KNHDyQmJmLevHmoqKiw5J9LCCGEEJER5RUkX19fxMXFQaFQ6I3X1tZi/vz5OHToECZMmICOHTsCADZs2ICSkhK88soriIqKAnB3CfRVq1YhKSkJSUlJGD16tO51kpKScO7cOQwdOhTz5s3TXY1KSEjA6tWrsWHDBrz99tsW+msJIYQQIjaivIKkUCgMiiMAcHJyQt++fQEABQUFAO4WTcePH4efnx/Gjh2re65MJsOMGTMgl8tx6NAhvdfR/jxz5ky9W3WjR49GUFAQjh8/jtra2jb/uwghhBDCB1EWSMbU19fjwoULkMlkuqtHWVlZUCqV6NOnj8G8JC8vL3Tq1AmXL19GfX297jUuX76MgIAA+Pj4GPyOPn36QKlUIisry/x/ECGEEEJESZS32LSqq6uxZ88eaDQa3Lx5EykpKSgtLUV0dDQ6dOgA4P9dSfL39xd8DX9/f1y9ehVFRUXo2LEjioqKoFardf99Y9rxwsJChIaGmuGvIoQQQojYibpAqqmpwdatW3U/29jYYNasWZg4caLecwDA2dlZ8DWcnJwAQHfLTPt87bix52ufRwghhBDrI+oCydfXF3v27EFDQwNKS0tx7Ngx/PTTT7h48SLee+89wXlK5lRYWIjCwkIAd3cD1hZRjbvkxEwbK08xs0T5Mo1U86VdKoSnv0uq74W5UL5MJ/WcibpA0lIoFPD19cWUKVMgl8uxYcMGHDx4EFFRUborR8au+GivHGmvDGmfb2wStnZc6IrU2rVrERsbq/s5OjoaAFBUVNSSP4up4uJi1iFwhfJlGqnla9asWQDoXLcGlC/TSTVnXBRI9woNDcWGDRuQnp6OqKgovTlDQgoLCyGXy+Hn5wcA8PPzg1wu181daqypOU0xMTGYMGECgLtXkBISEnSvyQu1Wo3i4mL4+PhALudqjj4TlC/T8Jqv+xU+69evx6xZs+hclzDKl+l4zVlzv+hwVyCVl5cDgO72WnBwMGxtbZGamgqNRqPXyVZeXo5r166hW7dusLOzAwDY2dmha9euyMrK0r2x90pNTYWtrS2Cg4MNfre/v7+ucCooKEBycjIAcHVgaMnlci7jZoXyZRqp5UupVAKgc90aUL5MJ9WcifIvunLliuAts1u3bmHjxo0AoFsPycnJCRERESgqKsL+/ft1z9VoNNi4cSPUajXGjBmj9zqPPfYYAODHH3+ERqPRjSckJCAvLw8RERFGJ3ETQgghRPpEeQUpMTERhw8fRkhICLy9veHg4ICSkhKkpKTg9u3bGDJkCIYPH657/syZM5GWloa1a9fi/Pnz6NChAzIzM3Hx4kWEhoZi5MiReq8/YsQIHDt2DMeOHcONGzcQEhKCoqIiJCcno3379njhhRcs/BcTQgghRExEWSCFh4ejtrYWWVlZyMjIQF1dHVxcXNCjRw+MGDECw4YN07uV5uXlhRUrVug2qz19+jS8vb0xbdo0TJ482eDSn0KhwOLFi/HLL7/gyJEj2L17N1xcXDBy5MhmbVZbWFiItLQ0qNVq2NjY6F2FEjuNRqOLmae4WaF8mYbXfNnYCH8Uas91R0dHOtcljvJlOl5zZux8N3iemeNokZ49e6Jnz54m/TdeXl6YM2dOs59va2uL6OhoXSeaKbTdbNOnT4enpydUKpXJr2FppaWlGDx4MG7cuAFXV1fs2bMH/fr1Yx0WFzw9PaFWqyXbytrWeMyXsS9F2nN98eLF3JzrwN24//3vf0OlUmHixIn47LPPWIfEBR6PXdZ4zNn9LoJoibJAEruYmBgMHjwYJ06cQEVFBby9vVmH1KSqqiq9lcPv3LmDwYMHIzk5GWFhYQwjEz+1Wo2ysjK0a9dOkpMQ2xqv+SopKREc157rqampXJzrALB48WK9gmjFihW4dOkS9uzZwzAq8eP12GWJ15wZO98bowKpBfz9/aHRaJCcnAyVSmWwB5zYREZGCo4//vjjqKystGwwnJHJZLr3WOzvsxjwmi9jV4Z4O9cB4PPPPzcY27dvH0pKSgT3nyR38XrsssRrzpp7JZifko+0WF5enuB4dXW1hSMhhJibsVsdly5dsnAkhPCNriC1AG+TtIOCglBWVmYw7uLiIvrYWeN1EiIrvOZLSpO07ezsUF9fbzDeu3dvLuJnhddjlyVec8b1JG2x422S9uHDhwXnTuzbt0/0sYsBj5MQWeIxX1KapL148WJ8+OGHemOTJk2Ck5MTF/GzxOOxyxqPOaNJ2mbE2yRt7Yrf91IoFDh58iTCw8MZRMQPXichssJrvqQ0STs+Ph4ymUzvG/2hQ4egVqt1OwoQQ7weuyzxmjOapG1GvE3czMjIgIODA+7cuaMba2hoQHp6uuhjZ43XSYis8JovKU3SzsrKMrjdUV1djYKCAnTp0oVRVOLH67HLEq85o0naRMff3x8NDQ16Y3Z2dnqt/4QQaWjfvr3BmFwu5+LqFyFiQgWSFXj22WfRs2dP3eV1GxsbeHh44O2332YcGSGkra1evVrvG71cLscnn3wCFxcXxpERwhcqkKyAg4MD9u7dC3d3d9jY2MDR0RGbN2+Gr68v69AIIW1sypQpWLNmDbp3744uXbpg/vz5WLRoEeuwCOEOzUFqAd7a/G/evIkuXbrobrPdunULjz76KM6ePYs+ffowjk7ceG1jZYXXfEmpzf/gwYN4/fXXdRO1ly1bhsDAQLz++uusQxM1Xo9dlnjNGbX5mxFvbf5TpkwxmIMEABMmTMCVK1cYRMQXHttYWeIxX1Jq83/55ZcNzve3334b06dPh5OTE6Oo+MDjscsajzmjNn8z4q3N/9q1a4LjFRUVza6krRWvbays8JovKbX55+fnG4ypVCqUlZXBzc2NQUR84PXYZYnXnFGbvxnx1vrbs2dP/P333wbjvr6+oo+dNV7bWFnhNV9SavM3xtHRkev4zY3XY5clXnNGbf5E5+eff4atra3B+JEjRxhEQwgxJ2Pf5IW2HyGEGEcFkhVQKBQGt9JkMhkUCgWjiAgh5tKrVy+DMQ8PDwQEBDCIhhB+UYFkBaZMmYLbt2/rjWk0GkRGRrIJiBBiNhUVFQZj1dXVUCqVDKIhhF80B6kFeGvzT09PFxwvLCwUfeys8drGygqv+ZJSm39BQYHBmEqlQmFhIW010gRej12WeM0ZtfmbEW9t/oGBgYKTtHmIXQx4bGNlicd8SanNPyAgALm5uXr/YNna2qJ9+/ZcxM8Sj8cuazzmjNr8zYi3Nv+dO3eiXbt2Bgfwzp07qc3/PnhtY2WF13xJqc3/+++/x9ixY3ULRapUKnz77bdwdXVlHZqo8XrsssRrzqjN34x4a/318PBAfn4+RowYgfz8fLi5uWHnzp3o378/69BEj9c2VlZ4zZeU2vxHjRqFM2fOIC4uDpWVlZgyZQpGjhzJOizR4/XYZYnXnDX3SioVSFbCz88PFy9ehFqtRlFREfz8/FiHRAgxk5CQEPTq1YvOdUJagZ9rYoQQQgghFkIFEiGEEEJII3SLrQV4a/O/F69tmaxQvkzDa76k1Oavxet7wQrly3S85oza/M2Itzb/xnhsy2SJ8mUaHvMlpTb/e/H4XrBE+TIdjzmjNn8z4q3N/168tmWyQvkyDa/5klKbvxav7wUrlC/T8ZozavM3Ix5bf7V4bctkhfJlGl7zJaU2fy1e3wtWKF+m4zVnzb0SzE/JRwghhBBiIVQgEUIIIYQ0QgUSIYQQQkgjNAfJihw9ehS///47AgICMGvWLNbhEEIIIaJFBZKVGD9+PH799Vfdz8uXL0dmZiZXnQeEEEKIpVCB1AK8LRT57bff6hVHAJCVlYVZs2Zhw4YNbILiBK8LobHCa75ooUhC+TIdrzmjhSLNiLeFIvft2yc4fvz4cdHHLgY8LoTGEo/5ooUiCUD5agkec0YLRZoRbwtFenl5CY67ubk1u5K2VrwuhMYKr/mihSIJ5ct0vOaMFoo0I94Wj/vkk0+wdetWgwr/s88+E33srPG6EBorvOZLagtF1tTU4Pjx4yguLsbjjz/OVWHHCq/HLku85qy5V4KpQLICDz74IEJDQ3HmzBndmJeXFx599FGGURFCzCEnJwdDhw5Ffn4+ZDIZnJyckJCQgLCwMNahEcIVfq6JkRb717/+pVccAUB5eTmeeeYZRhERQszlySefxPXr16HRaKBWq1FdXY3HHnuMu/lThLBGBZIVWL58ueD43r17LRwJIcTcLly4YDB28+ZNXLlyhUE0hPCLCiQrUFtbKzje0NBg4UgIIazcvn2bdQiEcIUKJCvg7+8vOG5vb2/hSAgh5ubu7i44/uCDD1o4EkL4RgWSFejcubPgePv27S0bCCHE7H744QeDjqKlS5fCxcWFUUSE8Im62FqAt5W0nZ2dBcddXV1FHztrvK4Uywqv+ZLSStpPPfUUkpKS8OOPP+LWrVt4+umn8cwzz3ARO0u8Hrss8ZozWknbjHhbSfvNN9/Ezp07DcZjYmJEH7sY8LhSLEs85ktqK2mHh4cjPDxc9zMvcbPG47HLGo85o5W0zYi3lbQjIyMRGxuLjz76SDc2ZcoUzJkzh2FUfOB1pVhWeM2X1FbSjo+Px9q1a1FTU4Po6GjMmTOHq/eDBV6PXZZ4zRmtpG1GvK2uW1BQoFccAcD27dtx7NgxDBs2jFFUfOB1pVhWeM2XlFbSXrduHWJiYnS3PFJSUnDt2jWsXLmScWTixuuxyxKvOWvuFVV+Sj7SYlOmTBEcnzRpkoUjIYSY2z/+8Q+9+SBqtRqrVq3CzZs3GUZFCH+oQLICaWlpguPl5eUWjoQQYm63bt0SHM/NzbVwJITwjQokK2Csi625M/kJIfwwdqvDwcHBwpEQwjcqkKzAhx9+KDhu7NYbIYRfvXr1MhhzdXU1uh4aIUQYFUhW4LXXXsPEiRP1xnr06IGNGzcyiogQYi6//PILfH19oVAooFAo4OjoiL1798LW1pZ1aIRwhe6xWImdO3fi9OnTyMzMhJOTEyZNmgSFQsE6LEJIG+vWrRsuXbqEhIQElJSUYPz48QgKCmIdFiHcoStIVqSurg7Xr19HTU0NVy2ZhBDTyOVyFBcXo7i4mKsVjgkRE7qCZCWefPJJ7NmzR/fzsmXLkJ6eztXiXoSQ+0tJScGQIUOgVCoBALGxsdi8eTOmTp3KODJC+EIFUgvwthfbmjVr9IojALh48SJefPFF/PDDD4yi4gOvew2xwmu+pLQX2+jRo3XFEXD3PXn++ecxceJE6mRrAq/HLku85oz2YjMj3vZi27t3r+D477//LvrYxYDHvYZY4jFfUtqLTWhBSLVajT///BNDhgxhEBE/eDx2WeMxZ7QXmxnxthebh4eH4LibmxuthXQfvO41xAqv+ZLSXmwymUzw23xQUBCd703g9dhlidec0V5sZsTb/kxLlizB1q1bDcY//R04g0sAACAASURBVPRT0cfOGq97DbHCa76ktBfbqFGjkJCQoDcWGBiIBx54gFFEfOD12GWJ15zRXmxE5+DBg4Lj27dvt3AkhBBzu3PnjsFYfX09F7cHCRETKpCsQHx8vOD4oUOHLBwJIcTcTpw4YTBWXFyM/Px8BtEQwi8qkKxATk6O4HhFRYVlAyGEmJ2xbiKhyduEEONEOQfpyJEjyMzMRHZ2NnJycqBSqTB37lyMGjVK8PkVFRXYtGkTUlJSUF1dDW9vb0RGRmLy5MmCy+srlUr88ssvOHr0KEpKSuDi4oL+/fvj+eefb/bsdp44OTkJjtOETUKsR2lpKesQCOGKKP+F3Lx5M4qLi+Hm5gYvLy8UFxcbfW5FRQXmzZuH0tJShIWFISAgAJmZmdiyZQsuXbqEDz/8UG92vVqtxpIlS3Du3Dl069YNgwcPRmFhIRITE5GamooVK1ZIrkjq0KEDLl68aDDu6urKIBpCCAv+/v6sQyCEK6IskN544w106NABPj4+2L59e5Obqm7YsAElJSV45ZVXEBUVBeDuJeZVq1YhKSkJSUlJGD16tO75SUlJOHfuHIYOHYp58+bpZt4nJCRg9erV2LBhA95++23z/oEWZmwfpg4dOlg4EkIIK8auJBNChIlyDlKfPn3g4+Nz3+fV1tbi+PHj8PPzw9ixY3XjMpkMM2bMgFwuN5iIrP155syZem2Jo0ePRlBQEI4fP47a2to2+kvEoWfPnoJrVPTs2ZNBNIQQc7KzsxMcp82pCTGNKAuk5srKyoJSqUSfPn0M1mDw8vJCp06dcPnyZdTX1wO42+p6+fJlBAQECBZgffr0gVKpRFZWlkXit5QxY8YY5Ecul2PixImMIiKEmMu4ceP05l4qFAr06NGDrhgTYiKuC6SCggIAxu+t+/v7Q61Wo6ioCABQVFQEtVpt9INCO15YWGiGaNnp3bs34uLidPswyeVyLF26FJMmTWIcGSGkrf3www+IiIjQ/fzQQw/h119/5WqlY0LEQJRzkJqrpqYGAODs7Cz4uPaeu/aWmfb5xu7Fa8e1z2ussLBQVzyVlJTonsfDHjSTJ09GVFQUcnNzIZfL8eCDD3IRN2vaHFGumkeq+dJekeHh73Jzc8Phw4eRn5+PoqIi9OnTBzY2NlzEzpJUj11zknrOuC6QLE27caVWdHQ0AOiuUPHA3d0dAJrsDCSGKF+mkVq+Zs2aBYCvc93GxgaBgYHU3m8iqR27liDVnHFdIGmvHBm74qO9cqS9MqR9vrFJ2NpxY1ekYmJiMGHCBAB3ryBp9zvy8/NrSfhMqFQqlJaWwsfHhy65N4NarUZxcTHlq5l4zdf9Cp/169dj1qxZXJ3rvL4XrFC+TMdrzpr7RYfrAul+c4YKCwshl8t1H2p+fn6Qy+W6uUuNNWdOk/axgoICJCcnAwAXB8b69esRExMDpVIJuVyOefPm4YsvvmAdFjfkcjkX77NYSC1fSqUSAB/nemNSey/MjfJlOqnmjOu/KDg4GLa2tkhNTTVYXr+8vBzXrl1Dt27ddG2vdnZ26Nq1K/Lz8wUvCaampsLW1hbBwcEWid9STpw4gdmzZ+s+5NVqNZYtW4Y1a9YwjowQYg4ajQY5OTm4cuUKbVJLSAtxXSA5OTkhIiICRUVF2L9/v25co9Fg48aNUKvVGDNmjN5/89hjjwEAfvzxR72iKiEhAXl5eYiIiJDcgmpffvml4Pg333xj4UgIIeZWUVGBsLAwPPjggxg6dCgeeughZGdnsw6LEO6I8hbboUOHkJmZCQC4du2abiwtLQ0AMGjQIAwaNAjA3QUf09LSsHbtWpw/fx4dOnRAZmYmLl68iNDQUIwcOVLvtUeMGIFjx47h2LFjuHHjBkJCQlBUVITk5GS0b98eL7zwwn3jKywsRFpaGtRqNWxsbIxuDikWxiZplpeXiz521jQaje49plzdH6/5MrYvofZcd3R05OJcB+6ug3T69Gndz3l5eRgyZAgKCgokeRukrfB67LLEa86auw+pKAukzMxMJCUl6Y1dvHhRt5+Yj4+PrkDy8vLCihUrdJvVnj59Gt7e3pg2bRomT55s8IGgUCiwePFi/PLLLzhy5Ah2794NFxcXjBw5stmb1Wq72aZPnw5PT0/RX8KuqqoSHK+urhZ97GLg6ekJtVot2VbWtsZjvoyd99pzffHixVyc6wB0cyPvVVxcjKysLHTt2pVBRPzg8dhljcecNXe/VVEWSG+99RbeeuutZj/fy8sLc+bMafbzbW1tER0drWvTN1VMTAwGDx6MEydOoKKiAt7e3i16HUu5ceOG4Hh9fX2zK2lrpVarUVZWhnbt2tG372bgNV8lJSWC49pzPTU1lYtzvSlpaWno0aMH6zBEi9djlyVec2bsfG+M/nVsAX9/f2g0GiQnJ0OlUhls4yE2Hh4egp1+tra2oo+dNZlMpnuPKVf3x2u+jF0Z4u1cb0pAQADX8Zsbr8cuS7zmrLlXgvkp+UiL8XTgEkJax83NzWBMJpNhwIABDKIhhF9UIFmBuro6wXGeJtURQppn7969Bl+K1qxZA3t7e0YREcInusXWArx1sbm6ugqOy+Vy0cfOGq9dGqzwmi8pdbGtWrXKIM6vvvoKL730ElfzRCyN12OXJV5zxnUXm9jx1sVmbOXwO3fuiD52MeCxS4MlHvMlpS62nTt3GoxlZWUhNzcXgYGBDCLiB4/HLms85ozrLjax462Lzdjecw0NDdTFdh+8dmmwwmu+pNTFZuybfH5+Pjp37mzZYDjC67HLEq85oy42M+Kts8XLywvV1dUG4wqFQvSxs8ZrlwYrvObLGrrYbGxsuI7f3Hg9dlniNWfUxUZ0jK2kzcPtAkJI25DaFkqEmBsVSFbA2C02Qoj12L17N+sQCOEKFUiEEGIFgoODWYdACFdoDlIL8Nbmb2dnh/r6esHHxB47a7y2sbLCa76k1OZvTFlZGdfxm9uMGTPwxx9/YOjQofjhhx9Yh8MFqZ3vBs8zcxySxFubf6dOnfDXX38ZjDs6Ooo+djHgsY2VJR7zJaU2f2OGDh3KdfzmolQq4erqqjtes7OzsWnTJpqa0ExSOt8bowKpBXhr8x8xYoRggfTwww9Tm/998NrGygqv+ZJSm//QoUNx7NgxvTFfX1/06tWLUUTi1rVrV4N/3FUqFR5++GFcunSJUVR8kNr53hj969gCvLX+vvrqq/juu+8MxufPny/62FnjtY2VFV7zJaU2/6SkJPTu3RuZmZkAAG9vb2RmZnIROwvXr18XHL969Srl7D6kdr43xk/JR1rsxo0bguPZ2dkWjoRIWVFREYYNG4bw8HA8/fTTaGhoYB2SVYqNjcXly5d1P9+8eRMvvvgiw4jEzdbW1qRxctebb74JX19fhIaGSnbOFhVIVuA///mP4PiGDRssGwiRrKtXr6JDhw44ceIEcnJysGPHDnh4eFCRxMDq1av1viHX19dj165dRtdDs3b//Oc/Bce//vprC0fCj5CQEHzzzTcoLS1FcXEx/u///g9z585lHVabowLJCuTk5AiOFxUVWTYQIlmRkZEGXSzV1dV44YUX2ARkxerq6gTHb9++beFI+PDWW2/h/fff1xtbsmQJZs+ezSgicbtw4QLS09MNxlevXs0gGvOiOUgtwFubv7FLxQqFQvSxs8ZrG6ulFRcXC46fO3eOi7xJqc1/1KhROHz4MJRKJYC753nnzp3RoUMHLuJn4bPPPsOSJUv0JhxTroRt377d6GO85Iza/M2Ixzb/06dPG4x36NBB9LGLAY9trJbm7u6OO3fuGIx37NiRi2NMSm3+b775Jg4cOKD7uaGhAa+//jodw81A5/r9jRo1Cp9++qngYzycHwC1+ZsVb23+ERERglV/SEgItfkboVar8fTTT+PgwYPQaDQYP3484uLiuGpltaRt27YhMjJSb0yhUGDbtm1cHGNSavN/6623DL7JL1q0CK+++irs7e0ZRSV+vLasW9qwYcPQrl07lJWV6Y2PGTOGi3MdoDZ/s+Kt9be2tha2tra6S+5atLu3ccOGDcPJkyd1P//8888oKytDYmIiw6jEa/jw4Th+/Diio6NRUVGBjh074vjx43B1dWUdWrNIqc0/OzvboEC6ffs2CgsL0aVLF0ZRiR+vLesslJaWIiwsDOfOnYNcLseMGTMEl5IRq+Ze6aICyQoEBQUZjNnZ2QmOE+DOnTt6xZFWUlIS1Go1fbs0Ijw8HNeuXUNRURH8/PwoT4z4+voiPz9fb0wul8PHx4dRRESKTp06BbVarTvfpYg+wazAM888g759+8LOzg7A3UnbPj4+eOeddxhHJk7GJhwDQFVVlQUjIcR0ISEhBmOdO3eGk5MTg2gI4RddQbICdnZ2OHr0KFatWoXMzEx4enpi0aJFaNeuHevQRKljx46wsbExuAxrZ2cHDw8PRlER0jxHjx41GLty5Qpu3Lgh2W/6hJgDFUhWwsHBAe+9957ukigVR02Lj4/H5MmTdXM55HI5du7cyTgqQu5PqJsQAG2+SoiJqECyEiqVChs2bEBmZibc3NzwzjvvwM3NjXVYovXUU08hJycHGzduRE1NDV599VV07NiRdViEtFhRUREeeOAB1mEQwg0qkFqAt4UiGxoaEBUVpbv0LpPJEBcXh9OnT3PTZcRCUFAQFixYoGv9Ffv7LAa8LqwppYUijampqeE6fnPj9dhlidecMVkosqqqCjU1NfD392/LlxUd3haKjI+PR2Jiot7iZ9nZ2VixYgU++OADhpHxgRaPMw2P+ZLSQpF2dnaor683GO/fvz8X8bPE47HLGo85s9hCkbdu3cLHH3+MuLg43LhxQ7eWBAD8+eefWLJkCWJjYxEaGtraXyUavC0Uefr0aYODt6GhAUePHkVsbCyjqPhAi8eZhtd8SWmhyK1bt2LSpEl6Y59++ik1GNwHr8cuS9u2bYOzszOioqK4yplFFoqsqKhAeHg4Ll26hEceeQQeHh7IysrSPR4SEoKjR49i06ZNkiqQeFs8Ljk5WXA8IyND9LGzRovHmYbXfElpocg//vjDYOzEiRNcxM4Sr8cuC2+99RZWrVqlN3bs2DFEREQwisg0zb2S2qqSLzY2FpcuXcJPP/2E1NRUPPPMM3qPOzo6IjIyEklJSa35NaSVCgoKBMerq6stHAkhxNxWrFhhMHbgwAHcuHGDQTREaqqqqgyKIwAYOnQog2jMq1UF0q5duzBu3Dg899xzACBYdXfq1AnXr19vza8hraRQKATH6VsSIdJjbC5IRkaGhSMhUjRnzhzWIVhMqwqkwsJC9OrVq8nnODg40JUKxhwdHQXHjRVOhBDpcXBwYB0CkQDtjgzWoFUFkpeX132vDl2+fJlWb2XMWCHEy87LhJDWc3FxYR0CkQChW7hS1aoCadiwYdizZw8KCwsFH7906RL279+P0aNHt+bXkFYKDAwUHHd3d7dwJIQQc7O1tRUc79mzp4UjIVLk5uaGpUuXGoxL8RZuqy4hLFy4ELt370ZERAT++c9/ory8HADw119/4eTJk1iwYAFsbW0xb968NglWLHhbKNLY1gN1dXWij501XhdCY4XXfElpoUilUik4np6ejt69e1s4Gn7weuyysGDBAixYsAC5ublQKpXo0qUL5HI5N3mzyEKRvXv3RlxcHGbOnImpU6cCuHuQde/eHRqNBs7Ozti6dSuCg4Nb82tEh7eFIs+fPy84XlJSIvrYxYDHhdBY4jFfUloo0piff/75vnNGrR2Pxy5LHTp0AADucmaxhSKfeuopREREYMOGDTh16hTKy8vh5uaGsLAwzJ49G76+vq39FaLD20KRt2/fFhzXfmMixtHicabhNV9SWijSmL///pvO9ybweuyyxGvOLLJQpJa3tzfmz5/fFi/FBd4Wj/Pw8BBcA8XGxkb0sbNGi8eZhtd8SWmhSGOefPJJruM3N16PXZZ4zZlFFoq0t7fH9OnTW/MSxAK0tz8be+SRRywcCSGElb59+7IOgRCutKpAcnJyQkBAQFvFQszE2FIMdXV1Fo6EEMJKUVER6xAI4UqrCqSBAwfiwoULbRULMRNjc5CEdvwmpDUyMzOxb98+o9vbEHaCgoJYh0AkpLS0FB999BHWrVvHdfNCU1pVIH300UdITEzE5s2b2yoeYgbTpk0THI+KirJwJESq1Go1hgwZgpCQEMTExCAoKAhz585lHZZVEmrld3d3R5cuXRhEQ6QoNjYW3t7eWLJkCT7++GPY29vj+PHjrMNqc62apH306FGMGDECM2bMwDfffIMBAwbA19fXYLKWTCbDggULWhUoablp06bh2LFj+M9//qMbGz58OFauXMkwKiIlr732GpKTk/XGVq9ejWHDhmHy5MmMorJOtbW1BmN1dXVQKpWwt7dnEBGRksrKSnz88ccG48OHD0dDQ4PlAzKjVhVIixcv1v3/U6dO4dSpU4LPowKJvTVr1mDhwoX4448/4Ofnh/DwcNYhEQnZv3+/4HhcXBwVSBZ29epVg7E7d+6goKCAriKRVlu3bp3gOE/rIDVXqwqkw4cPt1UcxAKCgoIQEBBAkzVJmzN2ZcLZ2dnCkRBfX1/k5+frjSkUCvj4+DCKiEgJz2uBmapVBdKoUaPaKg6u8LbVyL1oOX3TUL6aZ968eYiJidEbk8lkmD9/Phd5k9JWI99++y2eeuopyGQyXbzLli2Dk5MTF/GzQud68zz33HOYPXu2QY7c3d25yZtFthqxVrxtNdIYLadvGsrX/c2aNQtFRUVYsmQJlEolXFxcsHnzZgQHB3Nxfkhpq5GxY8fi6NGj2LJlC+rr6zFu3Dg88cQTXMTOGp3rzXP69GmEhYXp5hx5eHggNzeXm2PMYluNaBUWFqKgoMDo2jpDhgxpq1/FHG9bjdyL16XhWaF8Nd8HH3yARYsWcZkvqW01MmTIELRv3x4lJSUYMGAAbTHSDHSuN1/fvn2hVCq5zZnFthr57bffMH/+fFy6dKnJ50lpdjvP2w/wujQ8K5Qv0/CaLyltNVJWVoaoqCj8+eefAIBOnTrh0KFD6NatG+PIxI3XY5clXnNmka1Gfv/9dzz55JOoqKjAK6+8Ao1Gg4iICMyePRvBwcHQaDSIiorCwoULW/NrCLG4+vp6PProo3BwcEDnzp0xbtw4bi4fE+s2c+ZMnDt3Tvfz9evXERUVRbeNmpCZmYkxY8YgLCwMjz/+OC5fvsw6JCICrSqQPv/8czg5OeHMmTP497//DeDuxO1169YhIyMDsbGxOHLkCJ5++uk2CZYQSxk8eDASEhKgVCqhVCpx4MABDBs2jHVYhNyX9rjVamhoQHZ2tkFnG7nr2rVrGDRoEI4ePYrr16/jyJEjGDhwIOWLtK5AOnXqFCZOnAh/f3/dmPZbikwmwwcffIBHHnkEH3zwQeuiJMSCamtrcfbsWYNx7W0WQsTM2JILjo6OFo6ED+vXr0ddXZ1uGohKpcKdO3ewceNGxpER1lpVINXW1iIwMFD3s729PW7duqX3HO1kZsKWRqPBrl27sHjxYsTHx+t9wyT6ysvLjT5WXV1twUj4Ulpaig8//BD/+Mc/sHLlStrrj5HnnnvOYCwiIgLt27dnEI34VVVVGdx+1Gg0Bv+WEX3du3eHjY0NOnbsiGeffZZ1OGbRqknafn5+erPBAwICkJmZqfeciooK+tbNmEajwciRI3H06FHd2KpVq3Dx4kU4ODiwC0ykAgMDYWdnZ/APvIODAzw8PBhFJW7FxcUIDQ1FaWkplEolduzYgb179+Lw4cPUQWVhSUlJBmNnz56FUqmEra0tg4jEbejQoVi1apXemEqlQkREBKOIxM/Z2Vm3pU1DQwO2b9+OgQMH6hoDpKJVV5AeeeQRpKen634ePnw4EhMTsX37dtTV1SExMRHbtm1DSEhIqwMlLffNN9/oFUcAkJOTg1deeYVNQBxovOghAMyZM4dBJHxYvnw5SkpKUF9fD41Gg/r6ehw/fhy7du1iHZrVycrKMhirra3FlStXGEQjfk888YTBiu+urq54/PHHGUUkbvv37xfc7+/06dMMojGvVhVITzzxBFJSUnDt2jUAwKJFi+Dk5IRnn30WTk5OGDNmDJRKJT799NM2CZa0zIEDBwTH6danMLVarWs6uNe//vUvBtHwIScnx+C2rY2NDfLy8hhFRBoztkadtXv55ZcNbqfdvHkTc+fOZRSRuP3666+sQ7CYVhVIL730Eurr69GpUycAwAMPPIA///wTL730EkaOHIlZs2YhOTkZkZGRbREraSFjq4a6urpaOBI+5OXlCbZENzQ0NDk/yZr17NkTdnZ2emNKpRLBwcGMIrJexhbsCwgIsHAkfLh3SYR7SfGKSFt4/vnnWYdgMW0+OaBbt25Yu3ZtW78saYUPPvgAcXFxBv/ox8bGMopI3O7tymyM5iAJmz9/Pnbu3IlLly5BLpejoaEB0dHRGDt2LOvQyP+vqqoK7dq1Yx2G6BjbxNfX19fCkfBh0KBBCAgIMFgGYcqUKYwiMh+TCySFQoGPP/5Yr3X/1KlTOHXqlNXM0eBts9pu3bohMTERkydPRnl5ORwdHfH1119j/Pjxoo+dBVtbWzz55JPYvXu33vizzz6rtwEo+X+cnZ3xxx9/YPPmzcjOzkb//v0xadIkAOAiX1LarDYwMBC5ubl6YzY2NvDx8eEifkt7/fXXcejQIYPxOXPmUL6MyMvLw6RJk3Do0CHIZDIsXLgQCxYs4CZfZtusVmin4wMHDuCTTz6xmgKJx81qw8PDUVRUBLVarbsEz0PcrPz8889455138PPPP0Mmk2Hq1Kn44osvKGdNsLW1xQsvvKD7mafthaS0We23336LJ598EnK5HBqNBg0NDfjyyy9hZ2fHRfyW9sYbbwiOx8TE4OLFixaOhh/x8fF6P/N0bFl8s1prQpvVWofVq1dj5cqVlC8T8Hp8SWmz2pEjR8LZ2RlVVVUA7n5bHj9+PC23YERpaang+I0bNyhn9yG1870xevdbgMcNLLV43VyQFcqXaXjNl5Q2q/X399cVR8Ddv+2hhx7i6oqeJXl6euL27dsG4+3atePi/WZJaud7Y/yUfIQQUTt8+DD8/Pzw4IMP4qGHHqK9rBi5efOmwZharcbhw4cZRCN+27dvFxzfsWOHhSPhh0ajQVxcHJ5//nn84x//kOySMVQgEUJa7eDBgxgzZgxKSkpw584dXL16FR07dhT8x5qwcf78edYhiNLgwYPx22+/wdnZGTKZDK6urkhMTETfvn1ZhyZan3zyCaZPn464uDjEx8cjMjJSkusjtegW26ZNm/DHH3/ofv77778BAFFRUYLPl8lkkkweIeSuGTNmGIyp1WpER0dj//79DCIijYWGhrIOQbTGjh2LqqoqFBUVwc/Pj6v5NJZWUVGB2NhYXbOWdvmYN998E+PGjWMZWptrUYH0999/64qiexlbsZmne5OEAHfvUY8fPx5HjhwBAIwZMwY7d+6kSZtG3Dvn5V7Xr1+3cCTEmA4dOrAOQbQuXbqEuXPnIisrCz169MDq1avRtWtX1mGJ0o0bNwTb+W/cuMEgGvMy+dP+6tWr5oiDEFEZNGgQzpw5o/t53759GD58uGTvtbeWn58fcnJyDMYHDBhg+WCIIJ7asC0pNzcXAwcORG1tLRoaGpCfn4+wsDCkp6dTUSkgKCgIjo6OehPbFQoFunfvzjAq8zC5QNJuKyIm1dXV2LJlC/766y/cuHED1dXVcHNzQ0BAAMaNG4fBgwcbXMWqqKjApk2bkJKSgurqanh7eyMyMhKTJ0+mHa+tXG1trV5xpHXy5EmoVCq6iiTg+PHj6Nixo95q7R4eHli3bh3DqMi9aGshYT/88APq6up0XX4qlQq1tbXYuHEj3n//fcbRiY+zszN++uknREdHw8bGBmq1Gs7Ozvjxxx9Zh9bmJHGjtaqqCgkJCXBwcMCgQYMwceJE9OvXD7m5ufj8888NNh6tqKjAvHnzkJCQgODgYEyYMAHu7u7YsmULli5dKrgPF7EexcXFRh9rvKkluSsgIACFhYXo1KkTHBwcEBYWhtLSUigUCtahWR0XFxeDMZlMBj8/PwbRiF9VVZXBZ75Go6EGgyZMnjwZP/30Ex5++GH07dsXCQkJePjhh1mH1eYk8VXY19cXcXFxBh/GtbW1mD9/Pg4dOoQJEyagY8eOAIANGzagpKQEr7zyim5iuUajwapVq5CUlISkpCSMHj3a4n+HOanVamzfvh2ZmZlwdXXFa6+9BkdHR9ZhiVJTq6w6ODhYMBJ+1NbW6u1dderUKbi5uaGmpoZhVNbpzp07BmMajQaFhYXo0qULg4jELSIiAqtWrdIbU6lUiIiIYBSR+L3++uv49ttvdT/369cPu3fvxoQJExhG1fYkcQVJoVAIflN1cnLStWoWFBQAuPtBfvz4cfj5+eltpCmTyTBjxgzI5XLBfXl4plar8cwzz+C5557D559/jgULFiA8PBy1tbWsQxMlNzc3wRWTAwMDqag0on379gZjtbW1GDFiBINorJuxY5Q2qhX21FNPYd68eQCg615btGiR5Dqy2kpxcbFecaQ1ceJEBtGYlyQKJGPq6+tx4cIFyGQy3dWjrKwsKJVK9OnTx2BekpeXFzp16oTLly+jvr6eRchmsWvXLuzevRsqlQp1dXVQKpXIyMjAypUrWYcmSjKZDIcOHYKbm5tuzMPDw2iXJoHgSsTA3blJxLKM3QamqQPCZDIZPv/8c6xfvx4vvvgifvzxR8TGxrIOS7R++OEHwXFeNqo1hSRusWlVV1djz549uvvHKSkpKC0tRXR0tK4bQXslyd/fX/A1/P39cfXqVRQVFemKKt5lZWUZjNXX19NGjE3Izs7W+4emqqoKOTk56NWrF8Oo+ENzkMQjLi4Or776KuswREetVuO5555DfHw8bG1t8f332qcFsAAAIABJREFU3yMxMREbNmygJWoEiLFRy1wkdQWppqYGW7duxbZt23DgwAFUVlZi1qxZmDp1qt5zgLsz8YU4OTkBgKRuPymVSsEWX2Nr11g7jUaD6OhovW9EarUakyZNYhiVuBlr8V24cKGFIyHGJCUlsQ5BlH766Sds374darUadXV1UKvV2LJlC7Zt28Y6NFF69tlnBQtHHjZyNpWkriD5+vpiz549aGhoQGlpKY4dO4affvoJFy9exHvvvdfqb7OFhYUoLCwEcHc3YG2xJfZL17a2tpDJZAaXQJ2cnEQfOwt5eXmCBWV9fT3Ky8vh4eHBICpxS09Ph5ubm94Xi5CQECxevFgSx5h26Q+e/xZ3d3eu4zeXs2fPGnw2ymQynD17Fs888wyjqMTttddeM+gO37p1q+SOL0kVSFoKhQK+vr6YMmUK5HI5NmzYgIMHDyIqKkp35chYd432A157Jelea9eu1bs3HR0dDQAoKipq6z+hTWk0Gsjlcr3dvGUyGZycnEQfOwtNLahXU1Mj2CVk7X755RfU1dXpjWVmZuLo0aOSWEBu1qxZAMR/rjeFzndhd+7c0ftsBO5eda+rq6N8CaisrDQojgDg0UcfRV5eHoOIzEeSBdK9QkNDsWHDBqSnpyMqKko3F0l7JaixwsJCyOVywTVDYmJidG2MJSUlSEhIAADRry/Sv39/gw8AjUaDbt26iT52FpqaoO/v70/7NAk4efKkwTFma2uLjIwMREZGsgnKBPf7h3D9+vWYNWsW1+fLO++8w3X85iK0bhRwd2FNypehn376SXBcrVZzk6/mFr6SL5DKy8sB/L/JosHBwbC1tUVqaio0Go3evdTy8nJcu3YN3bp1g52dncFr+fv76yZ3FxQUIDk5GQBE/w/mhQsXYGtrC6VSqTeelZUl+thZaJynezU0NNBK2gKEWsvr6urg4OAgiWNMe0zw8LcInevA3aUYeIifBblcrnd7SKFQQK1WU74E3LveWWNSy5ck/porV64I3jK7desWNm7cCAC69ZCcnJwQERGBoqIivV3GNRoNNm7cCLVajTFjxlgmcAsS+sCkvZmEubq6Ci4I6ezsDHt7ewYRid/Zs2cNxjQaDfLz8xlEY92MFfglJSUWjoQPgYGBBnNnGhoaaFFNI6S43pExkvgqnJiYiMOHDyMkJATe3t5wcHBASUkJUlJScPv2bQwZMgTDhw/XPX/mzJlIS0vD2rVrcf78eXTo0AGZmZm4ePEiQkNDMXLkyCZ/X2FhIdLS0qBWq2FjY8Pt+g9qtZrb2M2ptrZWcJ5RTU0NlEolXUES8NdffwmO79q1Cx999JGFozGdsfdUe647Ojpyfa4Dd5sPOnfuzDoM0dm7d6/g+M6dO/HSSy9ZOBrx2717t9HHeDk/mvsZLolPeu2q0FlZWcjIyEBdXR1cXFzQo0cPjBgxAsOGDdO7lebl5YUVK1boNqs9ffo0vL29MW3aNEyePPm+lwm1k7WnT58OT09P0V+Jqa+vh52dncHcGplMJvrYWWjqm3ZlZSV1sQkw9oHj6OjIxTFmbHsZ7bm+ePFiLs71pqSmpmLw4MGswxAdY/NRCwoKuH6/zaWprZh4yVdTf8O9JFEg9ezZEz179jTpv/Hy8sKcOXNa9PtiYmIwePBgnDhxAhUVFaJf/6FXr16CE48ffPBBuhoioKmJhp6enrT4oYA33ngDn332mcH48uXLuTjGjBXF2nM9NTWVi3O9KdOmTePivbA0Y5O03dzcKF8CoqKiBOe58fTvSXNvN/Px14iMv78/NBoNkpOToVKpRL/aalpamuC4dhsWoq+pb0E0SVvY0qVLUVxcjP/+978A7k5y/e9//8vNhp/G3nPezvWmLFiwAOvWrWMdhui4uroKjvv5+XH9fpuLjY0NsrKy0KdPH91iw127dkV6ejo3+WrulS5JTNImTdu1a5fg+NGjRy0bCCdKS0uNPmZszzFytwFC+wEpk8loY1+RMfY5YO2OHDkiOP7zzz9bOBJ++Pn5Yfr06QgMDETnzp3x2muv6RZTlRIqkKxAWVmZ4Dj9Yy/svffeM/rY+vXrLRgJP5YsWYLVq1frJmmqVCpER0fjzJkzjCMjWqNGjWIdApGIadOmYd26dbh+/TpycnIwf/58fPnll6zDanN0r6AFeOti69atG3JycgzGfXx8RB87C2+99Rbi4+MFH5s9ezblTMCKFSsEx+fOnYtjx45ZOBrTWUMX29SpU7mOnwXKl6GCggKDq5EqlQrLli3DO++8wygq01hVF5ul8dbFtnDhQhw6dMhgfP78+aKPnYX+/fsbfczJyYlyJsDY6uNVVVVc5MsautgGDBjAdfzm0qtXL2RkZBiMDx48mPIl4ObNm4LjtbW13OTLqrrYLI23LrZhw4bh+++/xyuvvAKlUgm5XI53330Xr7/+OuvQRKuiosLgJKqoqKAJ2kaEhITgzz//NBiPjo7mImdS6mJbuHChQUdhVFSUbhcAoi8tLQ2+vr56x0BgYCBOnDjBMCrxeuihh+Dg4GCwVlz37t25ONcB6mIzKx47W2bPno3Zs2dDpVKhuLiYOjTuY/Xq1VAoFLr9xRQKBb777ju8++67jCMTJ2MTNO3t7bk4zqTUxfbpp5/CyckJa9asQX19PSZNmoSvvvqKi9hZKCoqgkajgY2NDVQqla6FvbS0lIuC2NKqqqoEF9JNSUnh5hijLjYiSGp75ZiDSqXCp59+qrf5akNDAz766COak2CE0FYjgPGNLYn5yOVyLFq0CLm5uUhNTcW3335LHYVN+O9//6t3K1ipVKKyshIbNmxgG5hILV++nHUIFkP/WhLSSE1NjeA3jDt37qCuro5BROJnrHCkgpKIXVlZmcFebBqNxmj3r7VrarNaqaFbbC3AWxfbvbSXkjUaDVdxW5KrqytkMplBfmQyGezt7SlvApydnQUvu3fs2JGLfEmxi43O9ebp37+/QX4aGhoExwmaXPyVl3xRF5sZ8dbF1pinpyfUarXBtyZyV2lpqeCJrtFoUF1dDQcHBwZRiZuzs7PgN24HBwcuzg+pdrHRuX5/Tz/9NI4cOYLvv/9et2dlTEwMJkyYwN37bQmVlZVGH+MlX9TFZka8dbHdS61Wo6ysDO3ataP5SEbk5eUZfay0tJR2RBcQFBSE3Nxcg/EBAwZw0dkipS42LTrXm2/dunV48cUXkZ6ejt69e2PAgAGsQxKt3r17C44rFAouznWAutjMisfOFi2ZTKaLmae4LWngwIFGH+vSpYsFI+GHsaIyNTWVi+NMSl1sWnSumyYsLAydOnWiDt/7qKioEBy3sbHhJm/UxUZIKyxcuNBgbMmSJQwi4YOxCa2XL1+2cCSEEHNq37694LiLi4uFIzE/KpAIEbB06VLMnTsXTk5OcHBwwLvvvotFixaxDku02rVrJzjeo0cPC0dCiOlu3ryJoUOHYsCAARg+fDiqq6tZh8QdXiZom4JusREiIDo6Gtu2bdP9vGzZMpSUlOCHH35gGJV4hYeHC85BmjRpEoNoCGm+8vJyeHt76yayFxQUwMPDA5WVlZK8KtJapaWlguNSLCqpQGoBavOXtoaGBr3iSGv9+vX4/vvvGUQkfgcPHhQcX716NSZOnGjhaExHbf7Wa/To0QZdfg0NDXj00Udx8uRJRlGJl7FFR5VKJTfHGbX5mxG1+Utbamqq0ceuXbuGgIAAC0bDB2PfHgsLC7k4P6jN33oJXfkEgJycHO7eb0sw1gGm0Wi4yRe1+ZsRtflL2yOPPGL0scDAQCgUCgtGwwdjOfH09OSi9Zfa/K2Xr6+vYJOBv78/F8eupTW1iS8v+aI2fzOi1l9ps7e3x+jRo5GQkKA3Pn78eG4+ACzN2LHU0NDAxXFGbf7Wa//+/ejcubPe7SGZTIbffvuN8iYgJyfH6GO85Iva/AlphWnTpjVrjNxlbF6Ch4eHhSMhxDQdO3ZEdnY2goOD4e7uju7duyMvLw9+fn6sQxMlf39/1iFYDBVIhDSiVqvx0ksvGYzPmDGDQTR8GDZsmOD4//3f/1k4EkJM16VLF2RmZiIzMxMZGRk0z7AJffr0YR2CxVCBREgjeXl5gpNaVSoVysvLGUQkfo1vR2p9/fXXFo6EENNlZ2djyJAh6NevHyIiIoxO3CbAyJEjBeccSnGXAZpQQUgjTV1CpltGwmpqagTH//rrLwtHQohpcnNz0b17d928lKKiIjz00EPIzc2l22wCbGxs4O/vj+vXr+uN9+/fn1FE5kMFUgvQOkjSJpfLIZfLDa4iab81Ud4MOTo6ChZJAQEBXOSL1kGyXjExMQaTdpVKJV599VXs2LGDUVTilZ6eblAcAcAvv/zCzXFG6yCZEa2DJG2VlZWCuWloaEB1dbXRCcnWLC4uDhMmTDAYP3z4MBfnB62DZL0KCwsFx/Pz87l7vy3BWBebWq3mJl+0DpIZ0TpI0tauXTt4e3ujtLRU941ILpfD398frq6ujKMTp/r6esHxqqoqLm5L0jpI1iskJATnz583GO/Tpw8t6yHAWEOG9iorD2gdJDOitVGkTSaTIT4+HmPHjtXdnrCxscG2bdsoZ0a89dZbguPvvvuu4LYtYkPrIFmv77//HgcPHtT7R9Pf3x/ffvst5U2AsfmGarWam3w190oXFUiECIiMjERGRgb279+PqqoqPPvss3jggQdYhyVaQisRA8ClS5csHAkhprGzs0NBQQEWLlyI8+fPo1+/fvjkk0/+v/buPSyqcv0b+HdghsMoiKAcBAVJpEJNzZQ8IIKRlpnpFtPLPGRempWaB9K2Xdt2uq90e6jUNDM1NVO3mrlt5wHPppWHUBQ8pJJ5QAREgQFmYNb7hy/za06wBp1Zs2a+n3+KZ80wNzfzjDdrred+ZHM2xNGszemKigoHR2J/fAcQWREdHY0333wTubm5XM1SCy8vL5SVlZmNy+mSFLkvpVKJjz/+2DDXeUnSuoiICIvjrlhQ8l1ARA/tySeftDj+7LPPOjgSIrKnFi1aIDY21mhMoVBg6NChEkVkPyyQiOihxcTEWBw3/SAlInnz8PDAgQMHEB8fD+BBcTRs2DAsW7ZM4sgePdc7J0ZEDpeRkWFx/Pjx4y75lyWROwsNDcXBgwexdOlS+Pv7Y/jw4S55WZIFUh2wUaR7+P7777Fx40ZotVoMHz4cL730ktQhOS1rN2nn5OTI4n3GRpHEfIk3depUzJ8/3/D166+/jp9++kk2l9TZKNKO2CjS9S1btgzjx483fL1161Z88cUXGDlypIRROa/y8nKL49VLzZ0dG0USwHyJUVhYaFQcVevSpYvVfmjOho0i7YiNIl1bVVUVJk2aZDY+fvx4vPHGG7Lp9eFI9+7dszienZ0ti9UtbBRJzJc4f//7360ek8NcB9go0q7YPM613b9/3+KZgoqKCpSXl0OtVksQlXOzdmbl+vXrsnifsVEkMV/iXLx40eoxueRN7JlglslENpDLB4CzqKqqkjoEolpVVVUhLS0NgwYNwvTp03mJrQbu1DCXZ5CITDRs2BD16tUza6kfEBDAjWptxAKJnJ1Op0NgYCBKSkoAAEeOHMHy5cuRn58PT09PiaNzPu40p3kGiciEQqHA+vXr4enpCaVSafjvt99+K3VossN/YMjZ9e7d21AcVSsqKsIrr7wiUUTOrXnz5lKH4DAskIgsePHFFzF69Gj4+/vD398fY8eORUpKitRhOa169epZHH/66acdHAmRbc6cOWNx/MSJEw6ORB46duwodQgOwwKJyILJkyfjq6++QmFhIe7evYtly5Zh+vTpUofltNq1a2dxnDkjZ+fj42NxnIsxLOvRo4fUITgM70GqAzaKdG06nQ6LFi0yulGzsrISCxcuxL/+9S8uAbbgyJEjFscHDBhgtUeSM2GjSPeVmJiItWvXmo337NmTebNgwYIFVo/JJV9sFGlHbBTp2oqLiy3mRqfTQaPRWP2Lk8xptVpZzA82inRfAQEBZmMKhQL+/v6y+307wp49e6wek0u+2CjSjtgo0rUFBgaiYcOGuHv3rtF448aNUb9+fYmikqd69erJonkcG0W6L9MbtIEHZ0LKyspk8d51tNGjR+Pw4cMWj8klX2wUaUdsHufaKisrzYojAMjPzwfAXkiWrFy5Eq+//rrZOBtFSodzXZzz589bHD979izzZkHnzp0tjnt6esomX2wUSVRHN27csDguCILFwomA1NRUswZygwYNQoMGDSSKiEicvLw8m8bdXWRkpNlc9/DwQGpqqkQR2Q8LJCITNV1G8ff3d2Ak8jFv3jxcv37daGzz5s3YtWuXRBERiVNYWGhxXOxlGHejVCqxa9cutGjRwjCWlJSEZcuWSRiVfbBAIjJRU6dYd+oia4uzZ8+a7eStUqmQnZ0tUURE4lhbZenl5eXgSOSjRYsWOH/+PH7//XecPHkSO3fudMk/HlkgEZnw8/Ozeszb29uBkchHs2bNoFKpjMYqKysRHh4uUURE4pSVlVkct3apnR7w9PRE8+bNERoaKpt7j2zFAonIxMSJE60eW7VqlQMjkY+0tDQEBAQYPigVCgU6deqE/v37SxwZEdnD+fPnsXTpUmzYsMFl79digURk4qWXXrJ67LnnnnNgJPIhCAIKCgoMjeIEQUB2drZslv0SkXjbtm1D69atMWXKFEyfPh1xcXEueTmdBRKRiZr2DwsKCnJgJPLRuXNns2aEhYWFGD16tEQREZE9aDQaDBkyBJWVlSgvL4dWq8X9+/cxbNgwqUN75FggEZmo6T4j3rhp2Z9//mlxPD093cGRENnmr6ux/iouLs7BkcjDtWvXzO7bqqysRFZWlkQR2Q/Pf9cB92Jzbbdv37Z6rKioCIGBgQ6MRh6sdWr29vaWxfuMe7G5L9PVl9UqKiqYNwsaN24MhUJhlpvg4GDZ5It7sdkR92JzbTX1QfLz85Pd79sRnnvuOfzwww9m4+PHj5dFvrgXm/tq27Ytrl27ZjbeoUMH2f2+HcHf3x/Tpk3D3LlzUVVVZejUPn/+fNnki3ux2RH3YnNtlvZmqlZZWQlfX18HRiMPn332Gfbu3WvUU6Zly5YYMWKELG7U5l5s7mvx4sXYsWOHURHp6emJBQsWyOK9K4VZs2YhNjYWO3bsgEKhwNixY9GjRw+pwxKNe7HZEfdncm0BAQGIiIjAzZs3DR+aHh4eaN68OdRqtcTROafo6GicPXsWaWlpuHTpEjp37oy5c+fKJl/ci8197d+/3+wMW1VVFY4dO8Y2FVYoFAqkpqYiLi4OxcXF6Nq1q6zeY9yLjaiOFAoFvvvuO/j5+UGlUkGpVKJBgwbYsmWL1KE5LUEQ8PHHH2Pr1q3IzMzE8uXLsXnzZqnDIqrVhAkTLI6PGTPGwZHIR2ZmJiIiIvDMM88gKSkJTz/9NAoKCqQO65FjgURkQYcOHXDx4kWsXbsWS5Yswfnz5/HUU09JHZbT+ve//40VK1YYvhYEAaNGjcKJEyckjIqodhUVFRbHrW1B4u50Oh0SEhKM9rDLzMzEK6+8ImFU9sECiciK4OBgDBw4EH369EGjRo2kDsepzZ071+L4+++/7+BIiGzTsmVLi+OtW7d2cCTycPbsWRQVFZmNHzlyRIJo7Msl7kHav38/srKycPnyZeTk5KCyshITJkxAcnKyxcffvXsX69atw4kTJ1BSUoLGjRsjMTERAwYMMNtPiohqZ20/K1fdgoBcx4kTJ1C/fn2jM0lqtRpHjx6VMCrndf/+fYvjclnibwuXOIP0zTffYNeuXcjLy6u1R83du3cxZcoUpKenIzY2Fn379kWDBg2wfv16zJ49m8thySAhIQFKpRIRERHo2bOn1OE4tejoaIvj3bt3d3AkRLZRKpXYuXOn0dhPP/0kUTTOr23bthZvyJbTCk+xXKJAevvtt7FixQqsW7cOvXr1qvGxq1evxp07dzBmzBi8//77GD58OD7++GMkJSXh1KlT2Ldvn4OiJmcWFBSEw4cPG5rs7d+/HyEhIVKH5bRWrlxpNqZQKKxeeiNyFj/88IPZEvV27dohIyNDooicW4MGDbBw4UKjMU9PT5dcxOISBVLbtm0RHBxc6+M0Gg2OHDmC0NBQ9O7d2zCuUCgwbNgweHh4YPfu3fYMlWSgvLzc6AbEarxcZN3w4cPNxgRBQFpamgTREInXp08fi+Pt2rVzcCTyMWHCBGzbtg2pqakYOHAgjh8/jm7dukkd1iPnEvcgiXXhwgXodDqLpwgDAwMRGRmJixcvQqvVcs8tN7Z8+XKrx/bu3Wv13jZ3lpOTY3F8//79jg2EiOzul19+wciRI3Hv3j0IgoDMzEzs27cPYWFhUof2SLnEGSSxbt68CQBWf4lhYWHQ6/XIzc11ZFjkZGralbpLly4OjEQ+rDWEFHNml4jkQ6vV4qWXXkJRURH0ej0EQcDly5cxYsQIqUN75NyqQCotLQUA1KtXz+Lx6g95jUbjsJjI+QQEBFhczejt7Q0fHx8JInJ+1u41WrZsmYMjIbLNu+++a3F8zpw5Do5EHnJycnDnzh2jVWs6nY7L/N3drVu3cOvWLQAP9nKpLrjktPKtOlY5xSyF8vJyhISEID8/HwAQGhqKGzduMG9WWLt3LyMjw+oKNzmpLpjl9PvnXBdn3rx5KC8vx9KlSw1j06ZNw5QpU5g7C2raPsjV8uVWBVL1maPqwsZU9Zkja2+A6p29q7366qsAIMtLcrzhuHanT582+lqOv2dHsbatyOTJk9G5c2cHR/PojRw5EoA83wOc67WbMWMGZsyYYTQmx9+1I1TfqmLKFW9PcasCqUmTJgBgOAtk6tatW/Dw8EBoaKjF42PGjEHfvn0BPDiDlJ6eDgBWH++M9Ho98vLyEBwczB2+RWC+xKmqqrI4XlJSIov5UdsH+6pVqzBy5EhZ/CzV+N61DfMljrWmsBUVFbKZH2ILObcqkGJjY6FSqZCRkQFBEIxWshUWFuKPP/5Ay5Ytra5gCwsLM9zgffPmTRw7dgwAZDmZPDw8ZBm3VJivmikUCouddNVqtUvkTafTAeBcdwfMV82+//57i+OCILhc3lzrp6mFWq1G165dkZubix9//NEwLggC1qxZA71ej5SUFAkjJJInpdLy31q+vr4OjoSI7KmmNiiuxiXOIO3evRtZWVkAgD/++MMwlpmZCQCIj49HfHw8gAcN7TIzM/HFF1/g9OnTaNKkCbKyspCdnY127dohKSlJmh+CSMYCAgJw584ds/HY2FgJoiEie+natSsuXLggdRgO4RIFUlZWltkWIdnZ2cjOzgbwoBdLdYEUGBiIefPmGTarPX78OBo3bowhQ4ZgwIABok4R3rp1C5mZmdDr9VAqlbLapE8QBEPMcopbKsyXOH369MGqVavMxgcOHCiLvFk7A1Y91319fTnXXRzzJc7jjz9u9Zhc8mZtvps9zs5xOMTEiRMxceJE0Y8PDAzE+PHj6/x61avZXnvtNTRs2BCVlZV1/l5SaNiwIfR6vcstybQX5qt248aNw+rVq40+IOvVq4eXX35ZFvOjYcOGFser5/qMGTM4190A81W7Zs2aWT0ml/lhbb6bcokCydHGjBmDZ599Fj/99BPu3r0rq12M9Xo9CgoKEBQU5HI31NkD8yXOmjVrzP56LC0txc6dO5GamipRVOJZujwI/N9cz8jI4Fx3ccyXOH5+flaPiT0zIzVr892UPH4aJxMWFgZBEHDs2DFUVlaa7evmzBQKhSFmOcUtFeZLnPXr11scX7t2LQYNGuTgaGxn7S9fznX3wXyJU1Nu5JI3sWe6WCYT0UO7d++exfHq+wCJyDWMHTtW6hAchgUSET00a93n5dI4jojEqWmrEVfDS2x1wFVs7oP5EmfChAn46KOPzMbnzZsni7xxFRsxX+L06tXL6plhueTNrVaxORpXsbkX5qt2/fr1MyuQvL29ERMTI4v5wVVsBDBfYgQGBlo9Jpf5wVVsdsRVbO6D+RJn8ODBZmMVFRWYOXMmFi1aJEFEtuEqNmK+xMnPz7d6jKvYiCtb3AjzJc7Fixctjq9duxaLFy92cDS24yo2Yr7E+fTTT60ek0veuIqNiCR3//59qUMgIqoTFkhEREREJniJrQ64is19MF8PTw554yo2Yr4enlzyxlVsdsRVbO6F+Xo4cpgfXMVGAPP1sOQyP7iKzY64is19MF8PR61Wy2JlC1exEfMlzmuvvYa1a9daPCaHuQ5wFZtdcWWL+2C+xFGr1dBoNGbjnTp1kkXeuIqNmC9xkpOTrRZIcskbV7ERkcOUl5dbHLe2/J+I5Il7sRER2cDaPRtc5k/kWqz9MeSKWCAR0UPz8fGxON6iRQsHR0JE9GiwQCKih3b06FGzMYVCgV9//VWCaIjIXsLCwqQOwWF4k3YdsA+S+2C+xKmqqoKHh4fRpbZGjRqhqKgIQUFBEkYmDvsgEfMlzrBhwzBnzhyLx+SSN/ZBsiP2QXIvzFftli5dajZ27949fPfddxgxYoTjA7IR+yARwHyJ0bNnT6sFklzmB/sg2RH7ILkP5kuc0tJSs39UPDw8oNFoZNEbhX2QiPkSJzw83OK4QqGQxVwH2AfJrtgbxX0wX+L07NkTW7ZsMfoLUqvVIiEhQRZ5Yx8kYr7EadKkicVxOeWNfZCIyGFGjRpl1B9FqVRixYoVaNeunYRREdGjtm3bNovjrnhZkmeQiOihKRQKLFq0CO+++y4yMzMRHx+PkJAQqcMiokesqKhI6hAchmeQiOiRiYqKwjPPPCOre3WISLyXX35Z6hAchgUSERERiWKtk7ZKpXJwJPbHS2x1wD5I7oP5so1c88U+SMR8idOoUSOL49ULGuSAfZDsiH2Q3AvzZRs55ot9kAhgvsRo0KABJk+ejE8++QRVVVWGlWtz586VzfxgHyQ7Yh8k98F82Uau+WIfJGK+xJs7dy4pGTaKAAATeUlEQVRiY2Oxfft2eHh4YNy4cUhJSZE6LNHYB8mO2BvFfTBftpFrvtgHiZgv8RQKBUaPHo1Ro0YhNzcXoaGhssoZ+yARERER1RELJCIiIiITLJCIiIiITLBAIiIiIjLBAomIiIjIBFex1QEbRboP5ss2cs0XG0US82U7ueaMjSLtiI0i3QvzZRs55ouNIglgvupCjjljo0g7YqNI98F82Uau+XLFRpHFxcXIy8tD8+bNZfW7kIpc37tSkmvO2CjSjtg8zn0wX7aRa75cqVFkaWkphg0bhq1btwIAOnbsiG3btiEsLEziyJybXN+7UpJrztgokojIDY0dOxY7duwwfP3bb7+hT58+srpHhMgZsEAiInIhW7duhVarNXyt0+lw6tQp3Lp1S8KoiOSHBRIRkQuxdqlDTveIEDkDzhgiIhcydOhQeHl5Gb5WqVTo1q0bQkJCJIyKSH5YIBERuZBPP/0Uw4YNg0qlgoeHB5KSkvDdd9/J6iZaImfAAomIyIV4e3vjyy+/hEajwdWrV/G///0PQUFBUodFJDsskIiIXJCHh4fojsFEZI6zpw641Yj7YL5sI9d8casRYr5sJ9eccasRO+JWI+6F+bKNHPPFrUYIYL7qQo4541YjdsStRtwH82UbuebLFbcakevvQirMl+3kmjNuNWJHctx+oJpcW8NLhfmyjVzz5UpbjVST6+9CKsyX7eSaM241QkRERFRHLJCIiIiITLBAIiIiIjLBAomIiIhE02q1SEtLw+OPP47k5GR8+eWXslrmLxZv0iYiIiLRhg0bhq1bt0Kn0wEA3nrrLWi1WrzzzjsSR/Zo8QwSERERiZKbm4uNGzcaiiMAqKqqwuzZsyWMyj5YIBEREZEo9+/ftzheWlrq4EjsjwUSERERiRIVFYXg4GCjxpAqlQpdunSRMCr7YIFEREREonh5eWHHjh0ICAgwNIeMjY3F119/LXFkjx5v0q4DblbrPpgv28g1X9yslpgv8Tp06IArV67g1KlTKC8vR2JiInx8fGSTN25Wa0fcrNa9MF+2kWO+uFktAcyXLdRqNbp27Wr4Wk5zg5vV2hE3q3UfzJdt5JovblZLzJft5JozblZrR9zA0n0wX7aRa764WS0xX7aTa864WS0RERFRHbFAIiIiIjLBAomIiIjIBAskIiIiIhMskIiIiIhMsEAiIiIiMsECiYjIBeXn5+P69etShyEbWq0WJ0+ehFarlToU2bh+/TqKioqkDsNuWCAREbmQCxcuwMPDAyEhIejUqRM8PT3xzTffSB2WUwsPD4evry/69u0LX19fREZGSh2SU9u6dSsUCgUiIyMRFxcHHx8f5ObmSh3WI8cCiYjIhTzxxBNme2INHToUOp1OooicW0JCAm7evGk0du3aNfTu3VuiiJxbeXk5BgwYYDSm0+kQFRUlTUB2xE7aDyk/P1/qEOrEFat9e2K+bCO3fImZx3KZ69Y2DJ03bx6GDx/u4Gic35EjRyyO796926xwImDVqlUWxysqKmSTL7FzWSHIZftdJ1NUVIQlS5bI7q+y4uJinDx5Ek8//TT8/PykDsfpMV+2kXO+VCoV3nrrLQQEBBiNc667B+bLdnLOmbX5/lcskB5CUVERNBqN1GHYJDMzE7169cLOnTvRunVrqcNxesyXbeScL7VabfXDknPd9TFftpNzzmqa79V4ie0hBAQE1JpgZ1N96aNx48Zo0qSJxNE4P+bLNq6aL85118d82c7Vc8abtImIiIhMeM6cOXOm1EGQY9WvXx+JiYmyu2YsFebLNsyX8+DvwjbMl+1cOWe8B4mIiIjIBC+xEREREZlggURERERkggUSERERkQku83cD+/fvR1ZWFi5fvoycnBxUVlZiwoQJSE5Oljo0p1NQUIAjR47g5MmTho0Y69evjyeeeAL9+/dHbGys1CE6nZKSEqxfvx6XLl3C7du3UVJSAn9/f4SHh+PFF1/Es88+C4VCIXWYboFz3Tac77Zxt7nOVWxuYPbs2Thz5gwqKyvh5+eH0tJSxMfHIzo6WurQnM5//vMfw8aebdq0wVNPPQVfX1/88ssvSE9PR0REBJo1ayZxlM4lPz8fn3/+OUJDQ/HEE0+gTZs2CAwMRFZWFvbu3YvCwkJ07NhR6jDdAue6bTjfbeNuc52r2NxARkYGmjRpguDgYGzevBlr1qzhX5VWHD16FA0aNEBcXJzR+Llz5/DBBx/A19cXq1evhkqlkihC51NVVQUA8PT0NBrXaDSYOnUq/vzzTyxevJj/0DgA57ptON9t425znfcguYG2bdsiODhY6jBkoXPnzmYflgAQFxeH1q1bo7i4GDk5OY4PzIl5enqafWACD1r5t2/fHgBks4ml3HGu24bz3TbuNtdZIBGJVP3BYOkDgsxptVqcOXMGCoXCZf6iJPfB+S6eq8513qRNJMKdO3dw+vRpNGzYEJGRkVKH45RKSkqwfft2CIKAe/fu4cSJE8jPz8err77qkvs0kevifK+Zu8x1FkhEtaisrMSCBQug0+kwYsQI/kVpRWlpKTZs2GD4WqlUYuTIkejXr5+EURHZhvO9du4y11kgEdVAr9fjs88+w7lz55CSkoIePXpIHZLTCgkJwfbt21FVVYX8/HwcPnwYa9euRXZ2Nt577z3+Q0NOj/NdHHeZ67wHicgKQRCwePFiHDhwAImJiRg3bpzUIcmCp6cnQkJC8Le//Q1Dhw7Fzz//jF27dkkdFlGNON9t5+pznQUSkQXVf0mmp6cjISEBEyZMgIcHp4ut2rVrBwA4e/asxJEQWcf5/vBcca7zHUBkQq/XY9GiRdi7dy+6deuGd99912VOGTtaYWEhAK4EIufF+f5ouOJcZ4FE9Bd//bDs0qULJk2a5FIT3h6uXLmC0tJSs/Hi4mKsWbMGAAw9UoicCee7bdxtrvMmbTewe/duZGVlAQD++OMPw1hmZiYAID4+HvHx8ZLF50w2bNiAvXv3wtfXF+Hh4di4caPZY7h1g7G9e/diz549aN26NRo3bgwfHx/cuXMHJ06cQFlZGTp37ozu3btLHaZb4Fy3Dee7bdxtrrNAcgNZWVnYt2+f0Vh2djays7MBAMHBwfzQ/P/y8vIAAGVlZdi0aZPFx4SEhPAD8y+6dOkCjUaDCxcu4Ny5c6ioqDBs+NmjRw8kJCS41AaWzoxz3Tac77Zxt7nOvdiIiIiITPAeJCIiIiITLJCIiIiITLBAIiIiIjLBAomIiIjIBAskIiIiIhMskIiIiIhMsEAiIiIiMsECiYiIiMgECyQiIiIiEyyQiMgpJCYm2rRNwYEDB6BQKDBz5kz7BSXSiBEjoFAokJOTI3UoRPSIsEAiItFOnjyJUaNGISYmBvXq1YOvry8ee+wxvPbaa9izZ4/U4RERPTLcrJaIaqXX6zFlyhQsXLgQSqUSSUlJ6Nu3L1QqFa5cuYIffvgB69atwz//+U988MEHDompY8eOyM7ORqNGjRzyekTkXlggEVGtZsyYgYULF6Jt27bYvHkzHnvsMaPjZWVlWLx4MQoKChwWk1qtxuOPP+6w1yMi98JLbERUo99//x1z585FUFAQdu7caVYcAYCvry+mTp2KDz/80DB28eJFpKWloX379ggKCoKPjw9atmyJadOmoaSkxOrrlZeXIy0tDU2bNoWPjw9at26NlStXmj3O2j1IUVFRiIqKQmlpKSZNmoTw8HB4e3ujTZs22Lx5s00/uyAI+Prrr5GQkICAgACo1WrExMRg7NixuHbtWo3P1Wq1WLRoEZ5//nk0bdoU3t7eCA4ORv/+/fHbb7+ZPV6v12PFihXo2LEjAgMDoVarERUVhX79+uHQoUNGj92yZQu6d++O4OBg+Pj4oGnTpujVqxe2bdtm089HRNbxDBIR1Wj16tWoqqrCmDFjEBISUuNjvb29Df+/detWfPXVV+jRowcSExOh1+vx888/Y86cOTh48CAOHToElUpl9j0GDhyIM2fOYODAgdDpdNi0aRNGjRqF27dvY/r06aJi1ul0SElJQWFhIfr37w+NRoMNGzYgNTUVO3fuREpKSq3fQxAEDB48GBs3bkR4eDgGDx4Mf39/5OTkYOPGjejVqxeaNWtm9fmFhYWYOHEiunXrhhdeeAENGzbElStXsH37dvz44484dOgQnnnmGcPjp0+fjrlz5+Kxxx7DkCFD4Ofnhxs3buDw4cPYt28fEhISAABLly7FuHHjEBYWhldeeQVBQUG4desWfv31V2zbtg39+vUTlSMiqoVARFSDxMREAYCQnp5u0/OuX78uVFRUmI1/+OGHAgBh3bp1RuPdu3cXAAhPPvmkcP/+fcP4rVu3hLCwMEGpVAqXL182jO/fv18AIPzjH/8w+j6RkZECAOHll182ev309HQBgPD888+Lin/JkiUCACE5OVnQaDRGxzQajVBQUGD4evjw4QIA4erVq4ax8vJy4fr162bf9+zZs0L9+vWFnj17Go0HBgYK4eHhQmlpqdG4Xq83eq327dsLXl5eQl5entn3zs/PF/WzEVHteImNiGqUm5sLAIiIiLDpeeHh4fDy8jIbf/vttwEA6enpFp/397//HX5+foavQ0NDMWnSJFRWVmL9+vWiX3/hwoVGr5+cnIzIyEgcP35c1POXLFkCT09PLF26FL6+vkbHfH19ERgYWOPzvb29ER4ebjYeFxeHHj164NChQ9DpdEbHvLy8oFQan9hXKBRmr6VSqSyefQsKCqoxJiISjwUSEdmFIAhYuXIlEhISEBgYCE9PTygUCsM/4jdv3rT4vG7dulkdy8jIEPXaAQEBaN68udl4REQEioqKan1+aWkpsrKy0Lx5c8TExIh6TUsyMjIwZMgQNGvWDF5eXlAoFFAoFPjvf/8LrVaL/Px8w2NTU1Nx9epVtGrVCh988AHS09NRWlpq9j1TU1NRWlqKVq1aYcqUKdixY4eon4mIbMN7kIioRqGhoTh//jxu3LiB2NhY0c8bP348Fi9ejKZNm6Jv374ICwsz3KP04YcfoqKiwuLzgoODzcaq7326d++eqNdu0KCBxXGlUgm9Xl/r86sLDktngMQ6evQokpKSAAApKSmIiYlB/fr1oVAosG3bNpw+fdooB5999hmio6OxevVqzJo1C7NmzYKPjw9SU1Mxf/58QzuDtLQ0BAUFYdmyZViwYAHmz58PpVKJF154AZ988onFwpCIbMcCiYhq1KVLFxw4cAB79+41/INfm7y8PCxZsgRt2rTBsWPHoFarDcdyc3ONVrtZem7Tpk2Nxm7fvg3AeuHzqFW/zo0bN+r8PWbPno2KigocOXIEXbp0MTr2888/4/Tp00ZjKpUKU6dOxdSpU3Hz5k0cPHgQq1atwpo1a5Cbm4tdu3YBeHDJ7Y033sAbb7yBgoICHD58GN9++y02bdqES5cuITMzE56ennWOm4ge4CU2IqrRiBEj4OnpieXLl+POnTs1Prb6jMiVK1cgCAJ69uxpVBwBwOHDh2v8HpaOV4+1bdvWltDrrH79+njyySdx9epVXLp0qU7f4/LlywgMDDQrjjQaDU6dOlXjc5s0aYLBgwdj586diImJQXp6OsrKysweFxQUhH79+mHjxo1ISkpCdnY2fv/99zrFS0TGWCARUY1atGiBtLQ05Ofno3fv3rh69arZY8rLy7FgwQJDT6LIyEgADy4z/fWS1vXr1zFt2rQaX2/27NkoLi42fH379m0sWLAASqUSQ4YMeQQ/kThvvfUWqqqqMG7cOLPipLy8HIWFhTU+PzIyEnfv3sW5c+cMY1VVVZgyZYpZoVlRUYF9+/ZBEASj8dLSUhQXF0OlUhnOCu3atQuVlZVGj9PpdIZ4TG8oJ6K64SU2IqrVrFmzUF5ejoULFyI2NhZJSUlo1aoVVCoVrl69ivT0dBQUFGDWrFkAgLCwMAwYMABbtmxBhw4dkJycjNu3b2PHjh1ISkrClStXrL5WdHQ0WrVqhQEDBhj6IOXl5WH27NmIjo521I+MN998EwcPHsSmTZsQExODvn37wt/fH9euXcOuXbvw1Vdf1dhz6J133sHu3bvRtWtXpKamwsfHBwcOHMCNGzeQmJiIAwcOGB5bVlaG5ORkREdHo1OnTmjWrBlKSkqwY8cO5Obm4r333jOsyBs0aBDUajW6du2KyMhI6HQ67NmzB1lZWRg0aFCNvZmIyAYStxkgIhk5fvy48PrrrwstWrQQfH19BW9vbyEqKkoYPHiwsHv3bqPHFhcXC5MnTxaioqIEb29vISYmRvjoo48ErVYrABC6d+9u9PjqPkgajUaYMmWKEB4eLnh5eQlxcXHCihUrzGKpqQ9SZGSkxfirX0MsvV4vrFixQoiPjxfq1asnqNVqISYmRhg7dqxw7do1w+Ms9UESBEHYvHmz0L59e0GtVguNGjUSUlNThcuXL5s9XqvVCnPmzBFSUlKEiIgIwcvLSwgJCRG6d+8ubNiwweh7fv7550Lfvn2FyMhIwcfHRwgKChI6deokfPHFF4JOpxP9sxFRzRSCYHJOl4iIiMjN8R4kIiIiIhMskIiIiIhMsEAiIiIiMsECiYiIiMgECyQiIiIiEyyQiIiIiEywQCIiIiIywQKJiIiIyAQLJCIiIiITLJCIiIiITLBAIiIiIjLBAomIiIjIxP8D/8rJlhR8C0IAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic,\n", + " p9.aes(x='factor(Pclass)', y='Fare'))\n", + " + p9.geom_point() \n", + " + p9.xlab(\"Cabin class\")\n", + " + p9.facet_wrap('Sex')\n", + " + p9.scale_y_log10()\n", + " + p9.theme_bw()\n", + " + p9.theme(text=p9.element_text(size=14))\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### more..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* adding [**statistical derivatives**](http://plotnine.readthedocs.io/en/stable/api.html#stats)\n", + "* changing the [**plot coordinate**](http://plotnine.readthedocs.io/en/stable/api.html#coordinates) system" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + " Remember: \n", + "\n", + "
    \n", + "
  • Start with defining your data, aes variables and a geometry
    • \n", + "
  • Further extend your plot with scale_*, theme_*, xlab/ylab, facet_*
    • \n", + "
\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## plotnine is built on top of Matplotlib" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As plotnine is built on top of Matplotlib, we can still retrieve the matplotlib `figure` object from plotnine for eventual customization:" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "myplot = (p9.ggplot(titanic, \n", + " p9.aes(x='factor(Pclass)', y='Fare'))\n", + " + p9.geom_point()\n", + ") " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The trick is to use the `draw()` function in plotnine:" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "my_plt_version = myplot.draw()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "my_plt_version.axes[0].set_title(\"Titanic fare price per cabin class\")\n", + "ax2 = my_plt_version.add_axes([0.5, 0.5, 0.3, 0.3], label=\"ax2\")\n", + "my_plt_version" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + " Remember: \n", + "\n", + "Similar to Pandas handling above, we can set up a matplotlib `Figure` with plotnine. Use `draw()` and the Matplotlib `Figure` is returned.\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (OPTIONAL SECTION) Some more plotnine functionalities to remember..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Histogram**: Getting the univariaite distribution of the `Age`" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic.dropna(subset=['Age']), p9.aes(x='Age'))\n", + " + p9.geom_histogram(bins=30))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "EXERCISE:\n", + "\n", + "
    \n", + "
  • Make a histogram of the age, grouped by the Sex of the passengers
    • \n", + "
  • Make sure both graphs are underneath each other instead of next to each other to enhance comparison
    • \n", + "\n", + "
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic.dropna(subset=['Age']), p9.aes(x='Age'))\n", + " + p9.geom_histogram(bins=30)\n", + " + p9.facet_wrap('Sex', nrow=2)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**boxplot/violin plot**: Getting the univariaite distribution of `Age` per `Sex`" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic.dropna(subset=['Age']), p9.aes(x='Sex', y='Age'))\n", + " + p9.geom_boxplot())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Actually, a *violinplot* provides more inside to the distribution:" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic.dropna(subset=['Age']), p9.aes(x='Sex', y='Age'))\n", + " + p9.geom_violin()\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "EXERCISE:\n", + "\n", + "
    \n", + "
  • Make a violin plot of the Age for each `Sex`
    • \n", + "
  • Add `jitter` to the plot to see the actual data points
    • \n", + "
  • Adjust the transparency of the jitter dots to improve readability
    • \n", + "\n", + "
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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mdXV1YWJiAvF4PAuRkZ2GkhdCCMkxpVIJjuOEZCUajUIsFkOpVAq34TgOPp8P8/Pz8Pl8WamJ4TgOfr8fHo8H4XB4y+NdyvDwMLq6urIyVkdHB3iex9jYWFbGIzsL1bwQQkiOlZaWoq6uDtPT0wAAiUSC1tZWaLVaAMszM6dPn8aHH34IlmWhVqtxxRVXYP/+/ZDJZJt6zHQ6jdHRUczPzwuP2dnZibKysqz8TOcLh8OYmppCd3d3VsZTKpVobm7G0NDQlmtoyM5DyQshhOQYwzBobm6G1WpFMpmEQqGARqMR/n1qagoffvghJBIJ6uvr4fP58OGHH8JgMGy6U63dbsfs7CzKysogFovBsiyGhoag0+kyZnyyZXh4GDKZDK2trVkbs7u7G4ODg1kbj+wctGxECCHbgGEY6PV6WCyWjMQFABwOB3ieh8FggEgkgsFgEL6/WaFQCDKZTKiv0Wg0SCQSiMVim/8hLmJwcBAdHR2QSqVZG3Pv3r0YGRlBOp3O2phkZ6DkhRBC8kylUoHjOKRSKQDLhbw8z0OlUm16TIVCgUQiIXydSCQgEonWnVzwPA+WZeH3+9dVNDs4OIj9+/dvOt617N27V1iOypZkMolAIACWZamDbxGjZSNCCMmzhoYGnD17FtPT05DJZEgkEqiurkZDQ8OmxywvL4fT6cTCwgKkUinS6TQaGhpWzfqsheM42Gw2zM3NgeM4qFQqdHZ2wmQyrXn7eDyOsbExfP7zn990vGsxGo2ora3F4OAgGhsbtzxeIBDA4OAgWJYFwzCoqqpCS0uLMDtFigclL4QQkmcmkwm33XYbhoeH4fV6YTQa0dbWBrPZvOkxFQoFuru74Xa7kUgkoNFoUFpauq77Li4uYnp6GqWlpZBIJPD7/RgcHMRVV10FuVy+6vajo6PgOA579uzZdLwXsm/fPgwMDODee+/d0jipVApDQ0OIx+OwWq1Ip9OYmZmBSqVCbW1tdoIl24aSF0IIKQBGoxHXXnttVsdUKBTYtWvXhu/n9/uhUCiEwxUNBgMcDgdisdiaycvAwADa2tpyUgi8b98+fOc73wHP81vqHxOLxRAKhYTdVmKxGCqVCj6fj5KXIkQ1L4QQQjLI5fKMeplkMgmRSHTB5ZVc1Lus2LdvHwKBAGZnZ7c0jlgshkQiyWgMmEgk1kzGSOGjmZcC4XK5sLi4CGC5J0R5efmOOvOEFL9UKoWZmRk4HA6IRCLU1NTQ83SHKi8vh91uh91uh0wmQzweR319PdRq9arbJpNJjIyM4NFHH81JLKWlpaisrMTg4CBqamo2PY5SqURtbS3Gx8chl8uRTCYhlUpRVVWVxWjJdqHkpQA4HA709fVBJpOBYRg4HA6kUilUV1fnOzRCBOPj45iamoJer0cqlUJ/fz8YhkF5eXm+QyNZptFosG/fPjidTsTjcej1+gsmquPj40gmk1lrTreWvXv3YmBgAHfccceWxqmrq4NSqYTP54NEIkFFRYXQKJAUF0peCsD09DSUSiX0ej2A/+tUWVlZSVXwmxCPxy/YF0IsFkMmkyESiVzwNnK5nH7v54nH41hcXERJSYnQ8ZXneczPz1PyskNpNJp17Uxa2Qm0nttu1r59+/CjH/1oy3UvIpEIFRUVWTk4kuQXJS8FIJVKCYVxACCVShGLxcBxHH2IbpDNZsMXvvCFLY1x4MABPPnkk1mKaGc594ODYRjqk0EwODiIffv25fQx9u7dC4/HA6fTCavVmtPHIsWBkpcCYLFYMDk5CYVCAYZhsLS0hPLy8qx2qrxcvPXWW6irq8M3v/nNTd2/v78f3/rWt+D3+4Uup9nidrvhdrsBACUlJSgpKcnq+Lkkk8lQWlqK+fl5WCwWpNNpsCy7Y5Y2k8kk7HY7WJaFSqVCRUXFps8UKkRLS0vw+/1gGAZms1mY5d0qjuMwPDyM+++/PyvjXUhVVRXMZjMGBwcpeVlDOp2G3W5HKBSCQqFAeXk5FApFvsPKKUpeCkBDQ4Pw5gksF6i1tLTkOariw/M8Tp48iYcffhhNTU2bGqOhoQHPPPMM3nvvPRw5ciRrsa3UNa3MsM3NzaGrq6to3ohXzuYBlpMwkUiElpaWTW3DLTSpVAoDAwNwOBxQKBSIxWLweDzo6uraERcQDodDqE/ieR7T09Po7u6+YMO5jZidnQXLsjmtdwGWn3/d3d0YGhrC4cOHc/pYxWYlgZyfnxcaHLpcLnR3d+/onVSUvBQAqVSKzs5ONDQ0gOd5KJVKiES0i32jJiYm4HA4cNNNN216DJFIhEOHDuHdd9/NWvLC8zzOnj0LlUoFnU4HAAgGgzh79izKysqKZreOXC7H7t27L7lttth4vV64XC6Ul5dDJBKB53nY7XYsLS0VTXJ5IRzHYWxsDCqVSihM9fl8OHv2bFaSl6GhIVRWVsJisWx5rEvp6urC888/n/PHKTaBQAALCwvCAZwAsLCwAI/Hg8rKyjxHlzv0CVkgGIaBSqWCWq2mxGWT3nnnHezZs2fdXUQv5PDhw+jt7UUoFMpKXDzPI5VKZSxDyGQy4fyaYiOVSndM4gIsT7kzDCO87hiGAcMwO+IwwFQqhWQymXEFLpfL13VW0XqMjIygq6srK2Ndyp49ezAzMwOWZbfl8YpFKpUCwzAZr0mJRJLRp2cnok9JsiPwPI933nknK1PKe/fuhU6nw8mTJ7MQ2fJsjslkgs/nA8dx4DgOPp8PJpOJEtUCsDLTGY1GASx3Yl25mChmgUAAbrcbyWQSHo8HwPLrJBAIZK2ea2RkJONIgEQiAbfbDafTKfw+s6WlpQVSqRSjo6NZHTefotEoFhYWMDc3B7/fv6kxlEolJBIJwuEwgOW/Acdxa/bk2Ulo2YjsCOPj47Db7bj55pu3PJZYLMZNN92Et99+G7fddlsWogOampqEtWhguWB3pYaE5JfBYEBbWxtsNhv8fj8kEglaW1thNBrzHdqmLS4uYmhoCBzHIRKJwO/3I51OQyKRwGw2b+nAxxUryxW7d+8GAEQiEZw+fRperxcAoFarsX///qwlSlKpFG1tbRgZGcGBAweyMmY+sSyLvr4+BINBYeZv9+7dG249oNFo0N7ejuHhYYRCIYhEIjQ2NhbVhoDNoOSF7AhvvfUWurq6hHNLtuq2227D3//932dt19HKIXmRSAQAoFKpdtTSS7GrqqqC0WhEIpGATCYr6qvWWCyG0dFRaDQaqFQqoR9PRUUF6urqoNVqM1ozbNbo6CiUSqWQCI2Pj8Pv96OiogIMw8Dj8WBwcBDXXntt1uq69uzZg+Hh4ayMlW+zs7MIh8NCzxmWZWGz2WCxWDZcKF5eXg69Xo94PA6pVJrTnjuFomDmrE+ePInHH38cR48exWOPPSZM2c/MzOCJJ57Axz/+cTz++OMYGhrKc6Sk0HAcl9VZEgDo7u6G2WzGX/7yl6yNKRaLodVqodVqKXEpQGq1GkajsagTF2B52SCZTArLXgzDQKPRQCQSwWg0ZiVxAZaTl9bWVmE8n88HrVYrJCp6vR4sy2a19qKzsxM2mw0cx2VtzHyJRCIZB1mqVCokEolN/75UKhWMRuNlkbgABZK89PX14cc//jE+//nP4/jx4/je976H+vp6pFIpPPnkk7j66qvx61//Gg888AD+4z/+gwq2SIbh4WF4vV6h3iWRSMDn8yEQCGz6TU4kEuGWW27BiRMnshgpIRfHcRyi0eiWPvBlMhmkUqlQA8HzPKLRaNbb4NtsNnR2dgpfq9VqYWYRWP5wlsvlG55FiMfjCAQCa9bMdHZ2gmVZLCwsbD7wAqHVahEOh8HzPDiOg8vlAsMwO6q/UC4VxLLRs88+iwcffBDt7e0AIEzTnzlzBvF4HPfddx9EIhE+9rGP4aWXXsLJkydx66235jNkUkDefPNNXHHFFTCZTAgGgzhz5gyCwSAAoLKyEp2dnZt6Q7j99tvx7LPPwu127/j1Y5J/LMtieHgYgUAAYrEYdXV1qK2t3fCSi0KhQGtrK4aGhhAKhcBxHMxmc1YPIOR5HmNjY3jwwQeF7zU1NSEYDGJhYUHY/bJ///4NFaU7nU709/cjFotBKpWipaUFdXV1wr+XlpbCYrHAZrMVfY+hmpoa4bTsubk5RCIR1NfXY3R0FC0tLZTEXELek5d0Oo3x8XEcOHAAx44dQyKRQFdXFz73uc9hdnYWNTU1GU/+urq6LR+NTnaOZDKJt99+G1/60pfAcRz6+/sRiURQUVGBdDqN+fl5qFQqtLa2bnjstrY2VFdX48SJEzh69GgOoidkWSqVwuDgIEKhEMxmMxKJBGw2m9AtdaMqKiqEmZCV3W7ZbLi3sLAAlmXR0dEhfM9gMOCqq66C1+sFx3EwGAwbqhdjWRa9vb2Qy+UwmUyIxWIYGhqCVqsV+sgwDIP29naMjY0VfbM6hUKBvXv34t1334XZbMbevXuhUCgwNzcHqVS6qfesy0nekxe/349UKoV3330X3/zmN6FQKPC9730PzzzzDMrLy1etP58/NQkAHo9H2AoILE/505Xy5eGDDz5AIpHAxz72McRiMQQCAeFvLxaLodFohN0PG8UwDI4cOYLXXnsNDz30UDbDJiRDOBxGKBQSmuJJpVLE43H4fL5Nz5iYTKasNKJby8TEBEwm06oC+fUe5riWcDiMRCIhJCor7e1DoVBGE7yOjg6cOHFiR9SNcRwHhmHQ1NQkzLSYTCZ4vd4d8fPlUt6Tl5XmSXfccYfwBD169Ci++c1v4ujRo6sSlfOLnADgt7/9LZ555hnh60cffRSPP/54jiMnheCdd97BoUOHoFarkUgkIJFIEI/HhWLFRCKxpd1CR44cwdNPPw23201bm0nOSCQS6HQ6qFQqoQA2Go1Cr9cX5Jbt6elpdHR0ZLU7tFgsFuo/VmbbV7Z3n6ujowM/+clPoNFoiv74hnQ6DYPBkLFDiOM4KBSKgvy7F5K8Jy8ajQYWi2XNF0F1dTWef/75jCfz1NQUbr/99ozbPfDAA7jxxhuFr0UiEXw+X24DJ3nHsizefvttfOc73wGwXKjY3NyMgYEBhMNhoavtuWvmG1VVVYU9e/bg+eefx9/93d9lK3RCMvA8D61Wi4mJCWG2cHZ2Fm63Gw6HA62trcLREhuxtLSEyclJxGIxob9LNs676evry3jPzQaj0YiKigosLi5CqVQiGo3CaDSumkVvb29HIpHAqVOndsQZcCUlJRgcHIRCoQDP80in0+jq6rpsP8PWm7TlPXkBgFtvvRV/+MMfcODAAcjlcvz2t7/FlVdeid27d0MqleKFF17AXXfdhZMnT8LhcODqq6/OuL/FYsmYVvR4PDuitTe5uDfffBMajQZXXXWV8L3a2loolUp4PB5IJBKh/8FW3HHHHXj66afxt3/7tzSVS3KmqakJcrkcc3NzcDgcqK6uRklJCfx+P3p7e7F///4NnRTs9/tx6tQpiMViyGQyTE1NIRwOo6ura0vP41QqhbNnz+Lzn//8psdYi1gsRldXFwwGA4LBIFQqFWpqalb9zDqdDrt27cLo6CgaGxuzGkM+VFRUQCQSwel0QiQSoby8XDi5nVxYQSQvR48eRTAYxD/+4z9CLBbjwIED+OxnPwuJRIKvfvWr+J//+R88++yzKCsrw7/9279lfcsfKU6vv/46jhw5kjGtzDAMrFZrVg/Uu+WWW/C9730Pp0+fxhVXXJG1cQk5l1QqFWZGYrGYUKgrl8tht9sRDAY3lLy43W6k02nhwk6pVMLlcoFl2S0l9FNTU0gkEhnFutkilUrXlZB0dnZidHQUd955Z9Zj2G4Mw6C8vHxThdmXs4JIXsRiMY4dO4Zjx46t+rfa2lp897vfzUNUpJAtLCxgaGgIX/3qV3P+WDqdDjfccAP+/Oc/U/JCigbHcRkzLAzDgOf5LR8GOjo6iurq6k0tY2VLZ2cnjh8/nrfHJ/lXEMkLKW6BQAAOh0NoLKVUKqHX61FbW5uV9fW1/OlPf0JLSwuamppyMv757rrrLjzxxBMIhUIFN/PH8zwcDgeWlpaEaWcq9tsePM/D5XLB7XZDJBKhrKwMZrN5w+PEYjHMzc0hHA5DLBZDJBLB6/VCqVQKz7mNzpaYTCZMT0+DZflG4AgAACAASURBVFnI5XJ4vV4YDIYtdxAeHR3NaE6XD7t378Z3vvOdgnw9ku1REB12SfFaWVe32Wz44IMP8N5772FqagqTk5MYGBhAKpXK+mOm02m8/vrruPvuu7M+9oUcPHgQer2+IDvuTk9Po6+vD263G4uLixmH45HcWlhYwJkzZ+ByuWC323H69Gm43e4NjRGPx9HX14eJiQn4/X7Mz89DLpdDoVAgHo/DbDajq6trwxcCJSUl6OzsRCqVQiAQgMlkQmdn55Z36IyOjmacJJ0Pzc3NkMvlsNlseY2D5A/NvJAtmZubA8/zUCgUEIvF2LVrF4LBIGpra+HxeBAIBDZ1JXoxZ86cgd/vz+pZRpciFotx11134bXXXsNdd921bY97KYlEAlNTUzAYDEILgaWlJczOzuasxwdZlk6ncfbsWWi1WmGbq9/vx9TU1Ib6THm9Xni9XuGAPoPBAIfDgfb2dpjN5g11qD1fZWUlrFYr0uk0pFLplrc2+3w+LCwsoKura0vjbJVEIkF7ezuGhoZ2xAnTZONo5oVsycoppul0GiKRCBKJBBzHged5MAyTkwPUXn31Vdx4441ZOe15I+666y6Mj49jcnJyWx/3YtLpNDiOy2glLpPJsnoYHllbOp0WtuOvkEqlG/7dn7+rhGEYMAwjvKa2amW3UTZ6sgwNDUGj0aC+vn7LY21Vd3c3HdR7GaPkpcCFQiGcPXsWNpsNLpcr3+GsYjKZwLKscNXvcrmgUqkQiUSgUCiyfsKp3+/He++9h3vvvTer465HdXU19u7diz/+8Y/b/tgXIpfLodPpsLS0JPSICAaDWZ/tIqtJpVIYjUZ4vV6hudpmfvcqlQoikUg4iJBlWUgkkoI8HXhgYGDLW62zZd++fRgdHc1qop5KpYQlQL/fn7VxSfZR8lLAAoEAPvroI0xMTGB+fh6nT5/G3NxcvsPKUF1djZqaGsTjceh0OojFYuh0OsjlcuzevXtVN+Stev3112GxWHDllVdmddz1uvfee/HGG28gHo/n5fHPJxKJ0N7eDp1OB6fTCY/Hg+rqalRXV+c7tB2PYRi0trbCZDLB6XTC5XLBarVueFbCZDKho6MD4XAYDodD2IZciMlLf38/9u/fn+8wAABdXV1Ip9MYHR3NynjJZBL9/f04ffo0+vv70dPTg/n5+ayMTbKPal4K2PT0NDiOE3qWRKNRTExMoKysrGBOHF1Ze66pqQHHcULPFZlMtqqt91bxPI9XX30V9957b1am0zfj5ptvxne/+128++67uPnmm/MSw/k0Gg3279+PaDQKhmGgVquz2radXJhKpcK+ffsQiUTAMIwwi7JRVVVVMJvNSCaTkMvlOdultxUr9Tz5unA4n0qlQkdHB3p7e7NSQGy32+FwOFBeXi7MhNlsNhiNxi3v0CLZRzMvBSwej6+qZUilUjnZwbMVDMNAo9EIZ7Ocez5LNg0NDWF+fn5bdxmdT6FQ4MiRIwW1dAQsJ5ErhaOUuGwvsVgs/O63klQrlUph1rIQnTlzBnq9vqDO+Lrqqqtw5syZrIwVDoehUCiEv6FSqUQymaT6sQJFyUsBMxqNYFlWKHr1+XzQarUF++aWa6+88gquu+46lJaW5jWO+++/HwMDAwW3hHcxkUgEdrsdi4uLYFk23+FctliWhcPhgNPpLLoPxY8++ggHDx7c9lnPUCgEh8MBt9u96sLt6quvhs1mQzAY3PLjKJVKsCyLUCiEcDiMSCQCiURSMLPcJBMtGxWwmpoahMNhOJ1O4eC29vb2giiW227BYBDvvPOOcAhjPjU2NmL37t145ZVXiuKwxmAwiN7eXuGEdoVCga6uLmpkt83cbjcGBgaQTCbBcRxMJhP27NmT9bqwXEin0/joo4/wpS99aVsf1+FwoLe3F8lkEjzPw2q1oru7W0goVmqDTp06hY997GNbeiyNRgOPx4OBgQGIRCKYzWYcPnyYlowKFM28FDCZTIbdu3fj4MGDuOqqq3DFFVfktSV3Pv3pT3+C2WxedShnvjzwwAP485//XDCFuxczPj6OZDKZcX6KzWbbcpt4sn6pVAqjo6OQSCSwWq0oLy+Hz+fD1NRUvkNbl9HRUYRCIVxzzTVZHzudTsPv98Pr9WbMRsXjcQwMDEChUKCiogLl5eVwOByYmZkRbiMWi3Hdddfh/fff33IMExMTqKysxNVXX429e/dueysGsjGUvBQ4sVgMvV4Po9F42U5fchyHV155Bffff3/BzDodPnwYAPDWW2/lOZKL43keLMtmXD2q1WpEIhE6tXYbxeNxRKNRoZX9SmF1sSzhnTx5Et3d3Vn/QI/H4zh16hTeeecd/OUvf8EHH3wgLAHFYjHEYjHhdyYSiaBUKlctER06dAg9PT1bWoaLxWIIBALC8Q7l5eWwWq3w+Xyb/+FITlHychniOA4sy4Jl2aL4AOvt7YXT6cQ999yT71AECoUCd999N/7whz/kO5SLYhgGWq0240OSZVloNJqCSQQvBzKZDHK5XFi6A5brkApxO/T5eJ7P2e66iYkJ2O12WK1WVFRUIBQKYXBwEDzPQyaTQSaTCf1vgOUdl+cv41xzzTXgeR6nTp3adBxisRgSiSRjJjWRSGzrBSPP84jH4zlp7LkTUc3LZSYej2NkZAROpxMAYLFY0N7eXtDr7r///e9x0003FVzjtY9//OP41a9+hfHx8W07IHIzmpqa0N/fD7vdDmC5MLG5uZl2JW0jqVSK1tZWDAwMIBQKged56PV61NTU5Du0SxoZGYHb7c5J8rJyWORKEbDZbBaWj5RKpfA78/l8Qp3Q+b8zhUKB66+/Hm+99daml5UVCgXq6+ths9mEXZ1SqXTb+iUFg0GMjIyAZVnIZDI0NzejrKxsWx67WFHycpk5e/ascKUDAE6nE2NjY3k/q+RCXC4X3n//fTz99NP5DmWVXbt24eDBg3j55Zfxz//8z/kO54K0Wi327duHQCAAAMKWdrK9ysrKhFOiRSIRjEYjFApFvsO6pDfffBP79++HxWLJ+thyuRw+n0+YgYrFYpBKpcKsYE1NDTQaDViWhVgsRklJyZq7LW+//XZ85StfQSQS2fRzu7a2FkqlEj6fDxKJBGVlZdtSYxiLxdDX14dEIgG9Xo9oNIr+/n5cccUVVHdzEbRsdBnheR5utxtGoxEikQgikQgmkwler7fgeseseOWVV1BfX4/u7u58h7KmT3ziEzhx4kRWtmrmklKphNVqhdVqpcQlj3Q6HSorK1FeXl4UiUsikcCJEydwxx135GT8xsZGAMsN4pxOJ0KhEFpaWjL6RJnNZtTU1KCqquqCbSKuueYayOVyvPvuu5uOhWEYWK1WtLW1oampads2R7Asi3A4DIvFAqlUCp1OB47jhIsNsjZKXi4jDMOsOjgumUxCLBbnvP6B53lhu+N6JRIJ/PGPf8QnPvGJgl3iuPbaa2E2m/Hqq6/mOxRC1vX6ulRNxbmNMN9//32kUqmcdZM2mUw4ePAgmpubUV9fjyuvvBK7du3a8DhSqRS33347XnvtNeF7W6nn286LuZX3tnP/dhzHFex7XqGgZaPLTH19Pfr7+5FMJsEwDJLJJDo7O3P6QgkEArDZbGBZFgqFAi0tLeuqX3n77beRTqdx5MiRnMW2VWKxGEePHsXx48dzthuKZVlMT08jEolAr9ejtrZ2zSvQdDqNmZkZuN1uiMViVFdX572hH9keLMtifHwcwWAQKpUKTU1Nq5YcIpEIxsfH4ff7IZPJ0NjYiJKSEuHfU6kUxsfH4XA4AACVlZV45ZVXcNttt+W0Jk6v10Ov1295nPvuuw/Hjx/HyMgIwuEwQqEQFAoFmpub110v5/V6MT4+jkgkArVajdbW1pzPwOh0OuF8LK1Wi2g0CpVKBZPJlNPHLXY083KZsVqt2LdvH6xWK0pLS9Hd3Y3KysqcPV40GkVfXx9YloVWq0UymURvby9CodBF78fzPF566SXcfffdBV1MDAD33HMP/H4/Pvjgg6yPHQ6Hcfr0aSwuLiIej2NychIDAwNrXhlOTEzAZrMhmUyCZVn09vYW5EnkJLtWaiY8Hg/kcjlCoRB6e3szdpilUikMDg7C4XBALpcjmUyir68vYyvwxMQEpqamhCM+enp68P777+OBBx7Ix4+1YY2NjWhra8NPf/pT+P1+qNVqxOPxdb3fAMsJ4JkzZ4QdTaFQCH19fRm7nXJBKpVi9+7dqKysBM/zMJlM6O7uLoqdaPlEyctlyGKxoKOjA52dnTmvaA8Gg4hEIjCbzZDJZDAYDEgmk5dczx0ZGcH4+DiOHj2a0/iyQa/X48iRI3jppZeyPrbX60U4HBaKB8vLy+HxeFb9/mKxGObn52GxWKDVaoW+QAsLC1mPiRSWYDCIUCiE0tJSKJVKmM1mRKPRjOcIy7Lwer1C0bBerwfHcfB6vQCWlykcDgdMJhMUCgUUCgUGBwdRUVGB1tbWfP1oG3bkyBH09PQIx6gYjUYkEgn4/f5L3tfv9yOZTMJoNEIul8NisSAcDm9LPZtSqURnZyeuvfZa7N27NyszUTsdJS8kpy60HHWpZaoXX3wR119/PaqqqnIRVtY99NBD6O3txfT0dFbHTafTGUtRDMOAYZhVdQscx4HjuIzbikSioujjQ7ZmrToXhmEyvn+h25z7PDr3PrFYDB9++CFuuummHEScOzfccAMkEgl6eno2fN/zf2fnfp8UHkpeSE7p9XrodDo4nU5Eo1F4PB7hyu9CPB4P3n33XTz00EMbfrxIJILR0VH09fVhampq2wrvGhsbsX//frz44otZHVen04HneYTDYXAcB5/PB4VCsWpKWaFQwGw2w+VyIZ1OIx6PIxwOZ9Q0kJ1Jp9NBrVbD4/EgHo/D5/NBKpVmvMY0Go1QV7HSTRaAUAsiEomwa9cu+P1+sCyLEydOQCQS4b777iuqD++SkhIcPnwYr776KsLhMHw+nzADcyl6vR5KpRJerxfRaBQulwtarfayPZKl0Im//vWvfz3fQWTbuV0sSX5JJBIYjUbE43FEIhFotVp0dHRc9A3hN7/5DSKRCL7whS9s6I0zGo3iww8/hN1uRzQaxcLCAhKJBEpLS7flDVir1eLHP/4x7rjjjqyd/K1UKqFUKuF2u4UCxM7OTqFl+gqGYWAwGBCNRuHz+ZBIJFBfX4/a2tqi+vAhGyeVSmE0GoXTkFeeI+cW7IrFYhgMBsTjcbAsC4lEgra2tozkVq/XQyqVIhAI4Ne//jWOHj2Ku+66q6iePxKJBK2trfjZz34Gi8WCmpoadHR0rGsZZmVZOxQKIRaLwWAwoKOjg1oLbLP1/r4ZfgeezubxePIdAlkDz/OXfCOMx+N45JFH8E//9E+49957NzT+1NQU+vv7haWmdDoNp9OJ6667bltOUE6n07jvvvtw22234cEHH8zq2MlkEslkEnK5/KI7mlZajItEosv2LKzLWSqVglgsvujrLJ1OQyQSXfA2J06cwFNPPYU//OEPRTvr8J//+Z8YHh7G97///U0lXxzHCV1/yfZabzNE+uuQbbOeN5E33ngDDMPg9ttv3/D4yWQyo7nVyof8dtV9iMViPPjgg3j55ZezvlwllUqhUqkuuRWbYRgoFApKXC5TEonkkq+ziyU3PM/jN7/5De6///6iTVwA4JFHHoHNZsPg4OCm7k+JS+Gjv1ARSSaTcLlccDgc69r6V2x4nseLL76I+++/f1PdR3U6HVKplHC4WiAQgEwm29Zp33vuuQfhcHhLnT7Xkkql4HA4MDc3B7fbvaFmf2T7JBIJOJ1O2O32nO9SWVpawtzcnLCNPht6enowNzeHhx9+OCvj5UtVVRVuueUWPPfcc5seI5lMYnFxEZOTk3A4HHk/MDEej8PhcMDhcBTNaeS5RE3qikQ8HsfAwAA8Hg8YhoFEIkFHR4dwRtFOcObMGczNzW16e3RZWRna2towPj4OjuOgVCqxd+/ebU1eNBoN7rnnHvzud7/DoUOHsjJmKpVCf38/nE6ncMVcX1+PpqamoqpH2OlisRj6+/uxtLQEkUgEsViMzs7OnLxGZ2ZmMDo6Cp7nwXEczGYz9uzZs6WeSDzP49lnn8Xdd9+9Iwq9P/OZz+Chhx6CzWZDS0vLhu6bSqUwMDAAh8MBiUSCdDqN6upqtLW15WVWJhwOo6+vD4FAQOiU3t3dXXCH1W4nmnkpEgsLC3C73cL5NAqFAiMjI1m74ioEL7zwAm655ZZNd4VlGAbNzc04dOgQrr/+elx//fV56TD70EMPYWxsDMPDw1kZb2W2zWq1ory8HBaLBVNTUwV/ntLlZm5uDl6vF+Xl5bBarVAqlRgdHc36azQajWJiYgJ6vR7l5eWorKyE1+vF4uLilsY9deoUJiYm8Oijj2Yn0DxraGjAoUOH8Ktf/WrD93W73XA6nSgvL0dZWRnKysowNzeX0dRvO01NTSEUCqGiogLl5eWQSCQYHR29rFshUPJSJILBIJRKpXClrdFokEgkMs4pKmZzc3Po6enBpz71qS2PpVarYTAYsrbjZ6Oqqqpw/fXX43e/+11WxovFYpBIJMIVn1QqBc/zO+Zvv1OwLAuVSpXxGo3H40gmk1l9nGQyiVQqlTHLolQqEQ6HNz3myqzLnXfeifLy8myEWRA+97nPoaenB2NjYxu6XzKZFA6vBf6vTijbf8v1CoVCGe0RtFotYrFY3uIpBJS8FAm1Wo1YLCZ8HY1GIZFIIJVK8xhV9rzwwgvo6upCe3t7vkPJiocffhh/+ctf4HQ6tzyWSqVCOp0WrrJisRjEYvG2JGccxyESiWQ898ja1Go1IpGIUI/EsixkMlnWX6MymQwymUyoe+A4DtFodNX2eWA5KWFZFizLXvQq/fTp07DZbHjssceyGms2+Hw+zM/Pb6rOb2UmdqOzLwqFQjhMFlh+zYlEIiiVSkSjUQSDwW19TajVaiE5XemGHIvFLrgxgOM4hEIhBAKBHZvgUM1Lkdi1axe8Xi8WFhaEK4L29vZNFbYWmmAwiD//+c/4xje+ke9Qsmbv3r1oamrCiy++iGPHjm1prJKSElRXV2Nubk7osNvc3Jzz3SDRaBQjIyNCDUdFRQWampoydnSR/1NdXQ2fzwe73S68Rjs7O7OeZCoUCrS3t2NwcBAsy4LneZSVla3qRp1IJGCz2YTlJLPZjPb29lU1YDzP45e//CXuvPNOVFRUZDXWreB5HidPnsSbb76JeDwOjUaDO+64A52dnRsa59ixY/j0pz+9odqXkpIS1NfXY2pqCsDy7qPm5maEQiHYbDakUilIpVK0tbVty0xVfX09QqEQ5ufnsbCwgEAggNraWpw6dQqdnZ0ZtS/JZBLDw8PCAZs6nW7N3lDFjvq8FJFEIoGlpSWk02mo1ept6V2yHZ577jn86U9/wvPPP5+TU5nz5ZVXXsG3v/1t/PznP4dard7SWCvddZPJ5CU7FGcDz/Po7e2F0+lEaWkp0uk0PB4PWlpaUF9fn9PHLmaJRAJerxccx0GtVuf078SyLMLhsNCA7vyk0maz4ezZs7BarRCJRHA4HCgtLcXevXszCr0//PBD/Pu//zt+97vfFdSSkc1mw7PPPouSkhIYDAa4XC5Eo1E89thjGy6C/vKXv4xQKLShCySe54WZC4VCgXQ6jZ6eHuh0OmGZLhKJ4Morr9yWbeXRaBQDAwMYGxtDTU0NdDqd0Cn54MGDQnuE8fFxTExMoKysDGKxGG63GzqdDgcOHCiKLeDU52UHkslkKC8vR1VV1Y5JXJLJJF5++WV88pOf3FGJCwDccsstUCqVeO2117Y8lkgkgtlshtVq3ZZD2+LxOLxeL0pKSiAWiyGTyaDVauF2u3P+2MVMJpPBarWioqIi538njUaDsrIyWCyWNWfDPB4PDAaDUK9hNpuFBHjFyqzL3XffXVCJCwBh5mClU3BpaSlisdimnoPHjh3DRx99hJGRkXXfZ6VrdUlJCbRarXBEx0qtkVqtRjqd3raO7kqlEnK5HFVVVUKypNfrEY1GM4rCfT4ftFqt8H5qMpkQDAZ31OYOgJKXgrKyxrqeybBUKrUjCjbfeustxONx3HXXXfkOJeukUikeeughvPjii+vaFbCePhKpVArhcDjnb0QrHVjPXVNf6d5KioNUKs1IVFb+lrFYTHj+vPPOOxgfH8ff/M3f5CXGC0mn05DJZEilUsL74cr/r6eG6PzXW2NjI26++Wb84he/2HRMYrEYPM8L8az8/3bOZigUioxam0QiAYlEkvG6lMlkGe8PiURC2Lq/k9DidYHw+/2w2WwIh8NQKpVoaWmByWRadTuO4zA9PY2ZmRlwHAeLxYKWlpairH3heR7PP/887rvvvi0vq2wlhtnZWUxPT4PjOFRVVaG+vj5rL/T77rsPP/7xj3Hy5Elcf/31a94mHA5jfHwcgUAACoUCDQ0Na06dBgIBDA0NgWVZiMViNDQ0oKamJie9XmQyGWpqajA2Nga1Wg2O45BIJFBdXZ31xyK5UVtbi76+Png8HmH5gGEYvPfee5BIJJBIJHjqqafQ3t6Oqakp6HS6vNdFLC0tYWRkBNFoFABgNBphs9mg1WrhcrmgVqsxNTUFlmXR0tKyKt5gMIiRkRFhd2ZbW5tQD3Ls2DE8+OCDGBoaQkdHx4ZjM5lMMJvNsNvtQuFuSUnJts6CV1VVwe12Y3FxEVKpFKlUCs3NzRl1TDU1NfB6vXA6nZBIJEgkEmhtbd1xXbfpYMYCEA6HcebMGSQSCWi1WkSjUdjtdpSUlKx6ws3NzWFkZARarRZKpRJOpxPxeBxlZWVF17Csr68Pzz//PJ588slVpyRvl9nZWfT19UEmk0EkEmFubg4ikWjd666XolAo4PF48NZbb6155EEymURfXx+8Xi/UajXi8TjsdjvMZnNGQhqPx3H69Gkkk0lYLBaIRCLMz89Dr9fnLPEzGAxQKBRCnU1zc3Ne+uaQzTm/5oZlWVgsFpjNZng8HrzwwguYmprCl7/8ZUSjUfj9flRUVOStLiIYDKKnpwepVErYuWU0GlFWVgZgeeajra0NBoMBPp8PHo8HVqtVWDKLxWL48MMPEQwGodVqEYlEsLi4iLKyMuFk6ZmZGbz33ns4fPjwhuMTi8Uwm82QyWSQSCRCAft2JgUymQwWi0X429bU1KCqqirjvV+pVMJkMkEikUCtVqOurg6VlZVF8/mw3qaiNPNSAEKhEKLRqLDmLJPJhPbi53+or1x9rKy7lpWVwePxIBaLbam7Zj48//zzOHz4cF67BE9PT2ccey8WizEzM4OGhoas7ar55Cc/if/93//F8PDwqq3goVAIPp8PVqsVDMNAqVTC4XBgaWkp44MnEokgHA4Lz5GVgkGfz5ezhEIkEqG6uppmW4qYxWKBxWKB2+2Gz+cT6kdisRhGRkZw1VVXwWw2g+d5OByOC2653g5+vx/xeByVlZUAlhP/hYUFXHfddUgmkzh16pTwb2q1GgsLC/D5fMJrIhAIIBgMrrr/Sg0IsNz35ejRoxgcHNzwrqWVMRsaGrLx426aSqVCTU3NRW+j1+u3pTYun3Zk8iKTyfLWoGwzWJaFUqnMyDiVSiU0Gs2qNxKNRoN0Oi3cNpFIQKlUQqfT5XzpaD2nQq/X1NQUenp68Mtf/jIr423FuVeaubg62bVrFw4dOoQXX3wRV111Vca/xeNxKJXKjNmTtf726XRaKNhbWdKSSqUwGo15n+onhS8ej0OhUEChUAizdj6fD7fccguA5XoShmEKti7iQnWA59afrEdtbS1uvfVWPPfcc3jqqaeyFt+lZPO9kyzbkclLsXWeXVl/np6ehkajQSQSgVQqhUQiWdWYyWAwYGZmBvF4HGKxGIFAAHV1dUgmkzlrRhSJRDA+Pg6/3w+lUomGhoY1z9SIx+OYnp5GIBCAXC5HXV3dBbcQ/uIXv8D+/fvR2tqak5jXq7KyEkNDQ8KODI/Hk9VZlxUPP/wwPvvZz8Jms2X00mAYBnK5HFNTUzAYDELXTJlMlvG3X9n5MDU1BbVajUQiIZw0vRMP6STZJRaLodVqMTk5CZVKhRMnTqCrqwtqtRp+vx8sy6KhoWFds7fpdBrT09OYn5+HSCRCTU0Ndu3ateUP55Wu2EtLS1Cr1QgEAsIMQiKRgEKhgNfrhUajQSgUglKphEQiwalTp+D3+4UTtZ1OJ/R6PcLhsLBcdK7HHnsMDz74ID744IOcN8VkWRZjY2MIhUJQqVRobm6GXq9HPB7H2bNn4fV6hffKbC1VF7v1TjxQzUsBkEgkMJlMiMViiEaj0Ol06OjoWLMORKPRQKPRCNv2amtrUV9fn7N16mQyif7+fng8HqjVakSjUTgcDpjN5ownWTqdxsDAABYWFiAWixEMBuFyuWCxWFatCXu9XvzXf/0XnnjiibwvSej1eojFYng8HiQSCdTU1KClpSXrV6BlZWV47733YLfbceWVVwrfX+nREY1GwbIspFIp2tvbVyWHK1tdVw6J0+v1aG1tpVkXsi4rW+3FYjGGh4fx/vvv46mnnoLZbIZUKkVdXR0aGxvX9T4yMTGB4eFhyOVypNNpzM7OQqVSbXmZYiXRCAQCiEajMBqN2LNnD1QqFeRyOQwGA7xer7Cpob29HWNjY1haWoJKpUI0GkUikRCSe5VKha6uLmGpbIXRaMTk5CQ++ugj3HTTTVuK+WJisRjOnDmDYDAIlUqFcDgMl8sFk8kEm82GhYUFKJVKxGIx2O12GI3Golv6z4X11rxQk7oCU2jTi16vFz09PUJNBrDcf6GlpQW1tbXC7Xw+Hz744AOUlZUJb4B2ux0tLS2oq6vLGPNnP/sZPvjgAxw/frxgmial02nwPJ/T7rFvvPEGvva1r+HnP//5mm/06XRa2KJMSC7wPI8nnngCjY2N+NrXvrbh+6fTabzxxhtQKpXC0RSZqwAAIABJREFUB20wGIRIJMKNN96YtTg5jlvzvWGlnYRUKoXb7cb7778v1LgAwPz8PLq7u7Fr166LvreMjY3hU5/6FH7wgx+gqakpa3Gfy+l04syZMxn9cxYXF1FXV4eZmRmUlpYKMbpcLlRXV2/49OudiJrUFalC++BayW3PjYthmFU9STiOA8MwGW8YYrF41e0ikQh+//vf45FHHimYxAVYjjXXbe9vvPFGlJSU4OWXX75gDIX29yc7y+DgIEZGRjZ9cvRKb5Nzn6cikWjdNSfrdaH3BoZhIJPJLvg6WYnlUu8tzc3NuO666/Cb3/xmy7FuBMMwa76nikSidfV5Iv9nR9a87HQ8z2NpaUk4bfhCHTazQavVQq/Xw+VyQa/XCweUnd+DRqPRQKVSYWlpCQaDAfF4HBzHrZph+OMf/wiFQrHmtuELOffnlUqlKCkpKajEZ2lpCaFQCGKxGBaL5YJTv2KxGI888gh++MMf4uMf/3hR9uYBlmvKPB4PkskkVCoVLBYLJV1F4vjx4zh8+DB27dq1qftLJBJYrVZMTU2hpKQEPM/D5/MJfVNSqRTm5uaEPiu7du3K2VLISl8am80GiUSCVCoFjUaz7r4rn/nMZ/DYY49hfn5+1blQ2YpPpVLB4/FAp9MhGAzC6/VCq9UiGAxicXEROp0OPM8jHA5DoVBgcnISFRUVRfvesJ2o5qUITU5OYnBwEC6XC3a7HeFwGBaLJSc7BcRiMYxGI8Lh8EVrMiQSCQwGA/x+PwKBAHieR2tra8Y26GQyiW9/+9v41Kc+hX379q3r8Xmeh81mQ19fHxwOB+bn5xGLxQomgZmbm8NHH30El8uFxcVFLC0trdmfZ0VDQwOOHz8uNCIsNolEAr29vZicnITX68Xi4uKaySwpPJOTk3jmmWfw//7f/9tScajJZEIqlcLS0hISiQQaGhrQ2NgIAMLZO7FYDE6nE16vF6WlpVk/WRtYfs/x+Xzo7e2Fw+GA3+9HaWkpmpub1/V4ZWVl6OnpwdzcHA4ePJj1+KRSKQwGA0KhkHCoolwuh1Qqxfj4OKamphCNRoWDHq1WK1wuF4LBIEpKSi7bA1Cpz8sOFQqFMDk5KTRL4nkei4uLKC0tzcnVA7A8q3LgwAGhPfyFrrL1+v/P3peHR1We7d9n9n0mM5OZSUhISMhGFlYFKcUFlaqt/epapVbbftb2s2p/WqWLl9uHShVFLaJcn9rLBW3r0mJbrVY/URGEAAECCVnJMvu+7+ec3x9c5/0yJIGZZLJp7r80zJzzzjnnfc/zPs/93LcaZ599NpGsPnUB+eSTTxCLxXDFFVdkfW6fz4fu7m5C/KVpGv39/TAajVPuxZJIJNDW1gaVSkVana1WK/r6+kZV8BSLxbjuuuvw1ltv4dJLL51xC5Tdbofb7UZxcTEoikIymURPTw8MBsMseXia46233sKKFSvGHTQLhUI0NTWhrq4OFEWRZ9jr9WJwcBBFRUVkI2U2m+F0Os+oSzIWhMNh2O12rFq1Cnw+H3w+H1arFYODg6iurs7qGDfddBPuvvtu3HDDDRMSgHNrot1uRzKZhMlkgtfrhVQqRVlZGYxGI+RyOWlTLy4uhsVigcfjmVYO39MRU791nUVO4Mox3M6eqwFzctoTCa4V8XTg8/mQSqXDAheGYfDmm2/i6quvzklNN5lMgmVZ8nv5fD54PN60MBnjWvKH7hS4roLT4aqrrkI4HMbOnTsneIT5RywWg1gsJs+BSCQCwzAT1qY/i/zA5XLh008/xQ033JC3Y3JyDhw4P6GhGWCBQDBhz0YqlQJN0xCLxWRtEovFOa2FK1euxJw5c/Duu+9OyBg5cHxAHo+XcZ0YhiHXcejfZ+fTmTEbvMwwSCQS8Pl8Ys5F0zRSqdSUeQNli127dsFisWDNmjUIBoNZf48j53G6PVxX0HQQIZRIJJDJZOT3cLXr0bRtOCiVSlx99dX4y1/+MuNIelwbKrfQcppE3P1IJBLweDzw+XwZpo4zARx/g0vdzzQkEgnY7XbYbLZh2j/vvvsuKioqMtr08w2ZTAaRSESuXSKRAE3T48rIBYNBWCwW2O128my1trbi0KFD8Pv9YFkW/f398Hq9iMViiMfjObVs83g8/OAHP8A///lPsqaGQiFYrVbYbLa8bQrlcjkEAgHC4TCx3Ein01Cr1aBpmogIJhIJsCw77dfz6YCZlbOeBRQKBaqqqtDZ2Ukmb3FxMfH/mI5Ip9PYtm0b6uvr0dXVhd7eXjQ2NmZFGiwoKMD8+fPR1dUF4OQLZu7cudPCY0coFKKxsREtLS2wWq1gWRZGo3FYa/hIuP766/H6669j9+7dWLVq1SSMNj8oKiqCz+eDxWIhqe66ujrI5XIEg0G0traSF2dhYSEaGhqmRaB5JjAMg46ODgwMDAA4ufutqqqakHLHRCAajeLIkSPw+Xzg8XgQCARobGyEwWBALBbD+++/j7vuumtCidVyuRyLFi3C4cOHCReqrq5uzHPVbrejpaWFuElHo1G43W44nU4wDAOFQgEej4dwOAyGYSCXy7F69eqcy+eXXHIJtmzZgo8//hhnn302jhw5glQqBZZloVKpsHDhwnF7rykUCtTX16O9vR2JRIJwBimKgsFgAMMwCIVCEAgEqKmpGVEEdBaZmA1eZiDKysqIsBkncDcdyKuj4YMPPkBfXx9++ctfwmAwIBqN4tixYygoKDjjokBRFGpqaqDX6xGPx4kx2XT5vQaDAatWrSLdRgUFBVnxWLRaLa644gq88cYb+MY3vjFjunX4fD7q6+tRXFyMdDoNmUwGpVIJhmHQ3t6OeDyOoqIiMAwDh8OBEydOTLmKcjZwuVzo7+8nRMl4PI7Ozk4UFBScMZM2HdDX10eMFYGT2YP29nYUFBTg448/hlAoxNq1ayd8HEajEatXryadgWPNICSTSRw9ehQSiYR06nz++ecAgLq6OggEAjQ3N4PP5+Pcc8+FUqmEx+MhgVsuEIvFuOqqq/C3v/0NKpUKQqGQEJodDgd6e3vR1NQ0pt8xFCaTCRqNhqhj0zSNZDIJkUgEPp+PRCIBgUAwZSa1Mw3T4w0wi5yhVqthMpmm1Yt8JLAsizfffBPnnHMO2YHJZDKk02mSpj0TKIqCXq9HSUlJhrDTdIFcLofJZMq5Q+CHP/whBgYGsHfv3gkcXf7BqbUajUZSEkgmkwiHw6RNlcfjQalUwufzTeVQs0YsFst48UkkEjAMk/UzOtUIh8MZgQLnUB6Px7Fjxw5cddVVk+Z+LJFIoNFoxlX6SCaTiMfj5PlKpVLg8XjEOoP7m0QiAUVRKCgoQElJCcLhMClp5oKrrroKFosFbW1tGcGDXC4/I4ctF3DBGOdfptVqoVAoIJVKodFoZgOXHDC93gKz+MrhwIEDMJvNOPfcc4k4UzKZBEVRE9I+OZNgMBjwH//xH3jttdfyLvI12eD8uYZyBGaS07lIJCLlCQCErzPeZ5RlWcTjccTj8Qm5x4lEgvAohkpEcL4+7e3tsNlsuPLKK/N+bg4Mw5BGgnyBM9flAgeus1IoFBL+G0ds5cqS0WgUUql0TJIRer0ea9asQXNzcwZfKBwOz3bRTVPMlo1mMWFgWRavvvoqrrjiCtTW1sJsNkMgEIBhGFRXV8+IdPxE46abbsKOHTvw5Zdf4pxzzpnq4YwZAoEAVVVVaG1tRTQaJV0g2fB/pgMKCwthMplgtVrJM8qVZ8eKRCKB48ePw+VygaIoFBUVobq6Om/t8WazGZ2dnSQrAYBwTTjOy9atW7FmzZoJM/1zu904duwYYrEYJBIJGhoa8nIukUiEhoYG4g3EMAwWLVoEj8eDEydOgGVZmEwmYnJosVggFotRV1c35nNef/31uOGGG+ByuRCPx8EwDDQazYx5hr9umA1eZjFh2Lt3L3p7e/HEE09Aq9XC6XQSVVaDwTBjeB4TCaPRiO9973t49dVXsXz58mlXEssFxcXFEIvF8Pv94PF4KCwsnDFpcI58bTKZiIPxeJ/Rzs5OosHEMAz6+vogFArz4qXj9Xpx7NgxqFQqaLVaBINBxGIx1NbWkixYJBLBl19+iZdeemnc5xsJ4XAYBw8eBI/HQ0FBAcLhMA4cOICVK1fmJVtRVFQEqVSKcDhMhBBDoRDsdjvS6TSMRiOkUinpbjodPykbz7iGhgY0NDQQ7RjumDOBcP51xGzwMosJAcMweOWVV3DFFVcQld2JEtGb6fjRj36Ev/3tb/j888/zam43FdDpdDO2U0IoFOZNGCydTsPlchEncADQaDRwOBx5CV640ganMaRWqwlvx263w+v14t///jeMRuO4shGnQyAQQDweJ8aIGo0GFosFwWAwb6UWjUaTkf2SSCQoLCzM+Mzp7AA44nIwGIRCoUBNTc2on6coCtdeey2efPJJ3HzzzbNByzTHzN3mzSInpNNpIvg2Gfj0009htVrxox/9aMzHYFkWiURiUvVCWJad1OsEnKy3X3vttXj11VdnnDbKLP4PnOMxt8vn8/kZ5FGapvNm4XGq6SnLsmAYBt3d3fB6vdBoNGhtbcXChQvR19eXl3OeitOZJ04HxONxHDhwAG63GxKJBIFAAAcOHEA4HB71OxdddBF4PB4++eSTCRkTp+ky0/SdpiNmMy/TAC6XC2azGTRNQ6/Xo7S0NG+LHMuy6OvrQ39/P2iahk6nQ01NzYQSKVOpFF555RVcd911Y65/RyIRHD16FD6fD3w+H5WVlWAYBjabDRRFwWg0IplMwufzQSaTobKyMidxqpHg8/lw7NgxYpK2YMGCYbu8icJNN92Ev/71r/jggw9w2WWXTco5Z5E/BAIBdHR0IBwOQyqVorq6Gnq9Hp9++imAk+24Op0OZ511Vl7Op9PpoFKpYLfbIZVKEY1GoVarEQqFUFhYiObmZvB4PKxevTpv2Z5TUVBQALVaDbvdDrlcjv7+fkSjUZIpKSoqmtJAxu/3IxgMksyQVCqF2WyGz+cbtZwpkUjw3e9+F//4xz+wdu3avI7fbrcTjpJCoUBtbe241yzO++3gwYNIJpMoKyvDihUrZgxRfjyYzbxMMVwuF1paWhAIBBCNRtHW1oaenp68Hd9qteL48eOkRc9ut6O9vX1CI//33nsP0WgUN95445i+n06ncfjwYbjdbmg0GojFYnzwwQfYtWsXaJpGLBbDu+++iz179iCVSsFutw/rEsgV0WgUBw8eJAq56XQaBw4cmDSlVZVKhZtuugnbt2+fFKuHWeQPsVgMhw8fRigUglKpRDKZxL59+2A2m6HRaCCRSJBMJokOUD4glUqxaNEilJaWQi6Xo7KyEo2NjaQb59NPP8W5554LHo83YS3SEokES5cuRXFxMTFhnDNnDhKJBPbv3w+z2Twh5x0PsglGrrrqKvT29qKtrS1v5/X5fGhtbQWPx4NGo0E4HEZra+u4W/E7Ojrw97//HU6nE9FoFHv27MFHH330tbAXmA1ephiDg4MQiURkF1NYWIjBwcG8efc4HA7IZDJIpVKIRCIYDAa43e4J06+IRCLYvn07br755jGTNSORCDweD4xGI4RCISQSCXw+HyiKglKpJPYIDMNApVLBaDQiGo3C5XKNedzBYBDRaJQYQHJiUoFAYMzHzBXXXnsthEIh3n777Uk75yzGj5GeHb/fD6fTifr6eixduhQrV66EUCjMazAsl8uxYMECLF26FFVVVVAqlSgvL8fhw4fR39+PJUuWIJVKoby8PG/nPBUKhQKLFi2CXq/HkiVLMGfOHGi1WiiVSnR3d0+pBIBarYZcLifdQx6PB2Kx+IwdZMXFxVi1alVe/Y4CgQBYloVSqYRAIIBer0ckEjltCetMYFkWR48eBZ/Px5w5c1BYWIji4mJ0dXVN6ro1VZgNXqYYnFMzBz6fT+rX+QCPx8tYQFiWBY/Hm7B07htvvAGVSjUuXQlubNw1YFkWNE2TGjv3G4aCz+ePmy9y6kI72QuvRCLBrbfeirfeegsej2dSzz2LsWO0uTQSJ2Sin6ny8nKcOHECy5YtQ11dHc4+++wJt9JgGAYMw2S0gHPt5lMJqVSKZcuWQa1WIxKJQCaTYdmyZVmRia+77jrs2rULbrc7L2OhKCqD/8SybFYdUKcD954Yet3z/f6YzuA/8MADD0z1IPKNoWJN0x2pVApWq5Uw251OJ1GTzUeAwePxMDg4CLfbDZvNBrPZjLlz52Lu3Ll5DWBYlsWRI0fw5JNP4pZbbkF1dfWYBb6EQiGi0SjRrIhEIkRHQqVSIRAIYP/+/UgkEhCLxeDxeEgmk6iqqhqzqqdQKITH44HX6wVFUfD7/ZBKpaiqqpo0ZVIAqKysxKeffoqenh6sXLly0s47i7FDIBAQM0o+n49gMAiRSASpVIp0Og2BQIBQKASKolBRUTGhz5Pb7ca2bduwYcMGLF26dNT5wDAMLBYLBgYGEAgEIJFIch5XPB5He3s7urq64HA44Pf7odFowDAMXC4XSktLx+y55na70dfXB6fTCR6Pl+HcngskEglKS0tRVlaG8vLyrI9TXFyMjz76CKFQCIsXL875vKlUCoODgxgYGEA4HIZCoYDP50MkEgHDMPB6vdBqtSgvLx/GbwyHwxgcHITD4QBN05DL5SOu1RRFIRwOo6Ojg6y1g4ODxF07EAhAJpPNuK6pbO/RbPAyxeB2AS6XC7FYDHq9HrW1tXlb4ORyOdGEiEajEIvFkEqlKCwszOtD3dPTg9///vdQKBQ455xz4PF4YDAYxhTAUBQFnU5HzNgUCgXOPvtsKJVKDA4Oor29HSaTCTKZDP39/YjH41i1ahUh5o0FAoEAOp0OiUSCkA6bmpomXV2Te8E9/fTTOOussyZMXGwW+QPnL5ZIJBCJREgppbi4GD6fD+FwGGKxGA0NDeMSvcsGr7/+OtLpNH7xi1+MujlhWRbHjx/H0aNHEY1G4XA44Ha7YTAYsl53UqkUWlpaYLFYIBKJwDAM3G43cbkvLS1FbW3tmBoPOA5bIBBAMBiE2WyGUqkc11zMVT+JoiiIRCK89tpruPzyy3MSFqRpGkePHkVvby/S6TScTidisRiqqqqQTqeRSqVgNBpRW1s7bA0OBoM4ePAgnE4nIpEIEU0cjStlNBpBURT6+/vh9/tB0zQqKyuh0WgQCATIZngyN2DjRbbBy2y30RSDz+ejuroaZWVlYBiGZBLyhVgshlAohBUrVpCJ4nA4MDg4iAULFuTlHOFwGP/+979x4sQJPPLIIygpKYHVaoXZbEZ1dfWYjikSiVBfX5/xtzlz5kAoFIKiKMydOxc0TZNadj5eCgqFAkuXLh33ccaLhQsXYu3atdi6dSs2b948o4Xrvi7gApZTSwErVqwg2ZeJvo+RSAT/+te/sH79+tNmVcPhME6cOEE4ZcBJYr/FYsl6vnIvxuLiYsJFY1kWtbW1mDt3LvEcGgs6OzuJPxJ3ro6ODphMpkntXvrWt76FZ599Fh9++CEuv/zyrL/n9/tht9tRVFRE7rnFYkFpaekZsziDg4NIJpNEGysej6O3txdFRUWQSCTDPi8UCrF69WosW7YMTqcT7e3t5J4oFApYrdbTdlfNZMyuitMEXEYk3wscTdNIp9MZEb5YLM4bIRg4GSD985//xEUXXYTS0lIAJ4OPfJ5jKLhJzOfzIZfLp0V9Pd+44447MDAwgA8//HCqhzKLHHDqy5Xr9pmMAPS9996DQqHAxRdffNrPpdNpMAyTkRXNdb4yDAOKojJ+L4/Hg1AohFQqHXOQwTAMksnksPUqlUpN+hwXi8X4/ve/j3feeScnPh1N06AoKuOeCwSCrI4Rj8eH/fZ0On3a71IUBblcDoVCMYzPeKrW0FcJs8HLVxxisZjUW4GTEysSieQ1ff2vf/0LyWQSF110EQAQx+iJ8C7S6XRIpVKIRqOktq5UKrPeWTAMA6vViu7ubpjNZqRSKSQSCdjtdlit1nGx//OJwsJC/PSnP8Uf//jHcbWAz+LrgUQigb/+9a+44YYbzlji4MqxPT09cDqdMJvNsFgsOWmDKJVKyGQyuN1upNNphEIh0gbMncPr9cJqtcLtdmdNVOYcy30+HyG1+nw+6HS6vGlf5YKrr74awWAQO3fuzPo7MpkMQqGQrCWcKWc2fLyCggJEIhEScHBZk5GyLqdCoVBAJpPB6/WCpmly/q+qh9yYOC9utxsPPfQQHn30UTz88MO44IILYDAY8PTTTwOYehn4mcR5mWjw+XyoVCq4XC54vV5Eo1GUlJSgsrIyL7tBu92Oxx57DHfccQfUajV8Ph+i0SjKysowf/78vO845XI5JBIJ7HY70dVYtGhRVgsD11p47Ngx+Hw+WCwWuFwuDAwM4MSJE7BarbDZbFCr1WMmCOYT9fX1eP/99zE4OIgVK1ZM9XBmMY3xz3/+E0ePHsVDDz102uDF4/Hg4MGDCAaD2LdvH/bt2we/3w+JRAKlUgmj0ZgVv0MoFKKgoABerxeBQAAURaGpqYl0NnV1deHQoUOwWq2kFFJYWJhVRobTQbHb7QiHwygsLERDQ8OUuNCLxWJEo1H8/e9/x2WXXZbVeiYSiSCTyWC32xEIBJBOp1FVVZWV9QSnE+RwOBAKhSCVStHY2JjVeiQUCskaHAwGQVEU6uvrJ01oM1/Idu2l2Bx79w4ePIg1a9ZAqVTim9/8Jv70pz+hubkZS5YswT333IP+/n78+c9/HtOg84V8tbd9lcARUfl8Pkkvjhcsy+L+++8HTdN4/vnnEY/HEYlEIBAIoFarJ7Q+nUwmSTks2x2Z1+vFF198AYPBAIFAAJZlsWvXLmg0GjQ2NgI4udMRCAT45je/OSU7vVNx6NAh/PSnP8Vjjz2GhoaGqR7OLKYhEokEfvzjH+MHP/gBbrjhhlE/xzAMdu3ahUQiAalUir179yIcDqOoqAiLFy+G1WpFQ0MDKisrsz43wzBIJBIQCoUk6PH5fNi9ezcxNUyn03A4HDj77LMJl+NMGJo54ErDUwW/34/vfOc7uO2223DBBRdk/b14PE6uTS6bIYZhEA6HQdP0mLqFRronMwnZNink/Ab7f//v/+Gcc85BT08PXn755Yx04PLly/Hll1/meshZTALEYjFxXc1XNuSzzz7DoUOH8Jvf/AYURUEqlUKv10Oj0Uw4sY7b3eQSYHCqk9yEpigK8Xg8Y0enVCoRjUanjULlokWLcPnll+OZZ55BMpmc6uHMYhriH//4B1iWxdVXX33az6XTaUSjUSiVSqRSKfB4PBQXF4NhGPB4PEgkkpyz1jweD1KpNOMlyQlIci9djqycC6eGz+dDrVZDrVZP+QtYo9Hguuuuw2uvvZYT90UikYwpi8vj8aBSqcbsaD3SPfkqIue3WHNzM26//XbS9TEUhYWFcDqdeRvcLPIHmqYRCARIGnO8CIVCeO655/DjH/94QhU88wmJRAIej0fk97nMzdAAnPM1mooU9Wi4/fbbEQ6H8Ze//GWqhwLgZMaN40pMln3CVCKRSMDn8xELD4fDQeTYpxrhcBh/+tOfcPPNN5+RFyEQCCCTyRAMBpFIJJBIJOB0OiGXy8EwDOLx+Jh1koZCJBKBZVmyzkSjUXg8HgSDwbwH4IFAgLhoD53H6XQa4XA4b0riN9xwA4LBIN555x34/f68HDcajaK/v594Qs0iN+Qcmsnl8lEXrIGBAeh0unEPahb5RSwWw7Fjx+DxeMCyLLRaLerr68e1UG3btg06nW7M/kVTAbVajfr6erS1tRG7gVWrViEcDsNisYCiKAiFQixZsmRalIw4qFQq3HPPPbj33nuxatWqKQ0WE4kEPvnkE7S2thKjz/POO29CjP+mA/x+P1pbWxEOh+FyuWC320HTNEQiESoqKrB8+fKsuAwThTfeeAMajQbf+973zvhZHo+H6upqvP3227DZbAgGgwiHwzAYDLDZbJgzZw7pFhwPtFotKisr0dPTg1gshu7ubshkMnR3d8Pv92Px4sV5ad09ceIE2traSBfSvHnzsGDBAgSDQRw5cgTBYBACgQBVVVWoqKgYVzZYLpfjkksuwbZt24jFQH19/Zh1mGw2G95//304HA5QFIU5c+bg4osvHrOo39cROQcva9euxYYNG7BmzRrCLKcoCrFYDE8//TQuvfTSvA9yFuNDT08P3G43qTc7HA50dHRgyZIlYzpec3MzPvnkE7z00kvTKkORDcrLy6HVakm5SKPRIB6Pw+v1Eq+k8Tq9TgQuvPBCfPDBB9i8eTOefPLJKQuuDh48iIMHD6KkpARisRh2ux07d+6EXq/Pm+ngdEE6ncaxY8eQTqchlUpht9vR39+PqqoqqNVq2Gw2tLS0QKFQTElHh8ViwY4dO7Bx48asSwSxWAw6nQ5z586FQCBAOBwGy7JYvHgxiouL8/JcURRFHNm/+OILlJeXo6qqCnw+H3a7HcePH8eyZcvGdY5AIIC2tjZifJlOp9Hb2wuVSoXe3l4kEgmYTCYkEgkcO3YMMpkMRUVFYz6f3W4nzvUtLS1Ys2YNjh49iuXLl+fs4ByNRvHZZ5/B5/OhoqICNE3Dbrdj9+7duOSSS7LqLJrFGMpGv//97xEMBlFVVYVrrrkGFEXh3nvvxYIFC+DxeLBhw4aJGOcsxgiWZYmIG6fLUFBQMObyUSQSwTPPPIN169YNE5GbKVCpVDAYDCgoKCBcHW7XOR0DFw7r16+HzWabMuNGrs1coVAQTSK9Xo9AIIBIJDIlY5pIxONxhMNhFBQUkNZ8qVSKZDJJSO+RSGRKUv4sy+K5557D0qVLce6552b9Pb/fD61Wi+LiYhgMBlRUVEAmk0GlUuU1IKYoClqtFnK5HPPmzSPH5uw9xuvxxPFquBc9x6vhylN6vR4URRHbg/F6hfn9fsjlctxwww3YuXMnIpEIEonEmBzgo9EoAoEANBoN0caRy+V5K0eEWs07AAAgAElEQVR9XZBz8DJnzhwcOnQIt912G2w2GyorK+HxeLBu3Trs379/wk3AZpEbOJ+LoWS5ZDIJoVA4psVq27ZtkMlkuOWWWzL+PpXusaeCYZgxj4dlWcTj8Skh7LIsS7qoRoJer8c999yDV199Ff39/ZM8uv+TTB8qGJZMJkFR1FeSHCgQCCAQCJBIJMhcSaVSEAgESKVSxCx0Kn77559/jsOHD+Oee+4BRVFIpVJZbUakUmnGWpBIJCbsN/D5/GEk4Gg0Oi4ROw5cxpf7zZx5K8drGyrMlk6nxy2PzwnlLVmyBE1NTXjjjTfAsuyYrptAIIBIJMoIfDiftq/iPJoojOlKaTQaPPjgg3jwwQfzPZ5ZTAAqKytx+PBhOJ1OUBQFhmHQ1NSU8wKyd+9efPzxx3jxxRczjCQ7OzuRSCSg1+tRU1MzZWnPVCqFjo4O2O12UBSFyspKlJWVZf07w+Ewjh49Sgz25s+fj3nz5k2KJPlQXhKPx0NFRcWIdfq1a9fio48+wqZNm7B58+ZJXew4LY+BgQH09fURA81ly5Z9JT2YJBIJKioq0NHRAYZhiHN5V1cXurq6oFar0djYOOnlsqFk+eLiYhw9ehQWiwUAUFpaiurq6lGfi9LSUmLQKhQKkU6nUVtbmxei7qmgKAp1dXU4cOAArFYrWJaFWCxGbW3tuI9dUFCAefPmobe3lwQrRUVFqKysRCKRwMDAAORyOeLxOCQSSdYt2qOhqKiIiPl9+9vfxn//93+jr68Pa9euzflYKpUKjY2N+PTTT9Hb20uuy8KFC7+SMv4ThVljxq8B5HI5CgoKIBKJoFKpUFlZmXOGLBAI4N5778X3v/99XHbZZQBOCl41NzeTyceJSg319JgscAJ0J06cgEqlAkVRGBgYgEwmy6oUlE6ncfDgQXi9Xuh0OvB4PAwMDECpVE44n4FhGBw6dAh2ux0FBQXk3HK5fNjYKYrCsmXL8PLLLyOZTKKpqWlCx3Yq1Go1iouLwePxoFQqsXTpUqxYsWLGcZ+yhUajgUqlgkwmg8lkAk3TpMw4d+5cyOVyFBcXT+rvf+qpp5BKpfDQQw+hs7MTPT090Gg0EIlEGBwcJOW8kSASiWA0GglPp7KyMu8O80Mhl8tRWFgIlUoFk8mE6urqvKh7UxRFZBk0Gg3mzp2LqqoqCIVC6PV6Yhmi0+mwYMGCUdcAhmFI2/jproFQKITBYIBYLIZOp4PRaMSOHTtw/vnn5xxwUBQFo9EIg8EAuVyO0tJSrFy5EvPnz59U76bpigkzZjzdTpTH40GtVmPRokW49dZbcyaEBoNB/PznP0dRURE2bdoEAOjv78cf/vAH9PX1wWQy4ec///mM5VpMJQoKCsa8Q2RZFlu2bEFhYSFuvvlm8neHwwGWZclxpVIpbDYbQqHQhLvnnopkMgmr1ZphNpdOp2E2mzF37twzfj8ajcLr9RLzN4FAgGg0CrfbPS636mwQi8XgcrlgNBrB5/OJz4zdbh+x+0Or1eLee+/F+vXrcdZZZ6GmpmZCxzcUFEWhpKRkylW0Jwvci8ZoNMJiscDr9WYQP202GwKBQM6kzbHis88+w2effYaXX34ZPB4PVqsVOp2OZDu1Wi2sVitqampGXadlMhnmzZs3KeMFTga8KpUKZrMZhw4dQjqdRlFREebPnz+uzCGPxxsxo8J1GJ0JVqsV7e3tSKfT0Gg0WLBgwWmdq2UyGTlufX09Wltb8cQTT+DRRx/NuQTP5/NRVVX1le3SmwzkvD2+7LLLkE6n4fF40NTUhAsvvBBNTU3weDxIpVKor6/Hzp07sWLFCnz00Uc5Hfull17KaANNp9PYsGEDzjnnHLzxxhu48sor8fDDD08b/5mvCz7++GPs3bsXDz300LAd5qkZlqnkvlAUNebzcwv9UPM3TrxrosGde+jYOT7FaDjvvPNwySWXYNOmTbMkv0nCaM/XZO2WXS4XnnnmGdxyyy2ora0lBPyhz+yprtZDMZXmpRaLBYcOHSJZjo6ODhw/fnzKxuN2u9HS0kIyiB6PB4cOHcpah4bH4+GBBx7AiRMn8Oabb07waGcxEnIOe8vLy1FWVob33nsvI0oNBoO47LLL0NDQgBdffBGXXnop7r//flx44YVZHbe1tRV2ux0XXngh/vWvf5G/JRIJfO973wOPx8P555+Pd999F7t37z6jc+rXFclkEhaLBZFIBDKZDHPmzBmTSiMHu92OrVu34tZbb8X8+fMz/q2wsBC9vb0IBoMQi8Xwer3Q6/UZaVSaptHT0wOLxQIej4d58+ahtLQ044VttVphtVrB4/EwZ86cMdWnRSIRioqK0NfXB61WC4ZhEIlEUF1dndX35XI5SkpK0N/fD7VaTUiNk6HhIZVKUVJSgmPHjiESiSASiUAkEqGuru603/vVr36F6667Di+88AJ+8YtfkL/H43GYzWaEw2GoVCqUlJQgFAqRFlJOh2M8z8XXEZxaqsfjgUwmQzgchlKpPGNZMhaLob+/H+FwGAqFAmVlZTlnatLpNDZu3IiamhrceOONRCgwEong6NGjKCsrg0ajQSgUQmNjY0YAEwwG0d7ejlAoBIVCgdraWiQSCdhsNlAUBZPJlKEvkkwm0dPTA4/HA4lEgsrKynHzesxmc0YJVygUwmw2o6qqasKfQ4fDgRMnTiCdTsNoNGLevHnwer0IhUJwOByIx+NQKpVE90ar1WZ1XJPJhN/97nf43e9+h8bGxtmKwCQjZ87Ltddei0cffZR4wXAQi8UoLCzEfffdh7vvvhsKhQLPP/88fvvb357xmKlUCg8//DBuv/12+Hw+dHd34+KLL8a+ffsQjUaxZs0a8tnOzk5Eo9HTlqS+rpyXdDqN1tZW9Pf3E3OvYDCIwsLCMXUW0TSNBx98ECUlJVi/fv2wHR1nw+7xeBCPx6HT6dDY2JhB2O3o6EBHRwekUikYhhnGQxkYGEBLSwtomkY0GsXAwMCYdDMoioJOpwPLsvD7/QCAurq6jEApm+9zCrwKhQINDQ2TQkTluniOHTsGl8tFnMClUilMJtOoGRiRSIQFCxZg8+bNmD9/PkpKSpBIJHD48GFYrVak02nY7XZC0GQYBgKBgKjDGgyGSecmzWSIRCISIMTjcajVaixYsOC0ZNdEIkH4TMDJ7EkoFMp5Tr7wwgtobW3F1q1boVAoMDg4iAMHDkAkEoGmafT390OhUGDx4sUZHJZYLIZ9+/YhHA5DLpcjFArh6NGjGBwcJCq0g4ODUCgUUCqVoGkahw8fRn9/PwQCAUKhEKxWKwoLC8dFxB8YGCDdQMDJTUssFkN5efmEks4dDgeam5tJ9xE3D2KxGL788ksIBAKIxWIEAgE4nU40NjaetnR0KioqKuDxePDaa6/hggsumNVoyQMmjPPC9dGPhEAgAJ/PBwBZR68A8Oabb2Lx4sUoLy9HT08P+XssFhu2MMjl8mHBidvtzjBj5PF4M85JMx/wer1wuVyEUMmyLGw2G/x+/5gEmt544w0MDg7iz3/+86gvueLiYhQVFYGm6WGLUCqVwsDAAPR6fcaiNTAwgLlz54JhGHR3d0OtVpNsTSAQQE9Pz5h4JkKhEPX19airqyMp9Vy/X1tbm5duiFzh8/mg1+sJAZdhGMKnON1cWrRoEW688UZs3rwZ27ZtQzweh9/vJ9ePZVkcOHAAKpWKZKHkcjmcTidisdi01rWZjtDpdDjnnHOyLilylhzc/dBoNETdNls11Z07d2LHjh149tlnodfrwbIsurq6oFKpoFQqYTAYUFpaCqFQiLKysozv+v1+hMNhcn6JRILm5mZUVVWRwDwQCKCrqwvFxcUIhUKw2WwZpHubzQaHwzGuZ6WoqAhHjhwhEg0ulwtlZWUTnnUZGBiASCQic0gikWBwcBCFhYWgaZqUAlmWhVAoHFPZ+c4770R7ezseffTRnAQDZzE+5HyVL7jgAvz6179GeXk5Vq5cSf6+a9cu/OY3vyGumx0dHVmRwqxWK3bu3Imnn3562L9JpdJhgQqnEzAUb7/9Nv7nf/6H/P9NN92UkUb/uiAWi0GlUmWQZSORCBQKRc5p3yNHjuC1117Dxo0bzxgIjqbzwS0EQ4MILqgCTr6gh+7GgJMBRDKZPG3t/kyYidmEUzkuXPdDNjyFn/70p9i3bx+eeuop3HXXXVCpVBmZK5lMBrlcnvG3aDQKtVr9lVPFnW6IRCLDOta4v2Vz7Y8fP45Nmzbh9ttvJ6q0NE0PmzcikSirecPNuaHcNZFIRETfuOdt6LPItYiPB2VlZaBpGidOnADDMCgrKyObjIkETdMZGS4+nw+GYaBQKFBVVYVUKoV4PA6TyTRm7SuRSITHHnsMP/zhD/HSSy9h/fr1+fwJsxgFOQcv27Ztw+WXX45vfvOb0Gg0KCwshMvlgs/nw5IlS7Bt2zYAJx/+bG5ie3s7PB4P/vM//xPAydJHMpnEunXrcNttt6G/vz9jl3PixAl861vfyjjGlVdemaEyyePxSAZopoFL9XNBGjepskEqlUI0GoXNZoNcLkcsFkMkEkEqlYLH44HVaoXX64VQKERxcfGoO6lIJILf/va3uPzyy3H++eeP+beIRCKYTCb09fVBr9eDYRgEAgFSchQIBDAYDBgYGIDJZALLskQye7RFLZFIwGq1kqzBVLRl54p4PA6XywWapqFUKkf0/yooKCA8HYlEAp/PB7lcnlUKWyAQYMOGDbj++uuxY8cOGI1GOBwOSKVShMNhiEQiuN1uHDlyBFKplBB8e3t7odPpZrMvEwiaphGLxWC1WiGXy4lZYDqdPuMa5Xa78ctf/hIXXXQRrr/+egAnNwQcX+PgwYNQKBQQCARgWRZLliwZNm/UajXkcjlcLheUSiXxMkqn0yRQ8Xq9KCsrA4/HIyVbp9MJrVZLTCm1Wu24nhcej0d0kxiGgVAoRCKRgNlsBk3TkMvlE1KiNZlMOHLkCCQSCSmZGo1G6PV6ErioVCpIJBIUFBSM+tuSySRcLhfS6TRkMhlR8OVgNBrx2GOP4Wc/+xmMRiO++93v5mX83NrNnTeXisZMRbYbKoodY3vGe++9h/3795MU41lnnYVLLrkE3d3dw4idp0MikUAoFCL//8UXX+CTTz7BvffeC41Gg5/97Ge49NJL8Z3vfAe7d+/Gtm3bsG3bttMu6kNLSDMJNE2jtbUVVquVqOKaTCY0NTVlnYq02Wxoa2tDOp0mLYNz585FT08Purq6IJFIkEqlwOfzsWTJkmEtzSzLYuPGjejv78drr7027hpuMpnE8ePHiXBcWVkZ5s+fTwKOeDyOo0ePwuFwADip4LxgwYIRFTETiQSam5vh8XjITnPevHnDCIrTCdFoFPv37yfCdwDQ1NQ0Yvv2wMAAOjo6kEwmoVQq0dTUlFPL+fvvv48HH3wQ69evJ0q9QqEQYrEYfX19RIeHoig0NDRAJpNBKBSisbFxVhl7AsH5+SQSCUgkEtTW1p6xZBSNRnH33XdDpVJh69atZAPT3d2Nw4cPo62tDfv37ydS+JWVlbjggguwatWqYZwBv9+PtrY2hMNhyGQyVFRUwGw2w+l0Ajj5gm9sbCQlnKHGhqFQCLFYjGw+xGIxli1bNm4D3ng8jv379xNRRoqiUF9fn/cWbq40zWV89Ho9FixYgK6uLrS2tsLhcCAajUKv1+PKK68c8b4kk0kcOHAATqcTfD4fLMuitrZ2xDbn999/Hw888ADuu+8+LF++fFxjTyaTOHLkCFwuFymD19bWDisNftWQbRA75uBlKJxOJ/70pz9h+/bt2L9/f4Y0c674+OOP8f777xOdl76+PmzZsgV9fX0wGo34+c9/joaGhtMeY6YGL06nEwcPHoTRaASPxwPDMLDb7ViyZElObqOxWIxYAMhkMsRiMezevRsqlYoEBW63GwaDYRjx+sMPP8SWLVvw8ssv51WDIJ1Og6KoEdOyHIGO8xkaLRDhyL2cxkg6nYbT6cSqVaumbfmjra0NPT09pGspGo0iGo3i3HPPHTEw5GTeRSLRmFLY999/Pw4dOoRNmzaBz+cjGo3i8OHDhIx87NgxWCwWLF++HFqtFoFAADweDytXrpz2GayZjGQyiWQyCbFYfMZMaiqVwgMPPAC3242XXnqJZAMikQg+/fRTRKNRdHZ2wu12IxaLoaioCEqlEiaTCcuWLRt13g4toXBZPuAkB+rUe88wDOLxOHbv3g2KokgQ7fF4oFAoMigDY0FnZyfa29vJXI7H4wiFQli9enXWhM1ckEwmSfDl9/uxa9cuss5yxogLFy4c0bH9xIkTOHLkCObMmQOKokg2avXq1SNuol988UX88Y9/xMaNG8fFn+vr60NbWxuKi4tBURS5Ruecc86EKCJPF2QbvIyZWRQOh/HOO+9g+/bt+N///V8wDINly5bhD3/4w1gPCQBYs2ZNRndReXk5CWS+6uAIZNxCwu1Icq03S6XSDF4QTdNkF86B45YMxeDgILZu3Ypf/vKXeRdPOl3miMfjZTUZ4/F4xnG4/x5vPX4iEYlEMu6FTCaD3+9HMpkcMXgRCoXjUmu95557sG7dOrz44ov41a9+RThj3DE5MzvOu0kmkxGTzvH6v8xidIhEoqyuL8MweOKJJ9Df348//vGPGWUMzk+JZVmyRiiVShKQ8Pn802r+DA2GOX2T0cAZBnKlTg5SqRSxWGxcnDRg+LyQSCTwer0T5ik29Npz6wV3PTgPq9E0XiKRCMRiMfm9YrEYDMOM+vkf//jHcDqduO+++7Bp06asRDJHQjQahUQiIeflyslT4bs2HZHTViudTuPdd9/FtddeC6PRiB/96Edob28HwzD4y1/+gr179+K//uu/JmqsX3lwWQduAUokEiQbMd7jqtVq4qyaTqcRiUQyUr/JZBKPPvooli9fjquvvnpc5xsvIpEI3G73MPdZpVKJdDpNJm84HIZQKMyrumkymYTNZoPFYhm1q240cHwju91O7qFarSaOxACIGutYy3E+nw82mw0ej2fEzgi5XI6NGzdi586d+Oijj8iizV0zziiPC2aCwSAUCgUJZj0ez4S+RGYxOliWxdatW3HgwAFs2bJlWIegRCKBWCwmgQPLskQOIZFIgGXZvChbc/MvGo1CqVQS6QGWZREMBlFQUACv1wubzTZmbqFKpSIkYeDkXBaLxWfsPgqFQnC5XPD7/aN2BnHt34ODgxmUBA5yuZy0RwMn11mapkeVZ1AqlYjH46SiEI1GIRAIRp3DFEXhnnvuwVlnnYXf/va3pE0+VygUioxrFIvFIBQKRw2CuYxQMBicUkHCyUJWZaPPPvsM27dvx1tvvUVaOq+55hqsW7cOdXV10Gq12LlzJ1avXj0ZYz4jZmrZCDhph9DV1UW6TziS23jB6TtwL+TS0lLU1NSQ3ceWLVvQ3NyM119/fUoJnBaLBa2trUSJc968eaitrSVdSsePH0dvby8h/TU2NuZNvj8Wi+HAgQPwer2kg2rx4sVZieb5/X4cOHCApOLVajWWLFkCsVhMdD4oioJQKMSSJUvGxDHp7OxEV1cXWZjmzZuHBQsWjFjueeONN/Dss8/iD3/4A+LxODGASyQSpCuNx+NBJpNh4cKF4PP5aG1tJQu6VqslvJhZTDxYlsULL7yA9957D88999yopXG73Y6Wlha0t7ejubkZPp8ParUac+bMwbe//W2cd9554yr/DZ1/nDVCOBxGOBwmViASiYS8kCmKQk1NTc6Z2lQqhZaWlox5sXDhwtNKOgwMDODYsWOkBF1RUTGsY8nn8+HAgQMk4zgaR8fpdOLw4cOIx+Pg8XhEqn+kbFI6ncaRI0dgNptJ6buxsXFE646hSCaTuOuuu9DX14fHH388Z0JyKpUifEAuI79gwYIR1zu/34/W1lZEIhFQFIWioiLU1dXNSM+xvHJeuPLFmjVrcOedd+Kiiy4iL71AIICCgoLZ4CWPCIfDxCI9ny6jqVQKsViMlGm4ibpr1y48+uij2LZtGxYtWpS38+WKcDiMXbt2QSqVQqFQIJVKwel04qyzziKLGrf7S6VSkEqlea39Hjt2DL29vSgqKgJFUQgGg6BpGueee+5pFwGWZfHFF18gEomQiedwOGAwGLBs2TLSWULTNBQKxZjuqdfrxe7du6HVaiEWi5FOp+FwOLB8+fIR+VAsy+LOO++E1WrFk08+iXA4THhQCoUCoVAILMtCqVRCKpVi//798Hq9MBqNZEdvMpmwcOHCnMc6i9zAsixeeeUVvPPOO3jmmWewdOnS034+HA6jtbUVR44cQVFREek2EggEOO+888asnRKJRLBr1y5IJBIy/xwOB5qamkjpKBaLoaWlBUajEQKBAIlEAl6vF9/4xjdy5p0NnRdn6qwLBoPYtWsXlEolZDIZWRvOPvvsjM3Fnj17CIkZODlvJBIJVq1aNSww4QJ5oVB4xnWEpmn4fD7S9ZOtiGY8Hscdd9wBp9OJjRs35kx0TqfT8Hq9YBiGZNBH+szevXuRTCah1WoJh6e2thYVFRU5nW86INvgJasQfdGiRWBZFjt37sRTTz2F7du3j5iOm0V+oFAooNPp8m6PLhQKoVKpoFAoyES22+3YvHkzfvazn01p4AKcXBhTqRT53ZzuwtBnjaIoqNVq6PX6vJPWQqEQZDIZuTZcupizChgNXBlu6OKrVCpJ2UsgEKCwsBAmk2nM9zQejxP3buBknX5oifFUUBSF+++/H6FQCC+88AJ0Oh2KioqIYGBhYSEMBgOkUinS6XSGmSZ3jU+Xmp9FfsCyLF599VW8/fbbeOKJJ84YuAAn1weRSISKigrMmTMHRqMRJpMJyWTyjM/q6RCNRpFMJjPmn0AgQCqVgl6vh16vJxlhjm/GlbHG4q81dF6cSRIgFouBpmmSCeTWBi7TCZy8lpFIJGNd4BoWRmoiEYvF0Gg0Wa0jfD4fer0eJpMpJ/VviUSCzZs3Q6vV4te//jUp3WcLTk7CZDKNmhGPx+MIh8MkeOTz+VAoFDNWLiRbZBW8HDx4EO3t7Vi/fj26u7tx0003wWg04pprrsGOHTumbZvqLE6PVCqFRx55BLW1tVi3bt1UD4e8kIcScNPp9KRJbiuVygxRxHA4DIlEckaipUAgGCaoyIkD5mtucGPgrg1N02AY5rRj02g0eOSRR/Dee+9h165do36Oc7Ie+gKKx+On7fyaxfjBsixefvllvPXWW3jyySexYsWKrL+rUCgIcRY4GXhkSwoeDUKhcMT5xwXMkUiEdMtxpUvus/kke9M0TQT3OFAUhWg0ikAgAIZhwLIsUqlUxnkpioJKpUIwGCTWB263G0qlMifVW24zMp5AcChkMhmeeeaZMQcwZwJHOB46Xq4t/6uMrL2N9Ho9LrjgAtx+++1Yu3YtBAIB3n//fWzfvh0URSEQCKCoqGha9KB/Xb2NcsVzzz2HvXv3Yt26dXA6nRAIBFCr1VP2wpJIJES4Kh6Pw+fzQafTobq6elIkt5VKJXw+H5xOJ8LhMGiaxsKFC8/IAaIoCnK5HBaLhRDmpFLpMJ+n8UAqlSKVShHDxVAohNLSUlRWVp6W42AymSAQCPD888/j3HPPHTHzQ1EUJBIJrFYr4TfweDzU1dXNcl4mCCzL4sUXX8SOHTuwefPmnAIX4GTwEggE4HA4SEmwoaFhXPorYrEYqVQKg4ODiMVi8Pv90Ol0qKmpweDgIPbv3w+n05lBGA+Hw6ioqEBZWVle1g2z2YwDBw6gt7cXLpcLGo2GcD+6u7tx9OhR+P1+MAyD4uJiVFdXZ3RRqVQq9PX1Yc+ePejs7ITf70dVVRVMJlNW4/N6vdi/fz86OjowODgIoVCYFxK0SCTCRRddhM8++wx//etfsXLlyrxljrlNn9lsRiKRQCAQgEQiQU1NzYw0X812zRmXzgvDMPjwww/x+uuv429/+xsikQjKysrQ29s71kPmBTOd8zIZ+OKLL7B+/XrccsstWLlyJRKJBPx+/7Aa8mSD8/QJhUIQi8UoLi6e1AmYSCTg8XjAMExWjsFDEQqFSGeGVqvNe1mLYRi4XC7E43GIRCIYDIastGAYhsFtt90Gv9+PTZs2jcrf8fv9hKys1WpnlXcnCAzD4Pnnn8e///1vbN68mcj+54pkMgm32024VPnQOho6/yQSCbRaLYLBIFpaWqDVaiGRSBAMBmE2m7Fo0SIYDAYUFhbmRSPI5XJh7969UCgUpHWay15yBrMulwv9/f2ora3FqlWrhmV8kskkdu7cCY/HQ/hhgUAAS5cuJZoyoyEej+OLL74ATdPQarUkgFu+fHneRBxjsRjuvPNODA4O4pFHHsmbaz3nMu73+yEQCGA0GvNOO5gsTKpIHXDypuzYsQOvv/463n333XwccsyYDV5OD5fLhZtvvhlNTU34yU9+kvH3kpKSM4oAzmLmwev14rrrrsPq1atxyy23TPVwvragaRpPPfUU9uzZg2eeeYYYcU430DSNzs5O9Pf3w+FwwO12Y8WKFSSTaLVasXTp0ry9fAGQTsKhBPS+vj6k0+kM9+lgMAihUIhVq1YNO4bf78fnn3+eMS63250V+dztdmPPnj0Z37Xb7aiqqiKmpvlAIpHAPffcg+PHj+ORRx6ZFtWK6YS8EnazgVQqxfe///0pD1y+quDaXEcTRsoW6XQaGzduRFVVFdauXZuhB3CqOeB0QDqdzjtpdKJIqJNBbuWUWnOFVqvFww8/jHfffRd79uw54+cZhkEqlZol7J4GNE0TfZVTkU6nh5FEE4kENmzYgH379uH555+fssAlGwV0zqpCpVJBr9fD6/Wiu7ubPH8cEX28GHrtOFVxDolEgticcM88x0cZrRzL5/PB4/HI9adpehg3ZjRwa9+pa+JImcqhelOn+00j/ZtYLMamTZuwZMkS3H333ejs7Dzj2GYxHLPe3TMAiUQCx48fJ/4dyK4AACAASURBVBmlkpISzJ8/f0zy8a+88gqsViu2b9+OgYEBWK1WqFQqJBIJCASCjF0HTdPo6+uD1WolvkQlJSWTwomJxWJoa2uDx+OBUChEVVXVGdO+Z4LT6URXVxfi8Tj0ej1qamrywkmJRqM4fvw4fD4fqTXn22QulUqhvb0dVqsVAFBcXJyzjsOyZcvwk5/8BE8++SSeffbZUVPhdrudvKhUKhVqa2tnbAp6omC329HR0YF0Og2lUom6ujoolUokk0l0d3cTbY65c+eivLwcDocDv/vd72Cz2XDXXXeN2xtoLAiFQmhra0MwGIRYLEZdXd2ojvEOhwNKpRJisRh6vR5z587Fnj170NfXR7x9cum6ORVD54xYLEZNTQ0MBgP279+P9vZ2uN1uwqepqqqCzWZDf38/jh8/DpZlsXr16hGfS4VCgTlz5mDXrl0Ih8NIp9MoLi7Oys6AM3rlTDQTiQTkcnnGNaJpGt3d3ejv7wfLshl6KoFAAMePH0c4HIZSqcy4RvF4HB0dHRgYGIDb7YZOp8M111wDgUCAX//617j//vtnZQlyRNaE3ZmErxpht729HRaLBVqtFiKRCFarFQKBIOca9/79+/Hss8/i8ccfz3jBxuNxKBQKNDQ0ZLiWdnV14dixYxCJREin0xgYGIBcLp9wLgRN00TASq1Wg6ZpDA4OQq1Wj/kl6vV6sW/fPrLz4UwKx+tKnUqlcPDgQTidTuLkbbFYSEtyvsCl1HU6HSQSCSwWC1iWzbkWv2jRIuzduxeffPIJ1qxZM+y3e71etLS0QCAQQC6Xw+/3w+/3w2g0jilY/irC4/Hg0KFDkEgkkMvlCAaD8Hg8MBqN5MWm0WjA5/NhNpsRCoVw3333IRAIEMNZs9kMg8EwaXyuRCKB/fv3IxAIQKlUIpFIwGKxoLCwcMTnlHNul8lk4PF48Hq9cDgcqKmpQUlJCQQCAYRC4ajBz+lw6pyJx+OwWCxkbRscHITT6YRUKsXcuXMJmbytrQ2FhYUoKyuD1WpFMBgcJlJHURS8Xi/MZjMUCgVZM5VK5RnHyuPxoNfrwefzQdM0dDod6uvrM9q4e3t70d7eDrVaDbFYDKvVSgLYffv2EdsDv98Pt9tN/JNaWlrQ29sLs9kMt9sNt9uNZDKJJUuWQKlUYsuWLZg3b94Zhe++DsiWsDubeZnmSCaTcDqd0Ov1ZJetUqngcDhyEiDyeDx4/PHHceONN5LOBpFIhAULFoz4+XQ6jf7+fuj1eiK/T1EU+vr6JnyCRSIRuFwuIhbHdSFxdvZjgcPhIAqhwMkyJ0dMHE83QTAYhNvtJuZpMpkMNpsNbrc7L10KwP+RKLmFGAB0Oh1sNhvq6upyCr74fD42bNiA6667Di+//HIG5wkA0YbgdowGg4EEekMD268zOFI2F0jr9XoilW+321FYWEjuk8fjwQMPPACRSIQNGzaQwN9iscDv948re5ELgsEg/H4/UWflAgKv1zviZqSsrAwul4u4Pvf19eHss88m60U0GoXFYkFNTU3OwX8oFILH4yHzm5szbW1t0Ol0KC0tRXl5OUQiEfx+P+bNm4eenh5UV1eTzLBKpUJHRwfC4XDGNWRZlswLjjCfy1hFIhFqampG/XeLxQKNRkPWRO7eK5VKRCIRcn1lMhm5xzKZjARqqVQKZWVl8Hq9EIlE8Pl8WLduHXQ6HTZs2IA77rgDF198cU7X8+uK6UVwmMUwcLLQ4+Gm0DSN3//+9ygvL8+arMmybIYBHDC8Jj2R4M6fz+OdWu7K1/E5u/qh/5/PsY/2DJx63myh1+uxYcMGvP3229i3b9+wcw0dO3cfZvVe/g+cVQUH7r+5ucL9v8PhwNatW6FUKnHrrbdmBAnT/ZoajUYsW7aMvKgrKyszZOkZhhnz8zfSM0VRFHG9Hm29O1X3ZbRzj/QM5+tanzo27tinOz43Fu6anfpdhmFw00034Te/+Q2efvppvPXWW3kZ61cds2WjaQa3243Ozk4cOXIEJ06cQCwWg0AgIMJG8Xgc0WgU1dXVUCqVYBgGFosFfX19JJo/NQ382muvobm5GVu2bEEkEoHFYiGtkKNxJjj1SpvNRlyIfT4fKioqJrxeLxAIEAwGYbfbIRAIEIlEkEqlUFNTM2L7cTweh9lshtPpJAqhIy0mZrOZLCRutxtarRYVFRXjKhtx94Zrr25rayPlNa61dLzweDzo7+/HkSNHiOdTOBxGbW3tiKXDSCSC9vZ2dHV1we/3E0XWoSgpKUEqlcKLL76I888/n6Rq+Xw+HA4HIaJ6PB7odDqUlZVNOzL3VEEgEMButyMWi4FhGHi9Xuj1esybNw80TcNqtcJqtWLLli0oKSnB448/Dj6fD4/HA4qi4Pf7IRKJIBaLYbPZEA6HIZPJJlTLSCgUkueUU63mPH1Ge0Y5/sjcuXMhl8thNpsBgGiJVFdXk2zc0GfO5/ON+MwBJzPJdrsdXV1dsNlsxK/MarXCYDAQJ2WbzUZkAbi2Z6fTCR6Ph1Qqhf7+fhiNRohEIrjdbojFYiKqyDAMBgYGwOPxkEwm4ff7MX/+/NPy0FiWhd1uR39/P3w+H7xeL3p7ewnHTKlUkiBlYGAAAMiaOH/+fJhMJthsNsRiMfD5fPj9fkgkEsyfPx9SqRSBQABOpxOBQACRSAQMw0Cr1UIqlaKqqgoikQi1tbWorKzEk08+iVgshsWLF48aFHm9XuzZswefffYZenp6wOfzUVBQ8JWYo9mWjWaDl2kEp9OJlpYW9PX1obu7m7gTcwZpwMlFqKamhogudXV1oaOjA6lUCn6/Hw6HI+OleejQITzzzDN45JFHwOPx0NraimAwCJvNBq/XC4PBMGoAo9VqkUwm4fV6kUwmUVFRgfnz50/4BOHxeNDpdES2XiQSoaGhYcSSUTweR3NzM/r6+uD3+zE4OAiWZaHX6zMmvlwuh0KhgMfjQSwWg06nQ1NT07iDCz6fD51Oh0AggJaWFvh8PmJ4abPZxs1rcLlcaG5uJtmXwcFBSCQSLFv2/9n78uBIr+r60/uu3tWSuiW19m1GmhnPYns8tsfYOBBI2WEzEAyBQCoUSwIUUGEJP3BsglMus7hsMGBIQQibIZjgim0w9njssaRZZGk0o6W1tXrf9/37fn+o3k231tZIms1z/vFY+tT9be+9++4995z9qwqDMW6D3++vWLCYWF059u7di+PHj+PYsWPEf5HJZNBqtSR8ZrFY0N3dfUWKXe0UZDIZ9Ho90uk0isUi6urq0NXVBalUCp1Oh6mpKXzrW9/Cvn37cP/996OjowNGoxH5fB6ZTAYajYbKG9lsFh6Ph3hFOxXAsPc0k8kQL6O/v7/qUqBOp4NcLicBw46ODtjtdggEgqrfOWbGODs7C6lUCofDgTNnzkAikZDYIhN8FAgERNZvampCbW0thEIhcrkcCoUC9Ho9zGYzEWXdbjfxzHQ6Hem78DyPjo4OtLa2rpsdcTgcGBkZoSDslVdegUKhoEBIqVRCq9WipqYGSqWSvMFaW1vR1tYGuVxObttMXbu/v58MUJnnUKlUQjweR21tLSwWC/bs2VNRXm5pacGePXvwne98B263GwcPHlwx30ajUfz5z3/GuXPnUCqVEAgEsLi4WBWv50rARRGpu1xxpeq8DA4OIh6PY35+HnK5HBzHIZ/Po7m5GQaDAfv27as4Pp1O4+WXX4ZWq6VdDuOK9PX1IRqN4qMf/Sje9KY34UMf+hCOHTsGo9FIwcri4iJ27dqFtra2dc8rn8+T8+vFxkYpX4fDgbGxMepEKhQKCIVCOHLkyKp8Ap7nUSqVtn2RCIVCePHFF2Gz2Wiycbvd6Ovr25I52uDgICmdAqDF57bbblv1eXg8HgwNDVWk+F0uF/bv37+qJofP58N73vMevOUtb8H73ve+Cz7Pa1jCSy+9hPvvvx933nkn7rnnHuj1euJ2MASDQbz88ssVZPHFxcWqhNS2AxzHbesGZK137rrrrqv4GTuO8cNmZ2dx8uRJHD16FEajERzHwev1kmjm8PBwxT1yuVwYGBiATqfDSy+9BJPJROPY6/Wiubn5gjSqMpkMXnjhBequYs7ybLOWSCTAcRyOHj26YfmJzS8ikWhNh2qe51EsFiGVStckwZ87dw6f+MQn0NPTg89//vMVWayJiQn8+c9/hkgkglarJfHK5uZm3H777cTHuVJx0XVermHrYCUB9vKLxWJwHAeRSFThN8LAcdwKHQKJRIJ8Pg+O4/Dggw+irq4OH/vYx1AsFsFxXMWxMpkMmUxmw/OSSqWXzFp9o8kim81WZAUkEglplKz1eTuxu2W6F9vNEWJO0Azs+tbS6lhtL8JS6avBYrHgK1/5Cn72s59hZGRkS+f6esfTTz+N++67D3fccQf279+PhYUFDA0NYWJiouK4YrFImTSGtcb4TmC7M6drbTCWv4vsusuPlUql9G6y82L3Zvk9Kh9PHMdVjGOxWFyVfs1qYJotzGSyVCpBoVCQtoxEIkGpVKqKx8bml7XmLdalpVAo1u3e6+npwfe//33MzMzgi1/8YoUBJeO7sb8v58RdhbmINXEteLmMYDabkclkyBE0Go1S++1q0ahcLodWqyU+TLFYRDqdhsFgwK9//WtScGSDRSaTIR6P07G5XG5H257D4TBcLhf8fv8FTywbgWnUsImflZku9u5Do9FArVYjEAiQKRzP85QSzmazWFhYwOTkJLxeb9WTTG1tLRnNcRyHqakpkmdPJpMrjq+pqYFMJkM0GkWxWEQ0GiU38bVw5MgR3HPPPfjGN75BnTRrIZFIYGZmBlNTUwgEAlVdw+sBv/zlL/Gd73wHH/rQh3D99dfDZrOhtrYWtbW1cDgc9KxSqRQSiQTi8Th1dmWzWXAct+12EltBqVSC3++Hy+Wi+SWXy2F2dhbj4+NwOp00pmtqaqgziL1zUqmU3jmO4+B2u4nHwuYgqVQKnucpGA8EAtRmHAqFkE6n6X1Mp9PgeZ7KNjqdDj6fDxzHkfP7ely8UCiEmZkZzM7O0rNgGYvJyUl4PB6cO3cOhUIBWq2WWrWLxSKCwSBUKhVmZmYwOjoKl8u1wrQxnU7D6XRifn5+wzFULZqbm/HDH/4QiUQCn/vc5yqsRxiPJpvNIhgMolAooL6+/qo3YyzHNc7LZYSamhoUCoWKQWuxWNDS0rIqsVQoFKKmpoYIZplMBs3Nzcjn83jwwQfxL//yL9i7dy+Apd2DWq2m9r10Or3m524HZmZmcOrUKXg8HiwuLiKTyWybB0o51Go1CoUCtT3zPI89e/Zsi8/LZiAWi2EwGBCNRhGLxQAAu3btQl1dHbLZLIaHhzEzM4NoNErEx2rSo1qtFoVCgYTj/H4/zGYzQqEQtdCXZ56kUim0Wi0tEhKJBAMDAxtyG/bv349nn30Wp06dwq233rrqzjEWi+HkyZP02W63G3K5/KK1+16O4HkeTzzxBH7xi1/g61//Orq7u5FOpysI0PF4HDabDel0GoODg0TSnZubA8dx4DgOPT09F6VkVA1KpRJGRkYwPj4Or9eLxcVFFAoFzM3NYXZ2FolEAk6nE/l8njhdOp1u1XeO53mMj49jbGwM2WwW0WgUc3NzxK/atWsXcdtYqZzNUalUCpFIhBzU+/r6UF9fT+RU5sVVKBQqODjL4Xa7MTw8jEAgAK/Xi0AgAL1ej+npaTzzzDMYGhpCIBDAwsICwuEwjEYjLBYL5HI5stksxGIxnE4njh07htHRUczOzqJYLBJfMJFIYHBwkKwUXC4XbWa2CpVKhTe+8Y149tln8fvf/x433HADamtradPq8/kgFouxd+9eDAwMbKu796XCNc7LFQqe54kIyFKDSqVy3fJJsVhEJpOhdsKPf/zjOHjwIL70pS+tOJZZ2u+kg3Q8HsexY8eI5FcqleDxeHasps/zPGKxGAqFApRK5SXdwTKeErOpB1bychgJei1eznLwPI9IJIIXXngBBoOBJkWv14vGxsZVZeZLpRLy+fy6dfXlcDqdeM973oP3v//9uOuuu1b8fmRkBMFgkIKudDqNXC6Hw4cPX7Ky4qUEx3F45JFH8Kc//QkPPfQQDhw4gPn5eZw5c4bIqrFYDBzH4cYbb8Tw8DByuRwFknNzc6itrcW+ffsuq6yLy+UivolIJEIul8PU1BQkEgk6Ozuprdnr9eLw4cOU8VjtnYtGo3jppZdgNpshFovB8zymp6fR29uLtrY2qFQq5PN5FItFeDwejI2NwWq1QiAQIJ/Pw+fz4cCBAyTOWI5SqYRsNguRSLRmxqFYLOKFF16ASCQisTnWtRSNRuF2uyn7HA6HUVNTg/3792NgYAC5XA6pVAqvvvoqpqenIZfLoVQqKfjZv38/+vv7cfr0abjdbjK0jcfj4DgOt9xyy7aVqNPpND796U9jfn4eDzzwAKxWKwqFAnU3KRSKq6LTCLjGebliwdj2jNnOmPfrQSwWQ6PRQKVS4ZFHHoFUKsVnPvOZVY9VKpUwmUzQ6XQ7pjORy+XAcRxNKIy/s1MZMYFAAJ1OB7PZfMkXAaFQCLlcXjFpZTKZFdkRjuOq5jgIBALIZDJIJJKK65PL5WveUzahbUYVt7GxEZ///Ofxgx/8AA6HY8Xvl/OLZDIZisXiReNqXE4oFot48MEH8eKLL+LRRx/FgQMHACy1oLe0tMDv98PtdqNUKmFgYABCoRCpVKoiWDWZTJdduQgAyTOwd0cmkxGPjs0Z7Hflz361d475Y7HxIBAIoNFoSJ0YWBoPSqUSuVwOUqmUvoMFQTKZbNXgRCQSQaVSrVsqYeXx8jIyK7kw/oxUKqXvUqvVkEgktGkUCoXU8ckCBKlUCqFQiEQiAWCpFFj+DNm1rMW7uxAolUo8/PDD6O7uxmc+8xnMzs5SOVilUl01gctm8Pq74qsYf/zjH6nb4VIxztluKJPJ0MLKFmpGgguHw4hGo5viwWQyGfIqKQfHcYjH44jFYjuyiDKFY5/PR+TmRCKBcDhcdTC2nJeTTCZX1eNZDzKZDBqNBuFwGMDSdadSqW1XvX3zm9+MN7zhDfj617+ObDZb8TudTkedF8CSGi/r0Hg9IZ/P44EHHsCZM2fw+OOPV3S4iEQi7N69G0eOHMGNN96Im266iVp65XI5wuEw8dlisdhFLbnxPI94PE4l5rUgl8uJYwWAFn+mmwIsLdgSiYRS/LlcDpFIhEq3DAqFAhKJhAinxWKRMi2BQGDFHOHxeBAKhRCLxbC4uIhoNEr8oAspEkilUqjVairD8zyPRCIBo9EIkUhEelbsejmOq7ADYIGNQCBAJpMBz/MoFApIpVLI5/MIBoPQaDQV1x2Px6FSqba9hCOTyfCNb3wDhw4dwmc/+9kVho6lUgnJZBLJZPKiiYleSlzjvFwl8Hq9+MpXvoKPfvSjOHr06CU5h2w2izNnzsDhcMDv92N2dhbA0vOwWq2wWCw4efIkpqensbCwgGQyCaPRuG5qleM4TE5OkjcIk91nwnljY2MYHR3F/Pw8GZ5t16SRTqcxPDyMqakpIhyGw2EiLDLNlY0WILVajXw+D7fbTZPcwMDApng5QqEQWq0WPp8PoVAIyWQSDQ0N6O7u3lbPIYFAgIMHD+KXv/wlPB4PDh06RL+rqalBNpuFz+dDKpWCUqlEX1/f64okmM/ncd9998HhcOB73/veqm3wzNJCqVRSOY11ET7//POYmprCzMwMSqUSbrjhhouSeeE4DufPn8eZM2fIkJVla5dDqVQim83C7XYjmUwik8mgv78fDQ0NcLlcVBbZvXs38a8GBwfhcDiwsLCAfD5POkssSHe5XIjFYkgkEkTqdblcZII4OzsLh8MBn8+HF198ERMTE5iZmaEAJxwOg+d5GI3GTWWMBQIBjZtwOIxEIoHa2lpcd911VG52Op0IBoPQ6/XYt28fOjo6KJMhk8kgEAgQDAbhdDorBByZmB7LjDIzSbFYjIGBgR15rkKhELfccgsWFxfx+OOP0zPIZDIYHR3FxMQEnE4nUqkU9Hr9jgof7hSucV5eB+B5HplMBsViEV/+8peh1Wrx7W9/+5KlEEdGRjA/P4/6+noAwOTkJE0IBoMBQ0NDJNDE/Hra2trQ19e35mc6nU6cOnWK/GKCwSCUSiVuuOEGOBwOTE5Ooq6uDkKhEH6/H3q9HocOHdqWezAyMoKFhQXS6ZiensbMzAyOHDkChUKBVCqFVCqFw4cPbxjAcBxH2aGt8HKy2SxSqRSRtXfKLHFkZAQf+chH8KUvfYm8sICl3R3LvqhUqtdV1iWXy+GrX/0qXC4XHnvssU3xt3iex/Hjx+Hz+SCXyyEQCJBOp9HR0bEtbsJMhVoul68aTDIei8ViIWG3UqmEm266adUsLev+KRQKUCgUFDTE43H6Hua8/NJLL5FvWLFYhNfrxd69e9HU1ESfx4Igt9uNmZkZWK1WiEQixGIxBAIBiMVi2Gw2BINBnDhxArlcDnK5HBaLBRzHobe3F6lUCjfccMMFCbFls1kkEgkqMbPW6kAggEgkAo7jYLFYYDAYVswdPM8T2TeRSGBubg4mk4nKfmweM5vN4DiOOqJ2EkwK4/e//z2+9rWvEa+QCXn6fD40NTWt6V13OaNazsuVF5ZdA4Cl9Ovk5CRcLheef/55nDt3Dk8++eQlC1x4nifJfXYOdrsdqVQKZrMZhUIBsViMyH1s8WVlkLUQDochl8tpkTSbzXC73Uin05SyZQu40WhEKBRCPp/flmwAM85jOz2JRIJcLkffp1KpEIvFkE6nNwxehELhtnRArbU4bTcGBgbwgQ98AA8//DAee+wxavkWiUTbZjh5JSGXy+H//b//B6/Xi8cff5wC9GqRz+eRTCZhtVopG5NMJrfcVssIsJOTk+A4DjKZDAMDAyvUqGOxWIVek1arpXG0WvAiEomIgFqO5e85Kw8zAUSxWAy5XI5IJFIRvKjVaqjVarjdbiiVShpDWq0WMzMzUKlUEIvF1JUYDocpaxIIBEhLphpdqtWw2rhh17jadZZDIBBQ2zsru7EFVigUUqZqsw7vW4FQKMRnP/tZiMVifOELX8Bdd92Fvr4+mntZ99fl7qG1FVzjvFwmyOVy5JVSDebn5zE3N4dkMonjx4/jr//6r1foh2z2M7cCpsBbrn/ABNaEQiGJM5XzKNjuaj2IxeIKLkuxWIRQKIRIJIJUKqUaPPu+cqJh+c+ZlsZmoFQqK0qQhUKB6uQASLjqSkzNVoMPf/jDaGhowMMPP/y6Eb9a7Trz+Ty++tWvwuv14nvf+96mAxdgKfCVSqXErwCWsiWsA+dC4ff7MTY2BoVCQdyaM2fOVIiaAf9HumVg4+hC3l2W8U2n0xAKheQ3xMAE3xjy+Tzi8TgymUyF+BsAIukykTWFQoFcLkfmiul0mroul4tsMjCuRyqVogxL+XesdQ0cxyGXy1V1PINEIoFEIqkIorLZbEWmZTNk/K1AIBDgU5/6FO666y78+Mc/xtTUFP2OdSFdrYELcC3zcsnBcRxmZ2cxNzdHombldu5rIRgMQqFQ4IknnsCNN96I22+/HeFwmCaDqakpzM7OguM4GI1G7N69e8dTmZ2dnTh58iT8fj8EAgEKhQKuu+46Up3s6urCyMgI0uk0KQNvZE1gs9ngcrng8/lo8m9tbYVKpUJbWxuGhobIwDGXy2HXrl00wfE8j5mZGUxPT6NUKsFoNGLXrl1Vl2w6OztJEI51Ee3duxcejwcymQzZbBZNTU0XXVPmYkEsFuOrX/0q3vve9+KZZ57BnXfeealPaceQy+XgcDiohNHW1oa6ujoUCgXcd999cLlcePzxxzfcpa8F1mXzzDPPkAyCRCJBR0cHjh8/jr6+vgt6j+bn53H27FmkUinilhmNRiSTyYr3nPFVXC4XpFIpcrkc2traNk0YLhaLGB8fJ5PT2tpaNDQ0wOl0UoCkUqmopBYIBPDaa6+RPENjYyNqamqwuLhIpZsDBw4gk8mQ8B0jxCYSCZw/fx4dHR0Ih8Nobm5ekd1IpVJ47bXXEAwGEQ6Hkc1mYbFYoFKpsHv37lWfl8fjweTkJBGC6+rqoNVq0d/fv2H2RKFQoLu7G2NjY9R0oNfr0dzcDJ7nsbCwQPON2WxGT0/PjmVKo9Eozp8/jz179uDs2bN49NFH8cEPfhA8zyMcDqO9vR2zs7NXranqNcLuJYbL5cK5c+eg0+mgUqmI9MV4HGvB6/Xiv//7v+H3+/GpT32K/DLa2trgdDpx9uxZ6PV6qNVq+P1+pFIp8hTZKajVahgMBtJUYAaSDFqtFnq9HlKpFGazeU1X5HLI5XIYjUbKcNjtdiLUKZVK6hpQq9Xo6OhAY2MjXaPL5cLIyAi0Wi3UajWCwSBisRgaGhqqGsys5q7VamGxWNDV1YWuri4oFAooFAo0Nzejo6Pjqs28AKD38rHHHsOtt966LcJblxs4jsPZs2exuLgItVqNUqlE//7Od76DqakpfO9736vw6dks2ILJnJBnZ2dhMpnQ09ODZDIJn8+H+vr6TenlJJNJHDt2DOPj4ySXzzp12tvbK0pHEokEZrOZiMQtLS1khrgZTE5OYnp6GmazGWq1Gl6vFyqVCu3t7ZBKpWTkqVarkU6nyVTUbDZDJBLB7XbTvKDT6dDa2gq73Q6LxQKdTgeLxQKZTEabHbvdTmPt4MGDFWON4zicOXMGoVAISqUSs7OziMfjJJngdDrp8xgCgQCGh4dJJJBt9jQaDWm1bET41+l0MBgM0Gq1sFqt6OzshEKhgMfjwenTp6FUKonMm81myUR3O5FKpTA4OIhMJgOlUom2tjYEAgE8/fTTsFqt2Lt3L0wmExYXF0mJ/UpBtZvsq3fWvUIQCASgVCppgNXW1sLv9yObza6bIWBEuY9+9KPI5XJIp9Po6+uDRCKBz+eDWq2miN9isZC9/E5nXxiRDsRAswAAIABJREFUbS2w2vFmoNPp1uRZ6PX6NQMgn89HgQawdB+8Xi/S6XRFO+R6UKlUK57DVowWr0S8853vxPPPP4+HH34Y999//1WXik6n0/D7/bRhYKWNb37zm5idncXjjz++ZXFFj8dDgbhQKERTUxN5TplMJrjdbsTj8U1JHMTjcWrl5XkeIpEImUwGVquVVJ7LoVQq0d7evqXr8Pl80Ol0FGQxfsrAwEAFxwUAlXEYH0Yul0MkEpEibjlEIhHq6+tRLBYxMTFRkbFgrb/LNwm5XA6hUAgmkwnBYBACgQBGo5H4NolEAslksiK75PP5IBQKqfzD/ralpQXxeBzJZLKqAH21eY49Y/b39fX18Hq9yGQy2955FIlEKNMGLGWE7r77bqTTaRw7dgwHDx6EQqEgde7lz+ZqwNWXS7rCIBKJKvRO1nMkZcjlcnjiiSfw9re/Hbfccgt19LBFdbnJW6lUotr06wnM2JKBGZq93u7DViEUCvHlL38Z58+fx9NPP32pT2dHsJx38txzz2FoaAjf+ta30NzcvK3fwfgcbIzzPL9pYiU7XiKRoKmpCfX19dBqtWhoaIDdbt+xd3wtDtpq31fODSs/fr3sUrnJIMNaLtiMf1YsFiESiSj7zP7NArrVsPw7Njq+GrDPKP//ixnoi0QivP3tb4fdbscjjzyCeDx+VXPVrmVeLjGsVitpEIjFYiSTSUqVroWf/OQnyOfz+Od//udVdwk6nQ5DQ0NwOBwwGAyQyWTo6uradO01nU5jenoa8XgcGo0G7e3tl0wN1OfzYW5uDvl8HhaLBa2trRCLxWR4mEgkoNFo0NzcTFksxpcJBAJIJpNYWFhAQ0MDYrHYhpYLq8Hv92NhYQEcx6Gurg42m+2yCYRyuRzm5+fpPjQ1NW1rrd1qteJjH/sYHnnkERw4cOCC2lUvVyiVSpjNZvh8PshkMvzhD3/Ac889h0984hPwer2kidLT03PBonJWqxUej4eMMpnqcrFYhM/ng8FgWJFdZFpJhUKBPM6AJbuJxcVFckNmXTpMkE0ikWyLDUehUMDs7CyCwSDkcjl5oQ0PD9MmK5VKoa+vb9XSqU6ng9VqhdPppI6cmpqadTOvIpEIdrsdZ8+eJXXeVCqFPXv2rDhWKpWipaUF58+fJ0JvIBBAfX093G43zGbzChFHi8WC+fl5iEQiCIVCvPTSS5DL5VvyRAsEApiYmIDH44HL5UJnZyc0Gg0ikQgaGxshl8sxNzeHQCAAkUiEpqamNbPTuVwOk5OTdM/b29thNpsRCASIE8RKbDKZDKFQCCqVColEAjqdDs3NzZDL5fjBD36Ab3/723jf+9635Wzb5YprnJdLDKVSCa1Wi3w+D4FAgKamJrS2tq65A5iamsJDDz2E++67b9WXMhKJYGxsDBzHUTux3W7H/v37N7XQ5nI5DA8Pw+/3QyQSIRQKIRgMkmfLxYTf78fw8DARHRcXF1EqlaDT6XDq1CksLCyQOmcikYDFYiF5b51Oh/n5eUxMTMBoNFIdmFkwVAufz0feNMViEQsLCxCJROs62V4sFAoFnD59GvPz86SzEYvF6D5sF3p7e3H8+HGcPn0at9xyy1VTPhIIBNDr9UgkEvjd736HZ599Fu94xztIV8hmsyGRSFBp6UJ8nFircCwWA8/z6OrqQn19PS1Gu3btqgg2A4EAhoaGKMvB3vlIJILJyUlqLWZSBDKZDCKRCM3NzaSxspXnw3EcxsbGMD09TeaSbrcbdrsddXV15GHU3t6O5ubmVb9LIBCQcShrN+7r69twA8REKNPpNKRSKbq6uiq4bOXQ6/VkoWKz2dDa2gqDwYCGhgb09PSs0CFSqVTQaDQIhUJwuVwAgKamJvq5zWbb1PONRCIYHBwEx3HQ6/XIZDIIBAK0kerp6cHMzAzOnj0LjuOQTCaxuLhIXLJyMEPMhYUFKBQKpNNpuFwu8DyPsbExZDIZ5PN5+n1HRweZ7NbU1KC/vx9NTU3UCPHiiy8iHo/jrrvuumw2WdXgGuflCsJGPBGGUqmEb33rW7j99ttx0003rXrM/Pw8OI5Dd3c3gKUgJBaLIZ/Pb6qeHolEEIlEqKZaU1MDl8uFUCi0JeLihcDpdJJrM7BUO2e7uUAgQEZuer0ebrcboVCIiMImkwlqtRrXX3898Vzi8TgcDgdsNlvVE/zs7CykUmnFOczOzqKlpeWSmxKGw2FMTEyQvLler4fX60UwGCS+wXZAKBTii1/8It797nfj+PHja76DVyKYo/HLL7+Me++9F4cPH8a5c+cgEAjI9HNychIajQb79u27oKCwoaEBDQ0NVZUTFhYWKt55hUJBHYkmk6mCzyYQCPBXf/VX5D20HUElW2SZOSMAykL19vau0JFZC9V0FC6HUChES0sLZZo2OraxsRGNjY1Vf359fT15TbG5A1gKEBn5t1qEQiGUSiXKJvX19cHtdmP//v0wGo3I5XJEzmbPLBgMYn5+fkX2MplMwuPxUEMBI0SfOnUKBoOBNkoKhQKzs7Ow2+246aabUCwWKzaU3d3d6O7uxp49e/D+978fTzzxBD784Q9XfU1XCq6ccOwa8NRTT8Hr9eLTn/70msewHRGDVCpFqVTalI8QgAoTtnJcihoqx3EVi0V5fVsoFNJ5som7/Fo5jqO2bAaJRIJisbipa1k+QTA+zWbv607A5/Nhenqa/FZmZmbg8Xh25NxaWlrwgQ98AI8++ugKLZErGfF4HA899BB27dqFu+++m36ez+dx/vx5aqsdGxvD+Pj4lsZBNcHFau/8RjpF5WNhq1iNA8Jam68WLA/0lvNgqsHyeXL5/Wdzb/n8s5w3xFDOiWJgnJ7lc0/5nL5WJryxsRHf+MY38Nvf/hbPPffcpq7rSsC1stEVglAohH/913/FBz/4QdTV1SEajZL2SDlyuRwWFxfJETUQCKCmpgatra2bSh0KBAK43W5yk2WCeI2NjZuuC3McB6fTieHhYdKkkMvlVWeCSqUSnE4nJBIJBAIBfD4fzGYzcVp4nkckEoHD4UAsFkNHRwdxE4RCIZLJJHmosLq4zWbblGYHu6/svkxNTUGj0aC7u7vivjJtmePHj2NsbIx8Xi4kbRuLxTAzMwO3241CoQCNRrPq4nTu3Dm4XC5otVqoVCrwPE+tt+FwmDQ/tqPcVygUoNPp8Lvf/Q5OpxOHDh3aMYuCi4VSqYT77rsPAPDe976XiLALCwvw+/3keqzRaNDZ2YlAIIC6urodtUYolUpYWFigjQjTMioUCpienqbvZirTzAxVpVIhFArB7/cjmUxS2zGwFIA7nU643W4ag36/H+fPn4fL5QLHcaR+KxKJSDuFCcclk0nivXk8Hng8HlLoXf4OhEIh+Hw+JBKJCmXfC0U0GsXMzAy8Xi84joNarUahUCAjR6YFFQqFSEZhPQiFQmpllkqlcLvd1EnFWp2rAStjs2CEea+x0r9IJEIkEiFbk2KxiHA4jNbW1hXzqFgsRjgcRigUAs/zmJ+fh9frRV1dHbVEs/mHCWSm02moVKo1x2BDQwN0Oh2++c1vUjbocke1ma9rwcsVgkceeQSFQgGHDx+G1+uF3++H2+2mBYuhpqamgv9RU1ODgYGBTbtMS6VSaLVaCjoCgQDxAjajG8DzPMbHx/HHP/4R4+PjcLvdZBxWW1tb1XkxCwC/3490Og2z2Yzdu3dDq9VCLpdjcHAQY2NjyOVyMBgMKBQKxAMAluriuVwOPp+P2gt7e3s3tehqtVpqQ2SGjMyjxmw2U1AxMTGB3/zmN1hYWEAoFMLY2BgEAsGmhaJisRgGBwcRCoWQTqfhdDohFApXLS96vV4IhUIkEgkyvsvlcpBIJCgUCnC73dvCgSkWizh9+jR5u/z0pz+F1WrddGB8ueGnP/0pXn75ZTz++ONoamqCz+dDNpsl09BcLgej0YjOzk6o1WrE43E0NjbuqHP78ne+UCiQu3M0GsX8/DwtsOl0msQUmelpMBiE2+1GJBJBbW0thEIhRkZGMDk5iWQySZ5hJ0+exOnTpzE5OQmn0wmBQED+R3q9HtFoFOFwGKVSCd3d3WhsbMTY2BjOnj1L5orJZLLi3SqfM9xuN4LBIEwm0wUbpobDYQwODiIcDiOVSmFhYQEAMDMzg6mpKUxMTODFF18kz63yQH4tSCQS6HQ6BINB+hw2d3g8HhgMhqqer0KhgFarRSgUonemv7+f/racT8XkKlpaWtDe3r5izAiFQhgMBtKi8fl8MJlM1NadzWbJYZs5fDPzzPXGdm9vL5xOJ37+85/j9ttv33a36+3GteDlKsL4+Di++93v4t5774VGo4HFYoFGo0E+nydNA7Z4CoVCUr1k5N8LnWSZ8RrHcdi3bx8NEI/HA5vNVtVOPh6P4+TJkwiHwzCbzaitrSVpbblcXpXUOtNvaG5uRnNzM5qammgAsvPp6upCR0cHGhoaEIlEIBaLqaYsFothsVhgs9lgt9vR1NS06SwEq5Hncjns3bsXdrud/GHq6+shk8lQKBTw3HPPIRKJwG63Q6/XQygUwuVyobu7e1O19KmpKYTDYdTV1dFO0O12V3jjMBSLRYRCIdhsNlgsFmSzWZRKJfT390OtVkOj0cDr9UKn011wtwwA2qU3NDSgpaUF8/PzOHHiBG6++eYrVrxuZGQEDz/8ML7+9a9j165dUKvVaGpqQlNTE3p6emC1WpHP59HS0gKFQoFIJAKpVIq2trYdJa6zd76pqQkNDQ3wer0wGo3Q6/Ww2WxQqVQ0BhobG6FWqyESiXD8+HHYbDbU19ejpqYGfr8fEokEPM/j3LlzaGhooKzF8ePHwfM82traYDAYSJfFZDJBq9VCJpPBZrOhsbGRjAcjkQhGR0dhsVhQU1ND4m41NTXUeDA8PAyVSgWDwYCamhpEIhHwPF81T2Y5zp49i0wmg9raWiiVSojFYoyNjSGbzcJms2FhYQEqlQr5fJ7mwng8vqG2iVKphNVqhdfrhc1mQ3NzMzQaDdLpNFKpVNUdW2q1Gs3NzbDb7WhsbFwRHEilUtTX16OxsRGtra3rimRKpVJks1kUi0Vcd911qKurg1wuRyaTwaFDhyigbGpqorHt8Xig0+nW1K4SCAS44YYb8Pvf/x7j4+M4cuTIZU22f10TdqVS6VXjdstxHL7//e/jL/7iL1BfX1+RzmTOxsvr4wKBYNsWk0wmQy6swNKLFY1GqzY/LBaLVJtliy77b7nPUTVgO5BysHpyeQp2uecRsBR8bLXNO5fLQaPR0HULhULi3rBzKRQKkEqlNDnIZDJy/t4MstlsxTsskUjW5Ng0NTUhl8thbm4OpVIJdXV1qKmpoWfGtDO26reyXNPjve99L/7pn/4Jo6OjK0THrgTE43H8+7//O971rnfhyJEj9HOxWEz3jnWtzMzMUFllz549F21+kUqlNIbKv7M8kCrXi1nu/8O6dljJkT27QqFAf1f+ngCo8CdbXoJhHkblfyORSGi85fN55PP5ihZldg4XClbaYWDWHFqtFjzPo1QqQalUkms7CwCqIUbzPA+hUFix8CsUik0bQDILlLUgEomqnn/y+XyF4axMJiOFcalUSm3e7HurGdtyuRwPPPAA7r33Xhw7dgx/+Zd/WeWVXb64KoMXNoCuBrzwwgtwOBx48MEH4XQ6STUWALk0V1MK4DiuwnG52tqnTqeDx+OBVquFUCgkFdCNAhfGQ2E29EKhkFyamXqwWCyG1+uFUqm84IyAQqGASqVCOByGwWBAsVhEJpOpmpfDcRyi0SiKxSKUSuW6QZ9Op4PD4SACXSwWg0KhoMldJpPBYrHA4XBAr9eTXLvJZNq0sjFTXdVoNPQ5NTU1UCgUKBaLiEQi4DgOGo0GSqWSpNQ5jkM+n8fx48eRSqWgUqkoSFx+DszpG1gqN66VTo7H44jFYohGo8jlcshms5DL5dDpdDhy5Ah+8pOf4LbbbrviuC8PPvggNBoNPvaxj615jFAoRE9PD5qamlAsFqFQKFa9T4lEgtpWJRIJtFotdDodiVCykoZKpYJMJkM6nUYikYBQKKxQrF0NMpkMNTU1CAaDqK2tpc9raGhAIBAgkj4TcwsGg5DJZLQIs/dGKBSSOSIj47JyBAvE2WLv9/shFouh0+kqsgSM35JMJpHP55HJZEg3iZ0rCyR0Oh14nic3bWBpXnC5XIhEIlAoFLBarRtmhk0mE7WHMy6OxWKh82WZRYVCAbFYjGg0Crvdvm7gwrhvrP2YdebxPI9YLHZJFWlVKhX5w2k0GqRSKSiVSnqei4uLiEQisNlsFNBWM7+0tbXh4x//OB5++GF0d3dfVBfszaDajcG1stFljEKhgK997Wu4++67cfToUUrB+v1+EiPr7+/f8GGXSiWMjY1hbGwMXq+XiKfVBDAajQbJZBJerxfJZBIAMDAwsC7nhXnFjI6Okq8Sx3GIx+MIBALQ6XTEIWHno1AoLiiAEYlE0Gq18Pv9CIfDyGQyJKa1EQ+j/L4w07r1zkOtVlNNPZFIQCwWV9wLgUCA+vp6xGIxOBwOhMNhmEwm3HnnnZs29CvnLsXjcahUKgwMDEAkEuH06dM4f/483G438Z5YOl0ikRAZ2uVyUZt8T09PRRo8lUpheHiYDOqCwSAJGpYjGAxicHCQJsx0Ok3k0EKhgDvuuANPPfUUNBrNFZV9GRwcxI9//GN885vfrOrZSKVSkrdfjlAohFdffRVjY2M4duwYmfYVi0XU1NRgdHQUZ8+ehdPphN/vB7BUrpqfn4fT6UQsFoPZbF5z584CHKa1lE6nYbPZsGfPHojFYrhcLuJCMAIpe/9Y2ywrM7F3QiAQoKWlBQKBAE6nE9FoFAaDAc3NzfD7/XA6nXA6ncjlcjCbzTSWZDIZJBIJjh8/jtHRUSISNzQ0wGQyka+Z2+1GNBpFIpFAXV0denp6IBQK8fLLL+PJJ5+kexKPxysW4dWg1WqRzWaJx6fVanHo0CEIBAK4XC7aVGm1WojFYtTV1aG3t3fN+8l4eGNjY0RsDoVCKBaLpJvDrFYuNrLZLKampuBwOCqI+Pv370epVMKvf/1rnD17FiMjIxgfH4dKpcKBAweqLnH19vbixIkTGBwcxNGjRy/L8lG1Gz0BfxXqBweDwUt9CtuC//mf/8GPfvQjPPXUU5QRyOfzFbvlaqJUt9uNoaEh0mzI5XIIh8O46aab1vQMKgfb6ZdKJRLbqub7mKAdE25iQlyJRAITExOwWq2k0plKpXDzzTdfcGknn88jnU6TSWM1g3JxcREnT56k80wmk8hkMjhy5Mia58HzPJFi1+pKKJVK8Pv9KBQKMBqNF3xNTF2UpcUlEgnOnz9P904gECAajUIgEODmm29eMVmzQIMpr5bj5MmT8Hg8ZBrn8/lgNBpx6NChiu8/duwY8vk8ZbICgQDkcjl2794NmUwGtVqNH/3oR/jZz36GJ5544rInAwJLC8Tf//3f441vfCM++clPXtDfR6NR8DyPmpoanDx5EolEAnNzcxCLxeSsbDKZaLfMtEW8Xi9mZmbQ0dEBs9kMnufhdrvR0tKC3bt3r/u9+XweqVSKyhwsoIjFYkgmkzh16hSUSiWkUimSySSCwSCuv/76iqAymUySGSHrTAqHw+B5HiqVCmNjY5SBZIKH1113XcXi6PV68cILL5DKq1QqRTgcxo033kjlIpZZEolEVHZeXFzEE088AZ1OB71ej1QqBb/fjze84Q248cYb1712JvDGslesjBqJRKhUy1rFGf9nLYRCIbz88suora0lyYP5+Xl0d3cTV2itwKVUKiGVStH92m7e0+joKGZnZ2GxWJDJZGiM3nrrrXjyySdx5swZdHR0kPqxVqvFP/7jP24q0FpYWMA999yDT3/607jlllu29fy3A9VongFXadnoakA+n8d//dd/4f3vf3/FwsMcmTeDbDZLbXvA/9VQq+WclJNfq0E6na7gDbB0rlarRW1tLcbHxyt2sSqVCrFYbEMzyvXADOo2A2Zsx86TdZKsdx4CgWDDDBEzmdsqVuMuRaPRiuBMq9XC6/Uim82uOFapVK66i+F5HtFoFFqttuJzGGegvLWWlR3KP5MFZQzvete78NOf/hR/+MMfcNddd235uncav/jFLwAAH/nIRzb9t4lEAqdOnaINhEwmo/JcPp+HVqulDYJMJoPL5UJTUxMFGkzddWBgAACoNLCakeJyrPWOlz9Hthlhmbh4PF5x7PLNh9lsprHNsg/s94xjsfwzcrkcBWcMPM9XcGVWe/cCgQAFfABo8a9msykUCleMO6FQeEGtv4xSwN5zoVAImUwGjUaz7udls1m89tpr8Pl8AJbuXX9//7aa3YbDYcogMX4d4xi63W4YDAY635aWFrhcLqRSqao2oQxNTU34wAc+gMcffxyHDh3aVhuRi4krt7/xKsezzz6LfD6Pd77znVv+LLlcTmTSZDJJfImdIh0yQl00GkU0GkUmkyFiH7A0seXzeRJlyufz5PR6McHcgxkKhcKG55HJZBAKhRCLxVAqlRCNRhEMBqsm+DHbBsYj2azQWzmHBQBJqK8XuOXzeYRCIYRCISJqLiclMoLwclEylUpVsXgxD5VyKBQK3HvvvfjlL3952XPNAoEAfvWrX+GTn/zkqlyLVCqFYDBIMv7Lcf78ecTjcRiNRuqeYe3MrH2VcRRyuRy0Wi0t6qzVlQU3DJlMhgKGdDqNWCyGRCKBeDxecdxa4DiO2uODwSC9H6y1Glh6tyORCKLR6JpCcxKJBEKhkEi5ACqUuVlZhblhs89hx280nzD+Fnvn2efJ5fKK76wWpVIJyWRyQ5pAsVikdnNgaT4UCoV0b5lg5UaL+OTkJOmu1NfXIxAIYHx8vOJ8UqkUdSutNScw3thq75dcLq8Y30zyQCwWQ6/XIx6PI5/Po1QqIRgMVjQMZLNZytRuhHvvvRcikQi/+tWvNjz2csW1zMtliFKphF/96ld497vfvS1RvcVigdlsxrFjx6je3dfXt2PBi06nQzQaxalTpyASiSCXy/GGN7yBFr2GhgYyMWPKod3d3Vtq470QNDQ0wO12Y3FxkVQrOzo61mw59Pl8OHPmDAn3sSwFEwvcs2fPuhmqTCaD0dFRTE9PY35+HhqNBna7HV1dXWhvb6+q1NXS0oJgMIjFxUUKNAYGBtYMXhKJBM6cOUNlDpPJhD179qCrqwvDw8NwuVwQCAQQiUTYvXv3CrXQvr4+nDp1Cm63GzzPQ6fToaura8X3vO1tb8MTTzyBP/7xj3jTm9604XVcKvznf/4n2tvbcccdd6z4ndvtxmuvvUZBbEtLS4UIIc/zmJ2dJZ6FXC5HU1MTzGYzlRBnZmagVCpRW1sLnU6Hjo4OjI6OYmRkBC6XizpxXC4Xstkska5bW1sxNTWFqakp+P1++Hw+2Gw20jRaK5PHWpcdDgfGxsZQKpVgNBqpnb2pqQnJZBJnzpxBJBIBsDQfDAwMrBj/5efBlF1NJhMaGhrg9/sxOjqKbDYLiUQChUIBr9dLDtkdHR0bkuStVit2796NkydPwu/3IxKJQCaTIR6P44UXXsCuXbuq5oYlEgmMjIwgEomQmWNXV9eKclEwGMTo6CjS6TRkMhn6+vpQX1+Pzs5OTExMUADR2tq67tjleZ60rtj7YDQaKVuVTqcpK+N0OqFQKKj9uqenh4jbExMTWFhYoNbx3t7eiqCpo6MDQ0ND8Hg8FCTu3bsXIpEI1113HU6cOIFz587R5u+WW27BK6+8Qu3wHMdBq9ViYGBgzXkMWAqS/uEf/gH/9m//hre+9a2b8nm7XHCNsHsZ4qWXXsKf//xn3H///dsSYLBaezabRUdHB1pbWwGA2mq3GxMTE0ScraurIyEnZq4mEolgsVig1WphNBrR2tq6pvHaToLpv2g0Guj1erS0tKzZpZDJZPDqq69CKpXCZDIhEong5MmTpMPBRPCsVuuqdXCe53H69OkK1dZ8Pk+t5zqdrqr2dqlUSq3QJpMJ7e3t6z5DFrjU19dDo9FQdwqbrDUaDcxmMzo7O1etNSsUCtTV1cFkMsFqtaK9vX3VgJp1rTz11FN4y1veclkSAX0+Hx566CF86UtfWuGFwwjMCoUCRqMRMpkMTqcTWq2WFoFYLIYXX3yRVJPz+Tzm5uZgt9tx5MgR2O12tLW1obe3F21tbejs7KSus6mpKdTW1qK3txfNzc3IZDJob29HS0sLOjs7kUwmMTIyAqlUSoT6YrEIo9EIt9uN2traFZmBdDqNoaEhhEIh0vFhJV6RSIQbbrgBBoOBApe6ujryy+E4boXuCjNSZHpANpsNnZ2dyOfzGBwcJK8ljuOQzWbJMJEFSRs9c4lEgqamJlgsFjJT3LdvH6xWK5mdrnady1EqlTA8PIx4PE5Kx/Pz82TEWv5MX331VQgEAhgMBlItNpvNsFqtpDtlt9s3FJFk5OByiQiWUW5sbMSpU6cQj8cRDoeRSCRQKBRgMBgQDochkUhgMBgwMzODc+fOwWAwQKVSkYI5450BS+PNbDZDLpdDr9ejs7MT9fX15K3FXLmZ7s3111+PfD6PV155BfX19airq6vwpVvvmtra2vCHP/wBiUQCe/fuXfeeX0y8rnVernT89re/xVvf+tZty0Sw8kZra2vFwAsGg9ReuZ2IRCIwGo20GBcKBarbsmBMKpVWzZDfSchksqraItPpNC1awP/V/VmKV6fTwe12I5PJrBpw5nI5hEIhaDQaOJ1OmM1mpFIpJBIJqNVqRKPRqgNJhUJR1Tmz+84mdIFAAK1WSwRNrVZb1Y5rLe7McrzjHe/Aj370I5w8eRIHDhzY+EIuMn7zm9+gs7MT119//YrfLX++EokEIpEIiUSCsh5ssYxGowiFQgCWyipWq5Xu0WoZEsaBKjfJZJwR1kLMzEeZpkttbS0CgQCVmJLJ5IpnlUgkSJ6GIGo8AAAgAElEQVSfqS/zPA+bzUYZBfYOGI1G8vLRarVr8kwEAsGK95CVG1lmQqPRIJFIQKFQbMoQEVh6d/v7+2EymSoCKI1Gg3g8Tt1E6yGTydB4YeVotVqNQCAAu91ecX/Knyk770QiAb1ev2mbk87OTgwPD1Mbc7FYxJ49e6hEbjAYMD09DYvFgkQigVQqBYvFAr/fj/b2dpKcYPMD+135vAhg1XGZSqUQjUbR3d2NcDiMQqFAcg2FQgEKhYLmcovFArfbTW7Ta0EkEuFv//Zv8eCDD+Jd73rXtnJ3LgaucV4uMzgcDoyPj28L14WB8TjK6+esM2cnZN2X121ZqnknFUlXA5NUX622vFkDNrFYTBMWsBR8MU0PYCk4WY8vw8Td2PeWl50KhcKOlPCYlkf5s2A6H2ynVygU1qy/bxYGg4Fapy83pNNpPPPMM/ibv/mbVTMEy58vsMSFkMlkKBaLyOfzEAgEUKlU2L17N7q7u9HZ2Ymurq4NuyNYaZTd49VMD6VSKZWrmPAaACodrNY9w0o27G9Y2YD9WywWQyQSkcUBQzkXZj2USiV6d8q5FQC2vOkpL8UxsGtZC+Wk4OXcHNZxtPw72L2o9jvWQ21tLQ4cOIDGxkZYrVYcPHgQNpuN5lH2nIrFIorFIvHb2JwgEolQKBQqRC2ZBhbTzFlrXmLvbKlUImNaxl9jz5d9z3IxyfVw5513QqFQXJHGjdcyL5cZnn76aVx33XUVO4itQiAQoLOzE6dOnSKr+1AohK6uLkxPT2+7Nw2r27rdbppA9u3bd9FEzJg5osPhIA7Arl27oFQqEQ6Hcf78eaRSKdTU1KCnpwcajQaLi4uYn58HsFSbX55Grqmpgd1uh8PhIKfu2tpa5PN5+Hw+FItF0tNYDVKpFHa7HePj41AqlZiZmaGOgpqamguWTl8N2WwW4+PjCAQCFVobPM9DKpWis7MTHMfB4XCQcmz5PdoK3va2t+Hv/u7vEAgENt0Vt5N44YUXIJPJcNttt636e51Oh+bmZszMzFBJz2AwIJlM4k9/+hN4nqfuDybKlkwmYbPZ1tzBM80Ov9+PUCiEZDIJk8mEXC4Hi8VS0dnC5PaZ4erk5CQaGxsRj8dXHFt+zgaDAVNTU/B4PHjttdeIo8Ik/0UiETo7OzEyMoJ0Ok0LbHt7+7r3KxAIkAR/Pp+Hw+HAyMgIampqyBSV4zi88sorlN3o6OiouuPPYDDAYDDA4/FApVIhnU7DYDCs2e2TTCZJP4d1Qfn9fqhUKgr6lmeB9Ho9iT2q1WrqnNtshxLP83A6nTSfWCwWsscYGxsjbaVQKAS1Wo3JyUnyMpJKpTh69Cjx5E6cOAGZTEblud7eXszNzWFmZqZirlo+j2g0GlitViwuLkKtVpOpJrAU0Oh0OhSLRUSjUSSTSbS0tFTVuSmRSHD33Xfj6aefxlvf+tbLsty7Fq5xXi4j5PN5PPTQQ/jgBz+47YJfGo0GOp0Os7OziMfj6O3thclkwsLCAtVXtwusbqtUKmEwGNDR0bGti/NGcLlceO2116DRaCidzET9hoeHqeTD3F6LxSJGR0dp98QcrMslzhkfoKamBnK5HI2NjTh48CD9rLW1Fc3NzesOfoPBQMRO9jc9PT3o7e3dsnUBA8/zGBkZweLiIvR6PVQqFZlgtra2orOzEwaDAU6nE6Ojo9DpdKTomUql0NDQsKUJzGKx4H//93/B8zx27dq1Lde0Hfjud7+LI0eO4PDhw6v+nhlssudrs9kgl8sxOTkJrVYLhUKBQCBAHCHGF2PaRcvBTCyZwzvrsrFYLGhtbUVXV1fFQi+RSFBbWwuJRAKz2UzeZI2Njejp6Vk1M8d24GNjYyTWqFarYbfbccMNN9DnM7VfqVQKo9GIrq6udRfwRCKBV199FUKhEAqFAqOjo4hGo7DZbCgUCiiVSujp6cHk5CRlAphDs8Viqer9EYlEFNzyPE/CcKtlhAqFAoaHh6k0w7SWrFYrZDIZ9Ho9enp6Ksbr8u8olUr0HZsday6XC6dPn4ZcLiehv/HxcRKPLBQKtEEwmUyknMzGWyqVgtfrJXPUUqmEcDgMq9UKq9WKsbEx4rwFg0HE4/EV/kfloqK5XA42mw27d+8mzs7evXtJnqK5uRkdHR1Vbxbr6+vx6KOP4vDhw9u6DlwornFerkCcPHkShUIBR48e3ZHPZ06r+/fvp4mtUCjA5XKhpaVl27/rUjHYmYUCGwQWiwU+nw8ejweZTIZ4BnK5HC6XC+FwGHq9nurDEokEc3NzaGlpqZgAhEIhTTgMm9nFCYVC2O32bc2qLUcmk4HP5yPhPZlMRuZu5bttn88HlUpFC29dXR38fj8ymcyWAimBQIA3v/nNePrpp3HPPfds+Xq2A+FwGGfPnsVnPvOZdY9b/nxPnDgBtVpNC2pdXR1CoRAOHDiwYdklHo/D5/NRMMj4X3V1dWhra1v1b1QqFXp6ejZ1baFQCB0dHVS6KhQK5AJdjtra2qrl4BmPwmw2IxwOE+GVdT+5XC4sLi4CAAUMTNG5vb29aq6eQqFAX1/fhselUilEIhG6lxKJBOl0GnK5fMMAWS6XV/Ud68HtdkOpVBJxW6/X4/nnn8fRo0dprBSLRUgkEvT39yMWi0Gj0VDAybq9WAdQY2MjcrkcEokE2RqwcWixWOD1eiva5xmkUil6e3vXPM9yTtVmYLVa0dfXh2PHjlEzx5WAa5yXywjHjh3DTTfddMEu0BuBEfa2qwZ8uaKcWwIs1efZta+G5feA/f2VKD692nWuZlAnFAorFrjy+vtWcccdd2Bubg5Op3PLn7UdGB4ehsFg2PQittn3qBzsnpcfu/zztgMs88GwnF9zIVg+RwAr36HlPJzVOCzbhdXmLY7jLjqHjoGdx/Jny362/DkzDsryeRcAtVAzsHF4scs3N998M4aGhi7qd24V1zIvlwlKpRKGhobwuc99bt3jeJ6H1+uF2+0GsBRtl7farQepVAqr1QqHwwGdTgeO45BKpdDZ2bkt18CQTCYxPT2NRCKBmpoaKt1wHIf6+voN2xK3CpvNBrfbTW2KsVgMdrsdDQ0NWFhYQDAYJDVdtVoNg8GAubk5SCQSCAQCBINBtLS0bDg55nI5LCwsIJlMQq1Wo6mp6ZK7mcvlclitVroe5oVT7poMLKlser1ehMNh6lpoa2vbFrXNpqYmtLS04MSJE5vuRtkJjIyM4ODBg5teEBobG+Hz+YhnEY1GV71HyWQSCwsLyOVyUKvVVBZgRqg2m41I0duVlmceW+FwGENDQ5RVZRL5P/nJT8BxHLq6unDTTTdtSn3aYDCQcjPj/+TzeXg8HszNzUGj0WD//v04f/48kskkZDIZQqFQ1VYYsVgMs7OzyGazMBqNsNvtEAqFcLvdZHZqtVrpPqvVatTX18PlckGn0yGXy5HcwsUA06VixpusZBWJRIhwz9S6T58+jWKxCLfbTd1fqVQKBw4coC4lZuvR2dkJs9kMv9+PYDBIasYtLS0rSifMj2lqagpisRi9vb3bmiU5dOgQHnvsMSqvXwm4xnm5TDAxMYGnnnoKX/jCF9ZdQBYXF3Hq1Clipy8sLEClUlVdomHy0qwu29PTs60aK5lMhrQnxGIxJiYmcOLECTo/p9MJkUh0QbLe1UKlUkGn0yGTyYDneTQ3N6OzsxMKhYJUKtPpNHQ6HQYGBmC1WsHzPKmTMp7BejXjQqGAkydPYm5uDvl8Hl6vF4lEAhaL5ZK6K7PaeCKRwNDQEDmP53K5Cvfu8nsELInfbaZOvhE8Hg9GRkZw++23b8vnbQU//OEP8cY3vnHdlPtq0Gg0ZEzKcRzdo/LAO5VKYXBwkEpuL7/8MhwOB7RaLUqlEgm5SSQS7Nq1a1tsI3iex7lz53D27Fl4vV5MTEzA4/GA4zgsLCxgfn6eVLXPnj2LQqGAjo6Oqse4RCKByWQifovRaEQ4HEY4HCZvIZvNBqvVikAggHQ6DaPRiP7+/g2D33g8jsHBQcRiMQrAcrkcAoEAzp07h3Q6DY/Hg3A4DIvFQiKQbL5Ip9NQq9XYtWvXjs4h5dBoNPB4PNTwwDaBzJ+pWCyiUCgQKTeTyZAPnFKpRE9PD7q6uqBQKOi6W1tb0dHRAbVaDZ1OR87edrsdnZ2dK8bh4OAgnnzySQSDQbjdbpw9exYmk2nbSPEGgwH/8R//gV27dl1w+Wm7cI3zcoVhZGQEXV1d6wYhPM9jenqaJlVgaTKYnp6GzWaranISi8XkNLsTCIfDiMfjxBtgbYOMUCiVSjE3N4fW1tYdTfuuVeM3GAw4fPjwinR7X18fkaSr2aUGg0EEAgEySGQGe6FQaEeE/zYDJvPe399Pk1symcT58+eJCwNsjgexWRw4cAA///nPkc/nL6lZYzabhcvlWlUVuBo0NDSsO5l7PB4kk0lYrVYkEgmUSiXynmlra4NMJkNnZ+eqC9KFIplMYm5uDrW1tXC73di7dy9isRhsNhuGh4dRLBZp/KlUKpw5cwa33HJLVSKIDGq1moTLXnvtNXAcR+7S2WwWDocDt956K2w2G0qlEmUtNwITy2T3VKPR4Pz587Rws3dzcXERXq+X+GFMHfdSIJPJIJPJ4LbbbiMDSK/XC4PBgO7ubgQCAQwNDREnR6/XY3FxEZ2dnRXvTnNzM5qbm1d8frm/1GrIZrM4duwYjEYjcZucTideeumlCgXorUAsFqOtrQ2zs7PYv3//lj/vYuDqIjtcwTh37tyGKodMa6FcS0QikaBUKl02/AzGC2Ao1yUA/q9DYrtr/5vFagvJZswdl9em2b+r8RW5GMhmsxXcKeYfU67VsZPo7+9HoVCAw+G4KN+3FjweDwBUJep3Icjn8zQe2bte/h6wRX07s3FMQ6RcW4Rp97Cfs/HGbC+28tyZ7xVbJJn2DduUSKXSqrM6hUKhYv5iuijLOSwSieSy8ckqlUoolUrkiQQszRW5XA5isXhNDsx2zQVMr6o8I6FUKinDs11oamoiOsKVgGuZl8sE09PTeMtb3rLuMUKhELW1tZibm6P0cygUQktLywVH36w7IZlMIhQKIZfLkTT48rQsM/cTCoUwm82rZom0Wi3xTFQqVcUgLxQK8Pv9aG5uvqS78a2gVCqRMSMzYVMqlUilUhAKhdvW8rxVsLZ4JsMeiUSg0Wgu2n1nHKDp6elNd9BsJ0KhEGQy2QWrVXu9XtLCsdvtK1ShOY7D4uIicrkcdDodCoUCmfxlMhn4/X5otVrMzs6SVcZaYNLyTC13tWMjkQimpqao3GIwGLCwsEBtzUajEfPz80gmk9Q1dyG+YTzPIxKJkChcMpmERqOBSCRCKBSilnJ2TplMBmKxGEajcd1AzWg0wuFwUEAUCoVgMplQKpWIb1EoFFAoFCq4F6wrkpnKMu2bXC6HSCRCpaXy7BIr57JSk16vJy8i1vJeDeRyObmBG41G8jJiXWNqtRoSiYTOn5UZ4/E45ubmoFQqYTabK4KbYDCIVCoFkUgEmUyGSCRCejVarZbkK5iJan19PRb+P3tvHmVXVWeP7zfP86v3Xs3zkKqkqjKQhEASmRRUwG4UBVuxbbUFbNsGWYLNFwcGsVu0XSpCs7pd2AoKdkMrC6RtEYQASVVSqVSlUvPw5nmep/v7o9b5/N6rKVWVSlKhs9fKWknl1b333XvOuZ/z+ezP3lYrmpqayGdpx44dG2pmazabMTo6umHHO9u4GLxsAsRiMQQCgdMKRwFAR0cHCoUC7Shra2vXnRLPZDI4duwYZmdnMTg4CKvVCovFgoqKCrS2tuLyyy+nEgir+QIggbNdu3YtCnDUajV27NiB4eFhBAIB1NbWorW1ldysGZ/kQkShUMCJEydgs9nA4/GQSqUwOTkJo9EIsViMnp6eNVnTn020trYimUzC6XSCx+NBpVJh27Zt57SzrLW1lYT/zhcSiQRUKtW6OF2zs7N47rnnEI1GwePxIJVKcdNNN1HJdWZmBjMzM8jn8zh69CjkcjkaGxvppezxeFAoFEhPyGq14pJLLlmypm+32zE4OEidQhqNBrt27SoLhh0OB37zm98Qz+TYsWPo7e2FVCqFRCKBUCjEddddB4fDgaGhIRQKBXR0dODDH/7wmp47x3EYHR3F5OQkgPlxXywW4fF4AMyXerq7uyEUCsmvh113TU0Nenp6lg1gzGYzurq6MDk5iXA4TMdKp9MYHByk4K2trY3Wnlwuh2PHjmF6ehpWqxWRSIT8idhz4TgOcrkcu3btoiByYGAALpcLYrEY8XgcsVgMer0eIpEIxWIRW7duXRXpVSQSoaenBwMDAzSfGhoaKJunVquxfft2DA0NkTAnj8fD5OQkZcGYGjOPx8PMzAyGh4cBzJf93W436uvr4fP5SLbCbDajtbUVbW1tEAqF+OAHP4gXXngBExMTAICWlpYN55OpVKoLii96MXjZBGCputV0ZkgkEnIFBubTh+sl287MzMDn8yGVSiGZTJJIlkQigcfjwejoKMxmMxEESwmffr8fExMTS5LmTCYTDh48SCli5s/CcRwkEskFpeJYCrfbDavVisrKSggEAuj1eng8HvT09KzKUO5cQiqVYufOnYhGo+A4Dkql8px3QtXW1mJwcPCcnnMhFnKb1oLXXnsN2WyWghW73Y4//OEPaGtrQyaTwdjYGHQ6HaqqqpBKpWC329HZ2YktW7YgEAjgnXfegdlspvvucDhgtVoX8c2y2SxGRkagVCopc+ByuTA9PY1t27YBmN8wvPbaawiHw2UvwVQqhdtuu40ybBKJBDt37sSVV16JQqEAlUq15oA1EAhgcnISFRUVEIlEyOVy8Hg86OrqIuFD1hlz6tQpaLVaIggzc8XlfMt4PB6am5tRU1ODfD4PqVRKz0ej0VAGpzTg9Pl88Hg8ZIpYWVkJn8+HoaEhmEwm7Nu3jz43MTGBSy65BB6PB263GzU1NYjFYpiZmcH4+Diuu+46VFRUIJ1OY2xsDBaLZVUEUZ1Oh8suu4xsVRYGxBaLBTqdjrI9IyMjFFwxheLKykqIRCKMjY1Br9dDKpUiGo3Sn1QqhdraWqTTaWg0GoyPj8NoNMJgMMBiseAzn/kMdSxZLJYNz6Iyb60LBReDl00Av99floY9HTaqPBGLxSCRSJBIJCAWiyGTyejvpez5QqGAXC5XlnpmafHlIBAIyl4a57uFeCPAFlb2vaRSKUmDb6bAhYG5AJ8vmM3mZQ0AzxXWuyBzHIdAIFCWSdPpdPD7/chkMlTaYKUdVrJhAbtMJqOSAMNyc4a1Ipc+K5lMVrYLZuVdZrAIzL8w/X4/JBLJohLTWsi5C8H8jFhJghHAxWJxWat3JpNBsViksS8QCEhA7nSQSCSL1gSZTLZkqYw9v2QySe3gpZwf5hEmk8kQj8cBgEowXq8XExMT5OZ+8uRJ7N27F1KplEo1q8VS17zU/7tcrjICs1gsRrFYRDabJU8ids9Ye308HqcSESuDsf8vvT9LEX43Cszs8ULBhXOl72FEo1FaJEOhEBkZsrbmM0U2m0UikQCPx4NaraZjKhQKTExMEJEzFApBJpNR0KJQKBAOh+mzzBVVKBQiGo0uIkEWi0Wq9yqVyg2dCOz6CoUCFArFqrQIIpEIUqkURCIRdDrdqu8lM1QD5jNb7PeEQiFCoRCkUimUSiUtoOsNzBKJBObm5pDJZKDRaFBRUQGlUrmmzBTHcYjH4ygUCpDJZJBIJEgmk0gmkxAKhdBoNKc9Xj6fp/GhVCo3rLSk1WoRjUY35FjrBdPzWUqobykw7aNisQij0Yi5uTm6h36/HwaDgYibbOesVqupRVatVtP9zOfz8Pv9xOlIpVJLlhVZ8BGJRKDVakkbpLRTRSQSQaPRwGaz0TGCwSDUavW6d+BMZj+fz0Mul0MikSAcDhOfiwUFrCFgIb+Cdd5kMhlIJBIKJEoDkFLFX6lUSsH/Shljdl3FYpHcurPZLEKhEOLxOLRaLQWGuVyOmgBisRhlr9nv2Gw2yOVyGAwGRCIR6j6rqKiARCJZ9aYjnU5TgME2dFKplJ4Fc/5m18K4VhqNBul0GgKBgDY7EomEtKFUKhWmpqZQV1eHQCAAn88HjUZD5aZzyQ2MRCJnFPSea1wMXjYB0uk05HI5JicnMTo6Sk6oDQ0N2Lp16xm9TKLRKI4fP45IJAJg3seiu7ub0sE2mw0ejwdOpxOFQgHV1dVIJBLo7OxEJBLBoUOHiN8xNTWFZDIJHo+HrVu3lvkvZbNZnDhxAm63m8S4ent7N2QyZLNZHD9+HG63G8D8otnb27tiS/LMzAxGRkaoq6m+vn5V9zKdTuPEiRNkelZVVYWtW7eiUCjAbrdTOY0ZNfb29q7LBsHv9+P555/H5OQkPB4PRCIR9u3bhz179qCrq2tVpY5isYixsTEilMrlclgsFtjtdurUaGhoQFdX17LfOx6PY3BwkGTgLRYLuru7N2TRlMvlZY7W5wMmkwm5XI6IoSshl8vh5MmTsNvtNIa9Xi/GxsYAzAdj1157LZVnuru7cfz4cTidTnAch6qqKpjNZvT398Pr9SKZTGJmZga1tbW0a16qNMxk5Y8dO0bHYh5IDHw+H1deeSWee+45IlUqlUpcddVV6wqei8UiRkZGMDs7S+VcFowVi0UEAgHyxGJk5YUEV41Gg9bWVoyOjpJcQFVVFTUTpNNpDAwMwOfzIZ1OU0nJYDCgrq4OW7ZsWbTByefzOHnyJGw2GziOo3nmcrkwMDAAr9cLoVCI3t5eXHLJJRCLxXC5XOA4DgaDgdYkk8mExsZGDA4OEh9m69atiMfjsNls0Gg06O3tXdW9C4VCOHbsGBKJBIkRMm4T84k6duwYkskkAoEAotEo8vk8xsfHYTabaR1nG65t27bh+PHjiEajRDRm63A+n8eePXvg8/nQ2Nh4zrRsgPlS5WYyUz0dLgYvmwBsx8Jq6FKpFPl8HjMzM6ioqFi3sFWxWMSJEydoF1csFuF0OqFQKMiUce/evUgmk6QIunPnTtTU1GBqagq5XA5msxnRaBR9fX1obGxEXV0dcrkcUqkUEokE1YsnJibgdDpRWVkJHo8Hj8eD4eFh7Nmz54w5LnNzc3C5XGRWFovFMDQ0BJ1Ot+TiE41GMTIyQrX4fD6P2dlZctxdCSMjI3C73aisrATHcbDb7RCJRJT5ufzyyxEKheByuaDVatdtoPnaa6/BbrdDKpWiqqoKyWSSnr9SqVwVkdDpdNICKRKJ4Ha78bvf/Q47duxAVVUV8vk8pqenodVql3xpchyHkydPIhwO0/d1Op2r9pw5Hc6GHP5aYbFYIBKJiFi9EqanpzE3N0ecJrfbjd7eXpp/VVVVZccwm8247LLLqGtEp9NheHgYPp8PVVVVqK6uhlwuh0wmw549e6DVapcNIisqKnD55ZcTYVWn0y3KdNTV1eGv//qvMTMzQ+TY9a4NDocDU1NTpPvDNk7Mr0ej0cBut6OpqQkGgwEmk2nJa29tbYVer0cymSRTSRaQzM7OwufzQa1Ww2q1Ip1OIxaLoampCdPT05DJZIuaFObm5jA7O0vX5fP58OKLLyKRSGDfvn3g8Xik/Nvc3Ixt27YRoZrpSAHz3Jquri4KggwGA8RiMSYmJtDY2Ije3t5Vld4LhQKGhoaIn8OCcebkfPLkSWoX1+v1mJ6eRiwWw5YtW9DV1QWXy4Xm5uYyP7PKykoolUokEgkKYJhRJ+v47OrqQmNj4znlB05OTuL6668/Z+c7U1wMXjYBRCIRUqlUWf2YpVdX4pWcDplMBtFolKJ3Pp9PLX8sI8JIgkzwqqGhgRZhFoUzoTGO4yhN6nQ6y2rbfr+f0p0AYDQaEQqFkM1mz5jvEo1Gy8o3KpUKTqeT0tULsdy9PF0tnqX5DQYDnUur1cLr9dJOXCgUoqKiAiqVColEAoVCYc3lsUKhAK/XC5VKBa/XS0GY3++HUChEMBhcVfASDochkUjoJSeVSpFIJOh6mDHjcqUblopnPAr2AtgonspCTY/zAaFQiJaWFpw4cQJ79+5d8bOBQIDagYH5gMLn86G1tXXZFudSki0wX8opLdVVVlYiGo2uijirUChO+0I1GAwbshuPRCJUxgHms5mlejBKpRJqtRoVFRUrChkyt/WlEIvFEAwGMTo6iomJCeL0sLKy3+9fFLwEg8GykrNGoyETUaPRCB6PB7lcToKAK/HNJBIJ9u7di4GBAYTDYXAch+bmZmzfvn3V5SJmoMhk/IVCIaRSKWKxGKRSKSmds0x1sViEwWBAPB5HQ0PDsj5TTGg0m81CKBRSFlmv15MR5LnsDAyHw7BarevuXD0fuChStwmgVCqpHMN0ItLpNFKp1Bml75lFeinpK5PJUO21WCzSzri0rs0mDQucBAJBmRgXE5krfWlLpdKy87A670aIcykUirIgjvFYWNAXi8WIt8O6Adi9ZNfLdk4rgc/nk2gWQy6Xg1gshkQiKSuBZDIZiMXiNX2/dDqNaDSKXC4HjUZDO/ZcLod4PE4tn6sN9iQSySIhr4UGcOx5L4WVxsdGYLPU0Ht7e/H222+f9nOMqM7AXixrecYymaxsrKbT6TWPk9WC4zhks1nk83kUCgWk0+lVZ7oWjh1m6Mjmfj6fJ1uD9YJlE9VqNbRaLZLJJNxuNzUALLW2LZxn+XweEokEqVQK0WgU6XSaApGFgd7C714oFKDT6bBv3z7s2rULe/bswa5du9Y0vtk6k06nif+TTqcpo8vn8yESiRAMBumeJZNJmsPZbBYCgQCRSKRs88TuwcLsJKMMnGuLkXfffRcqlWpZx/PNiIuZl00ARiZraGjA+Pg47HY7AoEA9Ho9vF4vTCbTuoIYkUiE9vZ2DA4OUpZAJBKhqakJGo0GNTU1sNvt1JFRX1+PbDaLQ4cOIRAIYGRkhAwKWSrd5/Mhm83CZDKV1Uebm5vR12E/fQYAACAASURBVNcHt9tNwU5PT8+GkHZLNRDYjnbbtm2w2+2YnJxEoVBAJpMhLoJcLqd7xwh2lZWVpzVy4/P5aG1txfHjx6m1O5fLobOzEwKBAP39/cS7AYAdO3asOq1rtVpx6tQpavfcsmULPB4PfD4fZmdnIZVKsXv3bqhUqlWrwVZVVcFut8PpdEIsFiOVSmHnzp2Ix+PUEaPT6UgqfiEEAgHa2tpw/PhxUuvk8/kbZvjm8/nOac1+Oezbtw/PPvssXC7XimWWpqYmBAIBuN1uCuq6urrWNPdaW1vR399Peh/A/DjZ6F10KpXCyZMnEQgEEAwGkcvlYDQaoVarsXXr1tPqDVVXV9PYYWq2W7ZsQSgUIrJuc3PzunWLQqEQpqen4ff7EY1GqQtJq9WStH5pKYWhvr4ebrebOnbsdjuJ/B09ehRCoZB0Vdh89vl8GBsbQzqdhlarRUdHB4LBIMbHxymA2bp166o9c0ohEonQ0dFB3Bkej4doNAqLxQKPxwOLxYLZ2Vn8+c9/JrVztgmy2+3g8/mYnJzE+Pg4hEIhWltbqUzHWtkVCgWVa5PJJMxm8znvEvyf//kf7N2797z6sq0VPG6z6MpvIM53e+Za4fP58KlPfQovvPACZmdnyYNGr9fD7/ejqamJ9B7WCo7j4PV6SRm3srKSCKb5fB4ejwepVApyuZxe0AqFAhKJhGrrO3fuJO5LLBaDQqFAdXX1okWdcUFYp4bZbN6wmi0zb2OGZ9lsFn19fTAYDBRwyeVy7N69m3a+LCUtFovJ5G0198vtdlOQUl1dTWnzYDBIRF6j0XhaDgVDMBjEO++8A7VaTSnvdDqNtrY2uFwueDweyGQyNDY2oqqqak1qqIlEgtRWNRoNaWBEo1FIJBJUVlauuNNk48Pn84HP59O42wh861vfQjKZxD333LMhx1svOI7D7bffjquuugq33377ip8NhUJwOp2U/mccrrUgEonA5/OB4zjo9foND+CKxSL6+/uJ6D04OIhcLofu7m4qI+7bt++0GYZkMlk2dliZLJPJQKFQwGw2ryvoSiaTeOedd2C322Gz2Ugqn/k/7dq1C52dncs6bEejUTidTvj9fkxNTaGhoQGzs7Po6+uDQCDAjh07oFQqUVNTg7a2Nhw+fJjKOZFIhDJRjOfCyNqXXHLJul/OPp8PoVAIwHypjGXkJiYmKFMbCoUQDAaxbds2mEwmFAoFTE1NUQkunU5TEFNXVwexWEwyGXq9Hul0mgjK51Jawufz4cMf/jAeeeQR9PT0nLPzLofVrqsXMy+bAEajEUqlEmNjY+DxeOjo6KBdgsFgIIGo9SwkPB4PZrN5yayDUCgs25WzLgbGim9vb4fD4YDJZIJOp1t2sWFYzWfWC4lEUiZ8NTIyQhoroVCIUshML4PVjU+XbVkIHo+HysrKJXfoer1+XS921j7OnqlKpUIsFoNMJsNll1225uOVQqFQoK2trexnpzMTLMVK4+NMMTY2hgMHDmz4cdcKHo+HG264AU8//TRuu+22FXfgGzGGNRrNujrQVotUKgWfzwez2QyXywWJRAKVSoVIJILOzk44nU7iZKwEuVy+iHC+GqHM04G1Wre0tFALcSwWA8dxOHjwILq7u1dcy9RqNdRqNWw2G0KhEJRKJXK5HLZt20Zimnq9ngLNXC5HWWCpVIpDhw6hqqqKSpYWiwVutxuJRGLdNhFLmSeGw2Ekk0maa0ajEX6/H1qtFu3t7fB6vZiamqJzMq6MWq0uuzaPx4MdO3asSv7hbOCZZ55BXV0duru7z8v514uLnJdNAB6PR+WdhYZeCw0AzwSnS7It5EuwNOl6zn22E3qsAwiYv3/s70xngeO4VQV75yLxuFF17fOZJF3ruROJBKamps6ae/lacfXVV0MsFuOZZ54535dyxmDjms1Pxl1j7cqrHftnG1KpFJ2dnairq4NGo8GWLVvWZFFROpeZtAP7bplMhsozbH1i92ChQWopt28jwWwAFnLkGE+IXf/Caymd90uZOpZ+9mzD6/Xiueeewy233HLBKZ9fzLxsEvT29uJPf/oTPvrRj2JwcJAGfCKRQHd39xkNrEwmg/Hxcfh8PohEIrS2ti6pkWIymTAzMwO/308pWLPZvKYdQTgcxujoKBm5bdmyZd27nZXAjMqYrkw6nYZOp0M+n4fT6YTRaFyxXh8IBDA2NkbCYR0dHatWLS4Wi3A4HHC73eDz+aitraXSUiqVwszMDOLxOBQKBZqamlBRUQG9Xg+HwwG5XL7murbP58P4+DjS6TTt2JghJGtVXQmpVApzc3PkxcPKh7t37z5tq63L5SIhw4qKCrS3ty+b0g4EAnA4HOQmzThXmwFisRi33XYbfvzjH+NDH/rQuluMAZCnVTgcpk48qVQKs9mMmpqaVb+cx8fH0d/fj1QqhZaWFuzdu3dV5QKpVIra2lrMzMzQSz0ajaK6uhpOpxMmk2nDMz9erxdzc3MoFAowm82or69HLBYjkUWdToeGhgYIhULodDqo1WqMjo5ifHwcbrcbOp0ORqOx7MVdKBQwNzdHHKO6urqydYlJ4zM+yOTkJPFfWBdYZWUlEokEDh06REFKdXU1mR0C/3+Wtq+vD21tbaipqTnjF3U6nYbNZkMwGMTk5CSamprI3Ztls7VaLfEKWUNDU1MT8vk8wuEwhEIhIpEIampqyrKBHo8HY2NjlEUuzcQzRKNRzM3N0Wfq6urWVRL74Q9/iIaGBlx++eVndD/OBwTf/OY3v3m+L2KjcSGZSzGo1Wr8/Oc/x80330xeKUKhEG1tbairq1v3ZCsWi2S6qFAoSJiOeZSUgjmZJhIJ5HI5VFVVrYmwmEgk0NfXRy/WcDgMr9dLWhsbCbFYjIqKCnLw7ezspPStxWLB1q1bl30RRCIRHDlyhOTdA4EAQqEQLBbLqhaAqakpDA0NkRorIxWKxWIcO3aMRM68Xi+CwSCqq6tRWVkJoVAIPp+P6upqdHR0rOq+hkIhHDlyhDx63n77bdhsNlRWVpLxoslkWva7ZjIZ9Pf348SJEzh06BBOnTqFWCxG/KSampplO4K8Xi/6+/tJGt7tdiOVSsFisSwaj36/H319fYjFYshkMnjmmWdQUVGB66677rTf8VyhsbERAwMDeOedd3Ddddeta04xk0CHw4FUKoW+vj4KSl0uFwQCwao4LhMTE3juuedIon54eBiZTAatra2nvS4ej0ft/NlsFkajETU1NdBqtaisrFwzyfh08Hq96Ovro84mm82GeDyO6elpUs9lQSvzRxMIBPjv//5vmhuMfNvS0kLrzvj4OOmkpFIp2Gy2spKKQCCAyWSCQCCAUqlEc3Mz6S21trbCYDDAarVS+YZlQqqrq9Hd3U3dTsViEZ2dneDxeLBarVCr1WdUosnn8zTPdToddRG2traiu7ubNmt8Pp+UfAUCAcxmM7Zv3w6TyUTKxsyolvHxgsEg+vr6yHDS5/MhEomgsrKSguJoNIojR44gGAwim83CbrfTvV/LmH7jjTfwxBNP4Bvf+MaqeSbnAqslVl/MvGwS1NbWorm5Ga+88gpuv/32Dak9A/MBBRNdYy9mn8+3rJrimehIsE4FtvOQyWRwOBwIh8PL6mScCZhT8loRCASQzWYp2JFKpXA6nYhGo6tSYZ2enoZer6fvFAwGMT09jcbGRvj9flRVVYHH40Gr1cLhcCAQCKCqqmpdJRSPx4NisQi9Xo9wOEzPkOlrOBwOIv0tBZ/Ph0AggFwuh0KhgKamJiQSCeIMTExMLKtUzDo+WAZLKpUSd2Dh4j87Ows+nw+j0Yh0Oo1Tp07hxhtvpMzEZgCPx8M//MM/4M4778Qvf/lLfOpTn1rzMRgZt6qqCqdOnYJer0c2m6XnMTMzg/r6+tNmUI4ePQoA1HGjVqsxMDCAyy67bFXzTygUoqOj45yU5WZnZyESiei6pFIpjh8/DoPBQF47SqUSNpsNjY2NUKvVCAaDkEqluPLKKyEUCsFxHCYmJjA+Pg6TyYRsNou5uTlUVFQQNycYDGJubq5sPEqlUvqO6XQaoVAITU1NtBnyeDyIRqO44oorqCTjcDggkUiwY8cORCIRGI1GCg7y+TzsdvsZZd5CoRC8Xi/Nc71eD7vdDpPJtGgeCoXCRd17TAl7KTBNqdI553K5EIvFiIvFNK7YMZgIYGNj46qDMo/HgwcffBC33HLLuoU2zzfOf2H0Iggf+MAH8OKLL67JLGw1WFgDZ7Xxi5jHWnYrLDVd2rnE+DdL8ZMYJ2Gjrm/h8U+nYstaN1kZUigU0jGY4+1asNy4KdUBeuuttyAWi9Ha2lpW798MqKysxFe+8hX8+Mc/xuHDh9f8++xeMx0hdj+ZDEE+n1/V82b+ZQwswNvoub8RYB5HDEKhkDyFSn9Wyu9g46Q02GZaMsDS84gddzkw/svC+cp+dq7afEu5NQwCgeCsjfWFc26hgeLCe386pNNp3HPPPairq8Ott966odd6LnEx87KJcPXVV+PnP/85Xn75Zdx4443Lfi4YDCISidBOdyWuBlPOfPfdd2GxWKDVapHJZM5Kd4lWq6UyjEKhIN7H2ey8WAuY4idrVQ6Hw8Tt0Wq1q9q1MBlwpvFQLBYRiUTQ0dEBlUpFppUymYz4Q1VVVTAYDJSp8Xq91FJusViWLMMwGI1GTE1NIRqNkn4OE5djsugrcV6Y0aNGo4FAIIDL5aJ2bZlMVtbBVSwW4Xa7EY1GqYRotVoRjUap5dRisUAul6NQKMBms8Hn85Gbrs/ng1QqxSuvvILe3l4YDIZN6SZ+4MABTE1N4Wtf+xqeeuqpZXeeTAmZafOYTCbS5WDZrtHRUcjlciiVStK1Wc13bm5uxvj4OLRaLSQSCdkSbFS3HuNlhcNh5HI50ieRy+WorKwkQUfG0VgpO2axWDA0NESKvF6vF/X19cjn80in05BIJKROzNYiJq3wv//7v9RNKZFISMNIIpGgoqICLpcLKpUKHo8HU1NTaGlpIQ2UeDxOnlAKhQJSqRQWiwU2mw1GoxH5fB6ZTAbZbBYvv/wydDodNBoNLBYLNBoNpFIpKisrYbPZYDAYkM/nkUqlyqwvWGmbtcazdnEmHcA6m0qhUqmoy1Gj0ZDA6EascxUVFZiamkIwGEQ0GoXdboder0ckEoHH40Emk0EikYDX6yVJEMbzWU25JZ/P4/7770cwGMS//Mu/XFC6LgtxkfOyiSASiZDJZPDCCy/gox/96JIDy+l0oq+vDx6PBy6XC16vF0ajcckFs1AoYHBwEH6/n8h1yWQS+/btQ21t7Yazy8ViMXQ6HdWgVSoVenp6zlsLYCnC4TD6+vpgs9kQjUaRSqVoR6PT6dDd3b2qyc+ChXg8Dp/Ph1Qqhfr6erS3t0Mmk5F1ATPsq6urQzqdRjAYhNlsht/vR39/P5LJJBm9yWSyZcnFcrkcKpUKfr8f2WyWSI2s26K7u3tF+XbmFhyNRlEoFBAMBunFceDAAXR2dlKX2cjICIaHh0lno1AooLGxkdx4LRYLurq6IBKJcOrUKZw6dQrFYpHKhXq9Hq+++ir6+vrwuc99btXGd+cDPT09sFqt+Ld/+zfs379/0f0vFAo4fvw4RkdH4fV6Ybfbkc/nUVVVBZ1OR1wPYD5tLxQKYTAYSGvldGDeU5OTk8SLuuGGG9YtClcKjuMwNjaGkydPIhQK4dChQ3jjjTdgtVoxNjaGI0eOwG63UzDLRNeWe5Gp1WpwHAePx4NEIoGKigrs3r2byojRaBRKpRI9PT1QKBQoFAp44403MDo6CqfTibm5OcRiMdx0003o7e2lrIVOp4PP58Of//xnHD16FLFYDMlkEsPDw8TR8/v9CAQCJNSp1+uJ9xIOh0l7yeFwwOl0Ip/PY/v27cQT1Ov1KBQKiEQi4PF46OzsRHV1NbmEHzlyBH6/H+FwGHa7HbFYDKOjo4hEIggGg3A4HNBoNGUbRFZK9fl8CIfDAICtW7duyIZQLpdDo9FgaGgIo6OjUCgUUCqVePfdd8nt3OFwYHJyEoFAAOFwmLyUTiduWSgU8OCDD+LIkSN49NFHz8oGdiNwkfNygeIv//Iv8bvf/Q7PP//8opRePp/HyMgIFAoFBQQejweTk5PYsWPHomMFAgE4nU40NjaiubkZuVwOLpcLMpnsrLXF6fV6XH755YtSzecbY2NjyOfzlGlgLtuXX375mjkZMpkMl1xyCVKpFHg8Xtn9ZHXocDiM3bt304vMbreXqemyl1Q8Hsfk5CRqa2uX7VKprKyExWIhHyWm/MsIwKdDfX09TCYTLrvsMkovy2SysusOh8NlhnjsmmtqavC+972vrMUzkUhgdnaWDCEBwO12QyKR4PDhw/j0pz+NAwcObOpdHZ/Px1133YVHH30UX/jCF/D444+X+ex4PB7Y7XYyA2VGqZWVlTAYDLj88sspC5bNZlEsFiGTyVb9nUUiEa677jrs27cPuVwOWq12w0jtiUQC09PTMJlMsNvtKBaLyGaz0Gq1kMvlOHHiBFQqFcRiMUwmExwOB7xe74pKzJ2dnWhqaiLPMD6fj7q6OnAch1QqBYPBQJkHl8uFo0ePYvv27di7dy/S6TSJ4ZWuOzKZDEqlElVVVZBIJKiqqoLX68X4+DhkMhmEQiGMRiPNHcYl6unpQT6fx9tvvw2Px0MaJeFwGDweD16vl3zPmPv3UqWeyclJItUC80TY119/Hb29vTQ/Q6EQ8XRKYTAYsH//frIJ2ciGBI1GA71eTyaZDocD8XgcHMfBaDQiEAgAAPbu3UseSIFAAKlUalluYT6fx7e+9S289dZbePTRRzeMU3k+cd7fLrlcDk888QQGBwcRi8VgNBrxsY99DO973/sAzLuM/uhHP6KF9fbbb98Qx9vNCoVCgU9/+tN48skn8f73v7+MQJrL5ZDNZssyGXK5HIlEYsljMa8N9oITiURkBXC2sZkCFwCUImeQy+UUwKwHfD5/2XIdM48r3YEzD6OFZoXMN4VxU5YDU/Vkf19PwLUSaTqfz4PjuEW19HQ6vYhPUCgUUCwWF3E2nn/+efD5fPzVX/3Vpg5cGAQCAb72ta/hsccew+c//3k89thjtAnIZrPg8/n0TNh9YZwMPp9fZvy5HjBS90ajUCgQB4dl6IRCIQWg7CXOykksODsdSkXv0uk0+vv7EQgEIBQKKbvS0dGBdDpNHl0CgYBKPktlxBOJBJWY2bhmgUYpT2shF4Z1WpXqvDB5fUZOX/j5hUilUmVzlI330ucpkUjIKmThho+VbzcabH6x+ZrP5yEWi+kZsY2hWCyGUqkEx3EIh8PLcl5SqRTuvfdejIyM4Lvf/e6G2X+cb5x3wm6hUIBer8dDDz2EZ599FnfeeSeeeOIJjI6OIp/P46GHHsKll16KZ599FjfddBMefvhhxOPx833ZZxXXXXcdamtr8Z3vfKeMrCWRSKBUKumly3EcotHoiiUHPp9PiwYzPFuPx8eFDq1WS7sXYD7ToFQqz4rrsUKhgFgsRiwWAzAfOEWjUWQyGajValpoYrEYJicnN8zA8kwgk8kgEolobuXzeeTz+SXbqOVyeZnbdjabxfj4OH7/+9/jjjvu2DBjx3MBoVCIe+65B1dffTXuvPNOvPTSSwBAJpnshVHqnXW2kc1m4XQ6iVMUDAYRCATKDDQZYrEYPB4PAoEAkWFZRiMYDJJzMduVZzIZMhgUi8WkgOvz+WC1WpfdCJUil8vh+PHjOHXqFNkImEwmTE9PIxaLQaPRkGs002BKJBJLdvhotVoKtrLZLAX3jGfEAnvWxRMKhWCz2eB2u6FQKGh9y+fzZNBqNBpXNQYNBgOi0Sg9Z6ZZc/ToUTidTupuYm7Wp0OhUMDs7CwOHTqEw4cPw+VyEcnY5/NhenoaNpttyedYCqlUCo1GQ/NLKpWSSncwGEQmk6EAJpvN4tSpU8hkMksGh263G5/73OcwOzuLxx577D0TuACbgPMiFArR3d1NxMKKigrq/c9ms3jrrbdw3333QSgUorGxEW+99RakUumK7pcXKueFgc/nY8uWLXjyySdhMplI6IvH40GtVsPj8RDxtKKiAl1dXUvuAJhdvMPhQCQSIfO1UpLm/xVoNBpqcWREwN7e3rPyohWLxcR9CQQCREDM5XKUAZqamsLg4CDy+TxkMhmJwJ0vZVSxWEyt7cwBt7m5GY2NjYsWbj6fD51Oh1AohEAggFgshl/+8pfYu3cvbrnllvNy/WcCHo+HXbt2QaPR4LHHHkM4HKZSGUvZp1IptLe3L1ta2Sik02kcPXoUExMTsNlseOONNzA3N4dAIACfzwedTkdj1m63o7+/HzabDVarFel0GhUVFRCJRPTyS6fT1BnENi81NTXQaDSQSCRwu91IJpPgOI44dAaDYdl5wXRumLcS45Lo9XoSymPk9OnpabIq2LVr15KlRLVajWQyiVAoRCUuJj5XLBbJGJUZSfb398PlcsHpdNJ6yH6Xz+ejt7cXu3btWlWQqdFoEI/HYbfbceLECUxNTZUJOkajUbS0tKzKYLZYLOLo0aN46aWXMDw8jLGxMczMzECr1SIajeLYsWPw+/1wOp0IhUIwmUzLHrN0frEAkOM42Gw2zM3N0VjMZrMYGBhAOByGVqslcVFWvuvv78edd94Jo9GIhx9+eFNpuayEC5bzkk6nMTk5ieuvvx5WqxX19fVlC3pjYyOsVut5vMJzg/r6enz+85/HP/3TP2Hr1q0UMTOL91gsBj6fTwJQy6Gurg4Gg4Fqs8sJkr3XwUwbI5EIOI6DWq0+qxkCs9mMAwcOYHx8HNlsFg0NDRAIBGRuKZPJsHv3btLOmJubI6XM84Xq6mpoNBqkUil6AS6341Sr1bj00kuRSqXwz//8zxAKhfi7v/u7c3zFG4sPfehDqK+vxyOPPILh4WE8/PDDqKqqoizA2fLtKoXVaoXf70d1dTWmpqaou6SjowPRaBRDQ0PYt28fUqkUhoeHoVAoiCRbOoYY94x1whQKBQQCAQgEAgpckskkDh8+jOrqaspseL1eTExMYNeuXUten9PphNvtRmNjIzKZDJRKJaxWK6RSKQXAPB4P27dvR21tLcLhMPmSLRWYy+Vy7NmzB+3t7eTHpNPpqIQjEokgk8mQTqcxMjJC5qYcx8HpdKKpqQnbt28n7SGNRrPqUo5UKsWuXbsgl8sRDAapY4hlSpj56mrWCb/fj+PHj4PP56Ojo4M6995++20yTC0NOq1W6yJPslKoVCpceumlSCaT8Pv9KBaLRJcoFotIpVJkUNvY2AihUIhkMknaQ7/61a/w1FNP4cYbb8RnP/vZTVfG3whsqm/EcRx++MMforW1Fdu3b8f4+PgiXoFCoViUWfH7/WVO0qUkrAsZH/nIRzA8PIyvfvWrePrpp4nrcjr+wkKwBe7/Opgq77kCKz2wNmVg/qXvdDqpDZOBdQSdbyiVylUHuEKhEH/84x/xhz/8Ad///vc3TUv8maCnpwdPPPEEvvvd7+KTn/wkvva1r61bjXc9YIEtj8dDLBaDwWAgHgfrcspms5RRYfNaIBBAIpGUldTFYnEZN2phyy/jwJXudFfi0AHz/AmxWEwlF7fbTVng/fv307FYFn01840RhxeSYkuvnbVEs+wBI8pnMplVn2cpCAQCCtRjsRhlbGQyGdRq9ap1kFjJSyqVEkdMLBYjlUpRBpxBKpUilUqd9phCoRBqtRp+vx8CgaCM65hIJJDJZGAwGCgwkcvlmJqawp133gmr1Yr/9//+3xkbv25mbJrgheM4PP744wgEAvj2t79Ng3NhoLKQeAkA//mf/4mnnnqK/v2Zz3wGX/rSl87JdZ8tcByHSCSCr3zlK7jrrrtw77334oc//OE5iaAzmQzt0tRqNd1vVrtmP2cttvF4HIVCAXK5fEPVVNPpNNLpNMRi8QXL02ELLAPbxTOuCNPhCYfDqKmpWZIYuFnR39+PRx99FPfeey8uvfTS8305GwadToef/vSneOaZZ/DQQw/h1VdfxS233AK9Xg+TybRqkm0ikUA6nSbC6mqgUqlIdl4ikZAuDyN2s9Z09lJlXTUcxyGTyaxpUyMSiaBQKBAOh2E0GsFxHILBIEwmE9Lp9JLXrFAo6NwtLS3QaDSIRCI4ePDgsqqxp0MsFqN5sdwmi5F/p6en6aUeDodhMplQLBaXzOoUi0UqicnlciqdjY6OIp1Oo6amBmazmTr4hEIhEokErbHFYrFMMbdQKCCVSoHP5y/q2JTJZJBKpfD7/dBoNCgUCkin0zAYDFAqlaR5FY/HEQgESFl5NWBkXbY2sL/rdDri1QDAK6+8gueeew579+7Fr371q03bCr1R2BTBC8dxeOKJJzA9PY0HH3yQJk1dXR3+67/+q2xwzszM4Nprry37/ZtuugkHDx6kf/P5fDLluhBRLBYxPj6Oubk5cByHa6+9Fk8//TQefvhhPPDAA2f15TYzM4OXX34ZXq+XpLn3798PPp+PgYEBCiZra2vR2dlJ11ksFqFQKNDb27tqw8GV4HQ6MTQ0RO2oHR0daGxsPOPjnmvU1NTA7XbDbrcTUZJZGoyOjpKJITC/QOfzedJS2cyYnJzEPffcg7/4i7/AwYMHL+j5thw++MEPQiwW4xvf+AaeeeYZdHd346qrrsLHP/7xFTl3+Xwehw8fxqFDh5BMJmE0GnHNNdegra3ttHO3vr4ewWAQTqcTQqGQMgtM14TH46G/v5/O43a7KQCuqKggy4vVgM/nY9u2beTVFAwGEQqFSKels7NzUUttVVUV/H4/bDYbdSrt27dvXYELswyYmJig7rWtW7cuycnj8/lwuVx47bXXKPPU0dFB5ZLu7u6ywCebzWJ4eBhOpxPAvPhbXV0dfvazn2FwcJACgd27d6Ojo4OCQKfTiWKxiJqaGrS0tFAZN5FI4MSJEwgEAuDxeKivt0PvNwAAIABJREFUr8eWLVsoo6rX67Fv3z784Q9/wMTEBHg8HmpqanDFFVdAJBLh2LFjGBoagtfrhV6vh9VqJcPW08FsNqOyshIOh4O6RRsbG9He3o5isYjjx4/jN7/5DaxWKz7/+c/j05/+9AX9Dlxtefa8E3YB4Mknn8TY2BgefPDBsgFYUVGBV155BYVCAS0tLXjrrbfwxhtv4Pbbby8jZMnlcqpPsh3EhfzH7XZjZGQERqOR9BgsFgt+97vfIRaLYc+ePWclgAkEAnjppZcQDAZJxM7n8yGdTsPj8QCYd56Wy+Ww2+20yDIX22QySXoRZ9I9E4vF0NfXB5lMBoPBAIFAAKvVCr1ef8FlYEQiEUwmE5RKJbRaLZqamoiHpNVqiXi4fft2aDQaOBwOSrlvVtjtdnzxi19Eb28vZTjP95w5G3/sdjteffVVKjcODQ2Ru/ell166bIA5MjKCV155BTKZDBaLBYFAAHNzc2hqajptSU4oFJLjeF1dHXp6elBdXQ2VSoVIJEIqsHK5HPF4HFVVVWhsbERNTQ1aW1vX3A0lk8lQWVkJmUwGr9eLpqYm6gpiL9jSbA6fz4fZbIbBYIDFYkFTU9O6My4+n488ktgLy263w2w2L/oeR44cQV9fH9rb26njkhF04/E4kYXZujgyMgKr1Qqz2QylUgmPx4OXXnoJJ06cQHt7O+RyOebm5uB0Oongq9VqsX//fvT09GDHjh3EJSkWixgYGCChSalUCpvNBpFIRMEHm7MtLS1oaGhAT08P9u7dS3M/n8/D7/ejs7MTbW1tyGQyq14rmamjWq2GVqtFQ0MDae68/PLLeOqpp1BXV4eHH34YV1xxBYALez5eMIRdr9eLl19+GSKRCJ/97Gfp5x/96Edx88034/7778ePf/xjPPPMMzCbzfj617++KRRbzyZY6pKlLxUKBUwmE+6++25873vfg1gsxu23377hAQxTStXpdGUqki6XC2q1mkS8mHYDk65m16nX6+F0OpFMJs+ofBSPx8vadFmZJZFIXDCM+VLIZLIl08R6vZ4csdmLkLUgb9my5Rxf5ergcrnwxS9+EU1NTbj77rvPW3fUuYDP5yNDvJaWFjQ1NeHPf/4z/v3f/x1isRh33333ksEIK22wANRiscDhcMDn860qlS8SiRYFBNFoFNPT01SyYk7LAoHgjDOSjEOnUCjo+MwVPh6PL9oJbxSnMJFIgM/nU6CiUCio022hwaHL5SIybzAYRH19PUKhEJLJJInbpVIpKBQKcNw84Var1VJgoNVqMT09TTIGPp8PFRUVCAaDiMfjaGpqgtvtpkCxFOl0GoFAgLoB+Xw+VCoVfD5fmbAhsLyxbTabhcViofWLrZWMQ3Q6iEQiykhxHIc33ngDP/jBD5BOp3HffffhwIEDF0y5eaNw3oMXk8mE3/72t8v+f0NDA773ve+dwys6/xCLxSTKxNQxgXky4Te/+U088MAD4DgOd9xxx4YMWGZ1D4A0FoD5ScJq0UxzgZX0WKdBqXhULpcjQawzgUAgIIM79nIsVXgtBcdx1Aq6EVop+Xy+TPjqTMBxK/NX+Hw+SQKw4KWUhLkWFItFcBy37nvAnjWfz182o+BwOPDFL34R1dXVuP/++zd9aWs9KH1mjAQbDAYBzL9cd+zYgUwmg8OHD+PGG2/EHXfcgRtvvHGRuB8TGmO8MI7jzmheiEQi4r2wOZhOpzfMrV0gENBcYgJ3y805hlwuh2KxCLFYvK75IhKJUCgU6J6zvy+8T/l8HnK5HNlsFhw3bzKbTqfB5/OJD8LmEjCfBSldx4B5vopKpUIgECAD1WQyCaFQCJlMRj9bKhhna0upGWUul6MAi+M4Ou9yKF3T2e+XXvNqMTk5icceewz9/f34yEc+gk996lMXXDZ6o7ApykYbjQtd50UqlSIcDuOtt97Cm2++iRMnTkChUKCtrQ3JZBISiQQ//elP0dfXh8rKSigUinUtYhzHYXZ2FkePHsX09DSlYv1+P4LBIBntXXXVVTCbzaQlEQ6HIZfLSZI7FAohk8kgEomgubmZrOLXA7fbjeHhYUxPT9MOlnVdtLa2li1ssVgMx44dw+joKGw2G8Ri8aId22oRj8cxMDCA0dFROBwOEvpaD7LZLPkEORwOiESiJbOFfD4fPB4PVqsV+XweiUQCuVwOXV1dyGQyGBoawtTUFOLx+JItoBw3r/3w2muv4dVXX8WpU6eQTqeh1+vXlPlKpVIYHBzEyMgI8ay0Wm3ZM5yZmcHf/u3foq6uDg888MCGErM3A1wuF06cOIGZmRna+UskEoTDYdhsNjLCE4lEuP7663HgwAFEo1E8/fTTePXVV1FbW0ulVolEgqmpKZKp93g8aGpqwt69e8vuWzabxejoKE6ePAmHw7GilIFIJAKfz8fs7CySySTC4TBUKhU6Ozs35FmIxWKMjo7i7bffxtzcHObm5lBXV4fOzs5FL9hisYiJiQkMDAxgZmaGslNrDc6YKarb7UYmk0E4HEZ9fT0aGhrA4/EQiUQwMDCAsbExZDIZhEIhEo9zOBxobm5GXV0drTulIngSiQQ2mw3pdBrJZJIMGfv7+zE0NASPx4NwOIxdu3ahs7MTwWAQdXV1qKmpWVJJt1AowGq1kmFksVhEe3s7acTMzMyUzZtcLoeJiQl6tiqVivRsStdKg8GAsbExnDp1itY8puujUqkoK+X1evH9738f3/72t8Hn87F//35wHIdQKASJRAK1Wv2eybysNhi7GLxsQjC57aNHj0KtVsNoNCIUCmFmZgaFQoFKKq+//jqmpqZgMpmoFrsWeDweDAwMQKPREGdFJBKhqakJEokETU1NuPLKK9HY2Ai9Xk/6EBaLBR0dHVR/F4lEkMvlaGpqQlNT07pLCYFAAH19fRCJRKisrKRujW3btmHr1q1l3y+Xy6G/vx+RSAQ6nQ7FYpF0Ltaauchms+jv70coFKL2SOZcu9agsFgs4sSJE7BaraTDYLVaodVql3wxsZ8Xi0UolUps2bIFYrEYfX19JFXucrmQSCRgsVjK7q3dbsdbb72F6elpCAQCxGIxBAIBcByHqqqqVe3qGOHP7XaX8YuYQRwADA8P44477kBXVxe+/vWvv+cCF4/Hg8HBQZJcZy/T+vp6WCwWeom0tLTgAx/4AL1Yu7q60NvbC4fDgV/84hfo7+9HY2MjWltbUVVVRTL5XV1duOaaa8oCa47jMDQ0hJmZGRIptNls0Gq1y45frVZL47uqqgrt7e0bJoHAFHbVajXUajVEIhF0Oh0aGxsXjaPZ2VmcPHmSvJJcLhdSqRQqKyvX9AIVCATEoWOl1ZaWFggEAqRSKRw5coT0W4D58lZzczNqa2uxZ88edHZ2QiaTLbnuKJVK6HQ64lA0Nzcjk8lAo9HAaDTCbDajra0N+/fvh0KhQH19Pdra2padM+y+5/N5aDQabNmyBYFAgOQ8+Hw+rFYrcWeGh4cxNTUFqVSKbDYLt9uN1tZWumdNTU2or6/H0NAQrFYreDweBYNGoxHJZBI+nw8KhQI/+9nPcP/99yOZTOKaa65BR0cHZY18Ph9ZLJwNq4nzgQuG83IRi5HP5zExMYGGhgaqkQYCAYyMjKCurg7JZBI7duyAXq/Hyy+/jMcffxy1tbXo7u5e03mCwSCJQAHzBGmHw4Genp4lGd+VlZWLJL5VKhU6OjrW+U3LwbR62Euzt7cXLperTOCJIRaLIRQKkeKpSCRCMpmk2vRaEI1Gy44llUrhcrkQCATWLEyWTCbhdDrJpVculyOfz8PpdC7Jd2BdCaUdFuPj48jlcnSv5XI53G43YrFY2QLFnI6lUimMRiNyuRzi8Ti8Xi+i0eiStfeFSKVSxMVgmhfsfHV1dXjzzTdx33334aqrrsIdd9xx3m0MzgY8Hk9Z1k4sFsPj8aClpQUVFRV4//vfT58NBoPo6+uD2WwGj8dDdXU1rrvuOnziE5/An/70J3z2s5/F/v37cfvtt+Pmm29e9pzJZBIOhwOVlZV0T5kC63Iu4Tweb0k9lI2A3++HQqEo42Y5nc4lOS8ulwtKpZLmpNlsJjXftQb7EolkSc5OJBJBPB4vm5OpVArbtm1btZBjqf5LNBqFz+dDT08Pent7AcwHbNXV1dT9txKYESU7d6FQwMDAAKkJM8zNzcFiscBut5eZnObzeYTDYezcubPsO7L1rVSagjm4P/fcc/jHf/xHGI1G3HXXXWhtbcXg4CCcTie0Wi21ZvP5fNjtdtTX16/qvrxX8N5l213AKBaL5FPCwOfz6WfMWM1oNOLWW29FMBjEvffeC7fbvabzsHQow0p133OBpXZtrJ683GdL7xOrh6/3vKXnOh1fZbXHZH9f7nssBVbDZyjlTZRi4b95PN6icXM6sNJV6bEKhQIEAgF+/etf46tf/So+/vGP40tf+tJ7MnABQEaADOx+rPTMFo6NiooK3HvvvfjJT36CTCaDW2+9Fffeey9mZmaW/P2leBJrHScbiaXWAmBpQ0PWgVP62VITy43AcnPvTOfkRs7x5bDUsxUIBIvmJvs3m99Mw+X111/HXXfdhTfffBM333wz/vVf/xUHDx4kXhL7HXYu9vPzNXbOFy6WjTYhBAIB4vE4xsfHidDp8XhQX19PCsNerxcejwcikQgdHR2IxWJ49tlnsX379lXvzEQiEe2u8vk8gsEgampqUF9ff17qp3w+Hw6Hg1xc/X4/TCYTGhsbFy2MzPjQ7XaDz+cjGo2Cz+ejvb0dYrEYNpsNw8PDOHLkCPmBqFSqJUmmIpGIfEQYx4bP56OtrW3ZUhyTY5+enkYgECBSs1AopDq+WCwmYb/29vZVd8mxNt1isQifz4eRkRHweDy0t7eXXQ/jvDDRsmAwCKlUipaWFjQ3N1OwkUqlMDExQX4tKpWKdoRMht1utxOJMZVK4Y9//COeffZZ3H333bj++uvfM/X05cC+f7FYhN/vh8ViWZL/IBAIEAqFEAwGIRQKSdG2paWFumGuuOIK7Ny5E2+//Ta+973vob+/H3K5HCaTCR6PBw6HA+l0mtpnJRIJUqkUEokEWltb183bWg6FQgEOhwM2mw2xWAxyuXwRP6W0PFkoFFZcC/h8Pmw2G/l1BYNBNDU1wWQy0Xmi0SiZfQLznUVzc3NwuVzIZrPkZbcchEIh/H4/QqEQBAIBIpEIxGIxWltbIRaLEQqFMDY2htnZWaTTaRLNXOl40WgUHo+HxOhyudy6S2/M1Zq1TGezWYTDYbS2tqKiooLWAKlUikwmg1gshtbW1jIVavYdg8Eg+Hw+fv/73+PFF1+Ey+XCwYMH8bGPfQzXXHMNlZ48Hg9mZmbgcrkQi8XI8oWVxTZCX2sz4CLn5QIHa5V0u91Ip9PYunUrPvShD0EsFiObzWJychIcx0GlUkGr1eKKK65AoVDAj370I1gslhV9MxgkEgmVG4B5QTUm/HQ+IJPJyMgsk8nAbDZj69atS2pX8Pl8GAwGUtFUqVTYunUr9Ho9RkdHcezYMZw8eRI2mw3hcBi5XI54IwszCAKBgPyfEokEpFIpuru7l10MOI7DyMgIOZ8Hg0G43W5UVFRAKpXSsZj7d1dXV5kGxenAFFkPHz6MiYkJSCQSki83mUzEOVGpVOQaHIlEoNFosGPHDvT09FCQw/g8DocDHDevIRSJRKhMxOPxiOuSSqWQy+Xw61//GqdOncJDDz2E3bt3r/r5XahQKBTkb5PNZmE2m9He3r5koCsQCKDT6SjYkEgk2LJly6KxotfrYTQaodPpMDIygp///Od47bXXUCwWKVAQiURQq9XkbNzZ2blkwHQm4DgOw8PDOHXqFJLJJFwuF0KhECnLMkilUuj1eto41NbWLrsWsHHHArfGxkY0NzdjZGSk7DxMrTebzeLIkSNwOBxIJBKw2WzgOG5Ft2ahUEjWCMlkEkqlEt3d3dBoNAiHwzhy5AhisRiZZ+ZyOSrlLQW2XjD3aZFIhG3btp2RCq1OpyMxOGYoybg3er2emhsKhQI6OjoWBYKsrPziiy/i8ccfh8vlwv79+3Hrrbeivb2dvm8ul8OJEydgt9shl8uRTCaJv1NbW4v29vYlN3gXKlYbvPC492CuqdTn6EIGa1/l8XhlJEmHw4HBwUFUVFRAIBCAz+fD7XZjx44dePfdd/Hkk0/i4x//OL785S9fsIZc603pJpNJvP7668jn85icnITJZEIgEIDZbCZzxpVEtVZz3ng8jjfeeANGo5HuLzOr6+zspM+x8s96FpVIJILXX38der2epMgdDgc6OzsXaUuwNumlSn5OpxP9/f3EHeC4eUO7pe7D+Pg47r77bigUCjzwwANnhVuxmcFx3Gnbg0vBymtLgZHPzWYz+Hw+jh8/jv/4j/9APB7HZZddhhtuuAFCoRA7d+6kz5yNslwoFMKhQ4dQUVFBY9Vut6Onp2dNEvWnQzgcxptvvlnmlmy329Hd3Y1cLofR0VEag7lcDoFAAAcOHFhVNnLhnBweHiZuCQDKYB08eHBVHYIbXS5iZceFx2St50vJRySTSTz//PP4xS9+AQC48cYb8eEPfxgKhQK5XA4ikYiO5/F4cOzYMSJEc9y8A/i2bdvKOFPvFaxWy+vCfLP9HwFru1wIph9RGtCwlPcNN9yAhoYGPPLIIxgdHcV3vvOdVRE3NxvWu7iU6muwY7C0LnOjPdPzFgoFFAqFRdoepToO7GfrBQt8SnchC7UrGFYKjpbiczBNjVK8/PLLePjhh3HZZZfh7//+79es1PpeADPUWy1W+uxC/lhdXR2uvvpqGAwGHDt2DPfffz+VOJeSw98oMB+chWN1tYaDazkPOzaDSCRCJpNBLpcrG09MQ4b9zumwcE4uNfeKxeKiMb3a450plpt/CzedwHyjwa9//Ws888wzEIvF+MQnPoFrr7227P4s/J2F6xmbw2cr4L1QcDF4uQChVCrB5/ORTCYhl8vh8XgQj8epjt7d3Y0f/ehHeOSRR/DJT34Sjz76KDHsgXkOhNfrRS6Xg0qlgslkOuucBtbRA8ynW1db18/lcnA4HEgmk9QiupI4mkwmg0ajgcfjoVp5qW7HWtSZOY5DIBBAKpWCSCSiTBdrI/b7/TAajeS1slE152g0Cr/fT+WE6upqZLNZZLPZNbdDsrESj8ehVCoRi8UgFArpPmSzWXz/+9/HCy+8gC984Qu44YYb3vP8lqWQy+Xg9/uRy+Ugk8mWLGmwzzDhxpXmjUKhIJ4FG+usY2X37t2YmprCb3/7W9x333146aWX8Dd/8zfYsWPHGX2HfD5PvBWFQoHKykoydYzFYlCpVMjlcsjn81CpVAiHw9Ryy0qH6wUzZWXfl51HrVYjn89jenoauVwOsVgMLpfrjEocBoOBuC5MLZe1IK8HqVQKfr8fxWKRzIAZl66qqqqsa2g9yGazGBsbw29+8xu8+uqrMBgMuO2223DNNdcs0v1h2kBMVZ1tYHg8HlKpFGQyGZlDln7fbDZL45fZ5bzX5/FFzssFCOZg6na7MTc3h5mZGXIsjcViMBqNUKvVuOqqq+D1evGDH/wAcrkc27ZtQyqVQn9/P2ZnZxEKhWCz2SAUCs8q2cvv91PN2+PxwOVyQafTnXaxyefzGBgYwOTkJOLxOOx2O1KpFE3qpcDn86HVakkjxuv1Qq1Wo6GhAdu3b1/Ty58JcTGSZTKZhMlkIuuEQCAAv9+PTCaDlpYWNDY2nvGCwe6Vx+NBOp2mRZ/jOLS1tZGA12rBnHpdLhfC4TD4fD66u7thNBrhcrnw5S9/GcPDw3jwwQexf//+9/yCtxSy2SxOnDiBqakpBAIB8psqnRO5XA5DQ0OYnJxEKBSCy+VCsViEwWBY8p6JxWKoVCp4vV4yVNyyZQtyuRyi0SgkEgk+8pGP4MYbb8TY2Bh+8pOf4N1334XJZFoX7+X/Y+/Mw6Mqz/7/PbPvS2YmewIhOwlJIAIKKAXbKlgr1oovaNUqWm0tbohvXWjrUlsVtFVxo661RV+XVn8WbdUKIioCSYAQspGQyUwyycxk9n3m/P7gOqcZCFlnJc/nurwkk5NznjPnnOfcz71873A4jMbGRrS1tcHhcKC3txcejwcFBQVQKBQwGAyw2Wzw+XwoKSkBh8PB/v37YTQa0dvbC7fbPepzNRaMEKPRaIw6zsyZM6FQKBAOh7F//340NTXB4/GwulLDc7jGi1wuB4fDYRdtSqUStbW1kzJeXC4X9u7di+7ubvT19WHnzp1oaWlhxQM7OztBUdQpOULjxWAw4Ne//jX+8Ic/wGAwYPHixfjpT3+KxYsXR+0vEAigqamJTao3Go0IhULQarVsMUBfXx/sdjvC4TAqKyvZsK7f70dTUxOOHTvG9ptjcrPSEZLzMg2w2+348ssvWYEiJhZaXl6OWbNmsdv95z//wR//+EecffbZWLNmDYxGI9t9llG2XLp0acwEr05m165d8Pv97MvAYrFAKpVi8eLFo/5df38/9u7di5ycHLZUvK+vDwsXLhwz0S4UCsHj8YCmafD5fAiFwgmtLG02G7788ktWrTYSicBoNKK+vp518weDQfh8PtYbEwt2794Nr9fLflfMCvC8886b0vXx+/0IBAIQCoUQCAT44osvsGnTJpSUlODuu+8+YwSuJoNer8ehQ4dYZehAIIChoSGcffbZrNfEaDSisbGR3YbJ21i4cOGo310gEIDf7wefz4dIJILb7WZ/Hu4FNBgMeOutt/DJJ5+grKwM119/Pc4777xxGxNjPStMFRmj1PvFF19AJpNBIpGw93ZdXd2UtUK8Xi97nOEVRR6Ph21WqVKp2A7OxcXFUXliE8Hn8yEcDkMkEk3aa3Tw4EHo9XpkZ2fDbDbj66+/xsDAAKqqqiCTyTAwMACdTodzzjlnXEUQDEajEa+++ir+7//+D2KxGJdccgnq6urYKsqT7xsmj5G5v5g8ngULFrBGiNfrZVuJDJ9vuru7ceTIkaj712az4Zxzzpm0SngyITkv0wAmRs88BBRFQSwWw+l0Rm23bNkylJSU4OGHH8Ydd9yBq666ijVehEIhW/IYD8LhMPx+f9TDJpFI4PV6o3oXjUQwGIzKG2DivuOJlfN4vCmVnAYCAbZvC3NspqyYgek3EyvC4TC8Xm/Ud6VSqVh38VQQCoUQCoUIhUL44x//iDfeeANr1qzB2rVrp3XcHAAbfmBetAKBgE22HL4Nj8eLyqMCMOZzIxAIojwLUql0RCM0Ly8Pt99+O6688kq8/fbbuOeee1BYWIjrrrsO559//pjXKBQKjfisMOOTSCTsfWWxWNh+Qcy2QqHwlHljMjBNHkcan0AgiFp0MMJzk2WiiuIj4XK52O+ByaVhjHwmp4QJu42Hnp4evPzyy/jnP/+J0tJS/OxnP4NcLj9lsXXyfeP3+6Pur+Hidgyn+269Xi+EQmHU/RuJROI2p6cKZ0Zt1TTD5XLBarUiGAyCx+NFTQA+n2/EybGgoABPPvkkZs+ejcceeww7duwATdOw2+0QiUSTejn6fD62rPl0MKqRTNkwADYuPtaqkplUGIOBacYWq2Z0o8FMXsy5MW0Z4nlsLpcLuVyO3t5eNufFZrON67saD/39/bjhhhvw//7f/8PDDz+Mn/zkJ1M2XAKBABwOR1qHapkKDybh0+v1gsfjRSVRSiQSNlEb+O+9GIsX6HAyMzPx85//HK+88gpqa2vxwAMPYPXq1fjwww9HNdqZirSTn5WRPIKMF5LZlqZpttFqvBCJRGynauDE88SEj5JBJBJh56ShoSHQNM1qsvB4PIRCIfj9fra6Zyyv57Fjx3Dvvffixz/+Mbq7u/Hggw/iiSeewOLFi9m5A/jvvXXyPMJ4wIZvx+VyxzXfMG1ImHuTyWM605PuSc5LGkHTNLq6unDw4EEYDAYMDAxAqVRiaGgITqcTDocDGRkZKCsrGzE+y+PxcN5554GmafzlL39BS0sLKisrMX/+/AlPIj09Pdi3bx+OHTsGg8EAqVR62slPqVTCYrFgcHAQTqcTCoUCNTU1Y8a6mWRDg8EAh8OBYDCIyspK1msUT0QiESiKQm9vL5xOJ1wuF2bMmIHi4uK46SnQNA2TyYR9+/ahs7MT3d3dbHhtqhPRrl27cMstt0Cj0eDhhx+OCitOFqvVigMHDqCrq4vVkVGr1WmXNyORSOD3+9Hf38+Kl1VUVES5r4e3eWC2KSsri1s5uVgsRn19PVasWAGn04mXXnoJH3zwAWQy2Yj9wyQSCbhcLnp7e9kFRUVFBVuePByBQAAul8uK1jmdTlYbKl5eOGYRw+jMuN1u5Ofnx/WYpyMQCKCxsRHNzc2w2+0wmUzsAlAikUClUrFCcGq1GqWlpaisrBzRy9rZ2YnHHnsMjz76KORyOevZZsqaGaO3r68PLpeL1Xw5OTTCbNff389uV1lZOa4QilQqhc/ng8lkYkUGR9IeShdIzssZQDgcZoWYZDIZ7HY79u/fD41GA4FAAI/Hw6q3MiGkjIyMMV90kUgER44cwZYtWxAKhfDoo4+iurp63OOyWq346quvoFAoIJFI4HQ64fP5sHjx4tNW8wwXbWMaPI4Xl8sFv98PoVCY8Biu1WplY/harTauQlCDg4P46quvoFKp2BwVn8+H73znO5Mudw8Gg3jqqafw5ptvYs2aNVizZk1MXhY+nw/ffPMNgBOhrUAgAIvFgrq6ulF1dFKVSCSCoaEh1rs2UsiR6eLLVCTFWgl3NJxOJ9577z384x//gFqtxrp163DhhReeskhhDBem0/BomM1mdpXONFiNN8ycxeVyoVQqkxKybGlpQXt7O5sfZDQaweFwMHfuXCiVSlbMMRgMso1xT56vjh07hhdeeAGffvop5s2bhyuvvPK0uTuMh5u5b043h9E0zS7SRCLRhOa64fevRCKZUFVlqjHenBdivKQofr8fzc0bD/4PAAAgAElEQVTNGBgYAEVRkMlkyMjIQE9PT9TLoa+vD3Pnzp2UUqTf78ezzz6LTz75BOvXr8eaNWvGtWru6elhk8sYjEYjzjrrrFMaNxLGj16vZ5NCGYxGI+bNmzfiCnos+vr68L//+7/o6+vDxo0bo8rlpwrToHD4vWg2m5Gfn4/y8vKYHYcQDWPE/P3vf4dWq8WNN96I73//+2eMumoi+OKLLxAOh9kXfCgUgsViwfLly8cMA/b09OCFF17Axx9/PKbRQpgc4zVeyB2fonR1dWFgYABZWVnIzs6Gz+dDV1cXKzoF/Ld52kRK+BhvjsvlAp/Px2233YY77rgDW7duxYYNG8aVmHZykzGmKdh0T/ycKowIHZNox1zr8ZaSRiIRtgLjiy++wNq1a8Hn8/HMM8/ExHBhlHyB/wq0DRcGCwQCEy57JUwMuVyOq6++Gq+++irOPvtsPPTQQ1i7di127dqVtMZ8oVAIXq933CJx8cTj8bDei9PB5LYwMNVfo81fJpMJDz74IC6//HIYjUY8/vjjePjhh4nhkkSI5yVF+eqrr9hwEfBfCWwmfCQUChEIBJCbm4s5c+aMa+XldrvR3NyMoaEhUBSFnJwcVFRUgM/nQ6/X4+GHH0YgEMAf/vAHVFZWnnY/fr8fe/fuxdDQECualJWVhfr6+rRtR5Bs3G43Dh48iAMHDsBisWDGjBlQqVSYOXPmuK6v3W7H4cOHMTQ0hB07dmD37t346U9/GpMwEdNLa2BgABwOB0VFRcjNzUVLSwv0ej3EYjFbUTZv3ry4ldwTTmVoaAjbt2/HP//5T1RWVmL9+vUx9bCNRX9/P5qbm+Hz+VgtqfGunGNJJBJBe3s7Ojs7EQ6HoVAoUFtbO2IZO+M1DIVCbOPb2traEcvEHQ4HXn75Zbz55psoKirCNddcM2UxQcLokLBRmtPQ0ACr1cpeSKbz8/z58zE4OMhWFY1X/ZGmaezfv59tlhaJRGAymVBcXMzqF/h8PjzzzDPYuXMn7rrrLqxateq0YSSv14vjx4/D7XZDoVBgxowZZNU9SYLBIPbu3ctWFplMJtjtdixcuBCzZ88e03Dx+/346quvYDKZ8Ne//hV6vR6XXnopVq9ePeXWEExjv97eXqjVatZzV1NTw3YRZozpvLy8tNSVOBPo7+/H66+/js8++wxLly7F+vXrUVhYGNdj2mw27NmzB2KxGFKpFA6HA5FIBIsXL064AavX63HgwAFW9I7p1r1o0aIR5yWbzYb+/n6EQiHodLpT1JKDwSDeeustbNu2DUqlEtdeey0WL16cdsno6QjReUlzioqKMDQ0xIqURSIRVFdXQyKRTEpIiuk8zCiCMtn/FouF3UYkEuGOO+7A7Nmz8eijj6KpqQn/+7//O2IcWCwWo6KiYkrnSDgBU/rOVCgUFRXBZDKNu6mjy+VCU1MTtm/fjoyMDNx7772sUNVUjRemimF4wz2meiI3N3fKomaE2JCdnY277roLP/rRj/Diiy9i9erVWL16NW688ca4GZQOh4P1cgAn2n4YDAY4nc6EGy9WqxUikYg1VLRaLYxGIzwez4jGi0qlGtErQ9M0du3ahSeeeAJOpxNXX301VqxYQTzKKQi5IimKSqVivSyRSAQqlWpK7lgulwsul8tqwwAnVhcnT2wURWHFihUoKSnBQw89hOuvvx6bN29OywqSdGGk1RxN0+MyXGiaxjvvvIOnn34ay5cvx49+9CPweDz09fXFZJV4urERUpPi4mI88sgj+Oabb/Diiy9ix44dWL9+PS666KKYJ/UyGigMzL+T4Z0QCARReS5MY9OJhEyPHz+Oxx9/HN9++y0uueQSrF27loRAUxii85LCCIVCqNVqZGRkTFl+nlHc7O3tRTAYhNvtRiQSQUVFxYj71mg0OP/88/HNN9/gpZdeQnV19YQriTweD44cOYLW1lYMDg5CKpXGXNTrTIDP58Nut6O/vx9cLhculwuRSATl5eWjilRZrVbceuuteOutt7B48WLU1dWx7nsej4fS0tIp68NwuVx4vV4YjUa2S7Db7UZJSUlal2OeyVAUhfz8fKxYsQIUReG5557Dnj17UF1dHVPtD6Yp4tDQECKRCKxWKzQaDYqLixOevC8UCtlwK+N1nDlz5rj6RPn9fvz5z3/GfffdB61Wi9/85jdYtmwZCYMnifG+64jxMo1QKpVsvxGFQoHS0tJRwwpCoRDLli3D0NAQtmzZAq1WO2oi73CCwSAOHDgAk8kEoVDIikFNphHbmQ6Hw4FWq0UoFILL5YJYLGabJ56O/v5+XHPNNejo6MAtt9yC2bNnY3BwECKRCFqtFrNnz46JeilFUWzfLIfDAYqiUFZWxvZRIaQuXC4XVVVVOP/889HU1ISnnnoK4XAYtbW1MTEuGO0jRkE2OzsbVVVVSVmgCIVC9nkRCASYOXMm24ByNBobG3HrrbeiqakJt956K6699tqkqf4STkBE6ggx5eOPP8ZTTz2FK664ArfeeuuYkwIjuDb8JWcwGE6b1U84AU3TYxoFnZ2d+PnPfw6/34/169ezk63JZEJJSUlM1HNHIhKJgKIoYrSkKbt378YzzzwDjUaD3/72t9Naj8fn82Hr1q3Yvn07LrjgAqxbt46EiFIEkrBLiCkXXHABcnJy8OCDD8JoNOLBBx8cdYXFvISHv+iYxGPC6RnLMNi3bx82bNiAyspKLFy4MKEqr0QILb1ZsmQJamtr8fTTT+Oaa67BLbfcgrVr106769rR0YF77rkHTqcTDz30ECl9TlOm111LmBI1NTXYsmULWlpacMstt4wqaMe0DjCbzQiFQmzIYaQMf8L4+OSTT/DLX/4SK1aswH333YfMzEy2L8vQ0BC4XO6Uq4sI8cPhcODYsWPo7OyMqvJLJHK5HL/61a9w55134sUXX8Rtt93GNks806FpGu+99x6uvvpqFBQU4NlnnyWGSxpDwkaECWOxWHD//feDy+Xi6aefPu0L02az4fDhw3C5XBAIBJg9ezapWpok7733Hn7/+9/jhhtuwKpVqwCcyO3q6OhgxQKLi4uJ8ZKiDA0NoaGhAcFgkPVA1tTUJLWdhtFoxO9+9zu4XC5s3rz5jA4jBQIB/P73v8eOHTtw8803s8nMhNSDiNQR4orT6cSvf/1ruN1uPPfcc9DpdCNuF4lE2PJs0j5gcmzfvh1PPPEEbr/9dnz3u9895ffjyZMhJJf9+/ezOkvAf0UnlyxZktTnwu/346mnnsLu3bvx0EMP4Tvf+U7SxhIvbDYb7rzzThgMBmzatIkV5SSkJqS3ESGuyOVyPPTQQ5DL5bjppptOazByOBwIhUJiuEySN998E0888QQ2btw4ouECJEdXgzAxfD5fVI6YUChEKBRCKBRK4qhOjOPOO+/EmjVrcPfdd+Pdd99N6nhiTX9/P66//np4PB788Y9/JIbLGQQxXgiTRiKR4MEHH4RMJsMvfvEL2O32pI3F6/Wit7cXPT09Z0wM//3338eWLVuwceNGLF26NNnDIUwBtVoNh8PBCrnZbDbI5fJRZQNomobFYkFfXx8sFkvcxAEpisIVV1yB22+/HX/4wx/wxhtvRP0+FAqhv78fer0+Ybk6fr8f/f39MBqNcLlck9pHb28vrr/+emg0Gjz66KMkpHqGQcJGhCnjdrtx9913QyKRYOvWrQnXeXA6ndi3bx+cTicoigKPx8PcuXPTOr9m586d2LhxI9avX48LLrgg2cMhTBGfz4fDhw/DbDaDoijIZDLU1NScVuiPpmm0traiu7ubVbKdNWsWSktL4+pp2717Nx555BHcdddd+PGPf4xQKITGxkYYjUa2erCyshLFxcVxG4PH48H+/fvZBrICgQD19fUTUhg3mUy4/vrrUVhYiPvuu49oS6UR473ORKSOMGUEAgHOOeccvPvuu2hubsb555+f0FBGS0sLrFYrcnNzIZfLEQ6HMTAwgMLCwrQsA21pacFtt92GK6+8kk3OJaQ3PB4PmZmZ0Ol0yM3NRVFR0ahiXBaLBUeOHIFOp4NCoYBIJILBYIiJ2vZoFBYWIjc3F48//jhKSkogEAjQ1taG3NxcKBQK8Pl89Pb2Ijs7e8rqzaejpaUFJpMJeXl5kMvlCAQCGBwcHPfz7HK5cNNNNyEjIwO/+c1viOGSZoz3/k6/mZ2QkqjVajzwwAP4+uuvsW3btoQe2+VyRQlMSSQS+P3+qF4n6YLFYsEdd9yB8847D1dccUWyh0OIITwej233MdYL1e/3s38DnFCzpSgKgUAg7uNctmwZrr32Wtx///1obm4Gn89njQaRSIRIJMKOLx44HI4oj5RMJoPX6x3XuUciEdx7770Ih8PYtGkTMVzOYIjxQogZhYWF2LhxI7Zt24Y9e/Yk7LgKhQIul4vNCXA6nZBIJGk3cYXDYdxzzz3QarW45ZZbEua9ikQicLlccDqdCIfDCTnmmUA4HIbT6WR7UcUSPp/PHoP5P03T7Ofx5sc//jEWLlyIJ598Ek6nkz0/n8/HJuHHC7lcDrfbzf7sdrshEonGde6vv/46Ghsb8etf/5oo5p7hEIVdQkxZuHAhVq9ejU2bNmH79u1T6oQ9XkpKSuBwONi4vFAoxJw5c9Kuwunll19GW1sbtm7dmjDDKxAIoKWlBf39/QCAjIwMVFVVxTU0cSbg9Xpx5MgRNr8uMzMTlZWVMcv30mq1KCgogF6vZz8rLCyMaWPF0aAoCuvXr8fNN9+MPXv2QCwWszkvs2fPjquyc3FxMWw2GwwGA4AThty8efNYL9Tp6OjowLPPPosNGzYgNzc3buMjpAYkYZcQc0KhEO68805kZWVh8+bNCfEgBAIBtrutQqFIu1XX0aNHcc011+BXv/oVlixZktDjdnV1ISsrCxwOB/39/cjMzMTcuXNJCfYoNDU1oa+vD1lZWQBOJIjm5+ejuro6ZseIRCIwm80IBAIQCATQarUJz+FqbGzEr371K2zZsgWzZs2CWCxOiAHl8/nYCiu5XD5ms0SaprFu3TrIZDLcf//9cR8fIX4QnRdC0uDxeNiwYQO++uorfPrppwk5pkAgQFZWFnJyctLOcAmFQnjwwQdx3nnnJdRwAU4Y+kqlElwuFxRFQaPRYGhoKC3zhRJFOBzG0NAQMjIywOFwwOFwoFKpYl7OzOFwkJmZifz8fGRmZiYl+byurg7nnnsu/vKXvyAvLy9hnh+RSIS8vDzk5+ePq8vz559/jiNHjuDGG29MwOgIqcAZGTYSCARxjcmmK4wg1lju17FgJM5PF5ahaRqlpaW46qqrsGXLFixevBhisXhKx0xXIpEIaJoeNYT13nvvwWg0YvPmzactnY0XSqUSXq+XDRMxK12VSpV2YbdEwXxHwH8rI4LBIEQiUUIbZSaKm2++GVdeeSUaGxtRV1cXl2MEAgGEw2EIhcJRjbRwOAy/3w8+n8/mwNA0jW3btmHVqlUoKSmJy/gIqccZabwEAoGEZOWnC6FQCJ2dnTAajQCAnJwclJSUTNiI8fv9aGtrw+DgIDgcDmbMmIEZM2ZETTZmsxmtra3w+/3Iz89HIBDAX/7yF9xwww0xPadUh6ZpdHV1oaurC+FwGFlZWaisrDwll8XlcuG5557DlVdeCR6PN2qzy3iQlZWFpqYmOJ1OcDgc+P1+VFVVEbmBMcjJycGhQ4dgt9tB0zRCoRBqa2sTfv0SgVqtxqJFi/C3v/3ttMaL1WpFW1sb3G43MjIyUFZWNi4PKE3TOHbsGDo6OhAOh5GRkYHq6mrIZLJTtrXZbDh48CCcTicEAgEqKipQUFCAxsZGtLe347777jsjvv9gMIju7m6YTCZwuVzMnDkT2dnZ0yaMO17HAwkbTQO6urrQ2dkJiUQCqVSKY8eO4dixYxPaB03TOHr0KAwGA+RyOUQiEVpbW1mDCDhR4tjU1IRwOAy5XA6fz4eFCxfitddeg8PhiPVppTR6vR6HDx8Gj8eDVCrF8ePHceTIkVPCCtu3b4dYLMZFF12UlHFmZmZi3rx5yM7OhlarRV1dHfLz85MylnQiNzcXc+fORWZmJnJyclBfX5/WoohjsWLFCuzcuXPE59jpdOLbb7+F3W4Hn8+HwWBAQ0PDuBaQBoMBzc3NkEql0Gg0sFgsOHjw4CltE3w+Hw4cOACv1wudTgeBQIDGxkYMDg7igw8+wPz580/bXy2doGka7e3taG9vB4fDQTAYxMGDB2EymZI9tJSDGC9nODRNw2g0Qq1WQyQSQSgUIiMjA319fRMq7/T5fBgcHGQnDrFYDIlEwlapAIDdbkcwGIRSqWQTDMvLyyEWi/HWW2/F4/RSFqPRCKlUCplMBpFIhKysLPT19UXpY3i9Xvz1r3/FFVdckbAS2JHQaDSoqqrCnDlzptUKb6pkZmaiuroas2fPTkhVXTKpq6uDVCrFF198ccrvzGYz/H4/tFotpFIpsrOzYbVax9UuZHBwECKRCGKxGDweD1lZWbBYLPB6vVHbuVwuuN1uaLVacLlcyGQycDgcmM1m7Ny584xpn+H3+9HX14fMzExIpVIolUoIhUK28orwX4jxMg3gcDhRhspkkgqZMsmT9zPWi47D4WDlypV46623pl0S6PDveSRD8cMPPwSXy8X555+fyGERCBOGy+Vi3rx5+Oabb0b8/fDQ8USMXx6PF6UtFA6HweFwTtkHh8MBTdNRz1E4HMbx48fhcDhw1llnjfuYqQxN06fMq8y5E6IhxssZDkVRKCgogMPhgMvlgsvlgt1un7B0vlAoRE5ODgYHB+F2u2G32+Hz+ZCXl8duw3h3mJWTyWSCSqXCxRdfDJ/Ph88//zwOZxhNOBxGR0cH9uzZg71792JwcHBK+4tEIujq6sLu3buxZ88e9Pb2jmsiyc/Ph8fjgcPhgNvtxsDAAPLy8th4Lk3TePvtt3HhhRemnZgeYXpSUVGBPXv2oKGhAUePHmXzotRqNbhcLmw2G/x+PwYGBqBQKMaVvMzosZjNZjgcDvT39yM/P/+UfBmlUons7GwYjUY4HA6YTCZIJBIYjUbMmDEj6YnSJpMJ+/btwzfffMPmuU0GkUgEnU6HgYEBBAIBeDweuN3uMzokOVlIb6NpgEKhgFAoZOPVs2bNwowZMya0QqIoCmq1GhwOBy6XC3w+H+Xl5VFhBoFAAJVKBZfLBb/fj4yMDFRWVkIul6Ovrw+HDh3CihUr4nKOwAmD4MiRI2htbQWXy4XH44Fer4darZ50+XRnZyebuxIMBtHT08O6c0dDLpdDKpXCZrMhHA5jxowZKC8vZyt4WltbsW3bNmzYsGHE5EQCIZUIh8Noa2vDBx98gMWLF8NiscBqtSIrKwsymQxKpRIWiwUejwdKpRK1tbXjeuYkEgnUajV8Ph8AYObMmVHPCQOHw4FWq2VbJDCJvf/+978hkUgSLjEwHJPJhMbGRtYzxOQBTqaLNTPPBoNBDA0NgaZpFBcXo6CgYNqEc8crkHlGVhsRohleGTQVeDweSktLUVpaetptVCoV5s+ff4rrc9myZbjnnntgs9mgUqmmNI7T4fP50NPTg6ysLDaHxGw2Q6/XTyqZLxwOo6urK6oZHkVR6O7uRkFBwah/y3i8CgoKRgyvffzxx6iqqiIrKkJawFRV8fl8BINBFBYWore3l22AyjSdDIVC4PF4E3rRarXaceUMCYVCzJ49O+ozvV4fU2HAyaDX6yEUCtl5TSgUQq/XY8aMGZOS7GAUwseSpJjukLARIS6cPHlVV1dDLpdj9+7dcTvmSJoqXC530i7cSCSCSCRyyv5OroQYi5O/C5qm8Z///Cepq0UCYSKEw2GIxWKIRCJYrVYApz4LFEWxDSQTxcDAQNKTpUeaI4DJ5RYOh8/nE8NlFIjxQkgIXC4XCxYsGLFaYTRCoRB6e3vR1taG3t7eUQ0RsVgMjUYDk8mEUCgEn88Ht9vNSrhPFD6fj+zsbJjNZgSDQfj9fgwNDU25b0pPTw96e3uxcOHCKe2HcGbAtAEwGo0xV+mNFRKJBDweD0KhEG63Gz6fD5FIZFRRRavVCoPBgIGBgZg3rmRwOBxJz3fJzMxkQ+WhUAiDg4PQaDREKDXOkLARIWHU19fj6aefRjgcHteKIhwOo7GxEQaDATweD6FQCAUFBaitrR3x7zkcDmpqanDo0CFYLBZwuVxUVlZOSbeksrISNE2jv78fFEWhpKQExcXFk94fAHz99dfIy8sjzeMIiEQiOHr0KHp6ekBRFGiaRlFREcrKylIqx0EqlaKmpgZ8Ph/9/f1wOByorq4+bTi2s7MTLS0tbPVMYWFhXJql+v3+pBsJBQUFCAQCbBPN7OxsVFRUpNT1OxMhxgshYTAKpO3t7aioqBhz+8HBQRiNRuTm5oLD4SAcDqO3txd5eXmn9aZIJBLMnz8ffr8fXC53ypU8AoEAtbW1qKysBEVRMakM2rdvH2pra6e8H0L6Yzab0dPTg8zMTHC5XASDQXR1dUGr1U4q4TOe6HQ66HQ6lJeXY+nSpadNrLTb7Th69ChbfciUNOt0uqjqxFgw3oVQPOFyuSgrK8PMmTMRiUQgFAqJ4ZIASNiIkDBUKhUKCwvR0NAwru2DwSAoimJLupnmgWPlnHA4HIjF4piVIFMUBaFQGJP90TSNhoYGzJkzJwYjI6Q7jAot8wJmckZStb0JRVGQy+WjVoT4/X5EIhGIRCIAJ86Nx+OdIjwXC07WsEomAoEAIpGIGC4JghgvhIRSVVWFpqamcW3LNHNkVGl9Ph8oiopLk0eaphOSd6DX62Gz2U6pmpgMkUgETqcTdrs9ZV92hNFhDGImlysUCoGm6ZTV/gkEAmOOTSAQgMPhsPdkJBJBKBRijZlYIhAIEnLv+3w+VjU4VYyl6Q4JGxESSmVlJd54441xbavRaFBRUYG2tjZEIhFwOBxUVlYiIyMjpmNi9GGG93sqKSmJS9z64MGD0Gg0yMzMnNJ+QqEQWlpaWE0JmUyGOXPmJD15kTAxtFotCgoK2HwJ4ITWSazv8VgxvAP56VCpVCgtLUVrayuAE8ZLXl5eXGQBxGIxqxETLywWCw4fPsweJz8/HxUVFUkPV013iPFCSCgVFRUwmUxsn6TRoCgKpaWlyMzMZFd8Y4nDTQaz2YzOzk5kZWWxYnQdHR3Q6XQxL8Nsbm6OiVHU09MDvV6P7OxscLlcmM1mHDlyBPPnzyeTahrBGOTMPS4UCqHRaFIy9EDTNNxu97hEFUtLS1nxOT6fD51OF5f7UiaTweVyxXy/DH6/H83NzaAoCtnZ2QiHw+jp6YFMJpuybhZhahDjhZBQGOnv5uZmfOc73xnX38TDYBkOE47i8U48DozAXTxWdIcOHcI555wz5f1YrVbIZDL2haDRaDAwMACfzzdpNWFCcuBwOGnREdnn8yEUCo3Lu0dRVELOSaFQwOl0xm3/Pp8PXq+X9RpxuVyIxeIRu2sTEgvJeUkDfD4fXC5X0hobBgKBmB2fw+GgrKwMhw8fjsHIYoNAIABN02wiMJN3EOsSTJ/PN+5Kq7EQCoVR14Opror16jYYDMLtdqek9gghsTAv7HgpZE8GlUoVV0OCx+NF5e8AJ57jeOTvECYG8bykMDRN4/jx4+js7EQoFIJEIkFVVVVC4+F9fX1obW2F3++HSCTC7Nmzp7yiKi8vx8GDB2M0wqmj0+kwY8YMHD9+nNXamDlzZsxLVY8ePQqaplFWVjblfRUWFmJwcBAmkwk8Hg+BQABlZWUxm1QjkQj279+PvXv3wu/3Izs7G9/73vfSwkNAiA92ux1AahkvarU6rsaLVCpFUVEROjo6wOfzEQgEIJfLiUZTCkCMlxRmcHAwSi/BZrPh0KFDWLBgQVwqbk7GZrPh8OHDkEgkUKlUcDqd7PGn0kxw9uzZeO+999g+KMmGw+Fgzpw5yM7OZkWvdDrdhLpuj4empiYUFRXF5NoplUqcddZZMJlMCAaDyMjImLSS8Ei0tLTgs88+g0qlglwuh16vx44dO3D55Zcn5N4jpB4OhwNCoTClvA5KpRJ9fX1xPUZxcTFkMhnsdjsEAgEyMzNJaDYFSP6bg3BanE4nuFwuO1moVCr09/fD4/Ek5AXidrsRDodZQ0WhUKC/vx8ul2vKxksgEMDRo0eT3lSNgcPhxPTlPxINDQ2oqqqK2f4UCkXcqos6OzvB4/FYLx/jmbJYLFNSLCakL06nM+75ZxNFqVTGNecFAJusS5qophYk5yXFoGma1Xw4ufFZOBw+pfFgPDlZAIpp+T5Vj4RMJsOsWbOwb9++qQ4xLgzPf4kVTKuDdBGn43K5Udee+XesvVHpzPBnNZWIV36S0+kctZfRVGCaqo4GM/8MR6FQxLXaiJC6EM9LCtHf34/Ozk4Eg0Go1WpkZmbCYrGgtbWVDd2Ul5cnTMtDrVZDKBSyRgaTbKtWq6e877q6OuzduxfXXnvtlPcVSywWC5qbm+H1eiGTyVBVVRWTGH9LSwvcbnfatAWorKzEkSNHYDQaIRaLMTg4iJKSEmi1Wvh8PnR0dMBqtUIkEqG4uDjlpOzjzcDAANrb2xEMBqFUKlFWVjapUEIgEEBPTw/sdjskEgkKCwsnHZJwu91ob2+H3W6HWCyO+XXxeDwxD5cEg0G0tbWhr68PFEWhqKgIM2fOjDKSaZpGb28vOjo6EA6HkZmZifLycgiFQkilUng8npiOiZAekGVUimA2m9HU1IRIJAKxWAyj0YjPPvsMIpEImZmZbMY70+cnEdA0zSawMqtMiqJiokFRX1+PhoaGlJp4nE4n9u3bB7/fD7lcDpfLhf3798dkjF9++SXKysrSRkSuqKgIP/zhD6FUKhEOh1FTU4MLL7wQHA4Hhw8fRm9vL/h8PjweDxobG2Gz2ZI95IRhtVrR1NSEcDgMiUSCwcFBNDc3T7gaLxQK4fDhw2hvb4fb7UZPTw8aGxsnJaMfCPzcvCIAAB3zSURBVARw+PBhmEwmCIVCeDweNDU1xTSZ1e/3xzxc3dLSgo6ODohEIvB4PBw+fDhKsA84sahjWoqIRCJ0dXWhubmZnSvjLVJHSE2I5yVFGBwcBI/HY19ucrkcDQ0NOO+881hX7cDAAGw2W8IqPqxWK3w+H+bPnw8AbHdlm802ZfG26upq8Hg8fP3111i+fHkshjtlbDYb/H4/2zxOKBTCYDCwq+KpsGvXLixYsCAWw0wIFEWhvLwc5eXlrBELnPiOzGYzsrOzQVEUJBIJTCYTLBZLSlWhxJOhoSHQNM3mf2RmZrK5YBPxStrtdgwMDCA7OxscDgdKpRIGg2FSeUVOpxNDQ0PsdRGLxejv74fVao2ZwRwMBmPatiAQCKCvrw86nY6VJQiHw9Dr9VECcEajESKRiD2PnJwc9PX1oby8HHw+P2kSEoTkQjwvKc5wLwfTWTlRnNyxlfG6xKK3h0AgwIIFC/Dpp59OeV+x4nQepal6mgwGA1pbW7Fo0aIp7SdZDD9/Ji9h+GexuiemG4wnc7gnlcvlTvoZH8krGsv8l+FGbKrA4XCIBtE0hXheUoTMzEz09vay5Xh2ux15eXlwOp0QCoXw+/0IhUIJzS1gKoqY6iaHwwEejxeTuHc4HEZZWRmeffZZXHzxxSgvL49JLs1UUKvVkEqlGBwchFQqhcvlgkKhmLJH4eOPP0ZhYSFmzpwZm4HGGb/fj56eHjgcDkilUhQWFrKeJ5lMBpVKBZPJBLVaDb/fD5qmU7YXTzzIyMhAV1cXbDYbhEIh7HY7MjIyJpzMKpVKwefzYbfboVAo2PDHZCr55HI5ZDIZ2tra2BCvTCaL6TM1FcNqJAQCAfLy8tDR0QGNRoNIJAKXy3VKXlhubi6MRiOcTid4PB4sFgsKCgogFotPWWDFAqfTiZ6eHvh8PqjVahQUFMDv98NisSASiUCpVCbsfg8GgxgcHEQgEIhKISAQ4yVl0Gg0qKmpQWdnJ/x+PwoKCrBw4UJ0d3fDbreDx+Ohuro6oSJhGRkZqKqqQltbGxwOB8RiMWpra6dsvNA0jdbWVlaG/6OPPoLdbsfChQuTGnqQSqWor6/H0aNH4Xa7odFoUFlZOSVdC5qm8eGHH2L58uUpt2odiWAwiIMHD8JsNkMqlcJsNsNqtWLevHkQiUTg8/morq7G0aNH4XA4wOfzUVNTM60SdtVqNWpra9lnNTs7G6WlpRPWLJJKpaipqcGRI0dgMpnA5/NRVVU1qe9SIBBArVbjwIEDCIVCbOgolvecUCiMeX5JeXk5uFwujEYjKIrCnDlzUFhYGLVNdnY26urq0NHRAZ/Ph6KiIpSXl4PD4cDn88VUCdvlcuHAgQOsKKfJZEJfXx+CwSC8Xi9rKFVXV8ddqC4YDOLQoUPo7+8Hj8dDJBLBjBkz4tIwNh0hxksKkZWVhaysrKhyZI1Gg2AwGBfp9/GQn58PnU6HYDAIoVDIGhxTwe12o7e3F3l5eTj77LPR0NCA+fPno7e3N+l5EyqVCmeffXbMXOQHDhyAXq/H9773vRiMLv7YbDZYLBbk5OSAoigolUoYjUZYrVZ2spbJZDjrrLPY+3I6rgR1Oh10Ot2UpQO0Wi3OOecc+P1+8Pn8Sb+I/X4/+vr6MH/+fPD5fHC5XFgsFvT09MSsPF8qlcZcU4XP56OyspJtmTHSM0dRFAoKCpCfnw+apqO+b4fDMSXNqZMZGBiA1+tFTk4OgBP3+t69e5GTk8N6Tl0uF9rb25GZmRlXkc3BwUH09/cjNzcXFEUhFAqhp6cH2dnZSfdSpwLTb9ZJA4Y/nBRFQSAQJLVTsFAohEwmi4nhAoCtXuLxeDj33HPR1taG/v7+lEq8i9XK5s0338SiRYvSxjMxUkXZ6XJa+Hz+tDRchhOL8+fz+ZDJZFPyIIRCIYTDYQiFQvB4PFAUBT6fD7/fP+XxMajValgslpjtbzjjqWI8OT8IQMwTxYPBYNQ8x+VyEQgEoj4Ti8UIBoNxn68CgQB7LQGwhlIqzZPJZHrPPCkC44nQ6/WnLTm12WwwGo0wmUwxF1BLFOFwGMeOHcPRo0dhMBjQ3NwMsViMsrIy/Otf/5pyBVOq0dvbi88//xyrVq0adTun0wmz2ZwSnWplMhl4PB4cDgdomobH4wGHwyFy6JOEubbxVoFlDJ+Ojg44HA6EQqEJVz+NhU6ng8ViYQ0imqYxODiI7u5uNDQ0oLW1FQaDIaHzE1OtFCtUKhWCwSB8Ph9omsbQ0BAyMjJYgVAAbPVhLCuvRkIkEiESibDfp9frBYfDSan2DMmEhI2SjMPhQGNjI9xuNyiKAo/Hw5w5c6Kk6vV6PVpaWliFSZ1Oh5qamrg/PLEkGAzi008/xbfffouBgQE4nU4oFArodDqUlJTg3//+d7KHGHNee+01lJeXj9oSoLu7G+3t7Wz4obi4GEVFRUmLactksqg8DIFAgKqqKuKmngTHjh1DR0cHG+ooKSlBUVFRzI9D0zQ6OjrgcrlgMBjQ0dGBnJwc1NXVnZI/MhWY8m29Xo/i4mK0traitbUVXV1dGBgYQFZWFvLz81FUVITa2tqEeIuPHz+OysrKmO2PEcA7duwYbDYbZDIZvve970Gv16O/v5/NJZo9e3bczy8zMxMzZsxAT08PgBNevkSKlKY6xHhJMseOHWPF54ATK7W2tjZotVpwuVy43W60tbVBoVBALBaDpmkYjUYYjca0qV4BgNbWVjQ0NEAmk8Hv90Or1cLhcGDWrFlQqVQwGo14+eWXsWnTpmQPNSb09fXh/fffx6ZNm05riAwNDaG1tZVVMg4EAmhvb4dSqUxqmEmn02HRokVTzsOYzlitVrS3t7PX1u/3o62tDSqVKuaGoNlsRnd3N2bMmIHCwkI4HA7Y7XYUFBTELNQLnJDi12g0aGtrg0ajQWdnJ9tGorS0FFarFWKxmM1ni3evMJqm0d7ejpUrV8Zsn4zKb05ODkKhECuep9Fo4HA4EIlEIJPJEuL94HA4qKioQHZ2NoLBYJTWDYGEjZKO2+2OUq0Ui8UIBAJsXJP5N7MNRVEQiUQppUw7HqxWK/h8PhuLZ5LsOBwOuFwuVq9ejQ8//BDd3d3JHWiMeP7551FWVsYK/I0EU7nBGAcCgQA0TaeEYmgs8jCmM0zYgfn+mP9PRj13LJgwDo/HA5/Ph0ajgUQiiUtuRFlZGQ4dOgS/3896C5lnmsvlIhgMgqIoBAKBmB/7ZHp6euB0OlFeXh7zfYtEIjaECoBtUqrVahMatqEoim0VQwyXaIjxkmRUKhVcLhcbT3U6nVHxVIFAAD6fz056NE3D7/dPWfE1XgSDQbhcrlMmL4VCwSbqBgIBeL1edvLj8/mor69HXV0d/vSnPyVp5LGjra0NH374Ia677rpRwz88Hi+quR/TnG4q7miXywWLxUKa1SUZ5hoyic7MtZ1qdYrL5YLVao26vox3hbmPmPyMWHpdGKqrq3HgwAEIhUI2yZaiKPh8vigNmFi2EQgGg7BYLDCbzVHzyv79+5GVlZVQ+YiR8Pl8cLlcI+b6hEKhKBE9j8cDi8UCu93Ozoc2mw0DAwOw2+2JHHbaQ8JGSaaoqAhut5uNp4pEIlRWVrJZ9VKpFGVlZWhpaYHdbkckEkFmZiYyMzPhdDpBURSkUmlK1P0bDAYcPXoUoVAIAoEA5eXlbDispKQE3d3dOHz4MDweD/r6+jBr1iwoFApUVFRAIpFg3bp1uOWWW/D111/j7LPPTvLZTA6aprF582YsWrQI1dXVo26bkZGBnJwcGAwGVuY8Nzd30onLXV1d6OjoQCQSAZfLRUlJSVqFFs8ktFotsrOzYTQaIRAIEAwGkZOTM6VwYE9PD9rb2xEKhaKur1arRV5eHgwGA7ttYWHhqEJqkUgEJpMJLpcLQqEQWVlZ4/KyzZ07Fy+++CICgQDKysrQ2toKsViMnp4eaDQatq3EeM/T7/ezL3KlUnmKV8Pj8aChoQFWqxU0TUOtVqOurg5yuRx79uzB3Llzx3WceEDTNLq6utDV1YVQKAS5XI6qqioolUq4XC60tbWxoqMlJSWgKAqHDh1ijZz8/HxwuVz09PSw0gwlJSWYNWtW0s4pnaDoM1Bb2Ww2J3sIEyIQCLAPsFwuH3HVYrPZ4PF4wOVyIRQKcfToUdjtdlAUhfz8fFbsKRkEg0E0NTVh586d4PP5KCwshEajgdfrxYIFC9hSRo/Hg66urqhxK5XKKHfo1q1b0dTUhO3bt8dl5RhvPvroIzzwwAN44YUXkJ2dPeb24XAYJpMJXq8XIpEIWVlZk1qdW61WfPvtt2yOhc/ng81mw4IFC0iybZIIhUIwmUzw+XwQi8VT0gWx2WzYu3cvm/vm9/sxNDSE+fPns9Uwg4ODbP8hnU532jJumqbR0tKC48ePQyAQsDlotbW1YxowNE3j2muvxTXXXIPLL7+c7X/GdGEXiUTjLl12Op04cOAA63FQKBSYN29e1Hxw4MABGI1GtmeTyWSCRqNBbW0tvvvd7+Luu+/GOeecM85vMbb09/ejsbERGRkZEAgEsFqtEAqFqKurw6FDh+BwOKBSqeDz+eB0OhEOh6HRaCCTyRAOh9He3g6PxwOFQoFwOAyBQAChUIizzz57Wj+z4128pYXnxeVy4ZlnnsGBAwcgFouxevXqmCZpJRtmshkNlUoFlUqFcDiMffv2weVyISsrC+FwGMePH4dEIknaKruzsxNtbW0QCATIyMiA0WgEl8sFn8+Hy+ViJzOJRDJq5Q0AXH311bjhhhvw6quvYt26dYkYfsxwOp3YsmULrrjiinEZLsCJ8EIslDq9Xm9UjgWzgvV6vdN6IkwmPB6PbfI5VZjryyxshEIhaJpmw8lcLnfc95zdboder0dWVha74DEYDBgcHByzISRFUViyZAk+/vhjrF69ekqepJaWFrjdbvY7GhgYQHNzM2uMMKXKSqWS9SyrVCrY7XZ8/vnn4HK5qK+vn/Txp8rQ0BBrcAAnBEX7+vrYBrqM0J1QKITZbIbdbmcbTjL6MW1tbSgsLGSNSA6Hg9ra2jGf2XA4DIPBAKvVyrZZYBqFThfSwnh5/vnnEQ6H8fLLL6Ovrw+bNm1Cfn4+ampqkj20hOPz+WC326HT6djSaqlUCovFkhTjhXE/Z2RkwG63g8/nQy6Xw2w2Iysra8IiXjKZDD/72c+wefNmKJXKtHrxvv/++5DJZLj88ssTfmwmf4bJI4pVjgUhNTj5+jL5EpPxtjKJvMP/diKCdsuXL8c777wDvV6PgoKCCR8fODFvOByOKC+LQqGA0+lEKBRixdnEYjFcLheb4+f1eiEQCPDuu+9i8eLFSZWL4PF4UXkujMAj88wNV+lmFNKHi+DZbDYEg0FkZGSAw+EgFAqhq6trzKRumqbR1taG7u5uNjHbZDJh3rx508qASfmZzefz4csvv8STTz4JiUSC4uJiLF++HJ988sm0NF6GPwSMxR/rVvWTQSKRQKFQwGKxsEnFZWVlk2pgtnTpUjQ0NODFF1+Mw0hPrB7jES0VCoXYuHFjUq6FRqNBTk4Om2PBlN+ni7IvYXQyMjLYHBqm9DorK2tS+VFisRg8Hg9utxtSqRTBYBDhcHjcQoTFxcUoLS3Fe++9h/Xr10/4+MCJKkOJRAKn08l6kzweD0QiUZRRVVZWhv3797O9jzgcDvLz8/HVV19h8+bNkzp2rMjOzmY9VgKBAC6XCwUFBcjMzERfXx9MJhOUSiV8Ph9kMhny8/MxMDDA5rdlZmaCoihYLBZ2waHVasds8OnxeKDX66HT6VhDaGBgAEajkRgvqQSThDZcbGnWrFn4+9//nqwhJRWRSISZM2eira0NYrEYoVCIfaCTAYfDQWFhIY4ePcrGpa1WK2prazF37txJlRVSFIXbb789DqM9Yfyp1WoMDQ3FtENushneuNPj8UAikUSFBQjpDZfLRXV1NTQaDdvlPScnZ1KeNZlMhtmzZ6OlpYVN+i8qKpqQLssPfvADPPHEE3j33XcnfHyGYDAIp9PJVmRRFAWFQnFKrlsoFGKrjBgPUXFxcUzF6SaDXC7HvHnzoNfr4fP5kJ+fj8LCQvZZ7OjowNDQECQSCWbNmgWNRgOTyQSn0wmBQAAOh4ODBw+yFVt+vx9yuXxM44Xxqg7/nhiDaDqR8sYLk+w2HKlUGuVaM5vNUUm6HA4n6eVz8aSkpAQSiQRWqxU8Hg+5ublJbWg4a9Ys8Pl8GI1GyOVy5OfnIy8vLyX73jAv8zPxpc7lcmOqqEpILbhcbsxCw/n5+VCr1fD5fGyodyIViytWrEBubu6kNIkYr4vH44HL5WKlIuRy+bglIMrLy1MiJKpWq0cMbcvlcsydO/eUBq/Dc6CY0F9HRwfC4TAUCgWqqqrGbDQplUqhUqlgtVrZxr0+nw86ne6MnNdOR/Kv/hiIRKJTYoAnC7u98847USGGa6+9FrfcckvCxpgMUi0coNFoUFdXl+xhjBsi+ESY7kw1n2zZsmUxGsn0JSMjA5WVlayC7nhDzkuWLMHBgwdht9vB4XBQX1+P8vLylFwwxouUN14YS3V4clhXVxebtQ0Al112GZYuXcr+zOFwMDQ0lNiBEtICLpcLhUIBh8NxRoWNCIR0gTyDI+N2u+F2u8e9fUVFBbxeL7hcLiQSyRkjcjdeozrljReRSITFixfjjTfewPr162EymfDpp59i48aN7DZarTYqcc1sNpOHgjAq4XCY3CMEQhIhz+DUoCiKDbNNx+8x5Y0XAPjZz36Gp59+Gtdeey0kEgmuvPJK1NbWJntYBAKBQCAQkgBR2CVMK87UaiMCIV0gzyBhNMZb/j99snsIBAKBQCCcERDjhUAgEAgEQlpBjBcCgUAgEAhpBTFeCAQCgUAgpBXEeCEQCAQCgZBWEOOFQCAQCARCWkGMFwKBQCAQCGkFMV4IBAKBQCCkFcR4IRAIBAKBkFYQ44VAIBAIBEJacUa2ByAQTofZbMY777yDyy67bNwy1AQCIXaQZ5AQC4jnhTCtMJvNePHFF0n/KwIhSZBnkBALiPFCIBAIBAIhrSDGC4FAIBAIhLSCGC+EaYVWq8UNN9xAYu0EQpIgzyAhFpCEXQKBQCAQCGkF8bwQCAQCgUBIK4jxQkh57HY77r33XlxxxRV46qmnEnbcTz/9FBs2bEjY8QiE6cqhQ4dw9dVXJ3sYhDSCl+wBEAhj8dFHH0EkEmH79u2gKCrZwyEQCARCkiGeF0LKYzKZUFhYSAwXAoFAIAAgnhdCirNlyxZ88cUXoCgKH374IW677TaYTCZ8/PHHcDgcKC8vxy9+8Qu2cuGHP/whbr75Zrz//vswm80499xz8dOf/hRPPfUUmpqakJeXh7vuugs5OTkAgHfffRcfffQR7HY7NBoNrrrqKixatGjEsRiNRrzwwgtob2+HVCrFqlWrsHLlyoR9FwRCqrFu3TqsXLkSu3btgsFgQG1tLW677Ta88sor2L17N9RqNW6//XaUlZXhs88+wzvvvAOz2QyFQoFVq1bhoosuGnG/Q0NDePHFF3Ho0CHw+Xx897vfxf/8z/+AwyHrbcIJyJ1ASGnuuOMOLF26FJdccgneeustWK1W7Nq1C7/97W/x2muvobi4GI8++mjU33z77bd47LHH8Nxzz+Hbb7/Ffffdh8suuwx//etfUVhYiNdee43dNisrC4888gj+9re/Yc2aNdiyZcuIyp9+vx/3338/FixYgFdffRWbNm3C22+/jYaGhrh/BwRCKrN7927cf//9eOWVV9Df34+77roLCxcuxBtvvIElS5bg+eefBwAoFArce++92L59O2699Va8/PLLaG9vP2V/kUgEDz30EHJycvDnP/8Zjz32GL755hv8+9//TvSpEVIYYrwQ0oodO3bgqquuQlZWFng8HtasWYOOjg4MDg6y2/zoRz+CTCaDRqNBdXU1Zs2ahfLycnC5XCxZsgSdnZ3stosXL4ZGowGHw8G5556LvLw8tLW1nXLcb7/9Fmq1GitXrgSPx0N+fj6+//3vY9euXQk5bwIhVbnoooug0WgglUpRX1+PjIwMzJ8/H1wuF+eeey66uroQiURw1llnITc3FxRFobq6GnPnzsXhw4dP2V9HRwfMZjOuuuoqCAQCaDQarFq1ijxrhChI2IiQVphMJjz66KNR7mMOhwOz2QydTgcAUKlU7O+EQuEpP/t8Pvbnzz77DP/4xz8wMDAAAPB6vXA4HCMe99ixY1izZg37WSQSwezZs2N3cgRCGjLW8xYKhRAKhXDo0CH87W9/g9FoBE3T8Pv9yM/PP2V/AwMDsNvtWLt2LftZJBIhonaEKIjxQkgrdDodfv7zn2POnDlT3tfAwACefvppPPDAA6isrASXy8Wtt96KkXQbdTodKioq8Lvf/W7KxyUQphvBYBCPPPII1q9fj0WLFoHH4532WdJqtdBqtdi2bVuCR0lIJ0jYiJBWrFixAq+//jr6+voAAC6XC7t3757UvhgPjFKpBHDCC9PT0zPitvPnz8fAwAD+9a9/IRgMIhwOo7u7e8SYPYFAiIaiKIRCISiVSnC5XDQ0NJw2X6y0tBQKhQLbt2+Hz+dDJBKB0WgcMcREmL4QzwshrfjBD34AiqLw4IMPwmKxQCqVoq6uDkuWLJnwvgoLC3HppZfi7rvvBkVRWL58OSoqKkbcViwW44EHHsBLL72E119/HaFQCPn5+bjqqqumekoEwhkPj8fDDTfcgMcffxyhUAjz58/HggULRtyWy+Xi/vvvx8svv4ybbroJPp8PWVlZuOyyyxI8akIqQ3obEQgEAoFASCtI2IhAIBAIBEJaQYwXAoFAIBAIaQUxXggEAoFAIKQVxHghEAgEAoGQVhDjhUAgEAgEQlpBjBcCgUAgEAhpBTFeCAQCgUAgpBXEeCEQCAQCgZBWEOOFQCAQCARCWkGMFwKBEFfeeOMNLFiwAEqlEgqFApWVlVi3bh3byZtAIBAmCjFeCARC3Pj973+Pn/zkJzj33HPx5ptv4s0338R1112Hffv2wWg0Jnt4BAIhTSG9jQgEQtzIy8vDBRdcgJdeeumU30UiEXA4ZP1EIBAmDpk5CARC3LDZbMjJyRnxdycbLq+88gpqamogEomQl5eHe++9F6FQiP39pZdeilmzZsHpdLKfvf3226AoCh9++GF8ToBAIKQkxHghEAhxo76+Hs899xy2bduG/v7+0263ZcsWrFu3DhdccAE++OAD3H333fjTn/6E++67j93mhRdegNvtxm233QYA6Ovrw0033YQbb7wRF110UdzPhUAgpA4kbEQgEOLG4cOHcemll6KjowMAUFRUhIsvvhi33347Zs6cCQBwOp3Izc3FL3/5S/zud79j/3br1q3YsGED9Ho9NBoNAOD999/HJZdcgr///e94/vnn0dbWhsbGRshksoSfG4FASB7EeCEQCHElEAjgk08+wb/+9S/s3LkTjY2NkMvl2LVrF+rq6vDxxx/jwgsvxIEDBzBnzhz27zo6OlBZWYnPP/8cS5cuZT+//vrr8cYbbyAUCmHXrl1YtGhRMk6LQCAkERI2IhAIcUUgEGDlypV48skn0dDQgI8++ggejwcPPPAAAMBsNgMA5s2bBz6fz/5XWVkJANDr9VH7W7t2Lfx+P+bNm0cMFwJhmkI8LwQCIeHU19fD4/GgpaUFO3bswMqVK/Huu++ioKDglG2LiorYsJHH40FdXR0kEgkOHjyIbdu24brrrkv08AkEQpLhJXsABALhzMVkMiErKyvqM6/XC71ej6qqKgDAokWLIJFI0Nvbi0svvXTU/W3YsAEWiwU7d+7EY489httuuw3Lly9n82cIBML0gHheCARC3MjMzMTFF1+MCy64ADk5OTAajXjqqaewZ88evPvuu1i1ahUAYPPmzbjvvvuwfv16LFu2DBwOB8eOHcM//vEPvPPOO5BIJGxuzPbt23HFFVfA5/Ohvr4eOp0On332GdGMIRCmEcR4IRAIcWPr1q344IMPcOjQIQwODkKr1aKmpgYbN27EsmXLorbdvn07tmzZ8v/bsUMiCGIgioJDVkloBARFQdyEh66UdRMUJ2vg2Em4q6nq5h8MezVxzonruqKUEmOMWGvF+75Ra43eezzP893svaO1Fvd9x5zz1+cBfyJeAIBU/FkBgFTECwCQingBAFIRLwBAKuIFAEhFvAAAqYgXACAV8QIApCJeAIBUxAsAkIp4AQBS+QAnRbu8uugpJAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic.dropna(subset=['Age']), p9.aes(x='Sex', y='Age'))\n", + " + p9.geom_violin()\n", + " + p9.geom_jitter(alpha=0.2)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**regressions**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "plotnine supports a number of statistical functions with the [`geom_smooth` function]:(http://plotnine.readthedocs.io/en/stable/generated/plotnine.stats.stat_smooth.html#plotnine.stats.stat_smooth)\n", + "\n", + "The available methods are:\n", + "```\n", + "* 'auto' # Use loess if (n<1000), glm otherwise\n", + "* 'lm', 'ols' # Linear Model\n", + "* 'wls' # Weighted Linear Model\n", + "* 'rlm' # Robust Linear Model\n", + "* 'glm' # Generalized linear Model\n", + "* 'gls' # Generalized Least Squares\n", + "* 'lowess' # Locally Weighted Regression (simple)\n", + "* 'loess' # Locally Weighted Regression\n", + "* 'mavg' # Moving Average\n", + "* 'gpr' # Gaussian Process Regressor\n", + "```\n", + "\n", + "each of these functions are provided by existing Python libraries and integrated in plotnine, so make sure to have these dependencies installed (read the error message!)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/stijnvanhoey/miniconda3/envs/DS-python-data-analysis/lib/python3.7/site-packages/numpy/core/fromnumeric.py:2495: FutureWarning: Method .ptp is deprecated and will be removed in a future version. Use numpy.ptp instead.\n", + " return ptp(axis=axis, out=out, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic.dropna(subset=['Age', 'Sex', 'Fare']), \n", + " p9.aes(x='Fare', y='Age', color=\"Sex\"))\n", + " + p9.geom_point()\n", + " + p9.geom_rug(alpha=0.2)\n", + " + p9.geom_smooth(method='lm')\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/stijnvanhoey/miniconda3/envs/DS-python-data-analysis/lib/python3.7/site-packages/numpy/core/fromnumeric.py:2495: FutureWarning: Method .ptp is deprecated and will be removed in a future version. Use numpy.ptp instead.\n", + " return ptp(axis=axis, out=out, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(p9.ggplot(titanic.dropna(subset=['Age', 'Sex', 'Fare']), \n", + " p9.aes(x='Fare', y='Age', color=\"Sex\"))\n", + " + p9.geom_point()\n", + " + p9.geom_rug(alpha=0.2)\n", + " + p9.geom_smooth(method='lm')\n", + " + p9.facet_wrap(\"Survived\")\n", + " + p9.scale_color_brewer(type=\"qual\")\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Need more plotnine inspiration?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + " Remember\n", + "\n", + "[plotnine gallery](http://plotnine.readthedocs.io/en/stable/gallery.html) and [great documentation](http://plotnine.readthedocs.io/en/stable/api.html)\n", + "

\n", + "Important resources to start from!\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# What is `tidy`?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you're wondering what *tidy* data representations are, you can read the scientific paper by Hadley Wickham, http://vita.had.co.nz/papers/tidy-data.pdf. \n", + "\n", + "Here, we just introduce the main principle very briefly:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Compare:\n", + "\n", + "#### un-tidy\n", + " \n", + "| WWTP | Treatment A | Treatment B |\n", + "|:------|-------------|-------------|\n", + "| Destelbergen | 8. | 6.3 |\n", + "| Landegem | 7.5 | 5.2 |\n", + "| Dendermonde | 8.3 | 6.2 |\n", + "| Eeklo | 6.5 | 7.2 |\n", + "\n", + "*versus*\n", + "\n", + "#### tidy\n", + "\n", + "| WWTP | Treatment | pH |\n", + "|:------|:-------------:|:-------------:|\n", + "| Destelbergen | A | 8. |\n", + "| Landegem | A | 7.5 |\n", + "| Dendermonde | A | 8.3 |\n", + "| Eeklo | A | 6.5 |\n", + "| Destelbergen | B | 6.3 |\n", + "| Landegem | B | 5.2 |\n", + "| Dendermonde | B | 6.2 |\n", + "| Eeklo | B | 7.2 |" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This is sometimes also referred as *short* versus *long* format for a specific variable... Plotnine (and other grammar of graphics libraries) work better on `tidy` data, as it better supports `groupby`-like transactions!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + " Remember:\n", + " \n", + "

\n", + " \n", + " A tidy data set is setup as follows:\n", + " \n", + "
    \n", + "
  • Each variable forms a column and contains values
    • \n", + "
  • Each observation forms a row
    • \n", + "
  • Each type of observational unit forms a table.
    • \n", + "
\n", + "
" + ] + } + ], + "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "nav_menu": {}, + "toc": { + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 6, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": true + }, + "toc_position": { + "height": "860px", + "left": "0px", + "right": "1657px", + "top": "106px", + "width": "212px" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/_solved/visualization_02_seaborn.ipynb b/_solved/visualization_02_seaborn.ipynb index 97d1ad0..48d92cf 100644 --- a/_solved/visualization_02_seaborn.ipynb +++ b/_solved/visualization_02_seaborn.ipynb @@ -2,62 +2,40 @@ "cells": [ { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "

Visualization - Seaborn

\n", + "

Visualisation: Seaborn

\n", + "\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", - "---\n" + "---" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { - "deletable": true, - "editable": true, - "run_control": { - "frozen": false, - "read_only": false - }, "tags": [] }, "outputs": [], "source": [ + "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "# Seaborn" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true, - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "source": [ - "> Seaborn is a library for making attractive and **informative statistical** graphics in Python. It is built **on top of Matplotlib** and tightly integrated with the PyData stack, including **support for Numpy and Pandas** data structures and statistical routines from scipy and statsmodels.\n", - "\n", "[Seaborn](https://seaborn.pydata.org/) is a Python data visualization library:\n", "\n", "* Built on top of Matplotlib, but providing\n", @@ -71,12 +49,6 @@ "cell_type": "code", "execution_count": 2, "metadata": { - "deletable": true, - "editable": true, - "run_control": { - "frozen": false, - "read_only": false - }, "tags": [] }, "outputs": [], @@ -86,20 +58,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "## Introduction" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "We will use the Titanic example data set:" ] @@ -108,8 +74,6 @@ "cell_type": "code", "execution_count": 3, "metadata": { - "deletable": true, - "editable": true, "tags": [] }, "outputs": [], @@ -121,12 +85,7 @@ "cell_type": "code", "execution_count": 4, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -278,35 +237,24 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Let's consider following question:\n", - ">*For each class at the Titanic, how many people survived and how many died?*" + ">*For each class at the Titanic and each gender, what was the average age?*" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "Hence, we should define the *size/count* of respectively the zeros (died) and ones (survived) groups of column `Survived`, also grouped by the `Pclass`. In Pandas terminology:" + "Hence, we should define the *mean* of the male and female groups of column `Survived` in combination with the groups of the `Pclass` column. In Pandas terminology:" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -331,107 +279,98 @@ " \n", " \n", " Pclass\n", - " Survived\n", - " count\n", + " Sex\n", + " Age\n", " \n", " \n", " \n", " \n", " 0\n", " 1\n", - " 0\n", - " 80\n", + " female\n", + " 34.611765\n", " \n", " \n", " 1\n", " 1\n", - " 1\n", - " 136\n", + " male\n", + " 41.281386\n", " \n", " \n", " 2\n", " 2\n", - " 0\n", - " 97\n", + " female\n", + " 28.722973\n", " \n", " \n", " 3\n", " 2\n", - " 1\n", - " 87\n", + " male\n", + " 30.740707\n", " \n", " \n", " 4\n", " 3\n", - " 0\n", - " 372\n", + " female\n", + " 21.750000\n", " \n", " \n", " 5\n", " 3\n", - " 1\n", - " 119\n", + " male\n", + " 26.507589\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " Pclass Survived count\n", - "0 1 0 80\n", - "1 1 1 136\n", - "2 2 0 97\n", - "3 2 1 87\n", - "4 3 0 372\n", - "5 3 1 119" + " Pclass Sex Age\n", + "0 1 female 34.611765\n", + "1 1 male 41.281386\n", + "2 2 female 28.722973\n", + "3 2 male 30.740707\n", + "4 3 female 21.750000\n", + "5 3 male 26.507589" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "survived_stat = titanic.groupby([\"Pclass\", \"Survived\"]).size().rename('count').reset_index()\n", - "survived_stat\n", - "# Remark: the `rename` syntax is to provide the count column with a column name " + "age_stat = titanic.groupby([\"Pclass\", \"Sex\"])[\"Age\"].mean().reset_index()\n", + "age_stat" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Providing this data in a bar chart with pure Pandas is still partly supported:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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0dHV1jfTuJOmoMdQA3xkRLQDV667+Ombm4sxsz8z25ubmIe5OktTbUAN8FXB19f5q4OH6lCNJqlUtlxEuB54EzoiIzoi4FrgTOD8itgDnV8uSpFH0poE6ZOYV/ayaW+daJEmD4J2YklQoA1ySCmWAS1KhDHBJKpQBLkmFMsAlqVAGuCQVygCXpEIZ4JJUKANckgplgEtSoQxwSSqUAS5JhTLAJalQBrgkFcoAl6RCGeCSVKgBn8jzRiJiK7AH2A/sy8z2ehQlSRrYsAK8cl5m/rIO30eSNAhOoUhSoYYb4An8Y0SsjYgFfXWIiAUR0RERHV1dXcPcnSTpoOEG+JzM/H3gj4BPRcT7enfIzMWZ2Z6Z7c3NzcPcnSTpoGEFeGa+UL3uAh4CZtWjKEnSwIYc4BHx2xFx/MH3wB8CG+tVmCTpjQ3nKpSTgYci4uD3+ZvM/Ie6VCVJGtCQAzwznwdm1rEWSdIgeBmhJBXKAJekQhngklQoA1ySClWPz0KRNEZNufXvh7Td1gl1LmSElH58jsAlqVAGuCQVygCXpEIZ4JJUKE9iasQN5UTRkXKSaCClnwRT2RyBS1KhDHBJKpQBLkmFMsAlqVBFnMQc6yeKxvrxSRoZjsAlqVDDCvCImBcRz0bEcxFxa72KkiQNbDjPxBwH/CU9T6R/F3BFRLyrXoVJkt7YcEbgs4DnMvP5zHwNWAFcXJ+yJEkDicwc2oYRHwXmZeafVctXAbMz84Ze/RYAC6rFM4Bnh17uoDUBvxzF/Y22sXx8Y/nYwOMr3Wgf32mZ2dy7cThXoUQfbYf93yAzFwOLh7GfIYuIjsxsb8S+R8NYPr6xfGzg8ZXuSDm+4UyhdAJvPWS5FXhheOVIkmo1nAD/KXB6REyNiGOBy4FV9SlLkjSQIU+hZOa+iLgBeAQYB9yTmZvqVll9NGTqZhSN5eMby8cGHl/pjojjG/JJTElSY3knpiQVygCXpEIZ4JJUqCI+jbAWEfF79NwJego916O/AKzKzM0NLUw1qf77nQI8lZkvHdI+LzP/oXGV1UdEzAIyM39afeTEPOCZzPxhg0uru4j4TmZ+vNF1jJSIeC89d6JvzMx/bGgtY+EkZkR8FriCntv5O6vmVnoubVyRmXc2qrbREBF/mpl/1eg6hioibgI+BWwG2oCbM/Phat3Tmfn7DSxv2CLidno+M+hNwKPAbOAx4IPAI5n5lcZVNzwR0fvS4QDOA9YAZOZFo15UnUXEv2bmrOr9dfT8rj4E/CHwd43Ml7ES4P8HmJaZe3u1HwtsyszTG1PZ6IiIn2fmqY2uY6giYgPwnsx8KSKmACuBv87M/x0R/5aZZzW2wuGpjq8NeDPwC6A1M38dERPp+YvjzEbWNxwR8TTw78Dd9PzlG8ByegZPZOY/N666+jj0dzAifgpcmJldEfHbwL9k5oxG1TZWplAOAP8N2NarvaVaV7yIWN/fKuDk0axlBIw7OG2SmVsj4v3Ayog4jb4/sqE0+zJzP/ByRPwsM38NkJmvRETpv5/twM3AbcBnMnNdRLwyFoL7EMdExIn0nDOMzOwCyMz/FxH7GlnYWAnwW4DVEbEF2F61nQr8LnBDfxsV5mTgAuBXvdoD+Mnol1NXv4iItsxcB1CNxOcD9wANG93U0WsR8VuZ+TJw9sHGiDiBwgcYmXkA+EZEfK963cnYyZWDTgDW0vNvLSNicmb+IiKOo8EDjDExhQIQEcfQc2LhFHp+qJ3AT6uRT/EiYinwV5n54z7W/U1mfqwBZdVFRLTSM0r9RR/r5mTmEw0oq24i4s2Z+Zs+2puAlszc0ICyRkREfAiYk5mfa3QtIy0ifgs4OTP/b8NqGCsBLklHG68Dl6RCGeCSVCgDXJIKZYBLUqEMcEkq1P8HOQfCTeZB88oAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] @@ -443,56 +382,45 @@ } ], "source": [ - "survived_stat.plot(x='Survived', y='count', kind='bar')\n", + "age_stat.plot(kind='bar')\n", "## A possible other way of plotting this could be using groupby again: \n", - "# survived_stat.groupby('Pclass').plot(x='Survived', y='count', kind='bar') # (try yourself by uncommenting)" + "#age_stat.groupby('Pclass').plot(x='Sex', y='Age', kind='bar') # (try yourself by uncommenting)" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "but with mixed results. The default Pandas plotting functionalities are not sufficient." + "but with mixed results." ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__Seaborn__ provides another level of abstraction to visualize such *grouped* plots with different categories:" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 14, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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+ "image/png": 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\n", "text/plain": [ "
" ] @@ -504,180 +432,103 @@ } ], "source": [ - "sns.catplot(data=survived_stat, \n", - " x=\"Survived\", y=\"count\", \n", + "sns.catplot(data=age_stat, \n", + " x=\"Sex\", y=\"Age\", \n", " col=\"Pclass\", kind=\"bar\")" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Moreover, these `count` operations are embedded in Seaborn (similar to other 'Grammar of Graphics' packages such as ggplot in R and Plotnine/Altair in Python). We can do these operations directly on the original `titanic` data set in a single coding step:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sns.catplot(data=titanic, \n", - " x=\"Survived\", \n", - " col=\"Pclass\", kind=\"count\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Check here for a short recap about `tidy` data." ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
\n", "\n", "**Remember**\n", "\n", - "- Seaborn is especially suitable for these so-called tidy DataFrame representations.\n", + "- Seaborn is especially suitbale for these so-called tidy dataframe representations.\n", "- The [Seaborn tutorial](https://seaborn.pydata.org/tutorial/data_structure.html#long-form-vs-wide-form-data) provides a very good introduction to tidy (also called _long-form_) data. \n", - "- You can use __Pandas column names__ as input for the visualization functions of Seaborn.\n", + "- You can use __Pandas column names__ as input for the visualisation functions of Seaborn.\n", "\n", "
" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "## Interaction with Matplotlib" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Seaborn builds on top of Matplotlib/Pandas, adding an additional layer of convenience. \n", "\n", "Topic-wise, Seaborn provides three main modules, i.e. type of plots:\n", "\n", - "- __relational__: understanding how variables in a data set relate to each other\n", - "- __distribution__: specialize in representing the distribution of data points\n", + "- __relational__: understanding how variables in a dataset relate to each other\n", + "- __distribution__: specialize in representing the distribution of datapoints\n", "- __categorical__: visualize a relationship involving categorical data (i.e. plot something _for each category_)\n", "\n", - "In 'technical' terms, when working with Seaborn functions, it is important to understand which level of Matplotlib object they operate, as `Axes-level` or `Figure-level`: \n", - "\n", - "- __axes-level__ functions plot data onto a single `matplotlib.pyplot.Axes` object and return the `Axes`\n", - "- __figure-level__ functions return a Seaborn object, `FacetGrid`, which is a `matplotlib.pyplot.Figure`\n", - "\n", - "_Remember the Matplotlib `Figure`, `axes` and `axis` anatomy explained in [visualization_01_matplotlib](visualization_01_matplotlib.ipynb)?_\n", - "\n", - "Each plot module has a single `Figure`-level function, which offers a unitary interface to its various `Axes`-level functions. The organization looks like this:" + "The organization looks like this:" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "![](../img/seaborn_overview_modules.png)" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, + "source": [ + "We first check out the top commands of each of the types of plots: `relplot`, `displot`, `catplot`, each returning a Matplotlib `Figure`:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ "### Figure level functions" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Let's start from: _What is the relation between Age and Fare?_" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 58, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 11, + "execution_count": 58, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -695,39 +546,31 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Extend to: _Is the relation between Age and Fare different for people how survived?_" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 59, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 59, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -739,36 +582,27 @@ } ], "source": [ - "# Include the 'survived' variable (column name) into the plot function to define the color\n", "sns.relplot(data=titanic, x=\"Age\", y=\"Fare\",\n", " hue=\"Survived\")" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Extend to: _Is the relation between Age and Fare different for people how survived and/or the gender of the passengers?_" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 60, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { - "image/png": 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DE4HTgSeVUtY+7J8QQgghhBCiC/osaNBGlXvTz/2lgfOA59ztzwHnu78/D3hVa12vtd4P7AXm9FX/hBBCCCGEEF3Tp2salFJWpdRGoAD4VGu9CojXWucCuP+Nc++eDBxq8fAsd1vbY96ilFqrlFpbWFjYl90XQoghRc6vQggh2tOnQYPW2qm1ngakAHOUUpM62F35OoSPYz6ltZ6ltZ4VGxvbSz0VQggh51chhBDt6ZfsSVrrMuBLzFqFfKVUIoD73wL3bllAaouHpQA5/dE/IYQQQgghRPv6MntSrFIqwv19IHAysBNYAlzn3u064F3390uAy5VS/kqp4cBoYHVf9U8IIYQQQgjRNbY+PHYi8Jw7A5IFWKy1fl8ptRJYrJS6EcgELgHQWm9TSi0GtgMO4HattbMP+yeEEEIIIYTogj4LGrTWm4HpPtqLgZPaeczDwMN91SchhBBCCCHE4ZOK0EIIIYQQQogOSdAghBBCCCGE6JAEDUIIIYQQQogOSdAghBBCCCGE6JAEDUIIIYQQQogOSdAghBBCCCGE6JAEDUIIIYQQQogOSdAghBBCCCFEH1FK/VIptU0ptVkptVEpNbcXjnmuUureXupfVVf268uK0EIIIYQQQgxZSqn5wNnADK11vVIqBrB38bE2rbXD18+01kuAJb3X087JSIMQQgghhBB9IxEo0lrXA2iti7TWOUqpA+4AAqXULKXUl+7vH1JKPaWU+gR4Xim1Sik1selgSqkvlVIzlVLXK6UeV0qFu49lcf88SCl1SCnlp5QaqZT6WCm1Tin1tVJqnHuf4UqplUqpNUqp33b1hXQ5aFBKHauUusH9faxSanhXHyuEEEIIIcQQ9AmQqpTarZR6Uil1fBceMxM4T2t9JfAqcCmAUioRSNJar2vaUWtdDmwCmo57DrBUa90IPAXcqbWeCfwEeNK9z6PAP7XWs4G8rr6QLk1PUko9CMwCxgL/A/yAF4FjuvpE4shWVFXPrrxKahucjIwLYXhM8EB3SYhWquoc7MqvoKiygdSoQEbHh+JnlcFScQRyOqAiCyw2CE/pfP+KHHDUQ1gy2FrMWtAaCndCyT4IjIKokVCeBZU5EJ4KsePAL6DvXocQose01lVKqZnAccAi4LUurEVYorWudX+/GPgUeBATPLzuY//XgMuAL4DLgSeVUiHAAuB1pVTTfv7uf48BLnJ//wLwx668lq6uabgAmA6sB3APq4R28bHiCJdTVss9izfyXUYJAGGBNl64cS5TUyIGtmNCuFXVOXjiiz3886sMAKwWxT+umM6ZkxMHuGdCtFGeDSufgDVPgS0QTnoAplwGAeHe+zbUwPZ34ZP7oK4cplwBx/8UIoeZn2d8CS9fCs4GSJgMY06D5X82P1MKzn4Mpl8FFmt/vTohRDdorZ3Al8CXSqktwHWAA8+Mn7bRf3WLx2YrpYqVUlMwgcGtPp5iCfB7pVQUZpRiGRAMlGmtp7XXrcN9HV29TdegtdZNT6CUktvQR5H1B0ubAwaAiloHj322h7pG5wD2SgiP3fmVzQEDgNOl+cVbWzhUUjOAvRLCh21vwXdPgLMR6ivgw59C5irf++ZsgHdug5oScDlh44uw+r/gckFVIbx3lwkYAMadDV//1fNYreGjn0Dxvj5/SUKI7lNKjVVKjW7RNA04CBzAXOCD565/e14FfgaEa623tP2h1roKWI2ZdvS+1tqpta4A9iulLnH3Qymlprof8g1mRALgqq6+lq4GDYuVUv8GIpRSNwOfAU939UnEke2gjwuvLdnlVNX5XLAvRL8rrq73aiuvbaSitnEAeiNEO+orYcOL3u0ZX/reP2+zd9vml6G6wAQcZQc87a5G0K7W+zrqobYEIcQRLQR4Tim1XSm1GZgAPAT8GnhUKfU10Nld2jcwF/mLO9jnNeBq979NrgJuVEptArYB57nbfwTcrpRaA/gYBvWt0+lJykyEeg0YB1Rg1jX8Smv9aVefRBzZJiWHebWdPSWRyOAuZQQTos+lRgVhsygcLs9o6oiYIBLDZT63OIJYAyBuvFmH0FJUO3lDQuK926JGgj0Y/IJh2HFw4GvTrjXYQ6ChRTr14NiurZkQQgwY96LlBT5+9DUwxsf+D/loy6fNNbvW+lng2RbbbwCqzT77gdN9HG8/ML9F0x/afwUenY40uKclvaO1/lRr/VOt9U8kYDi6TEuN4N4zxuFvM38OJ46L5Zr5w7BaVCePFKJ/jI4L5Z9XzyDKHciOjA3m75dPJyrEv5NHCtGPbH6w4E5zcd8kcjiMWOR7/+RZkDitxeP94aSHwD8UAkLhjD9C0gzzs23vwHlPQKh7HU9EOlz6ggQNQoh+o0xM0MlOSj0BPKu1XtP3Xeq6WbNm6bVr1w50N44KLpfmYEk1DQ4XKVFBBNul7p848uSU1VJe20h8mD9RwRIwdFG3on85v/ZAwU4o2A5Wu1nAHJne/r7l2WaaUkO1yYYUP9Escm5SW2YyJvmHmuNU5EBNMQTHQ2hcn78UIUS7htyd1a5eGS4CblVKHcSs6FaYQYgpfdYz0a8sFsXwmJDOdxRiACVFBJIUETjQ3RCiY3HjzFdXhCebr/YERpivJmFJ5ksIIfpZV4OGM/q0F+KoU1JVj1JK1kUIIYQ4+tRVQmMNhMS1HhkS4ijWpaBBa30QQCkVh3cuWSGaldU08OGWXB5ftherVXHPyWM4ZUICIQEy3UkIIcQg53KaxemfPQTlh2D6dTDreohIG+ieCdHnupRyVSl1rlJqD7Af+AqTW/ajPuyXGKSW7y7ivre3klNex6GSWu5evInV+4sHultCCCFEz+VthhcvMjU2qotgxV9g1b9NMCHEUa6rdRp+C8wDdmuthwMnYQpDCNHM6XTx0qqDXu3vbc4dgN4IIYQQvaxgB7ja1DBa+1+olM85ceRSSp2ulNqllNqrlLq3u8fpatDQqLUuBixKKYvW+gtMRTshmlksipRI70WqybJwVQghxNHAHuzdFhQDVsnmJo5MSikr8ARmffIE4Aql1ITuHKurE83LlFIhwHLgJaVUASDlgkUrSimunpfO+5tzqXeYyqWh/jZOn5QwwD0TQgghekHiNIgZC0W7PG2nPQIhsQPWJXF0GXbvB1cCjwBpQCZw34E/nPVyDw45B9irtc4AUEq9iqkMvf1wD9Rh0KCUStNaZ7oPXgvcjSlJHQ785nCfTBz9pqdF8vYPFrDxUBlWi2JaagRjE7wrTgshhBCDTmQ6XPkaZK8z9TISpkDS9IHulThKuAOGp4Egd1M68PSwez+gB4FDMnCoxXYWMLc7B+pspOEdYIbWulop9abW+iLgue48kRg6JiSFMyEpfKC7IYQQQvS+qOHmS4je9wiegKFJkLu9u0GDr5zAnVd29qGzNQ0tn2hEd55ACCGEEEII0an2cvf2JKdvFpDaYjsFyOnOgToLGnQ73wshhBBCCCF6T+ZhtnfFGmC0Umq4UsoOXA4s6c6BOpueNFUpVYEZcQh0f497W2utZbK6EEIIIYQQPXcfrdc0ANS427tFa+1QSt0BLAWswDNa623dOVaHIw1aa6vWOkxrHaq1trm/b9qWgEEIIYRoy+WEskwozx7ongwO5TlQehCc3UjKWJEDpQfA2djr3RKiv7kXO98MHMTM8DkI3NzD7ElorT/UWo/RWo/UWj/c3eN0NeWqEEIIITpTkQMr/wmr/wV+QXDSr2DSJRAo99m81FXA1jfg899AQzXMuRnm3Q7hyZ0/tr4atr8Dn95vjjPzBjjmRxCR2ulDhTiSuQOEHgUJfaWrxd2EEEII0Zmtb8PKx8DZAHVl8ME9kLVqoHt1ZMpaA+/fDbWl5v1a+YQJIroiZx28+wOoKTEVmtc8DeufBy3LL4XoKxI0CCGEEL2hvhI2PO/dvu+L/u/LYLB/uXfbhhegtrzzxx5a49228SWoLup5v4QQPknQIIQQQvQGawDEjvdul5z+vkUO826LGQd+AZ0/1tcUpuhRYG+b4l4I0VskaBBCCCF6g80PFtwB9mBPW0Q6jDhhwLp0RBt+HES2CKj8guDYu8Dm3/ljU+e1DtBsAbDoF63feyFEr5KF0EIIIURvSZkFN30O+dvMxW/CZN931IUZGbj2XcjbDI56iJ8AcRO69tioYXDVYsjbAo21EDe+648VQnSLBA1CCCFEb4obb75E5yLTzVd3RKSZLyFEh5RSzwBnAwVa60ndPY5MTxJCCCGEEOLo9Sxwek8PIiMNYkBV1zvYV1hFZZ2D9OggUiJlEZsQ4ghUng0V2RAYBVEjwDLI77k5G6FkH9RVmjv9IXED3aOeqy03r8nqB1EjZVG0GJweCr8SeARIAzKB+3iovKfF3ZYrpYb1tGsSNIgBU1rdwKOf7+bZbw8CEBVs53/Xz2ZqasTAdkwIIVrK/A4WXwNVBeAXCGf9FSZdDDb7QPese+orYe3/YNlvTPAQORwufR4Spwx0z7qveC+8dxcc+NpsT78WFt0HYYkD2i0hDosJGJ4GmiLedOBpHgqnp4FDbxjkt0rEYLY1u7w5YAAoqW7gt+9vp6qucQB7JYQQLVTmw5s3m4ABzKLbd38AhTsHtl89kbsZPn3ABAwApfvh41+YUYfBSGvY9KonYABTL+PgNwPXJyG65xE8AUOTIHf7gJOgQQyYvIo6r7YNh8ooq5WgQQhxhKjKh/LM1m1aQ1mm7/0HA199P7gCaor7vy+9oaEGdn7g3X7w2/7vixA9097K/iNixb8EDWLAJEcEerUtGBFNZPAgHfIXQhx9gqIhONa7PXQQT3vx1ffEqRAY0e9d6RV+gTB8oXd78vT+74sQPdPe3Ygj4i6FBA1iwExKDufuk0djtSgA0qIC+cWZ4wi2y1IbIcQRIjwZzv+XuTAFUApO+c3gTqmaOBXm/sCzHRgJZ/558AYNFgvMvB6iRnnaRiyCYccPWJeE6Kb7gJo2bTXu9m5TSr0CrATGKqWylFI3dus4Wuue9GNAzZo1S69du3aguyF6oMHhZH9RNVX1TtKiAokNDRjoLglxtFHdeZCcX1vQ2iy0Lcs0ow4xY8BvkJ+r6qugaDfUlZuF0FHDBrpHPVeZZ16T1W5+R0FRA90jcXTr1rm1U32QPam39FnQoJRKBZ4HEgAX8JTW+lGlVBTwGjAMOABcqrUudT/mF8CNgBP4odZ6aUfPIR9qQgjRKQkahBCi9/VN0HAE68vpSQ7gx1rr8cA84Hal1ATgXuBzrfVo4HP3Nu6fXQ5MxBSgeFIpZe3D/gkhhBBCCCG6oM+CBq11rtZ6vfv7SmAHkAycBzzn3u054Hz39+cBr2qt67XW+4G9wJy+6p8QQgghhBCia/plIbS7Ct10YBUQr7XOBRNYAE1lKJOBQy0eluVua3usW5RSa5VSawsLC/u030IIMZTI+VUIIUR7+jxoUEqFAG8Cd2mtKzra1Ueb14ILrfVTWutZWutZsbE+0uAJIYToFjm/CiGEaE+fBg1KKT9MwPCS1votd3O+UirR/fNEwF1mkywgtcXDU4CcvuyfEEIIIYQQonN9FjQopRTwX2CH1vqvLX60BLjO/f11wLst2i9XSvkrpYYDo4HVfdU/IYQQQgghRNf0ZRWtY4BrgC1KqY3utvuAPwCL3YUlMoFLALTW25RSi4HtmMxLt2utnX3YPyGEEEIIIUQX9FnQoLVeQfs5bE9q5zEPAw/3VZ+EEEIIIYQQh69fsicJIYQQQgghBi8JGoQQQgghhBAdkqBBCCGEEEII0SEJGoQQQgghhBAdkqBBCCGEEEII0SEJGoQQQgghhBAdkqBBCCGEEEII0SEJGoQQQgghhBAdkqBBCCGEEEII0SEJGoQQQgjhrb4SHPUD3Yve43JCXQVoPdA9EWJQsg10B4QQQghxBKnMh53vwZr/QngaHHsXpM0DpQa6Z92Xvx1WPw0HV8C4s2D6NRA9cqB7JcSgIkGDEEIIITw2vQKfPWi+L9gOGcvgps8gcerA9qu7KnLglcuh7KDZXrEbstbBZS9CYPjA9k2IQUSmJwkhhBDCqMyDbx9r3eZsgNwtA9Of3lC02xMwNDmwHEr3D0x/hBikJGgQQgghhGGxgT3Yu93m3/996S1Wu3ebUmDx6/++CDGISdAghBBCCCM4Bk56sE1bLCRNG5Du9IrYsTDixNZts26SNQ1CHCZZ0yCEEEIIj7FnwDXvwL7PISwZRiyCmNED3avuC4qGcx+FAysgdzOkzYW0BeAXMNA9E2JQkaBBiE6UVNez7mAZ6w6WMDo+lLnDokiJChrobgkhRN+wB8PIReZrINWUwKFVkPkdxIyBYcdCZHr3jhWRBtOuNF+DVUmGCXyK90H6AkidC4ERA90rMYQM3aChaI85EdWVQcocSJoONh/zHsWQ1uh08cyK/Tz+xb7mttnDInnyqpnEhg7iOb5C9JOaBgebDpWz8VAZCWH+zEyPJC3ax5x5YeoH5G6EzFVg9TNpTuMntrv7gaJq1h4spbiqnulpEUxNicDfz9p//e1LLies+Q988bCnLXkmXP4yhCYMXL8GSnk2vHqVyWYF8M3f4bRHYN4PBncqXDGoDM2goWgPPHcOVOaabaXgyjdg9MkD2y9xxMksruFfX2W0altzoJQ9+ZUSNAjRBUu35XH3a5uat0fHhfC/G2aTEimjdV4OrYLnzgZno9n2D4XrP4TEKV67Hiyu5tpnVpFZUtvc9s+rZ3DGpMT+6m3fKt0Py//Uui17HRTsGJpBQ/5WT8DQ5IuHYdzZ3R99EeIwDc2F0IdWeQIGMHd3Pv8N1FUOXJ/EEanB6cLh8q4eWu9wDUBvhBhcCirq+N37O1q17SmoYltOxQD16AjmcsKqf3kCBjAVmXd+4HP3rdnlrQIGgIc/2EFx1VFSwdnZaFK9tnU0Vag+HL5ed2Nt678XIfrY0Awa6sq922qKwFHX/30RR7S0qCBOGhfXqi062M6ouJAB6pEQg0eD00VFnfdFTW2DcwB6c4TTTlOErK2WN7haqPHxHpbXNNJwtNzQiEiHCee3bguMhNgxA9KdARc3HvzDWrdNvRIiUgemP2JIGprTk5JngbKAbnFynXcbhMQOXJ/EESnY38YD50xgXEIo72/JZUZqBDcvHEGqLIQWolPxYQFcOSeN51Z6CmvZrRbGxEvQ7cVqh9k3m5HwltpeOLuNSwjFZlGtRkKvW5BOfNhRkhHIHgQnPwTRo2Hbm2bd4TE/gqgRA92zgaGscOL9sOcTsyB65ImQOA2Q9Qyi/yitvadeDBazZs3Sa9euPfwHOhth/3JY9juoLoS5t8DkS4fmPEnRJVprymsbCbbb8LMNzQE6MWh166qi2+fXNrJKa1i85hCvrT1EenQwPzl1DLOHRaFk8aa3mlLY+T6s+KsJIhbdByNPBn/vheNOl2bV/mL+8skucsrquGpuGhfOSCEpInAAOt6HtIbaMpPRaSgnK9m+BBZfA6lzIDzVJHKpyoPbV0P0qIHu3VA15E5iQzNoaFJfaeYJBsf0XqeEEOLIMqBBA5igu7i6gSC7lSD70BzgPiw1JWY0vAvpNKvrHNQ5nESHSGKGo9quj+GVy1q3+QXBD1ZC5LAB6ZIYekHD0D57+4eaLyGEEH1GKUWMXNR2XVBUl3cNDrARPMQ/yoeEhEkQMxaKdnnajv+5WfshRD+RM43olnqHk8o6B+GBfvhZZbqOEEKIFqqLzXQi/1BwOqC21HwvVZi7JzwFrngFMr4ygcPwE0wdD5nmJ/qRBA3isG3PqeDxL/aw7mApJ46L48ZjhzMqTkZsjkiNNWCxg1X+qwsh+kFlPmx5HVb/G4Lj4JRfw7Z3zFqN5Fmw8KeQNLXrxyveC2WHICjaTMMpyzRrEcNTIXrk0Lpojh5pvoQYIHIlIQ5LTlktNzy7mvwKkzP6ldWH2JFbybM3zCYiaAgvUjvSVOaZ/O7rnzND2vNuM9VUhRCiL21ZDJ/cb75PmAKfPQRZa8z2zvfg0Eq4aVnXCpJlfAmvXgkN1SZT0Liz4ctHTOZDvyC49AUpyipEP5J5JeKwZBRWNQcMTTYeKuNgSc0A9Uh4cblgzX/hg3sgd5P5EH/uXFNJVQgh+kpVIXz3T892/ARPwNCkugiK9nR+rMo8ePs2EzAAjD8bvvidJ1V6Yw28cxuUZ/VO34UQnZKgQRyWAD+rV5tFQYCkIT1yVOTAyn+0bmuogvxtA9MfIcTQYPM304iaaBdYfExo8OtCWtjqotaF7XwVX60uNPsJIfqFXOmJwzIqPoQzJrWuZ3HTcSMYFuOdR1wMEIsFbD4WG1r8+r8vQoihIyAMTvqVZ53Bro9gxrWt9xl1KsSN6/xYIXEQMcyzbQswaWhbCkuS+kpC9CNZ0yAOS0SgnYfOmcA5U5PYV1DFhKQwpqdF4G/zHoEQAyQsCU58wExPahKaBAmTB65PQoihYfjxcMPHprJ1QASkzIExZ5ipkjGjzHbL0Yj2hMTBhf+G1642Iwrb3oHT/wifPmBGHYKi4cL/SNAgRD8a2sXdhDha1ZVD5krYtdRk2xh9CsSOHeheiYEx4MXdhOi28izzFRgFUcOh9ADUFENYMkSkDnTvxNA2hFJ3GTLSIMTRKCAcxpxuvoQQYrAKTzFfTWJGA6MHrDtCDGUSNBxpKnKhYDu4HBA7rmtp6UTPVeRBwTb3+z7W5AMXQgxdJRlQuMvMpY+faKbLiMPnaIDCnVB2EELiIW68KfImhBh0JGg4khRnwOvXQt4Wsx0SB1e/bcrHi75Tsh9ev87MuQUIjoVr3pY1AEIMVTkb4IULTBVjgLT5cOFTEJE2sP0ajHa8B2/d5EmVuvDncMyPwF+SZwgx2Ej2pCPJvmWegAGgqgDWPmPy7ou+s/8rT8AAZtHdqqfA5Ry4PgkhBoajHr7+qydgALM+KHPVwPVpsCo5AO//yBMwACz/IxTtHLAuCSG6T4KGI0neZu+2Q6t856cWvSdvq3db9hpTPEgIMbTUV5qRhraKu1CQTLRWV2rez7aqCvu/L0KIHpOg4Ugy8kTvtskXgz2o//sylAxf6N026WKZd9sNVXUOvthZwD2LN/KnpTvZmlM+0F0S4vAERsHEC7zbU2b1f1+qi0yq0ddvhOV/hoJ+ukNfW25qLLx1Cyx7GHK3dP4YX0KTIaLNujyrXdaMCTFIyZqGI0n6Ajj2bvj2H6Cd5sJ10kW9c2xnIxTsMIv7gmMhfhIEhvfOsQe79Plw3E/g20fNQugJF8DkSwa6V4ftUEkNu/IqUQrGJYSRHNmFqqu97POd+fzo1Y3N2899e5A3vz+fsQlh/d4XIbrFYoFZN0DRHtj9kalyvPBnkDy7f/uhNax/Hj7/tdneBqz5L9zwoUk92pd2vg/v/sCzvfopuHGpSc5xOELj4OL/wVs3Q8k+CI6Bc5+AmDHtP6Zor1k43bQAPSyxe69BCNHrJGg4koTEwaJfwrSrzHz6yHTw66ULv10fwuvXN88t1bNvInPaj8motJESGciI2BCsliGXctgIjoUTfgFTLzdBQ8QwsPf/BXdP7Mqr4NpnVpNfUQ9ASmQgz94wh1FxIf3Wh7KaBv726e5WbVX1DjZklknQIAaXqBFw8X9Nxh+rHSKHg6WDApY1JeZC11EH0aN7p35A2SFY/qfWbZU5kL+tb4OGqgL44uHWbXVlkLPx8IMGgJSZ8L2lUJVnRnHCk9vfN2cDPH+eqTMDkDgdLnkWooYd/vMKIXqdBA1HGqufOw91Lyo7BO+1Xoym1vyHnKBF3LBUYbdaeOKqGZwyIb53n3cwsdp6/33vR29tyG4OGACySmtZui2PUP9kAvyshAfZ+7wPLq1xuLyLRTqcg7eApBjC7MEQN6Hz/cqz4P17YM9Ssx2aAFe90QvZ11xmxNmruQ8TNFQVmDUIgZFQkd36Z7oHCTlCYs1XR5oWoNe1mNKYuwEyv5WgQYgjhKxpGArqK1pnAnELcZYB0OB08dM3NpFdWtvPHRO9weXSbMgs82pfd7CU21/ewMX/Wsny3YU4fVzQ96aoYH9uXzSyVZu/zcK0tIg+fV4hBtSh1Z6AAaAyD7551NQn6InwVJh3e+u2wEgzZae31ZbB2mfhX8fCM6eaNR3jzvb83C8IEqb0/vO21FDTOntgk+K9ffu8Qoguk6BhKAhN8r7rZbGSY/HMFS2raaSkpocfcmJAWCyK86YlebVPTApja045ewqquOHZNWzPrejzvpwxKZHHLp/O3OGRXDgjmVdunsekZFk7I45ihT4WJ2euNDdresJihbm3wjmPQeocmH0zXLsEYkb17Li+HFhhUqNW5ZvF18t+axJzDF8E066G697r+3pBgREm8UdbqXP79nmFEF0m05OGgqBIOO+fsOQOyN0IwbHsm/97fv+t585zUngA8aH+A9dH0SMnjYtnz/wqXlh1EIuC86cnk1lSQ12jmVLgdGn25lcyuY8v4COC7Jw7LYmzJidgsSiUGqLrZMTQkTTNu23c2WZUoKdCE2DmdWadm7UPP663vOHdtu0tuPpdsFqhP/4fKwXTrzbFNre9aRZCH3+vBA1CHEH67CyklHoGOBso0FpPcrdFAa8Bw4ADwKVa61L3z34B3Ag4gR9qrZf6OKzorsTJcO27UJmL0x7KniwrRdWmLkRcqD+PXTGduLCAAe6k6K6E8AB+edZ4rl2QToPDxW/e28a3GSWt9gkJ6L97BFarDGKKISJlDiz4Eaz8h5n3nzYfZt/U8cLpw9WXAQNA9AgfbaPB1s/3FSOHwXmPwwk/B4ufSddqkXOJEEeKvjwjPAs8Djzfou1e4HOt9R+UUve6t3+ulJoAXA5MBJKAz5RSY7T2tQpMdFtgBARGYAVOj4DxiWGUVjeQEBFAQtjgyhYkvPnZLIyINdmSrlswjJX7S9DuwaSpKeFMTJJpQkL0uuAYOPF+mHaFWcwbOXzwpbOeeAGsfcaz9s0eAjOuHZi++AV2nJJVCDFg+ixo0FovV0oNa9N8HnCC+/vngC+Bn7vbX9Va1wP7lVJ7gTnAyr7qn4D06GDSo4MHuhuiD5wwNo43b1vAnvxKwoP8mJIcQVKEBIZC9AmbHeLGD3Qvui9hskmLmrvJjJYkTIH4LmSOEkIMKf29piFea50LoLXOVUrFuduTge9a7JflbvOilLoFuAUgLS2tD7sqxODl72dlRnokM9J7YV61GDLk/DqExY6F4DhAQ1DUQPdmcNMaqgvNqIl/6ED3Rohec6RMFvS1yspnfkit9VNa61la61mxsZ3kfRZCCNFlcn4douorYfNi+M+J8PQiWP+CScMqDl/ZIfjiEZO+9vkLYP9ycPWgxoUQR5D+HmnIV0olukcZEoECd3sW0LKEZgqQ0899E32hvgqy15lc5mFJkL6gb6uZ9pWGanPnyD/cZKPqRQWVdTQ4XMSHBeAnC4iFOLrUVkD2Gshaa4qUpc6HyCNsFOfgt/DWzZ7tJXeAf4hZ69Ce6iJzXgyJB782STScDlO92uoPoUOoaKjLCaufgm8fM9tV+fDCBXDT576zbAkxyPR30LAEuA74g/vfd1u0v6yU+itmIfRoYHU/9030he3vwrs/8GzHjIWr34SI1PYfc6TJ3w6fPAD7PoPYCXDWn2HYMT0+bF2jg6Xb8vnd+zsoq23gijlp3LJwBCmRQd3vZ95mk7owYSrEjetxH4UQPaA1bHwBlt7naUueCZe9BGGJ7T+uv21e7N225hkYf5539iKXEzK+hA9+DGUHzD4n3g8xo83PyzLh28dh3TMm7eypD5sUtPZuntcGk8pcWPOf1m0uBxRsl6BBHBX67LamUuoVzELmsUqpLKXUjZhg4RSl1B7gFPc2WuttwGJgO/AxcLtkTjoKVOTAp/e3bivaBbmbB6Y/3VFTCu983wQMAIXb4aWLoWh3jw+96VA5P3p1I4VV9TQ6Nc+vPMgrqzPRuhuVm3M2wH9PgbdvhbdugWdO811dVQjRO8qzIX8b1JS0v0/ZQVj2u9Zt2evM444kYT6WEEak+U53mr8N3r0Dxp4Bx/3EtH36oKnorDWsfx5W/xucjVBVYEYwcjb0bf+PFDZ/CIr2brdLwhFxdOizoEFrfYXWOlFr7ae1TtFa/1drXay1PklrPdr9b0mL/R/WWo/UWo/VWn/UV/0S/cjZaObKtuWo7f++dFd5limI11JjDRTv6/Ght2SXe7UtXptFUVX94R9s/fPQUOXZriuDbW93v3NCCN9cTtj1ETx1PPxzATx7NuRs9L2vs9H3+e5IOweOP9ukWW1iC4BpV/retzwLZt8Im16B5X+C0gOQPh8qcs0Uzg0veD8mZ32fdPuIExwLpz3cui1qFCROG5DuCNHbpCK06DthSTDzBjPHs4ktYHClJrQHg1+QCRRaCojo8aFjQrwrcKdFBbI7r5L1mWVMSAwjNaoLQ/ouFxTt8W7vhcBGCNFG4U547Woz7QSgYJsZ3bvhIwhuc5c5PAUmXghb3/S0+YdCbDenDjobzf/16gIITYLoUb1T/Kw8G469yz1a4IKAMBMM+JqGafWDL35HcxGY3I2mbfz55lwZORwq81o/JiSh632pzDOv0RZg6jUMtpoXo0+F6z80oyvBsZA6ByLTu/748iwoyQC/YIgdI9mXxBFFgoauaKw1J4Cmk0DK7MG5mLe/Wf1gwZ1muHbDi+YD7oR7IX6iz90bHC7WHyxl8dpDaODSWanMTI/EbhvAxcFRw+G0R+D9uzxtUy7v/od+CzPSIhkbH8KufDNCYLdaOHdqEtf9bw0OlyYlIoBnvzeHUXGdfGhYLDDzOjjwdev2yZf0uI9CiDZKD3gChiZFu8x0zLZBg18gnPiAmeqz5XWInwwLf+qZ/384nI3mGEvuNM9v84cLn4bx55p1TD2x9U3Y+Z45JgocdZA2D6Ze4R2U1JR4AoYmWWvAWWcWTx93D7x6FTgbzM+iR5t0rl1RsB1euRJK95vtCefBaX+A8KQevbx+5Rdogq3urHvL3QwvX+IJuqZfCyc9ACFxHT9OiH4iQUNX7P4YXr/esx0zFq5648jLgHGEqG90kllSg0Up0qJS8DvhXph9k7kL1cFiuPUHS7niP981fx69szGbl2+ax/yRPuaI9oGymgacLk10yxEApWDKpWZ0pCTDZApJnNIrGZTSooP47/Wz2ZZTQU2DE6fLxZ+X7sbhMm9AXkU9u/IqaXRqQvxtHY86jDgRTv+DmS5gscIJv4Bhx3b4WnflV1JZ62BYTFDngUlvKs2E+gozEiX54MVgExTj3RYQAQEt7oiXHoTCXebGSdwEOOlBmH+7mQLk180ii0V7PAEDmOrT7/wA4idB9EjPftVFgPIOYDqSPNMEDY4WUyNT5vgexfCVDSksGfzDTDaldS+YwMjVCMpqqkwX7TbnTV8Kd5t1HlY77PvcEzCASaQx4TwIv6jrr2Wwaqg1619ajtJseB7GnwVjTu/58StyzPtcnmU+z5JmmBElIQ6DBA2dqSponfkC3It5Nw2poKGqrpG8inpC/K0khLf/oZdTVsvfPt3NG+uzsCjFdfPTufX4kcSH+figbcnl4u0NWa1uYGkNr6w+2OdBQ22Dg2U7C/nrp7uoaXBy68IRnDM1yRM82IPNXbe0eb3+3CmRQaREBlHX6OTif31LXkUdABYFPz9jHE98sZftuZWE+tv49XkTOWtyIv5+1tYHcbnMBcK875sUicrS4Z2poqp6fvf+dt7ZaLIaB/hZeO6GOcwd4Xmfaxoc5JbVEeBnJTmylypJOxpg5wdm1KauDOImwgX/av9iQogjUdx4mH8HrHzcbCsLnPN3z+dB3haTZrO60Gwnz4SLnjHpVn2pyDGPaag2I5hx432PHFTle49wNFSZz6jokaauwo73zI0DpeD4e2HsWRDYhQvDcWeZdVGlGWY7NMmMMvgSPxmmXQUbXzLbVj8451ETTFQVQNYq2Lmk9WPC2hkpKNgBz51tAp3JF8OhNd775G6CSUdI0OBy+Q6kSjLMAnGNGVWpLoD9K0yGrPRjIGaUZ9/iDMj81mSZSpsPKbPMFKS6Mshc6X3s0oM973d1IbxzO2Qs87Sd+rAJOGtLTfXvro4GiSFNgobOOBqgpti7vbG6//syQHblVXL/O1tZc6CEmBA7vzt/EieNj/dZU2DptjxeX5cFgFNrnvnmAJOTw7lgRorvg+dsNIWEinby41GXYZuUyktbPesHupNI6HCtzyzj9pc9C/Ueem87QXYbl87uv7SwAX5WLp2VytZsk1XlpPHxfLg5l+25ZiF5Zb2DexZvYmRsCFNTI8yDstebD/rifWZ60ohFENr53OFt2eXNAQNAXaOLXy3ZxuJb5hEeZGd/URUPf7CDz3YUEBZo44GzJnDWlESC7D08XRTugDe/Z+ZMg5kLvuROuPZdCIzo2bGF6C8BYXD8z83i4apCM4e/Kb2x0wHf/csTMIC5u7t/ue+goSwTFl/nWShsC4Br3jb1bNoKSzLTh1qOBgSEe1K37v/K1Fdo8s5tcPkrMO7Mzl9T7Bi4/j0zPcjlMheRES1uitWWmT6W7IfwVBOQTLvKfDZGj4RY9zq1oBizgHrF31ofP2m67+fdv9w9MgI4neYCu6zNRXL0KO/H9bfivbD1Hdj7CYw9EyacC1EjzM/yt8ML55mACcwU5nnfh69+b7Yj0s05Lmq4+X2/clnr7Hvn/ANmXmtGXUcuMqMrLbUcReqM1ibta9ssTvnbWwcMAF88DHNvNb8rezBcu8QEMEJ0QCpJdSY0AWbd1LrN6je4FvO2o7ymgUMlNVQ3ONrdp6qukQff3YpFwe2LRnHC2Dh+vHgTu/K8syI5nC7e25RDWlQQNx83ghuPHU5ieACf7SjwcWSgYCc8dw6s/Q8cWEHcZ3dyZ8xaksJNoSCl4Mq5hzeak1tWS05Z7WGlLf1ip3f/nlt5gJoO3pe+cOqEeG5dOAK71cLEpDA2HCrz2udAsTtYzd9u7tCt+x8cWA5v3ghb3+jS8xT6yM60O7+SijoHjQ4XT36xr/l3VlHr4KdvbGZrdkW3X1ezkv2egKFJ7kbzISfEYBIQZu4STzgXEiebzwQw69+yfdwtL2gnxWrW2taZhRx18PlvTVHMtqJHmTUMTek7A8Lhwv9A5DCzve4578dserXLL4nwFLOId+zprQMGRwN896QZPfngHjPnfvn/QcJk8/rjJ3ruvlssJvnFtKvNNMnASDj3CUia6fs5q/I931ut5ljxkzxtEy/sev/7SnWxWej+xW/h0Cr47EF47y5Pxewtr3sCBjABY+lBE1yBCYJyN5nvc7d4p+v+7FdmtMnmb4KxmDGmXVlgwY/aD7jaqsgxlaifnA9Pnwjbl5i/RzCjWG011nj+bhuq4eu/tg5IhfBBRho6Y7XBvNvMPNQNz0N4Opz8oBmiHcRW7y/mV+9uY2deJQvHxPDLM8czNsF7GDu/op5jR8ey9kAJT365l9TIIO4+ZQw5ZbVMSm6d1cJmtXDJzFR25FXw0qqD2CyKy+ekMSGxnfnyeVvM3PYWEjb+g9+c+C7v7NNcOTeNmeldWztQVtPAOxuy+eunu2l0am47YQRXzkkjNjSg08fGhXlnMUoMD8Bm6eHiwsOUEB7Iz04fx1Vz03C4XLyxLous0tapGWND3X3N3eT9QbD8TzDh/E4rsA6L9s4ZfuLYOGJC/Cmqquf9zd4X8fsKq5gzvIfrD3xNmQqJ75VMVEIcEQJCYeJF8OUjrdvbW1/UNssQQPFuM+3IP6R1u8VqFj3HTzLTX0ISW49eRPi4wdIbRTRL9sLXf27dtuEFmHm97zvTkelw9t9g4U/MOoVwHzUgmow4Ab7+i/k+ax3YAs0ox7gzzUXz/uXmzv1AKt5jRota2v+VGX1ImeUJCFoqO2huOJYfMttNF+++Uu02VHkWjcdPMJmXSvebNYAxo8zoU1dsesUEc2CmOi2+xhxr2DFm4b09pHVa7mHHtk4VXLjDZM+yeX8eCtFERhq6IiLNVLy89Ru49m0YflzvpLkbIBmFVVz/vzXsdI8WLN9dxD2LN1FW0+C1r92m+HZfEV/uLkRryCyp4Q8f7cTfz/frd2GKlNU0OKmoc/DU8gws7WX2UD6OoSycPD6Bx6+cwYKRMdhtVu99fFi9v4SH3ttORZ2D2kYnf/t0D1/sameEo42FY2KJCPJr3vazKm49fmSXn7s3WS2KtOhgRsSG8vsLJ2NvMQXs0lkpTEh0B3a+3lOLtUtZVCYkhfHIBZMIspvXNy01nJ+fMY5Au5VgfxsjY72DiugQe/deUEvxE2HOrS36a4NzHxvwyrgOp4t1B0v4yye7eHzZHjZnlXWvwJ4QAFMvM1WSwdzJPfbH7a+HSvBx82nKZe1fKCtlpqukzfee7jTjmtaLrO0hZp1ATzXUmNoUXu0+RkOa2OxmOk54srkLv/1d+Ohek0Wv5Rz9pBlwwVNmFMVRC6NOgbpK+Or/zJ3vYQshdW7PX0NPdPb5NeVS75+lzIb8reZ7q92TMTBugvdC+Jnfa11cL8SdpjVhUtcDhuoiWPs/7/as1ebfmNFwzTsw7Dgz+jPtKhM07PnEs++Uy3slwYc4uslIQ1cpBaFHR9qzA0XV1DS0/hDYllNBdmktEUGtLw5Lqxv5dl/rNR0OlyavvM7ruE6ni7c3ZHu1f7Yjn3On+bjblDjZnMBqSz1ti+7r1kXkR1u979i9uvoQF0xP8bn2oqVxCWG8fut8Nhwqo77RxdSUcK9RlIFwzMgY3rvzGDJLaggP9GNsfBjhTcFN4jRzh76uzPOAE+7rUmq+ILuNK+aksWBUDLX1TpIiAwgPNL/3sEA/Hjh7Atc+s5p6h8vdj2imJEf0/AUFhMOi+2HSheZDLmp4r6Su7al1B0u58j+rcLqzVv1j2V4W3zrfs3ZEiMMROQwu+KdJL22xmb9zq5/vfZNmwHlPwCf3Q105TL4UZt9sbgD4krvZXOgdWm0u+kad5LkgTZ4JN35q7tgrZbYTJvk+zuG+nphxULTT0xYc65nT3xFHA3zzqGfROJiA59IXzMVxwXb48Ccw5lRTl+Djn5n346QHzMV25HAz2j+Qokeb4OXAck/bmDM8ay1GLjJrXL551GwvuNNkWAxJMO/d8T/1BIfxE8zaga/+ZEaUpl0NUy9v/++jq2wBJvBoGtlo0jL4TJ0NV7xqCq76BZppVf5hZn3mjOtgWjsL34VoQYKGISg00PsEFehn7jK3FWC3EhVsp6S69ShEiI99rVYLY+NDWXugtFX7qLgQr30BM3fzuvdh+zsmneCki8ydkBbyyms5WFxDSIC5Ax7g5/tPdlSs93OMTQjt8hSj0fGhjI4/soroWCyKsQlhPqeNETcOrnvPvHfFGTDlErOIsIuUUj6nKQHMGR7FkjuOZV9hJaH+foxLDPNMi+qpwLA+yULVXU6X5plv9jcHDAD1Dhcfb82ToEF0nz3YXCB2xj8Ypl9tkhg46s2d+foqyFxlAo7oUZ7iZqWZ8P7dkL3WbO9ZamqznPuE54ZWwmTfoxc9ERwDl/zPzJfPWGZSsZ78oO/pUG2VZJj1EC1lrjQF8kJiYd8XZorqlhbrsT77Ddzwoff0rIESFAXn/sO83/uXw8iTYNTJnnSlIfFmLcJUdwXtiDQzE2HUSWa6lb3NyELqHLjsebOmoOVi5Z7wD4FFv4QXL/Bk2IpI9z7X+od43tc5N5tUrq5GCEsFWw8DFzEkSNAwBI2JD+XimSm84c5yBHDfmeNIj/auAzAmPpSfnTaWe9/a0tx2zMhoJiX5vhN/xZw03tuUQ0WdOXHFhNg5bWIHGX0SJrV7N2xrdjk3PbeWvIo6lIJbjhvB908Y6TUaAnDyhDie/fZA8yLfUH8bV85JR/W06NGRLHFKn6QrVUoxNiGUsQlHVhDVF1xaU1Hb6NVeXufdJkSfaZr3X7QX3r7VExiMORPO/KO5EC3c7mlvsucTMxe9r0fB4yfARU+bwm6BEZ7F2J1xObyTH4BnDr+v+fN+Ab6nrvYnrU2djZK9EBBpphXNvdV8+WKxeE8X66gGjV9g9+t1tGfYsXDjZyb1qz0IkqZ1PhrUG2texJAiQcMQFB7oxy/OHMe5U5MorKwnLSqICUlh7V5gnz05keSIQPYXVRMe5Mfk5HDSY1p8aJRlQd5maKhiUtx43vr+AnbkVWJRiglJYQyP6eIHTAvV9Q4e+XBHc90CreHfyzM4bnQMx472nu87NiGMxbfNY3tuJS6Xi3EJYUfcyIE48vhZLVy/YDgrM0patZ8zZRBVoBVHj82LWwcGuz+EsWeYlJztLrPpp/U3foEdL2r2JSLdZGRqOXc+NMmkeAWzENov0LNQGOC4H3dYBLRf7F9uskQ1ZROacjmc9rAZdTlSWSyQPN18CdFHJGgYoqKD/Vk4pmtZKUIC/ThuTCzH+dq/LBNevRry3BkkLDZGXf0Wo6Ye36P+ldU0sOZAiVd7dpmP7BNuw2NCGB5zhAxp95KDxdUcKqkhPNDOyLjgbtdKqG1wsCuvkpzyOpLCAxibEEpgT+suDLBNh8p4d2M2hZX1XDAjhTnDo3xOm+vMMaOieeLK6Ty1PAN/PwvfP34UM9Iier/DQnSksc5MgWnr4DcmaAiJN+sX8lukb00/xrQfqQJC4fQ/QuJUsxg6fQHMucWTjjRpGtzwkSlKV1tqsr+lzhnIHpv1Vu/f3Tr96OZXzdqDkYsGrl9CHAEG91WDGHjZ6z0BA5jh6E8fgGvf88zF7YaIIDtzh0ezYm9Rq/bkiF4e0j2Crdlfwo3PrWme6nX7olHcunAEYT7WpHSkweHk5dWZ/Pb9Hc1tD5w9nmvnDcPPNjizgG3NLueyp1ZS12imPry3OZcnrpzBWVMOfxF9SIAfZ01JYtG4OCxKEdC24rYQ/cEvAEafZmqXtNS0VqmuzIw6pM03mXkSp5kFtE31Ao5U0SPMfPsFPzRpRNsubE6a3vVaBP2hvhJK9nm3V3UtG1+Xjl+4y/zeooYdGcXrhOiiwXnFII4c1UXebaUHzSKvHgj2t3HvGeNIbFHo7daFI7yzGlUXmec7yorSlFTXc+9bm5sDBoAnvtjLjrxOiqxV5kFlfqumjKJqHvlwZ6u2Rz7cSUZRBykTj3CrD5Q0BwxNHlu2m0of6xO6Kshuk4BBdE1FLuz8AFY/BRlfmTShlXlQdsh3etKumnIpJLeofTD2LBh5gvk+ItVUm975gVkkvfVNU7ytN+elV+b7rh3RU0qZhcP9mQmpoRoOfAOr/2MKnZVndf4YMBmHRpzo3d6VbFGdqSk1xfv+cxK8dBE8dQIc/LbnxxWin8hIg+gZX4uYp13VOvVndZH5MPUPNQvc9nwMe5fB6FNM9obIdAAaHC42HCrl9TWH0MBls1J547b5ZJXWemdPcjpg3zL48KdQngmzbjTH2vyaqao65TKTJi/QR+ahQaCsppF9hd5VPH2lugVM1dIti02BN4sVffwvyEk5g01FYFFw5qQE3mtRtM3p0pTWDN7Fvr7qKDic/Ta7Wwxl1UXw/l2w+2OznTrXpBFe/ieoq4DZt5iCoN25mI8ZBVe+boqDKau5E92UpSd6FFz2IrxzGxxYAeFpcOFTppJzT9WWwba3TVE6l9MUZpt86cDM4S/aAwU7zchL/EQI6+b6oq1vwZI7PNvpx8DF/+u0+CX+IWb9wrt3QM4687l1+h97J31t3mZY/W/Pdn0lvH+PyRbV0cJpIY4QEjSIZjUNDhodLsJ9ZCdqV+I0uPhZWHqv+TCddrXJMNGUZzxvK7x5o0mxN+VyKDsAmd+Zn+391AQP5z8JSrG1UHH5U9/RdD341oZsXr5pHvNH+khLl78VXr3cc1cvMh1eudSzvWOJ+YAdf0433gmjvKYBP5ul2+sIeiI62M6kpDC25rQeWUiJbGd6VsYy+Pje5k31wd3ULArih0vDcLg0x4yM5vxpybyz0dTRiAjyG9RTvWYPi8LfZmmuJQFw54mjDnvqlhCHrWCHJ2AAGHsmfPRzz/Z3j5siWQt/cvjHrimBHe/Cir+C1d/UrRl9qidN5shFcPMXZr/g2M4vgLvqwAoTCDX5+BcQFOO7cFmTxjozohwY6bsAWk2pKfLW1UxLYKa7Pn+eScMKkDAVLn3eOzNRZ8oOwSe/bN128BvzudGV9yx+AlzzFlRkm/5HHubzt8fXKE7hDlOjQ4IGMQhI0CBodLpYlVHC3z/bRXF1I9cvGMZZkxOJ6Upufr8AmHSBKVXfWGsyYzTle66rNBeyhe6pMVHDzIKyJqEJZuj9jRugLJORE67irtmz+dtqc4dda3hl9UHfQUPRnhYBw3DI2+I9LWDtMzD69MPOP11aWU1D5jpU1hpq7aFUpc8jMn1Sp0XifKotpz5zNeRsQkekYU2fi19UeqcPCw+y88iFk7n1hXXkltfhZ1X87vxJBNisrNhTSEJ4ACNCwVK821Rmrcw384VbTAtLzvqAsQm3sC2ngm/2FXPvGWNhI6RFBfLnS6aSGtV+hpLCynoyS2oI9rcyPDoY/yNs2s7k5HBevWUeL6/KpKCyjivnprNgRC/lPBeiIy0rIQdFmWQQba1/HmZ97/AvBPd+2vri/Y0b4Oq3TM7/JmFJ3b/73p6WdRKarH8OJl1ssvK0lbUWlv/ZFGebeoUZXY50122oyjcF5gp3mIJtSdPMlKvOpiY56mHF3zwBA5j1cge/OfygwVHX+jhN6it976815G4yN7SsNkidZ0YWAiMO73nbU1cJtSWmMrPF2vqzKv2YIzsrkxAtSNAg2JJVzrXPrKKpvtWDS7ahteb6Y4Z3/SC+KhHXFJniQ03aTimZfRN8+qvmnN3h3/yOq6ffwZKYk9hXVOvzIU0c/mGUTLmN7RGLKCOEEeGK8Vkb8SvZ1eb5fOQI78yBr4l/6wpPfvHgWIoveZvoYYdZNElr6te9gP9nnjtejcmzqb/kefwjOv/Qn5ISwTu3H0NWaS0RgTbWHizjvCe+weHSXDclmF8GvYV943Nm55A4U0V16X3Nb1p1cBqlmZ6ifFFB/iy9ayHRwfYOA8KduRX84KV1ZBTVYLUobj9hJDceO8JTjfoIoJRielok09Mi0Vr3ej0Ol0tTVF1PsJ+N4AA5TYoWokebKSv1lWbefGCk9z5RI01hr8PhbDDz74OizIJoVyPs+thkHWoZNDTWmTvTgZHmTn5viPYxXz96tO+AoWAnPH+uee0AX/0BKnLgrL+Y/mSvhw9/bNrALN4+9ieQOsv7WC011JibP235WpTcmbAUGHeuGbVpYguA2LG+989aA8+e5akfYQ+B6z+EpKmH/9xt5W4y5+WD30DyHDMC/u7tZrQoaiSc8Ufz9yTEICALoQXrM0txtbk4/8+K/ZRU93BxcUA4xI73bJdkQNIMz7azwXOSdove+gxXTfB8EF4xx3fV0YzAyfy06Eyu/8TJXZ+Uc/4bZXw57a/g32INw8wbfBcP6kB1ZRmhK/+vdUGi6kL8sr87rOMA1OTvw/+rh1u1+WWvoTF7a5ePER8WwMz0SBpdmvve3oLD/Yu6OKnIEzCAyeyxfYlnAV9ABNsiTyKnxRqIUfEhjE0I7TBgqG1w8qelu8goMiMWTpfmsWV72ZJd1uU+97feDhgyS2r448c7OevRFVz/7BpW7y/2uYZCDFExo+CatyH9WDOFKHKYufhrYvOHE37uXQm4M8pqgoWZN5gLzJyNcOzdkNCigGPeFnjrZvjnfDPnvmBHu4c7LBMuaB382ENgxnW+9y3c6QkYmmx6CcoPQWWBGeFtChgAdn1kCtN1JjDCrKNoqzsV5O2Bpmr1zO+Zz6GU2eZ3Fjfee1+Xyyxob/lZ1FDVOuDorso8ePVKM/1La8haBUt+CNcugZuXwfeW9n4FbyH60JC9hVZa08DW7HJyy+tIjghkcnIYYYG9dNemA5W1jWzNKSertJb4sAAmJYcRFey5iNtfVM22nHIcTs24hFDGJba/kLewsp4t2eUUV9UzLCaYSUlh3cq97yu3fUSQX/em47QUFAVn/xVeusSchLe8Duc9aS5w930OIT7SYwaEERMewmkTA7l0Vgoz0yN8HnpbkYuvMjzTBFwaHlhRz9QT/0RcxttmuHz4wsPusk03Yqvxzghlqy8/7GM5Gup8ZpFy1nsvcO5MQUU9TnfAYFEQ2ZjvvVPuJrjsJZh6OZWRE3hpWS1QS0SQHw+eM4GJHfwtNSmraeCbfd6vP7OkZ9mwBosGh5Mnlu3htbUm00phVT3X/Hc1795+TIf/F8XQUhg+mYJFT2FpqEQHRjP6ymPxK9xqpmjGTTALeA+XxQohsfDeDz1ty35r/k8DlGfDy5d6Lsi3vGaCiOvf6/n0lsTJ5gI2dzNopwlU4if43tcW4N3mFwxWu5kWlLPB++ddyVykFEy/0iwC37LYPM8J90FK1+s27MyrYGduBX5WCxOS4hl+5v/B8T81QVBAO/9/tat1kNOkIte77XCVHvB+7dWFpiZFNz6fhBhoQzJoqKl38Njne/jfNwea2+46eTQ/OGEkdlvfzd1udLp44buD/N9SzxSaq+emce8Z4wkJsLE7v5Krnl5FYZW5wx/oZ+WVW+YxLTXC61gl1Q388u0tfLLdc/H4xwsnc1k7d+Y7MjM9kuhgO8XV5k6LUvDjU8YSGtAL01HSF8AtX5lRhsAIiB1nTt7H3Q0lB0zF0LKDzbtnzvoFL22tpbrBwe0vr+eVm+cxPc17+L/lAtgm+ZV1VI44i7h5l3e7u/5hsdTNvJmAz+/3NCqFSp9/+AeLSKV21FkE7v2gxROE4owec9iHSgwPwG610OB04dJQ5JeEV86UEYsgfT74BRIK/P0yB7kVtQTZbSR1cdFzWKAf09MiWLmvdWG9rj5+sMstr+ON9dmt2uodLnbnV0nQIAAorW7g1+9t5/3mbGT7+O35E7l67tk9G/VyNsCGF73b93wC488203TaXtwWboeS/b0zJz52bPvTd1pKmGQCo4IWowcn/cpki3I0mvPQlsWtH9PVICpyGJzzqFlEbvEzCS66+J5uyCzliqe/a07FHB/mz4s3zmV0fCdTQa02M1X24Det2ydd2LU+d8Tuzhio23xe+cu5RAxOQ3J60t7CqlYBA8A/lu0lo+jw7wAfjgNF1fz1092t2l5clcneQrM468tdBc0BA0Bto5NnVuzH4fS+QN6ZV9EqYAD47Qc7ONSNO8Kj40N59ZZ5/O78Sfzk1DEsvnU+x4zqxUWlMaNgzKmm0mfLuz1Rw0yGinP/ASfcx6FzF/PzrWms2l/C1uwK6hpdLF7r+w7VuIRQLG0+S04ZH09ye9mFDoNtyiXUn/wwRKThSpxG/aWvEZg++7CPExYWTvXCX1E69RYITaA2/UQKL1hMUNK4wz7WiNgQ/n75NILsJqh9NTua+gX3mA8kMOkYT/wl+Hlef3CAjVFxoYd1wR/sb+O+M8YTG+IZ/bp6bhqTU7pfqG8w8bdZCfWxhqHpfRdiV35li4DB+P2HO3s+GqesnkrJ/qGerEOh7hFZPx+JC5Rq9X++X4SnwOUvw/n/hOPvNdN+plxmfmbzM1Oq4iZ4+jfnVk+Buq7wCzALhqOGdTlgcDhdPP11RqvaLfkV9SzfXdi15xx5Ipz3hKnFEDsOLnnWFNHrqehRsPBnrdsW3Akxh3/jSIgjwZAcaahsUTCridOlqfLR3puq6h3Nc9J99Sez2PtDZ19hFQ6Xpu0ASFMRK4syFzq1jU6q6h3UNnavsNDo+FBGx/f+YqzqegcbD5WxPrOUhPAA5gyLIj26RQq+6FHNFTEffmEdKw+1TklXWOm7LsHE5HD+fc1MfvXuNvIq6jh1QgI/P32sp45DNzicLlxo7OEJ2I69A6ZfgcVmx78Hi9Ri0sZREP5rsmbdgSUwjPioCKxto50usFoUZ0xKYHxiKMVVDcSHBeAfOhemXmzmF0cO870YvRsmuxdgHyiuJtjfxqjYEEKGyGLghPAA7j9rAj953VPlfGJSGBOT5M5gr6nMh6zVkLcNEiaa6Se9lTq0H/j6/KhpcFLT0IOibmCmJ82/HRKnmAxEFhsERcOoU8zPY8aaTEWbXvE8Zt7tA1NROGq4+fIlfgJc954ZAfELNP3z8zGlqRc1OF0cKPL+/Mws7WIgFxgB0682xfSU6r2sSX7+MO8HJrtg2SEITzZpZO3tZ64T4kg2NK4E2hgWHdRqOo7VovjRSaM4WFzD5qxyJqeEMyU5vNtpJnfmVbAhswyXSzMtNYKJ7irGaVFBjIwNblW0KyLIj2Hui+gTx8fz4qrW6fuunJvms0rtiNgQrpufTlSIPxW1jUQH2ymoqCPJXUHZ6dJszS5n46EyguxWpqdFMCqu/zM0fLgll5++sbl5e1RsCM9+bzYpkd4nzUtmpfDxttZBwxWzfU+38rNaOGVCAtNSI6hpcBIf5t/tgKHR6WLtgVL+83UGlfUOvnfMMI4dFUNIcO+MtsSFB0F452lWO6OUIik8kGB/G5GBdrBZujd3uguSIwN7ZdSmLZdLs7+4mvKaRpIjA4kP69uLie44c3ICyZGBbM0uIyEskGmpESQOkelZfa6+Ej5/CDa+7Glb+FOYeL7JChSR1mvBb18ZERPMRRNCuDS1glBnCQW2JJbkhPfOFD5nA3zxO3C6Cy/aQ2DECeb7gFA4+dcw/lwo3mPuiCfP7PML8m4Jjum9NKIVOWZdQGAUhfZk1mWWkVlSw7iEMKamhhMeaCfIbuPyOan86t1trR56wtjD/FsKck+Fbawz6V4Ld0FglEkb290ieoHhsn5BHDWGZNAQEWjl6UtHsierkGBdSXx8Mg98nsvOPM/C2n9fPYPTJvlYqNuJrdnlXP7Ud1TVm7tR/jYLb39/HhNCaoj2C+SJq2bwyIc7+GZvMdNSIrj/7PHN+fJnp0fyxwsn86dPdlHX6OKWhSM4ZYLvO3ARgX7syK1k9QHPeoD7zhxHsHtR85r9JVz131XNi2ejg+28esu8DkcTSqrraXBo4sP8eyUjTV55LY982Dq7x97CKrbnVPgMGuaOiOaJK2fw+Bd70BruOHEUczvJvV/vcFHX6KLBoenuEoxNh8q46j/fNWeQWr2/hCevmsGZkw//99+XtueU8+jne1h7oJTjx8Ry2wkjGdMHo0N9pa7Rydvrs3novW3UO1wkhAXwz6tn+FyzMpCC7Dbmj4hmvtR96H1Fe1oHDMOOM4HEv48Hl8NkIbr0uSM6o8zIUBd/iHoPv6+eBmCCUiw47ynsgV1fsOuTywnf/dMTMIBJILHzA3PRCmZEZtyZPXueweTQKlh8rclC5BcICx/m8bXpbM0303h/dtpYbj1+JFaL4rSJCZTWNPDUVxkE2q389LRxzE7v5rll98fweovsUSlz4dJne78+hhCDzJAMGhoKM5hR+iUzNv0DKrLRkcP4vzn/x1VLbVS6L/Z/9+EOZg+LIirk8FJ2frAltzlgALhnTiBpG/4EW16AkDjGnfYI/7pyISW1mrAAv1YVbEMD/bhsThqLxsXh1JqEsIB2L9535Vey+kDrxap/+3QPp01MIC40gMeW7WkOGACKqxtYmVHsM2iob3Tyxa4CHv5wB+W1jVw/fxhXzEnr8d3VRqdu9V40aW8KVYi/jbNG+rEwOhaA0Ag/aGdaTH2jkw+35PLgkm1U1DmYmRbJ7y+czJiEw7+IXrazwCvl7FPL93HiuDifozx9qbCyjozCaqwWxci4ECLd1blzy2q54dk15FeYD8u3NmSzI6+Cl26a2yr7Vr9oqIGi3VBXZhaytzdNoY1deZX84m1PHva8ijp+8vomXr9tfv+/hi6obXRit1q6NZ1MtMPRZrrhiBNMhqAmJfvgkwdMLvumKshHmsLt+K192rOtNfaPfwLpc83C3e7STjMtqa2qgu4fczCrKoC3bvFUUW6sJXbZj7ln4WK+t9Q0Pfr5Hk6flMCI2BDiwwL44YmjuXRmKlarIi60myMwlXnw0c/MerHIYaaeQtYqyNssQYMY8oZk0BDUUARfPNxcHVKVHmDKN7dz5+xneGSFaSupavCZoaczOWW1zd+PiAnkEtdSQtY/aRrqK+CVywj63icEpbZ/VyquC1M2fM2frW100uBw0ehyNV9ctlRU5d0GsCmrjNteXN+8/diyvfj7Wbh90ehO+9GRhPAArpyTxnMrPaMh/jYLY9u7sC/OgA/uxhk8AlBQtRfO/htEj/TadUduBXcv9sw7X5dZyu8+2M4/r5lJ8GGmnfUVGAT52ejvS8W9BVXc/tI6duWbEa/jRkXz+wunkBIVREZRNRMSw7l6XgT1Dhf+Ngsr9hRxsLimfy+4ayvg20fh6z+b7YAIuPK1LuVSz27xf6PJvsJq9hVUk+VXS3p0EOH9kPa4M3nldXy8LZfX12YxLiGU6xcMY3JKxEB36+gQNdJ8NRXscnj/TbD/S3Oh1hQ0aG3SVPoFdlgES2vN5qxyPtuRT12jk9MmJjA1NaLnqaPbqin2bqsrhzofFYi7YEduBct2FlBaU889075H0KE2NWEmnt+t4w56VQUmZWlLWhPjKADMCEK9w0Wdw/NZqJTq+VTCxlrKE+axJvk6vsi1MyJMc3xQBqPqqzp/rBBHuSGZPclWX+5dTr66kDH+Zc2bV89PJ54SKM0El4tGp4ucslpKq1sXI2vr3KmeOxEXjfEjatcrrXfQGmfeNvYXVXd6rI6MjAshuE1GlxPHxZIUGUhYgB+Xz/aefzk91fdQ7YbMMq+2l77LpLidIKOr/KwWblk4grtOHk1yRCDHjormpZvmMi7B96LSiszNvJX8E87LOJdz953Dm8k/oyJzs8999/tYNL58TxFFPoKlzpwwNhZ/W+v/CredMKLDNS0VtY1kl9VS3/SB5WgwOdq7SWvNG+sONQcMAF/vLebrvaZmQmiAjchgP/7yyW4eX7aXv3yym4lJYYT0d1af/C2egAHMaMN7d5mLvE74Wr+QHBFITnktH2/N472NuRwoHtgPZqdL88w3+3loyXa25VTw5vpsrnx6FXsLKjt/sGhX0/mzzBppMu9MvRLCkk3l3raSZpqpSqWZUHYIx+pnyFn1FqUr/gv7vzbTeHzYnFXObS+uo7S6gUan5q5XN7C2zWhsbYOTnLJaKusafR6jSyKHg7XNXMjYCWaR62HanV/J5U99x5+W7uI/Xx/g3k1xVJ/5D5M9KH6yGXHp4AZTr3PUm/n8hytnIyz/Cyz7HWR+13qKVVeUZ5mF085GtNbkltVSYwuH0ATvXW2eaYPzhkeR6mOqa4+EJfF2wl3ctLSOlzZX8NsVlVy3KpnMiLm9+zxCDEJDcqTBGpnqnTvZ5o8KiiI2pI4r5iRzeUIulicWAYrM897kqT0hvLE+m8TwAB48ZyLHjorB5uMO1tzhUTx62TQ+25FPTIQNV0gCFmcjDSnzsdYUYs3bSG69P4v+/CVj4kN4+PzJzB4eddivYWRsCC/eNJc/f7KLnbmVnDU5kRuOHUaw3UZNg4PS6gZuPm4E723KISTAxsUzUyiq8v1hEB3ifXc3KSKQgF6oWZEcGcRdJ4/hmnnpBNltBFq1qWJamWdSCdoCIWct1JSwynoc93y6r/mxP/4MHr9oAlF7iwgJsDEiNqS5EF1MsHef06ICCS3ZgmP/DiqiJrPfNoJh0cFEdzLFbHJyOK/fOp+l2/OorHNw5uRExieEsiuvErtVkRYd3GqKypr9Jfzm/W3syqviytnJ3DuxlIDVj0N1Ecz7vsl2EnR4c2nrHS6+3uNdVG39wVKumJOGw6l5q039gOdXHuTSWamH9TzNSg9C9lqoLjbzx5OmtZu6sbS6gc1ZZewrrObSgEy8Jo0U7jBBQ5D5O66uc5BVVoO/zUpaVBAW93s3NiGUu04ezd8/2wOYNKY3Hzec+97aQnWDEz+r4i+XTCUtMrj5Mf0tp6yWZ9ukY66sd7Arr7L/Ewm4XFC8FyqyISTeZKGxDfxIzOE6WFzNv7/K4M31WaREBvKrcyZy7FmPYm0sBxeQvw3WuKf7BEbCMT+Cp46HsGQOzf8t/90/hle3VREfaucBOyz034k9yTsBwKZDZVw0M4XXVh+i3unk4hkprD1QyuxhUdisFnblVfLnpbv4anchk5PDuf/s8R2vpyk7ZBYc2wLMomP33zex4+Cyl00RtspcSJwO5z7m+bkvJRnm/1xQlMmC5F68vOlQGeW1ngvsJbtrOFAzglev+Zggf3v7Bcma1FeaqYL1VSZdaEQ3zweNtaZq8TePmoBtwZ0w/ATwD+7skSZg+N/pnpsmX//FVDweflznj62tMEXqPv8NOGrJP/0ZXisbw6bsSgL9rDxy2mOEvXu9KZKpFA3H38+3FXFEBZdw2sR4bjp2RO/UE2oht8rFX75unao1u7yBHeU20rr59gpxtBiSQQNhKXDCL8wUJbeGUx4hjySuX+Dk2ogthL51AwCNCdP512YXL28+BMD+ohq+9+wa3v7BMUz1UXTNz2ohKsRORZ2DD/c2svCUJ/nmYBUv7VakhiquP8PJngobUMbu/Cp+8dYWHr18GgCJEYFE+bgYbs/0tEievnYWVXUOooLtzUGMy6X5fGchJTUNLBobR02Dg0c/28MPFnlP8wGYmRZJSmQgWaXmpG+zKO45dQzBvZhmMzrEH5wO2PoGLLnD3Imy2uHE+2H1UxAcx2KbdwXS1zaXUVVXxIZDZVw3P51bFo6gzuEiPTqI86cl8c5GU+zIbrXwyLF2ol6/ABpriLIFsH/RC9z6YTB/u2waqVHtf/gppZicEk5sqD8urXG6NHcv3siynYX42yz86KTRXDU3nfAgP/YVVHHtM6ub12WcEZWL9bOH2Tf6OhqUnbTN7xHscsC0Kw/r/Qnws3LKhHi25bSe4jAlJdzcdWvwXhvicOnupXksy4RXroCCFplGLnkWJl7gtWu9w8m/lu/j319lADD+9HDaZi93JkzD6s6Usr+oigff3cbyPUX42yz8+NSxXD47lbBAP0L8bdy6cAQnjYunpKaeyjoHD767jWr3a2h0al5bc4jjRscQOUBrHKwWhd1miui15OsGQZ/b9QG8eaO5+2uxwVl/NSk3B1Hg0OBw8sQXe6lrdHHzwhE4nZoH3tnCE1fNZHKyWbvEyQ+a19VUdX3xdVBfgWPyPTyzN5BnN5r2gyV13PxhHW9dHcN0H1PLbVbF8t2FXD4nFaVgzYFSFoyMRmOKYd712gZ25JoRo3WZpVz3v9W8d8exrVNAN8nbDC9e7FljMOpUOOdvJoOOxWLqztzyJdSWmbvhHaXo3P81vHqFucBXCk74Jcy7DfxDfU6BLaysp3b7UoIKVpo0oCmzTTrWtqqL4ItHYO1/zXZwLFz1OiRNb78v7clcBS9d3GJ7JVzxGow9vf3HVOaZYCVvS+u1KtoF3/4DUueZug0dyVoFH/7EfB8Sx7cNw8Bipay2EadL83bFGM64+gviGrMhKAZ77Fh+qP244YRGIoPtnU89a6g2KX79QyAkjuyyGkqrG4kL9W93GrBTa6///wCNLRa+HSyqZl1mKUVV9UxNiWBqakS/r38TYiAMzaBh72emyuaJ95uTnV8Qu/wnU59ziKkRFoIKN5qTu9bkj7iI179qfSHn0iaTja+gYX1mGdf8dzUAcaH+vJCRzJNfmkJAG4Cluy388MTRQBnjE0M5fWICl7mzLY1NCOVvl05lQlLXC2kF2W0EtZnDHxLgx63Hj2Dx2kPEh/njdNlJigjgmJG+U+ANjw3hpZvmsiWrnOoGBxMSww6rD52prG0kp7yOFMdBgpfc6Rm6djbAl783uca3vUVynPeJOjLITrY7mHlu5UFSo4L43Qc7GBUXzF8vnca5U5Moq21kZHADk5deau5IATjqGJf5KrWN1/H1nmKunGGlIXcrrtJMVGgC/tHpOIv2Qk0ROmIY2Y5Qwst3oVyNFAWO4JgRMUxMCsfh1Cxee4gJSWGcMDaOjKIq/P0sXDo7lahgP+Jiynki8fc88UU5jU7NohE38WBVLsNqyyEwnLLqBirz9+IoOogtNAZr3BiqnRaKqxpIDA8gLSqIzJIaGhwuzp6SSFiAjfJaB0pBeIANp1PzwZZc5gyPIjzQj5TIQEbFhbAtp4L6Riep5MP2ryF2jLkD2p6GajPCU55l7py2TdP48b2mAJM73WVxZT37i6uxKMUHmzxVaJ/YHsDweQ+QsOYP5vcYlsyOmQ8RWWcn3u7iP1/vZ7l7xKTe4eKRD3cwPjGU40bHNrdVNziornfS6HAREmBrTn0MUFTVwMbMMqoanExIDGVkm7v7uWW1lNc1Eh8aQKPTxc68SmobnIyOD2FEbM8XziZFBHL3KaP57fuerF8pkYFM6O9q0CX74Z0fmIABzN3fD+6GlFl9lma3L+RX1DMmLpS3NmSzZFMOQXYrNx03nNzSGia7U1HjHwopM833L19m1n4BhcGjeW1r6+lqWsPuMph+YAUEx0F4mlkf4aynriGCkbEhPPnlPpwuzUnj47AqhdaarNKa5oChSUWtg/1F1d5Bg6MBVjzaelHy3k/g0OrWaTdDE3xOn2mlqgDevd0zHVZrk1J1+EJIm8vU1PDmSu9NbpvmT/SKX5mgYNPLcMNHkOqeGlOeBRlfQs4GSJgCNn8zKmALgLzN6E8eJP/MZ6hRAaRGBuHXZtollQVQUwhBMSYTU9420A7Y/Kp339c85Vn4Gz3KU1vA2QgZX8GhldC08uukX8PnD5rXB2baIi3O59XFUJVnRpJaLiY+8HXzt+UjzyW7PrBVAdQVe4uIvGwa5071nNsCgcCmaZkul1n34Gww6Xpb1j8o2En5tk/Jc4YSouqITJvInnyw1hazzxpD+qiJTPMx0pQYHsj3jh3G/pxCTk11kVtr5a3dTubGaSjcTYkK4753DnBaUj0Jfg5e+tqPoumjOGtKPyySrik1N3uqiyF6BMSONxWthegnQ++vraYUvvqDGS7OWmPaUmYxfpydyZv+CPWV6PRjYdEvYdnvCKzOIT5sYvNd+CbtTZ94Z4OngvEpE+J5fW3rKSX1Dhe1DicWBWdOTuQvn3hOkLvyKrn/na08d8McQgN7NuQ6OTmcT7fl8/gXe7FbLXz/hJGkR7W/QCw9Otj3HbduaHA4ySqtRSlFg8PJL9/ZytoDpbx2SgNznW3WcTTWms+dkgwunFHOa9tszXfxA/2sTEoOZ0mLi9Yy91B+bEgAb67P4oWVB3FpiA315z+LHmbqZ1eaCywgsCaH6EAbh4qraNj0Jfb37zQHmX8Hep8N67ePmbtigZGknfs4WWXFNDic2CLyWL2/gaU7Cgnws3DV3HTyys3vPyrQjx+dNJq88joanZqXMoJIio1GUQFovsioYkxMOj9XVrRL05jxNakffM98iFqsVB17P/funs7yAzWE+tt4+IJJPPLhTvIq6vjTxVN44ot9zRfRI2KCuGJuOg9/sIPh0UE8edUMXlqVybqDpcwdHsVV0yKIfWGuO/ANhKvfgvQF3r8QRwOs/R988ktP24I7TYBV4L44riluvlu4OauMhz/Ywar9JQTbrVx/zHBW7itmfWYpKzJrub5uBn8//0Py8vPZWhNBSEMKJ2pNSXUDH23N83r6HbkVHDc6lrKaBv748S5eWW1qkVgU/Oz0cfzrq32U1Zjf60nj47hr8SbKaxuZkBjKny8xQbTTpfliVwH3vrmZoqoGxsWHcsOxw/jVuyZ9a6i/jRdvmuszkD9cF81IIS0qiC92FTIyNoQTxsQ2p0XuN9WFzRfPzVxOMx1mEAUNfhbFl7vy2Z5rXktNg5PHPt/LM9fN9P2AmDEm3SUQkPUNCWGnktGmaFeYtQGePctcKJ/2CHz7GDgbscxewtsbPOfbz3cUMDY+lPwK83fd9uIc8Fn9m/pKk+qzrcKdXX3ZHjUlUHbQu738EDCXSUnhvHzzXP7z9X6yy2q5brI/i/KeMQEDmN/59ndN0FBbCu/dbQIYMCMQY06DFX83qVnTF6BGncxHa3fy8IoKrluQzi0LR3rWEh38Bja+Yqa6VReYaZSf/NKMYvlKZGD1hyV3mnoF826H4+4xxeYKdkLuRljzX9OnxGkw+yYYdTLs+dQ8dt4PTEADkL0e3r4NinaZ5z7vcRh5shmxiRzR/HSu0JRW53owo6m78ipgqo8L8rpyWPc8fPmw+RwZdw6c+hszTau+kp2HCvj5lslsyqkmIsiPh0OiOGXL97HnbwL/UDICHycv4jQSwlp/Llotih9O0fgV/B3bN59DcCzfP+W3WD77B+z9jMjYCTxzwv34f3wPVOZxWupxrKy8l+Kq6E6nwvZITYnJLLbxRbNtscJlL8HYM/ruOYVoYwguhPauyMzYM7F9dr8nm9LBFeZElzKb6J0v8NAxga2q2Y9LCCW6nekTgS0KjDU4Xdjb3ukBc/cLfA5Nr88so7CHC5C11ry3KYePtuWhtXmev3+2h01Z5T06blfkltXy2/e3c8rflvPQkq389v3trD1QCkCWK9J73rx/aPPCxinf3sniCyP49VmjefCMUTxwlrmgbCnQPQR8zKgYnvv2YHOq1MLKeh5YY6d87KXN+zonXsjuwlouG+XAvvRnnoMkTkV983fPmpbaUtSnD5AZNJFTPk/gL7vjSIw0AVRdo4v/rthPoHs0J8Buo9Hh4q312Ty+bC8r9hYTYLNyTosPtQ/21JJba6G8KJvoz+5x33UDXE5Clv+am8eai5jKege/eX87Z0xOYHRcCMt3F7a6655RVENeeR1hgTaOGxPLz97YzIdbcskqreXN9dn85uP9lI673OzcWAtL7/edwaV4D3z2q9Zt3z1pikQ1mXE9hCZSU+/gn1/uY9V+s4C0usFMLzlpvKdIUkmti8UHgrn+Mwt//raCp5ZnEGCzEhrgx0Qfd+SbanLszKtsDhjAjNj95+sMrpmXTmyIPz84YSRZpbXNc7y351ayxv23s7egitteWEdRlXl/duZX8u+vMjh7SmLze/mPZXuo72ZF9JYiguycMiGBRy6YzI3HDmdk3ACk/gxNMHdlW7LafS8cPoI1NDawYp/3IvmS8hZ3/StyYddHpn5D+jGmYBkQufVZHjg2lJb3ZybEBzG59DOz4agzI2RTLgP/UDYcKvN6nq/3FHH/O9v4xVub+f7xI1r97KIZKYz2tU4lMALGneXdfjjTfgp2wNa3zGuL9pGFLsCMsiilmDUsisevnM7rN8/h4py/EL3z5db7Np3kcjZ5AgYwF4vLfmcCBoCD36KzN5LXYMfh0vx3xQG+3uOem192yIwq5G8ziQzytpiRlMmXQkkGjcMWtV7cbbGaKsa5G83owcrHzdoFgIosM1pSa/5vkrsR1j8H064xAcQF/4YRJ5qfVRXAGzeYgAHMc756lVmHATD82Ob3x164iQAfn5eh/u3c28xaC5/e71lLsfM9WPsMuFxUlpfxy5VONuWYQqplNY3c8c4Bdo933ziqr2TE8ruwlB/yPm5DDYFf/hZbxudmu7oQy7vfhzQzMVMVbsf/o7tgwnkA+B/6mln7/412dPFzuzLPBFebF5sRo64uGs/f6gkYwHxuvn+XJyWtEP1g6I00BEWZCqRL74Mpl4I91Axx+4e2zqi0bxlc8C8o3MlCtYE3L5jCN1XxuDTU1DsI9vc9f/HcaUm8tPogjU7NJ9vy+d4xw/ibe+EnmArQx4yIZFjEOIIDve9eJkeY7Ec9UVHbyLtt7tgArDlYyonjPcXiqusdVNY1EhVsx94Li54BPtuRzwvfmQvDySkRPL5sb/PP/rymkWkLH2Xkih+b99o/jPoz/oZl40v4BUVTPOZy1mTXU+KneXpFBo+cN4FQfysl1ebuzxWzU/kuw6Q7bJlmr8nm3BrKZhxHePZXMOUyXFj59TnjabA1UJ9yHHvTLibLEcbJdTl4vdqSDFIDanBpWLI5l+sXDCMu1J+CSvNBkOGu4l1UVc//Ld2Fw/1BvjOvkme/PcBtx4/kzfVmlGliYhgRgXZclSVYyg949TPKWQhEu4/XQLC/jeTIQPYXV3vtm1NWS2xIABFBfl4pSzfm1HBw4nwiedY0FO0072vbxZO1Jd4ZZ1xO8As2dw6nXWXuFFr9yCmq5Itd3nnhtdZEBPoxLS2C40bH8Keluzx9LK+jut5BXFgAPz5tDBsPlTXXOzluVAzT3Xf/S3xkCyuqauC0iQmcPy2ZH7++kY2HWge2mSXVzf862hTTyCiq5swpngJ823MqqKp3dLuS+xElIg0uesZccNWVgT0Yzn3CZNUZREJVLWNiA9ld2PpvN9bfwXubcpgVWUvCZ3egMr81P7BY4cKnzfQsVyPHOlfz1uXz2NMYS6i1kUk5b5Cy+hHPgZwNpr5BZS7Th9fwbpvnHxMfwrqDpRworiEswM6/r5lJWXUD8eEBTEoOb1Unp5nFCrNvNhfph1aa7Xm3mzv7XZG1Fp4/10wJbBoN+eqP5oLZaof5d3huJLjZrBZsVjvMvhF2f+T5gbLARHNxSkOLzyelTL2UNtS+T4mfdkvz9oeb80iNDGIq2QSs+KsZqQJzsVqRQ/a5r7L5uAU0NqQQd8LLjCz9hmCbk6CIBFj9dOuDl7pHTKoKPNOQml/zGtPX0AT46k9mqmR+lfn9tE2b2tQWN85Me7rmLcjbSrCzkR+6hnHTS56MeUF2a/PUxibV9Q6q6hqJzV7vfddz65uw4IfkN/qzLqv1+6M17G+MZFJTQ20pIY0+sr5V5cPuD1u3ad163UZVAfh7zrMh+z8iSJcDnUxjrMyDd26Hfe7AV1lMNrGujBY0jT61PV5deefT5IToJUMvaAAYe5bJ3JO91qSXW/csLLoPvvyj52Q+8UKoLQftwr7rXcaklPF61dnYbVYmJ4W1W1l5WmoEi2+dz0db83A4XSwcE8uUlAiWbssjJTKQk4bZGf/xOVCwg7JJ13PtnOt4frU5kfvbLPz+wsmU1NSTX1lHelQQId0IIALtViYmhXGwTVrS4TGeIGXjoVL+7+NdbM0u5+QJ8fzghFGM6uEdVYfTxdsbPMFKXnkd6dFBzf3IrWjgiuXRvHbx+4RUH6IiKI2r3yrimNR7SB0D7+xpxM8GY+OrqW908Yu3t/PoJRPYV9KA3WbBohQvrjIBSdsUqQATE4KJsBbAyBM5EDCGBzan8nXGRgL8LNx5wm9ZsaeMlRnFrL8ymbZ5TnT0SDaWBQHmrt3KfcVMS43gk+357vfOjDwUVzd4Xbzuzq9q/gyNDrZzw7HDCQ6w0RgejytyOJbS/a32L7HGAc7m/WvqHWzOKueC6clszW49UjAuIZTPduRj8VHkTynwVy2CgfHnmXnebYWnmbvWTXcGwWyPOxumXmYeYzHvZ1igHyNjQ7wWZKdGBrH0roUUV9Vz1uMrWl0zHDsqpnlR4bTUSJbceSz7CqoIslsZmxDaPGSfHh2ERdGqkN7U1HDSooII8bcyLTXCK2iY5k4T7CtBQFigjboWIwvnTks6rEQCR7xRJ8Kty6EixyxyjR4JvVCpvc/lbTV3RbWLyLgJPLwwiGuXNDRPO7xoQggRuozrXsngg9OqSGwKGMAEs5//Fk76FRTuxK+hnGnxAUxLSDV1XD5+rPUFq9UOygp15Rxv28rE+HFsyzcBSlJ4ACNiQ3jTnXVsZUYxJ42P46bjWo84NCvcBdnrzDqSpGlw5avm4tbmb2pLdGUBuqMRvn3cBAxgLjQ//ZVZxF6SYdYPbHsHkmf4fvywY+Hqt2Hd/8yo7MzrIXmW+VlEOky6COLGm+OGp3k9vDFqLDta/DdPjgzkjlc28OEZdQQ0BQxNqvLZn5nJ49ujSY6o4JPtjcSFHsfC4SH8tuBPBLa92G9KKRvmI7VsWLLJvrRnKVzynPlM3fYWzL8T7CGe0ZAmwS0CgYg08wUc0+jgpZsC+WhLLlHBdk6ZEM/EprUvQM6hDByH1uJXlYMjMhav30jCFPAPJTRUER/m71WvKMbWIngNjCQwMhEv9mDTn7LM1u3WFs9msbX6v6hjx2EJ6EJ2tbzNnoABzGj3B/eYNMOhPs7dLUWNaF5r2Sx1PoRKwTnRf4Zm0FCSYTInZa0xQ7IzrzeL3KZfBSufgDm3omuKUB/cZfYffx5+48/g3IYkAmwWhseGEBHk+wPEYlFMT4v0SuW3aFycuSvw1PHmTkZgJBHbX+AnI8s578aHKXXYSAgL4IPN2fxr+X60hhPHxvLguRMPe62B3WblgmnJfLO3uHmqx/jEUIa5MwgdKK7m2mdWU1Fr7ga/tT6bzOIanrl+tu87b11ks1qYkRbB+sxShscEs/lQGdfOT+ePH+1qnks8Ky2c0B2Lidn4BMy8m0mJp/PGNjN64G+zcO8Z4/j9h2bucGpUEB/tKGb+yBgUplryT04dS53DSWyIP9ctSOf5lQfR2lx8/26BhfClP6UxdhL/rLqcrzPMBWhdo4s/fbqPn542lpUZxfx+czC/P+F+bMv/YNY/BMdQddL/ce+rnqJNI2KDySwxwc7M9AhmDTO/z6Rw74wbEUF+JIUH8LdLpzIqLpTJKeZDzi88nvpznsT/javNmgGLjeoTfs0/t/oDNQTbrdxzyhj+9MkuympMfvJLZybxxvoc/KwWbjhmGHsKKml0arbnVHDCmFi+3O1JBXjNrASGZz1rNkadAsf92He2ksh0czfrne+bi6DIYXD+PyHGO5tWXFgAPz1tLLe9uI66RvM7WzAymknJYcSHBxAZ7Mdjl0/ngXe3UlbTyKz0SH519gSCW0whGB4T3BxktTQ2PpR/XjWT+97eQnF1A1NTwvnDhVOa/+YumZlKbnkdn2zPx99m4daFI5vf97Hxodxy3Aie+tpkcbIouPf0cfzrywyUgjMnJXDFnLR2K6gPWpHpPasy3N+y1pjsRxXutQXBMcy+6H+8f2I+B5wxhFkdpDo28q9dU8yPXT6m05UfMtNnVvzVzIF3TwMheoSZ+vLmjWZKis0fx8m/wbbqXwAM3/gX/nj2exRaYtBo9hVU8X8tRsTAjOT6lL8dnjvbU7jN6mfShvpaI9QRZ51JQdxSQxVkLIMD35jXNvlSk+bYF79AEyyOOtH7Z+FpJnBY9juzPe1KGHmiGRV3PzZjxn1sWOEkPToIp0sTHWKnsLKe3TXBxLZNM64UNZZgGhwuJsfa+AQoqKznzS31XHj2HSwo2eH5PU6+BPzdF+9J0022q02veN6rY35kKntPvNDUaVj3P/Ozdc/ASQ+ZzFiOWjPyEhgJsWN9vvxAPxvHjIrhmFHeSTuKCnIIX/Zzgve7p2jNuQWdPBuV7V6b6B8GC38GfoHE+8HvL5jELS+sb77Jc9n0OMbnuUdP7MG4Lvg3Fl//t0LiTJD3ymWeEdpRp3imVAEs+BFsX2K+twWgTv9jxxm0mtSWebdV5kKj9yizl7gJJiB7/27zd5o8C87+C3QlWBGilyjddphxEJk1a5Zeu3bt4T3I2Wj+0214oXX7iQ9QFjqKnIoGhqkCgpb9svXPz3kMZl7Xsw4fWm0W7SVMMYFDcIyZazrpIhh1Eks2ZvPDVze2esg9p4zmhyeNOaynKa9t4KqnV3H82DhsFoXFosgrryUi0I+fnzGeL3YWcMOza1o9Rin45K7jSIkKNusG8reZO4ZWP4pj5/BdvoVPtuczLiGMUybEtcpZ73JpMktqzJ1E7eK7/aVsyCzDalHMHhZJbIg/m7PL8bNayCuv4ftBy0j97iEASqbeyr7Jd+Oy+FFZ5+AXb28lISyAs6YksjmrjOhgf4bHBPPp9nwmJ4fx1Neeu/b3nTGW+SNjqKp3kBYVTGBdHjpvOxVBKZz/an6r/OcAd508mnUHSthbWE16hB9PneqPvb6UhvBhvLTbSr1To7W5IJ07PIri6gbCA/0YmxBKbKgJFirqGvnL0l3NVa4tCv5+2TTiwwKoqncwPCaY5IjA1lNkyg7hKDmICo5CR44io7Seoqp6kiICqW1wsiWrnKp6B+MTQ5mYEEhRSTkWiyI5NoZ9JbUcKKomIshOfKg/m7LK2JlbyeSUcOYOjybGkee+65hi7pB1pKrAfNgExUBIbIe7bsgsZV9hFcH+NiYmhpHWJnDNKaulut5BQnjAYedJzy2vpbLWQXx4AOFtgtSK2nr2Fdbgb7MwLiEUi8UzolRZ28iu/EoKK+tJiw5idGwIeRV1NDg1KZGBkvKwfd2KpLp1fv3s1+Ziv9WBvgfzb4eCHVQQzO/XWXhlq7lIevF0K8d+dXnru6fjzjYXUtnrzPYxd8Epvzbfaw3F+6Ayh0MNofx+ZQ3nptQQoqvYVR/NurJgrp0/DLvNgs2quOLp76iuNxd+80ZE8ddLp5HkK3BY+TgsbXPOH30aXPYC2PxNggSLBYuz3ow8+AhOHU4XLq1xffsEAct/R0PKMVgcNdiyV6EvegZVX2nusCdMgYhurE05uBKePaP1ezX5MjN9SWtc0aNZUxXNuxtzUEoxe1gUf/90FwdKapmZHMR/RnxF5Jq/NT+0aPqd/CDrJKqdNv42v5Ybl1k4VGruzKdF+vP2eYFEl2yAhkoaig+yc9zt5OpY4sMCGBNYQVDhBpPFJyIF3r/HBERn/QWW/9kzDSos2Uy5+vw3nj4vuBOO/3mH1b2b1VebhdjF+yi1JxD5xsWtfz7jOhyjTsNmwdS/iBnV/COnS7Mnv5IDxdVEBtkZGxdMRM0BnJX5WCOSzehRm99jfaMTpcBuwXwGFu81QU7MKJO5qjzb1MIITzU/qys3UwY7ylzXUs4GePrE1sHbuLNhzOnmWmD0yWZNj68Uu03Ks8w01NAkCOy9LIeiW46yu1SdG3ojDTWlzdk5Wqku5KvGOby4x8bigOe9f75jSc+DhqBoczekRX0IRp7UPKXk233FXg/5aGseNx03wiutake0hpAAG098sbdV+89OM3d3gtpUEU4KD+Cm44bz+492UlTZwP9OUUS/eRE01uKKGs1Lw/7BX781cz/fJYeXvjvAK7fMJzUqiKq6Rj7ZlkdksD92m6KsppFnvtnP6RMTcWnNk1/s4weLRuJ0afIravlgcy7HHz+ZVIDASLKTT2dHYR2NzjriQuz89NQxoBQ/e8MzrzXAz8JD50xkX0Elf71kKgF2K/WNTjIKqxgVXE9gcB376y2c/q/dVNbDCWPrGRVn5jI3uemYYUxKCmNycjiNDhf7CivZ5xfL9JGR5BVV8/bGtex2V2OODPLj5AnxzPORojYswI97Th3DKRPiKaysJzUqkP99e4APNpvFaFOSw7h90Wi25pQTGWRnwchohkdE0hjUgPIPJdhuZ0y8nTHxoezMq+CSf62kqt5Tg+EfV0zjnKme4f9xCX7NFbRX7C3iT0t30+Bw8emOfP7v4qkQFU8dLuItAbS9dK93OCmoqCfIbjVThELimlOq1tQ7yCiqoq7RRUK4PymRnqCgweHEpTXV9U7sVquv1AG+L7x80Fqzv6ianLJaYkL8GREbTGJ4IIntfNaFBfozPc13koHQQD9mDWs9saxtMCMGmK8MQwXbwWKH8edQUVLDRxkrmn/0yHo/njntKRK++ZW5kTLubEiYZO7qxo4zx2sKHsBc5MWMgphRlBwq46Nd32AGJu1cPTeSmoZaLn/6OwBmpkXw8k1zySuvJ8jfyriEMGJD28lu42sxaUUW5dU1fLgrj8DqHI53riQyY4mpPzDjWog3dWVcLs26zFKeWbGfwsp67j/xLLJPOoHnNlYQbodrz4uhpt7KaTO7sR7F6TApNov2mBN725t8W16DiefD+LNYk1HMFU9/1zz9b3VGIS+e5Q9FB6lWIeTFXojfsAX4V2fTEJLCb1bZWH2ohgA/C7aKHF6d1cCukDm4tGJs3UaiszJh7f9w+Ufw7uQn+dmLmWhtpuz8/KRUbqj/loB1/zafYQvuMBfU9hAz1WbX+6YTky8xxd5a+vYfMOF8kz7YLb+ilkanJjE80FNIU2vYshi2vQ0pswlMTjQjFS3XFux8D+eM72ELifKapmO1KMYlhjHOnZzhQEEZebllNJaXYq8NIVhVkxJlpuRW1Tv4Zm8RTy/PwG6zcOvCEcwbMRH/xCmeA4a3qewW1o1pQfH/3955x7dVnf//fbRlSZ7y3it29t4J2WG0jDIKYZQ9WigU6Pfb8m1/3aVAoS3QQqGUkbLK3oEEAiEkIXtPxytxHO+9ZI37++PIshUriQMpVprzfr30snV1JX10dfXc85zzjBFy1feDH8tVnMJvy+Txd26Tj3/xIFz9riwIcDSivoLDqVCcJE4/p6GzQZYsLPksaLMvYRj/WOXDbhFoSaMQfepHA7IaRNNBuXxsO2IwWb0Tdr4tl6VHXAhZZ4Atjn64O3uXdHso/kQmZgOj0qJ5eX1wNYcp2bFY2g9Bh37As1NGvY7zRqewsbyROJuZLo8Xs0FHTrwcYA1JdHDx+FQSHBZ0OsHw5EjueWM7TZ1uxqXZsW58KlCRoqLwGv65poUrp2QSE2FEA97bWsneqlbSYyMoqWuj26vxk9e3kRZjZXZBPHMKEnhhbTkGneCySRm0dHlYsuMwbq/GHfOHoDM2QHQme2c+wpq2dJ5ZXUJNq4v5QxP57oQ0nltdhtNuClTK6XL7ONTUSabTzuIvy9lysImFhU4eGFuH5bn/g+YDpBZewO/OuJY7lrXy+b5a7v3OSPZWtdLm8nDmsERmDInnsU/3s66skYJEB3cvHEJatFw9WLmvNuAwADR2uHn6i1Luv2hUv6ZePp+P9aWN/GHJbopr25mR6+Tq6Vks21WD16dx3phUvv/CxsCFO9Ji4MVzTIxY8h28sXm0zb8fW8EchE7HpvLGIIcB4E/LipiZH98v/K20rp2bFm8INHOrbXNxy/MbuXh8Kv/4vJSLx6fJsrr+QXRpXTuPfLKPt7dUkhxl5effHkpzh5t3t1XyvSkZNHZ4eOSTIqpbXcwrTOCWWbmMy5ShQCv21XHTvzYExic5ThvPXjuJjLjQZUe3VTTx2d5autxe5hYmMDo9OtB0afmeGm59cRNdbh96neBX5w7juxPS/zuSlRX9yV8Ie49IIi34FhxcD5ueIy06g2VXT+Dy12spqmlnarqFuI4SmQhqjZWlZp0FcnCl+WRzs1Ax9MiQy78uGsv/e3snXW4v8ZHmQM4TwMYDTSzfU8OdC0KHwgSRN18OZvugTbyRFzfVsGZfFX9zPItj3xvygcrNchLpuo8gOp1th5rYvnMHt6Ucwiw87GhJ5Edv99rxT/Y389jlowd2/I5k/zJ4+XJ5LGbcKasudfXJ+3Eky8ko4IW1vdXkIkx6/nVGM0mvXReY1dbSJ0PeAsSnv8OQMo5fzPo9G6p8VDZ3URs5kkltH5O6/ALQvGgTbpAz6l1NlI3/GT//rCXIX3lg+UHO+M4Chi9Mlz0b2utg02LwumDSzWC9XFbDMph78zv64k/qbevy8P62Su77cA8d3V6umZ7FNVOzSI62ysTrnud+8RDm2DxY8BvphLRVQ9oEtMJzMb90sTwmE66XK1ohumLXNbdi2fkyWSv/T4YcGSwcXvAY7aPPw2Yxsqa4npv/1eucri6u58UbJjMtRJjU10JvlOd6yngZkrRvKXzYp7Kfzwtrn5S5Cjrd0V9HoRgkTj+noXKzXAo8vLU3MTR3Drr0yTxxVSaapiFK9sqkowYZP828X0DNDvjkV3J24ewHZCyp3iiXKBef11vZYPc7sOB3MP2H/d/b6wpeluy7HZiZ72RCZjQbypsASI+xsiijGd0jM+UKxYLfSqfEfOyEZZvZQEaslYcuGc2mA03YzQYKkxykRctBX2O7i2HJkfzxo310umV+wK/OG05lUwcGnaDctIi45GnscUxBWKO5/0ILv31/N4eaOjEbdFw/Ixu9gJLaNqpbXPz0je2ArFSiE4LFa3rrkj/5eQm/PHcYRr2e0rpW7luym8evGMevkv7KZFM+f/hwU+Bi9NHOKmwmPVNy4kiPjSA9JoLn1pRxuFnOLH24/TBb/GUVr8hqIfrtqwIxp6bdb3BmvofpWTewubKTzm4vP/tWIQ6LkdRoK3e9spXSOnkBKqppZfuhZioaO6ho7CLbGcHcwgSW7+mtGrTjUAsuj7ef07C1oplbX9wUKJf7RXEdrS43t8/L48viBj7aWRWU6NvS5WFNjZUR8cPQN5Zif+0yWq/+BEfGKEI0HcXtD3E4koqGDjq6veQ4beQm2Nl9uIWKxk70Oh0en8bL6w9iMej5+beH4tU0Hv2kKJCUfqipk1tf2MTdCwtYtb+eRRMz+L83twd0Lt1VjV4n+INzJBrw+w92BQ0QSura2X6oKaTTsO1gE5c8sSZwPP6+opgXbpjC1Nw4DjZ0cPerWwO5EV6fxi/e2cm4jJig5MbeD++CQ+tl80VrjPyNHS32+wi6PT62Hmxixb5arCY9s4bEMyLUe4TA4/Wx1e/4mA26QPECxVcge5asNLThKWnrxlwlB/2vXxfYxRmTzTtXvk6FlkBWwxcY//2H3ucv/J2sGNVjJ3e/LRODQ2Ay6PnWqBTGZsTg8fqCmoL1sHxPLbfOyTt+dbi0SfDdxTKMprsNpt5Ksy2XR94u5f4zjDhWH6Gh5ZBcBYlOx9RczlXFd2Ns2EfHiCu4e0cWQxIiuGqogQ4P/HObix0HGzhrpJz06fb4KK1ro6XTTZzdTLyvnuKaJjq6uslKjKO828Fy/7k4NzGRsdY4REetTC6efQ+se1Jem+ILYM7P8en06ACXu9egfH9iNImrfxJ0vREH1wY61YvKTTjfvYb3r3iT+v3rydE3IVbc37vv6ofxnfMn9p35PE2RBbg8vRUAwR8lpkVLR2Hy92Xpzx5W/QXOuh/OmyaTtre/2nstBTCYabMkUFrRjMvj5Rfv7AzYjydWlOC0mbjxjFy5orDzdVn+HBD1RbDsF/gW/g7dp7/HN+4adD0z9ABrH5dO1Zx7+n29om4fSZ/f03s8PF0kf3on9SkjMafk8dzq0n7PeWdr5dGdhooNUPKpPA+yZ8vcF/txEpn70pP0XLOz/2OdjX6dOmpau1hf2siG8gaGp0QyJScuUML6a+NxQ2OJrGYVkzWwcDHFac/p5zTY4uUP/ewH5Gx6dxvU7oOIWFLt/pCL6ng5YBl5iTQEB9bJZWCQiaQvXQY3fCIrYFRt718K7fP7YcR3+i8jxmRDyjio3NS7LTJVlp1DJv4+ceUEimrb8Hh95LZvIfnd86UB6WqCd38okyJzZh3143V2e/H4fHR2+4LyI84dlczcwgT+vf4guQk2LEY9vz5vGG0uLw6LgV2VTUzKdtLU2U2NfQJ3fGBjX3UlUMnk7BjmDU1g8ZpyXB4fj31WzHPXTqSoupGSum4uHJvC3MJE7BZDUInVHrZXNPPn746izeVlxd5qoqxGJgzLo6G9u99q+3vbDnPdjCxeWHsAo17wv2cVcv+SPURajMwpTOAHs3PRALu3ic/mf4A9IQuf10WKqMPbXM0N9gK8PkiMNLGuvInDzV1omgw56rksXDU1ix0VTYxMjybCrKekrp2hyZGMSo2i0+1l6a5qZuY7OdzURae7A6fDxIayRtaXNTA8ObJff42tFc3ctWAIY9OjgzoJ91Cni2PNwrfQ+9ykNG6krs1E094ahiY7ePi7w7EaDXS6fcRFGHHqWomt/hJ0Brqi8xA2J2ajnhibibsXDuFAfQfbDzUza0g8OfE24u1mbp+XR1Wzi7e2HuLm2Tl4fVq/krs+TXaYfu7aiZTUtXNEASiW7qrmjnn5REUYqWvtXxq1rcuDy+1lf20bda0yHyMn3s5Hu6qCjkdP74WJWTE0tHcHmrb1oGlQ3drFcEIM6EtXwIuX9N5f+ZDshnuUZmZur48D9R24vF46u71898k1gfPpb5/u55Wbpw7IcdhY3sjlT63F6z8ojy7fz3PXTmJCVkw/pzEUnd1eyv3lcjPjbL3dak9H4nIga5q0jUJAeyMs+XHQLqKxFH31DvJHng8Vfcr7xhfKwVjfiRVNkwPT3DlHfcueULnJOXG8tSX4vJ9dED+wctKmCJlwnT4VfG7Y/Q6dpWswGsbgRSdLY0alyc/VWC5tuMcFpZ+T31GMsUE6LLqYLK6IMXJO54fYN/4DjBFcNP0nrDMnQtkqvAYLa9rTWFfWRGVTJyPTIrEZ9BxosqDXWWixWvnBC+sCv89/GHQ8d9WniNYqonQusrf9CfOC38iBns9LV0c7RcZYanZXc92MbD7bV4vL42Nhlg7Rp9FoAHffsqHV2FuKiKn+EK269zxvz/0W9UMuJcHsI/fQKjR3MU+fM5YfLOsITABYjXrSItyykERFiLyXrS/BdR/KxybdCJv+JcPUIlNpmfcAF7zaTEndF2TGRfCTswq5b8meQLGMl9dXcOnEDCI9roDDEMDThbDGwve/RLf1xf7vu+V5+X5HRAMYO2r6T9h1NWNy1aMT+dhD9IIItQ2Q/Sr+fWVv3saGZ+CcB+X7nigjLpI9Lvoy+WbQG3C5vTz6SVGghDnAjLw4Hlk07utXiWuvgzWPweqH5XeYOw/O+aOs0KZQHIPTy2loPgTLfyNXGXqYfQ/kzAyeJcieKZcOP38AxlwJu94Ifh3NJ2eZUsf1jzEFOfsdantErOz98OVjsO8j2Sxm5l1BzkWcw0ycwyyTVp+4rX/jl8otIZ2Gbo+PtaX1PLq8iNx4O3uremt65yXYiYowcecrvZ97aJKDMRnRvLTuIN8amYzNrOeGxdL458XbuWh8Kvd/KCuPrC1tZHxmLFajPlA2saKxk5+9tYPF106kqqWT21/eTE68nREpkWzok0tw7qhkCpMd/Pb93aTHRHD2yCRufXEz9e3d3L2wf4J3crSFWn9vBFk1qJkHLh7JXz4u4qLx6awra6DT7ePJlSVoGpj0jdy1cAgrXXaqWwy8tlGGBp05PJHCJAePfLIfIeDCsak47WbaXB6m5cQSG2Hk0eX78fg0nHYTt83No6nDzXNryrhsYgbjMmL4eFc1y3ZXMzYzhqf8CdgPXzqmn2a7WXax/vvHxVw6MZ1fv7sr8JgQkB5rZ9FT60mLsXLP2RNoaunmcEsjmbER7Kxs59nVZQDE28387dLhsNhfDz5lMp8N+y1RKXmkx1h5c1NFoDvunqpWxmfGkBRp5v3tVeQ4bfzPwgIijHo8Po3kKEvILuaPLt/PZRP7L98n+5OSEx0WrpySwd9X9M4M6nWCIUkOXlh3gN++t8t/3HX885oJtHV5+r1Wq8uDT9OId5iJt5uDmhXqdYKUqN58iPo2F/tr2ojSuyj47A/BWWVdzbKMYwinobG9m2dWl/HYp/I7nJwdww/n5vHIJ9Jp7ej2smJf7XGdBq9P4+lVpQGHAWQzxDc2H2LX4RYuGpdGVMTRE70PNXbywEd7/Mmn8jy7e2HBgHM+/uvw+aBio1w93fwCTL4FXG39duvu6pDlMmOyejfq9LLnQr/X7H+OhWJmvpO5BQks9/cZGZ0WxXfGhg5t6oenG8pWwooHZCfu4d8hubOIH0+ewXN73Jz9rb9hqfxS7hNfCOP+DBXrYPPzGIZfFHgZS0cVF8Ssx7Tyr/7XdeH87KfMveRFeOUOmvK+w99rzmdNmQwxqm9zMTQ5kmdWlTEiNYodFU1BDr3L4+OtHY2s2NdCdUsXd83+JdcYO7Af/pim6FE8fiCRJ9fvRtNkbtrTV47kqS/KsFmtUHCOXPnuQYjgOHwh0Jsd0N2BJ3k8Rt6nfNrveKhqLHd1FmNZcntg17k2Jw/Pf5abl7QQ7zDz0Cwj2a0bwRgROrY/OhPQyeIMy++FIQuh4BxqEqYz/3U3LV3SjpXXd/DC2gOcMzKZt7bISk258TbMRh1dRgeWI/snAZ1mJxGRSRAZolxqTHb/BqKAOS5DRgb0vZ5GxGGJTUGnE1wzPZulu6oDx96k1/GtUSFeH+T44cjytZ//EfLmyQiFEyF9Elz+qiwe4HHJKlTZZwAyxLRvuB3AF/vr2V/TxqTsI4uGnyAH18IXfXJNij+RK1nzf63CohTH5PQ6O6q2BTsMIJd6UycEb7NEysZv138MIy8GR4gLj7+jJ0kj+3dunXHX0ZOV4gvkrMTNK6UDcbTwC5MNnCGqJkWFvghuq2jie0+vY11pIylRlqBY+YXDEnnliFyJ3VWtJEZaEAIKkx28sqF3Vmp/bRtbDjYzss+A60BDB4mRvUmE0f6BVFOnO9CZeX9NG8NSooi0SF80IzaCOLuJez/Yw5clDby6sYK7XtnK5ZNlTe7q5i5GpPY2w9HrBFdOyeSD7b1Jic2dHl7dWMH4zFg+3HEYnU7HE5+XBHyybq+PZ1eVEmU18sqGioDR/2hnNW0uL3E2E5oGr286FAh7Kqpp588fFwVK8dW1dbN4dTnpsRF0uX08u7qMg40dVLd2ccPMHJ5dVRbQY7cYWDAseBn6jvn5PLGimL1VbdjMem6bm0duvJ3RaVH85rzhLF4jn1/R2MmP/r2FunY3f12+n/95bRsOi4G0GHmRq21z8djKA7TMk2EClsq1FHZs4ObFG9hV2RJwGHrYWN4YqGJVUtfO8j01mI16DHrBjTOzgzrpjkmPYltFMxvKG6lu7Qo0XANZAepn5wwlOdqKTie4akoWP5ybR5zNxPCUSJ69diIWoz7gMPQc91tf3BTULLCH66ZnYTLocZgN3LVwSOBcsRh13LUgH4f//DjU2MHtL23m0ie/ZPGqEkR3a7/XCtXACmR1p0c+6f0O15Y2crChk9z43tC9I/NFQuHTNFqOqLIF0Nnt4fkvy9lS0RjiWb0s31vN2/7Z7Z7z7LMQzfFOG3Q66eztfAtGX0Zb8mSaR14bvI/RSmuUPyk4ebSsjiSEzA3LnN6/MtGE6wf01mkxEfz5sjG8+YNpvHbLVJ6+ZiI58ccO5QxQsQFeuAgOfilnxD/9PcTlcn7jM/xqmgXDnrfloKq+GPa831vMoqMeEdU7aNaSR2Pa9kL/w1K6AuILKIqeHnAYQK6OPPF5Cd1eHwmRJtq7+ztNHd0yJ82nwYOfVrCr3Q6fP8j2ZhNPrKsP/CYrm7t4YkUxjyQvI6VpIww7T3a2Fjq5or3gN0G9JrRJN3NYi2ND3m2UJCyApJG80T6GpAiNrC0PBotor2OWrZwl8+t4d/SXnNH4OmLfEtkEzzkkuLmYyS4H0AJZKWrmXbLp2soH2VDlpuWIiYbi2jZS/TbQYtRxy6xczAY9B33xVEwO7mTfmnsexTp/f4r0KcHXSINZ9lsKUUXusDGNhoWPSicHwBpD9YLHqDdIWz4hM4ZXb5nK92flcvu8PF69ZSpj+tjIIHwhOjh3t4fefjyMVulQXfkmXPO+TGr3hwm5vb6Qc4/uUHGtJ0qo1aHd7/RrOqhQHMnptdIQKiGrqyn0qgDIusvWaDj7vt5kNJAl0ZL9iW3OfFnPe/MLMu9h7JVyqe9Y9eL1xuOWvMRkgzk/h4rzA0nJJI85alfSlUV1gY/hsBj59qiUQIyvXidw+/obGk0Dh8VAzRENcEAOymYVxLP9kLzA5cbbWeZvdHbpxHQEEGHS9Wsg9+gnRdx0Rg42s4HceBu3PB+8vNzU4Q5Ux3h+7QEun5TBjZMS8LZUEZuYzi8/Kg+sZgDMGhLPe9sqSY+18ubmQ8wLMUiNjjCxqbz/4G5jeSNDkyP5Yr8MH3N5fLy1+RA3ntF/Nqikrp3GPh2L39pyiHNHpWA26IKauW0+2MS4jBgWDE2itctNaoyVD3dUsflgM/OHJvDc6nIONnYwMy+eWUOc/OytHbi9vc93ezU8fYz+UytLuXZ6Fo99VgzA9kMt1E+dHOgrGtOwFadjBO4j44n89D3NVhfX0+hvPvfc6nLuXDCEbo+PlCgrWyuaAkn2f/xoH7fNyeXqaZl0dnvJS5CrTj2kxli5a8EQrpqSicWoJ9Jq5NM9Nf1+Ji2dHuIiTDx33UT+/lkJnW4PN52Rwwx/HHB5Qwf3LdnDxePTsJr0+HwaL649yKjUaFJjIlhTUs8qf8Ww94ra+f6MG0lf2ScpUOggK3QVkW2Hmvtt+7Kknmm5cRTXtiEEzC04foyxUa/jmmnZrCkJ7gw7Mi2ad7cdZndlK7OGHP11Pth2uN+2pTuruXzyKdRb4WQz7nsyjn3t37EWr2DNhL+QNymWpP3/pjMyl30FNxER5U9OtkbD7J/KMA1Xi5yhThwO656Sqw4Tb4CMKQN+6yirsV+PnAGxf2n/68CeD4iKSmVMy3IoWhL8WHudHKSCXDWe9b+w7h+0RuVijMrDWhMcpthuS8fUXoNb6w2Vshr1QV3Shaeba4frWHtEeP2I1Cje6RNueKhdR+mMhyjRZwPFQfuuPdhBa2YUjjWPwIQbZZht9qxAUzBNb4Yz7wNHEts8qZz/9CEKEh0UJFm4cOLjfLCigXNzdeDu76y73W6GxprAMko2NxsVLSe9qrbBqMvAaJHHUAgZHtRzfMZdLb/TxjLi7VlAcAhrvMPMtNw48hPsFCY5AtWOIkwGfra/gJtnv0yS5xDN+hjerIrj2wb/ZFZsNlzxunx/d4fMn0gcQSjKG1z8dHk8/zP5ZdKM7ezrsPPQu108fU0XSZFWDHod4zNjGZ85gBn8hGH9qzhNuA5iv0a3dlP/1ZHMOBtTc2KDbFN6jDVQ0ORrEapEbNpE6fApFMfg9HIaEoZKQ+bpM0gefcVRq3MEyJsvVx1q98qLXPLo4Bn/5FHy5vOd3KW9jMlw43Ko2SNnSJJGHnWlIdLa+1WuKa5nWEokd8zLZ9muapo63Jw1PIklO3pn8GMijHR7fLR1eXCGKEM4Jj2aIn9FobOGJzE2I5pbZuWg0+lYV1KPw2Kko9tHQmTwc1tdHlYV16HXCUak5AXNdofizc2HuNFxgOxV/0NH6nR+Pus+HttgwufTOGtEEu1dHsrqOwLNfox6HXqdCAon8fk02aG7z+cDyE+0s7aPwXXaTXh8Wshu0pmxEUEhXRmxEWw/1ExhkoOZ+U7q2lyMSY8mMzaCn7yxjak5ceTH2zEbdIE4ao9Xw6TX0dLp4f3th0mKsmAzG/rF9Rv7xMl3ur29JQaRjdSSKpcG7tc4J1Oxo4NIi4EJmTFBoV9nDk8K+nzjMqLR6wR6nSDHaeOhpdJp/NH8/H5Vuf76aTGLr5vEGWNDO69CiECXZ5Bx4wadCHKg4h1m4hwmRqRFMTUnDp9GUK8Es0FHm8vDP78IHgWZ/Md/V2Xv8W7p9PDIoSHcOftPpOx5RvaSmHGXzAEKQW6IC+fI1CiEgKk5cfxgdi6j0weWCD09L46/LhrLE5+XYNTrOHN4Im9tlqESmUepGNXDtFxnP4djck6IymmnEylj4PplULUdvU5HTmw6S7XLqMuaCwYLs1PS5e+1B6NV2s8eotNliEbPAPSbwBLdb5PXHE1l/veIs5uIODK0BWQnaoADa6CzHi5ZjF5noXr49WSVLw9MUnkjM2hOnEzM3pfJjdxDStQYKpu76fJ4g/qU7Krt4heZ+3n8zEKe2CmwGHWcPTKFl9YF/3ajrAbmvJPM3Qv752pMSo8gqmatXBGp2SHDdeqKQG+AxOHsqHFzx6qhuNxebjgjnrkFPsrqu5hb4OQPK8oYkujgxZ2NXDr2ZhLX9ikNbjDjih+BIy/EpFXKBJkrsfIhOXifdjtkzux93BYHQ84EYGiXm+/P8vG4P/zRpNfxwEWjQjZzS42xcsmUIVzx0iZ8mgwV+t4UJwWJfQa2MRnydhycdjNVLS7u+rjn2t+KzaQn5ihNWo9J5jRY9JIMM26ugBGXyFWdkxzWE2k1cu+Fo3htw0E+3FnN1NxYrpqSSXLUSQh9zJwqncnSFfK+PUF+bwPpeq44rQk7p0EIcRbwMKAHntI07b6T9uIJw+DKt2QVpIZiGH25bDxzvB+K3ghp4+XtWPwnYgEThsnbcZiW6yTSYqCly8NHu6q5YFwq9y/ZQ36ig+LaNuYUxJMWE8HyPTUUJtm5ZEI6936wG58mG9qcPyYlEGaRFmPl/DEp7KtuY3ZBPN3d3bR0dPH+9iqy4iK4YWY272+Xg6rWTg/njk7m3a1yxjXebubWOXkcbOigqdPFTWfk8OePeytvxNlMeP0z72aDjgcuyCez7A1IGEpE5nimGYt4PzaHpk4372+r5PdzY8me5CU+ppkDY1N4c1MFd84fwuOf7ae9W1Z+WjQ5g+ZON0OTHew+LAeiadFWChIdvOoPuzpnZBJGncBhMbBiby1XT8viX2vK8GnS4bphZja//0DODkaY9Fw6IZ3rnttAW5eb62fm8O7WSpbtquZgQwfPXDOJZ1eV8t72w8wbmsjdC4fw0NJ9rCqu48cLC9jsr/D0zpZKbpiRzYNLe6u6zC6IZ2dlbxfcHKeN6hY5YzU8JZLrJidh/de9IATNhZfxZlMudrObhEgz54xMZlJ2LAcbOhiRGoVBLwKJ1067ietnZHPJ39cgBPxgTh52i4G3tlRSXNPGlJxYvuwzuJ2WG8fIPqFhxyM33sbDl43hJ69vp83lwWk38ddFYwMXsFDJpplxEdwwI5snPu/Nj5iZ7wwMGCdkxfD0ql6H4tVdHaQlz+T2ay9F6I29M5UhGJ8Zy8y8OFbulysVsTYTt8/LJyfehl6IEyrparcY+fboFPITbfzl4yIeXLoXt1djTmF80ApMKM4Zmcw7WyspqpEOdmGSnTOH918NO+1IKJQ3IAX4Xgo0d6ZgMeoxDyQxGb45hwHk6vDKB3vj54WO0qE3c+YbMDrFxKuTb0W/+i+9+6eMk83MwN8R+U7Y8gI2r5uycb9k+YyXSHeX4tEZOaDPItsUA1U7SKkr4unzl/DsXgPryxtJjjIzd0gcy/fVU17fyS59AWdt/TFzYnIRxgh2Rf8vj/pzgnQCfjQ9nkiLiZn5TjJjI7hqSibPry1H02Re0k/Gg+39j6Sumj0yfMfdDo3VuMxOnqkeRkldO2aDjji7iccuG4vL3Y3ZaiXSaqaqpYsN5Q38vXkS106/l4z9L9IdmUHV8JuwJR6ti7VZhiNlTper8aajO9p2i5Fb5+azcHgSDe3dZMRGBIUUHsmCYYm8c9sMyuvbcTrMFCZFBjrInwi5CXbuObuQe2VTD/Q6wb0XjjzupMDRX3AupE0BT7ssrvIfIttp48dnFnDL7FwiTIagCaavRXQGXPw01OyWk6jOIQNyvhSKsOoILYTQA/uABUAFsB5YpGnarlD7f6WOpSAT87r9P/b/oqSf3YdbWLW/jtYuNzPzncRY9OyrbsNi1JEcHcH2ylYqmzqJtBoZnxFNp9tHh8uDw2rEZtJR0dhFp9tLVpyVOHc1lU3tGPR6kiMtNJtTaOv2YtQJkkxttDTW09zeSVykDb0jmbJWaO5yE2cz4dN8HKjvJCHSQqLDxM7DrSzdVU1evJ35QxPQNI3DLS6SIi2MslRjLF6G3tWMJ3449fGT2VSvR9M0spwRONrKcdfuR2+JxJU4iu1V3ZTXtTEmMxaTXmAyCGqau8iItRJj1bOnphOfpiGE4MuSRhxWA3ohWF/WwA0zc+hye7lvyR5sZgMXjkslKdJCnF2ubBTXtuPxaURajAghVxsiTHp+9/7uoMZ7kVYDV0zK5PEVMjRgZp6Tc8cks7+mjem5TjrdXlYW1RFrM3HmsCSau7opqW0nzm7CaTPz49e2cqChkzHpUfzm3GG4PW46ur1kx1loa++AhlJsVjOrGqLoxMT0PCdDEh0cbu5kU1kTlc0dZMZFMCIlipo2V6Dj7Y19+jgAPHnVeBIiLdjNBvQCPt5dw5qSOqbmOFkwLIEs54kvRZfVyzCuxEjLgJJ969tcbCxvZOvBJvITHUzKjg08r7a1S1biWi2dtxl5Tn57wQiynQNbfq9vc1FU3UaX20tugp302K9fivBAfTvFte1EmPTkJzoGVKWkuqWLoupWhBDkJ9iDVmjChG+uI/SpTNV22b/H1Q65s6mNHEFRfRcWg56hUW6slV/CgdUQPxTSJ0NLJbRXQ0yODPdoKAZPF42OAmqaWjlQ34ZRryc9zkaaqQNz/W4Zlpo4Ao8pks5uL3aLgabGBvYdbpQlleMjydQOykIbOgMkjuCQN4qDDe1EWU3kJERhjuodpNa1uthb3Uprl5scp40h5ma5woCQIUFCB42lYI7EF5tHSbOP6pYuEiPNZDvt/QahXd1eqlo7Ka/rQCcEqTYfXp2R5BgH9hPs/B5udLk97Ktuo9Zf/S0vwR606qtQfAVOu47Q4eY0TAV+pWnamf779wBomvaHUPufdhe1k0xDu4vWTg9bDzbxo1e2BJKI7zm7kCf9s8Nun4/UqAgev3IcWQMczAVoLINHx8v4z8m3yPJ5Jcvhwqdg1CXB+57kUIS6VhdLd1WxeE05qdFWbpmVS0GSnaZ2Nzq9wOX2EWc3ER1h4oElu3msT7UgkLP+r94ylfL6Ds5+eGW/1799Xm+lHoC7FuTzrzUHqG1zke208c6t03BYQw8469pctHS6cdrNIWfNNL/TM1A0TeOqf64L5G70cO6oZB69PHR4T7jg8ngpq2vH7dXIjIvAcYoPTMIU5TQMAs0d3Rj0AptZndMKxX8pp53TEG7hSalA3wDOCmBy3x2EEDcBNwFkZKjltK9DrM1MrM3M2rL6oDJ/f/54H3cvGEKW04bJoKcw0UFi1FeYPdWbZQ5Ie51c+u8hRHWLkx2K4HSYuXxyJuePScWgF4GQiMgQA/moEHGtSVEWDDqB2aDDpNcFaoj3oO+j12LU0eX2BUqLJjjM6I8xg+W0m3Hajx56cyIOQ8/+PdVH+pJ8CpT9NBv0FCQNPExK8Z9F2deTRyi7olAoFKcy4bY2F2q0FLQUomnak5qmTdA0bUJ8/H8ulvB0YnxmbFA51W6Pj4KkSBYMS2LWkPiv5jCArKO98N7gbYkjIHlgXX5PBjaz4bgx1LMK4oMSEo16wc1n5GIy6MmMs/Gj+cFVMabkxFJc21uJS5aJlTkdep3g9nn5RJi+WX980aSMoARvm0nPuUerM65QHAVlXxUKhUJxNMJtpaEC6Nt5Kg2oPMq+ipNEbrydl26cwqYDjbR0eRiTHh3Uo+FrMfRciHwfDm8GRzKkTYCo/s3FBpPCJBmKtKm8kS6Pj7F9Pr9eJ7hiSgYjUqPYfbiF9NgI8hPsFFW3MTwlkmEpkSRGmhmS6KCj28uYtKgBdSE+2YxJj+aN709j04EmdALGZcYwNFnN4CsUCoVCoTg5hFtOgwGZCD0POIRMhL5c07SdofZXMbcKhUJxXFROg0KhUJx8VE7DYKJpmkcIcRvwEbLk6tNHcxgUCoVCoVAoFArFN0NYOQ0AmqZ9AHww2DoUCoVCoVAoFAqFJNwSoRUKhUKhUCgUCkWYoZwGhUKhUCgUCoVCcUyU06BQKBQKhUKhUCiOiXIaFAqFQqFQKBQKxTFRToNCoVAoFAqFQqE4JsppUCgUCoVCoVAoFMdEOQ0KhUKhUCgUCoXimCinQaFQKBQKhUKhUBwToWnaYGv4ygghaoHyr/BUJ1B3kuV8XcJREyhdJ0I4aoLw1BWOmuC/U1edpmlnneiTvqJ9/W88fv8pwlETKF0nQjhqgvDUFY6aYBBs66nMKe00fFWEEBs0TZsw2Dr6Eo6aQOk6EcJRE4SnrnDUBErX1yVcdYajrnDUBErXiRCOmiA8dYWjJghfXeGKCk9SKBQKhUKhUCgUx0Q5DQqFQqFQKBQKheKYnK5Ow5ODLSAE4agJlK4TIRw1QXjqCkdNoHR9XcJVZzjqCkdNoHSdCOGoCcJTVzhqgvDVFZacljkNCoVCoVAoFAqFYuCcrisNCoVCoVAoFAqFYoAop0GhUCgUCoVCoVAck9PKaRBCnCWE2CuE2C+E+Okg6nhaCFEjhNjRZ1usEGKZEKLI/zfmG9aULoT4VAixWwixUwhxR5josggh1gkhtvp1/TocdPk16IUQm4UQ74WRpjIhxHYhxBYhxIYw0hUthHhNCLHHf45NHUxdQogC/zHqubUIIX4UJsfqTv+5vkMI8ZL/NzDouo6Hsq/H1BR29jWcbatfh7KvA9MUVrbVryks7eupalvDidPGaRBC6IG/AWcDw4BFQohhgyTnWeDIhiA/BT7RNC0f+MR//5vEA9ytadpQYApwq//4DLYuFzBX07TRwBjgLCHElDDQBXAHsLvP/XDQBDBH07QxfWpPh4Ouh4EPNU0rBEYjj9ug6dI0ba//GI0BxgMdwJuDqQlACJEK3A5M0DRtBKAHLhtsXcdD2dfjEo72NZxtKyj7OlDCyrZCeNrXU9W2hh2app0WN2Aq8FGf+/cA9wyinixgR5/7e4Fk///JwN5BPl5vAwvCSRcQAWwCJg+2LiANaWDmAu+Fy3cIlAHOI7YN9rGKBErxF14IF119dCwEVoWDJiAVOAjEAgbgPb++sDhWx9Ct7OuJ6Qsr+xpOttX/vsq+DkxPWNtW//uHhX09VW1ruN1Om5UGek+YHir828KFRE3TDgP4/yYMlhAhRBYwFlgbDrr8y9RbgBpgmaZp4aDrL8D/Ar4+2wZbE4AGLBVCbBRC3BQmunKAWuAZf7jBU0IIWxjo6uEy4CX//4OqSdO0Q8CDwAHgMNCsadrSwdY1AJR9HSDhZF/D1LaCsq8DJdxtK4SJfT2FbWtYcTo5DSLENlVv9giEEHbgdeBHmqa1DLYeAE3TvJpc5kwDJgkhRgymHiHEt4EaTdM2DqaOozBd07RxyDCRW4UQZwy2IOSszjjgcU3TxgLthMkSsBDCBJwHvDrYWgD88bTnA9lACmATQlw5uKoGhLKvAyDc7Gu42VZQ9vUECVvbCuFlX09h2xpWnE5OQwWQ3ud+GlA5SFpCUS2ESAbw/635pgUIIYzIC9oLmqa9ES66etA0rQn4DBmvPJi6pgPnCSHKgJeBuUKI5wdZEwCaplX6/9YgY0gnhYGuCqDCP4sJ8BryQjfYukBe/Ddpmlbtvz/YmuYDpZqm1Wqa5gbeAKaFga7joezrcQhn+xpGthWUfT0Rwtm2QnjZ11PVtoYVp5PTsB7IF0Jk+73fy4B3BllTX94Brvb/fzUy5vUbQwghgH8CuzVN+1MY6YoXQkT7/7cif/h7BlOXpmn3aJqWpmlaFvI8Wq5p2pWDqQlACGETQjh6/kfGa+4YbF2aplUBB4UQBf5N84Bdg63LzyJ6l85h8DUdAKYIISL8v8l5yMTGwdZ1PJR9PQbhaF/D0baCsq8nQpjbVggv+3qq2tbwYrCTKr7JG3AOsA8oBn42iDpeQsbUuZEzBdcDccjEryL/39hvWNMMZDjBNmCL/3ZOGOgaBWz269oB/MK/fVB19dE3m95EvcE+VjnAVv9tZ885Pti6/BrGABv83+NbQMxg60Imf9YDUX22hcOx+jVy8LYD+BdgDgddA9Ct7OvRNYWdfQ132+rXouzr8XWFnW316wo7+3qq2tZwugn/gVQoFAqFQqFQKBSKkJxO4UkKhUKhUCgUCoXiK6CcBoVCoVAoFAqFQnFMlNOgUCgUCoVCoVAojolyGhQKhUKhUCgUCsUxUU6DQqFQKBQKhUKhOCbKaVAoTgAhxHeEEJoQonCwtSgUCsV/E8q+KhThjXIaFIoTYxHwBbLpkEKhUChOHsq+KhRhjHIaFIoBIoSwA9ORzaIu82/TCSEeE0LsFEK8J4T4QAhxsf+x8UKIFUKIjUKIj3pa1SsUCoUiGGVfFYrwRzkNCsXAuQD4UNO0fUCDEGIccCGQBYwEbgCmAgghjMCjwMWapo0HngZ+PwiaFQqF4lTgApR9VSjCGsNgC1AoTiEWAX/x//+y/74ReFXTNB9QJYT41P94ATACWCaEANADh79RtQqFQnHqoOyrQhHmKKdBoRgAQog4YC4wQgihIS9SGvDm0Z4C7NQ0beo3JFGhUChOSZR9VShODVR4kkIxMC4GFmualqlpWpamaelAKVAHXOSPvU0EZvv33wvECyECy+lCiOGDIVyhUCjCHGVfFYpTAOU0KBQDYxH9Z71eB1KACmAH8ASwFmjWNK0beSG8XwixFdgCTPvG1CoUCsWpg7KvCsUpgNA0bbA1KBSnNEIIu6Zpbf4l9nXAdE3TqgZbl0KhUJzqKPuqUIQPKqdBofj6vCeEiAZMwG/VBU2hUChOGsq+KhRhglppUCgUCoVCoVAoFMdE5TQoFAqFQqFQKBSKY6KcBoVCoVAoFAqFQnFMlNOgUCgUCoVCoVAojolyGhQKhUKhUCgUCsUxUU6DQqFQKBQKhUKhOCb/H2XazM00oUxwAAAAAElFTkSuQmCC\n", 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\n", "text/plain": [ "
" ] @@ -780,7 +614,6 @@ } ], "source": [ - "# Include the 'sex' variable (column name) into the plot function to split into subplots\n", "age_fare = sns.relplot(data=titanic, x=\"Age\", y=\"Fare\",\n", " hue=\"Survived\",\n", " col=\"Sex\")" @@ -788,24 +621,16 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "The function returns a Seaborn `FacetGrid`, which is directly related to a Matplotlib `Figure`:" + "The function returns a Seaborn `FacetGrid`, which is related to a Matplotlib `Figure`:" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 61, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -814,7 +639,7 @@ "(seaborn.axisgrid.FacetGrid, matplotlib.figure.Figure)" ] }, - "execution_count": 17, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } @@ -825,24 +650,16 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "In the last example, we are dealing here with 2 subplots. Hence, the `FacetGrid` consists of two Matplotlib `Axes`:" + "As we are dealing here with 2 subplots, the `FacetGrid` consists of two Matplotlib `Axes`:" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 62, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -854,7 +671,7 @@ " matplotlib.axes._subplots.AxesSubplot)" ] }, - "execution_count": 18, + "execution_count": 62, "metadata": {}, "output_type": "execute_result" } @@ -865,20 +682,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Hence, we can still apply all the power of Matplotlib, but start from the convenience of Seaborn." ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
\n", "\n", @@ -895,8 +706,7 @@ { "cell_type": "markdown", "metadata": { - "deletable": true, - "editable": true + "tags": [] }, "source": [ "### Axes level functions" @@ -904,24 +714,30 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, + "source": [ + "In 'technical' terms, when working with Seaborn functions, it is important to understand which level they operate, as `Axes-level` or `Figure-level`: \n", + "\n", + "- __axes-level__ functions plot data onto a single `matplotlib.pyplot.Axes` object and return the `Axes`\n", + "- __figure-level__ functions return a Seaborn object, `FacetGrid`, which is a `matplotlib.pyplot.Figure`\n", + "\n", + "Remember the Matplotlib `Figure`, `axes` and `axis` anatomy explained in [visualization_01_matplotlib](visualization_01_matplotlib.ipynb)? \n", + "\n", + "Each plot module has a single `Figure`-level function (top command in the scheme), which offers a unitary interface to its various `Axes`-level functions (." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ "We can ask the same question: _Is the relation between Age and Fare different for people how survived?_" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 66, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -938,54 +754,31 @@ } ], "source": [ - "scatter_out = sns.scatterplot(data=titanic, \n", - " x=\"Age\", y=\"Fare\", \n", - " hue=\"Survived\")" + "scatter_out = sns.scatterplot(data=titanic, x=\"Age\", y=\"Fare\", hue=\"Survived\")" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, - "outputs": [ - { - "data": { - "text/plain": [ - "matplotlib.axes._subplots.AxesSubplot" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "type(scatter_out)" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "But we can't use the `col`/`row` options for faceting:" + "But we can't use the `col`/`row` options for facetting:" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": { - "deletable": true, - "editable": true, "tags": [] }, "outputs": [], @@ -995,24 +788,16 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "We can use these functions to create custom combinations of plots:" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 82, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -1021,7 +806,7 @@ "" ] }, - "execution_count": 26, + "execution_count": 82, "metadata": {}, "output_type": "execute_result" }, @@ -1046,12 +831,9 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "__Note__ Check the similarity with the _best of both worlds_ approach:\n", + "__Note!__ Check the similarity with the _best of both worlds_ approach:\n", "\n", "1. Prepare with Matplotlib\n", "2. Plot using Seaborn \n", @@ -1060,10 +842,7 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
\n", "\n", @@ -1079,33 +858,116 @@ }, { "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Summary statistics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Aggregations such as `count`, `mean` are embedded in Seaborn (similar to other 'Grammar of Graphics' packages such as ggplot in R and plotnine/altair in Python). We can do these operations directly on the original `titanic` data set in a single coding step:" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": { - "deletable": true, - "editable": true + "collapsed": false }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.catplot(data=titanic, x=\"Survived\", col=\"Pclass\", \n", + " kind=\"count\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To use another statistical function to apply on each of the groups, use the `estimator`:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.catplot(data=titanic, x=\"Sex\", y=\"Age\", col=\"Pclass\", kind=\"bar\", \n", + " estimator=np.mean)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ "## (OPTIONAL) exercises" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
\n", "\n", "**EXERCISE**\n", "\n", "- Make a histogram of the age, split up in two subplots by the `Sex` of the passengers.\n", - "- Place both subplots underneath each other. \n", + "- Put both subplots underneath each other. \n", "- Use the `height` and `aspect` arguments of the plot function to adjust the size of the figure.\n", " \n", "
Hints\n", "\n", "- When interested in a histogram, i.e. the distribution of data, use the `displot` module\n", - "- A split into subplots is requested using a variable of the DataFrame (faceting), so use the `Figure`-level function instead of the `Axes` level functions.\n", + "- A split into subplots is requested using a variable of the DataFrame (facetting), so use the `Figure`-level function instead of the `Axes` level functions.\n", "- Link a column name to the `row` argument for splitting into subplots row-wise.\n", "\n", "
" @@ -1113,24 +975,21 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 83, "metadata": { - "clear_cell": true, "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 27, + "execution_count": 83, "metadata": {}, "output_type": "execute_result" }, @@ -1153,10 +1012,7 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
\n", "\n", @@ -1164,7 +1020,7 @@ "\n", "Make a violin plot showing the `Age` distribution for each `Sex` in each of the `Pclass` categories:\n", " \n", - "- Use a different color for the `Age`.\n", + "- Use a different color for the `Sex`.\n", "- Use the `Pclass` to make a plot for each of the classes along the `x-axis`\n", "- Check the behavior of the `split` argument and apply it to compare male/female.\n", "- Use the `sns.despine` function to remove the boundaries around the plot. \n", @@ -1178,20 +1034,17 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 19, "metadata": { - "clear_cell": true, "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -1212,20 +1065,17 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 20, "metadata": { - "clear_cell": true, "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -1246,30 +1096,21 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "## Some more Seaborn functionalities to remember" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "Whereas the `relplot`, `catplot` and `displot` represent the main components of the Seaborn library, more plotting functions are available. You can check the [gallery](https://seaborn.pydata.org/examples/index.html) yourself, but let's introduce a few of them:" + "Whereas the `relplot`, `catplot` and `displot` represent the main components of the Seaborn library, more useful functions are available. You can check the [gallery](https://seaborn.pydata.org/examples/index.html) yourself, but let's introduce a few rof them:" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__jointplot()__ and __pairplot()__\n", "\n", @@ -1278,29 +1119,24 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 21, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 30, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1319,29 +1155,24 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 22, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 31, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1353,40 +1184,28 @@ } ], "source": [ - "sns.pairplot(data=titanic[[\"Age\", \"Fare\", \"Sex\"]], \n", - " hue=\"Sex\") # Also called scattermatrix plot" + "sns.pairplot(data=titanic[[\"Age\", \"Fare\", \"Sex\"]], hue=\"Sex\") # Also called scattermatrix plot" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__heatmap()__" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Plot rectangular data as a color-encoded matrix." ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 23, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -1445,7 +1264,7 @@ "male 41.281386 30.740707 26.507589" ] }, - "execution_count": 34, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1458,14 +1277,9 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 24, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -1474,13 +1288,13 @@ "" ] }, - "execution_count": 35, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1492,44 +1306,33 @@ } ], "source": [ - "sns.heatmap(titanic_age_summary, cmap=\"Reds\")" + "sns.heatmap(data=titanic_age_summary, cmap=\"Reds\")" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__lmplot() regressions__" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "`Figure` level function to generate a regression model fit across a FacetGrid:" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 25, "metadata": { - "collapsed": false, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1549,20 +1352,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "# Need more Seaborn inspiration? " + "# Need more Seaborn inspiration?" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
\n", "\n", @@ -1575,30 +1372,21 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "# Recap: what is `tidy`?" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "If you're wondering what *tidy* data representations are, you can read the scientific paper by Hadley Wickham, http://vita.had.co.nz/papers/tidy-data.pdf. \n", "\n", @@ -1607,10 +1395,7 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Compare:\n", "\n", @@ -1641,20 +1426,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "This is sometimes also referred as *short* versus *long* format for a specific variable... Seaborn (and other grammar of graphics libraries) work better on `tidy` (long format) data, as it better supports `groupby`-like transactions." + "This is sometimes also referred as *short* versus *long* format for a specific variable... Seaborn (and other grammar of graphics libraries) work better on `tidy` (long format) data, as it better supports `groupby`-like transactions!" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
\n", "\n", @@ -1666,15 +1445,17 @@ "- Each observation forms a row\n", "- Each type of observational unit forms a table.\n", "\n", - "
\n", - "\n" + "
" ] } ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1688,7 +1469,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { @@ -1706,6 +1487,13 @@ "right": "1657px", "top": "106px", "width": "212px" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } } }, "nbformat": 4, diff --git a/_solved/visualization_03_landscape.ipynb b/_solved/visualization_03_landscape.ipynb index 5bd25c3..32d68b9 100644 --- a/_solved/visualization_03_landscape.ipynb +++ b/_solved/visualization_03_landscape.ipynb @@ -4,11 +4,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "

Visualzation - Python's Visualization Landscape

\n", + "

Visualization - Python's Visualization Landscape

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -31,13 +28,14 @@ "\n", "To have support of plotly inside the Jupyter Lab environment\n", "```\n", + "conda install -c conda-forge nodejs\n", "jupyter labextension install jupyterlab-plotly@4.14.3\n", "```\n", "\n", "To run the large data set section, additional package installations are required:\n", "\n", "```\n", - "conda install -c bokeh datashader holoviews\n", + "conda install -c conda-forge datashader holoviews geoviews\n", "```\n", "\n", "To run the 'bokeh-pandas' backend:\n", @@ -45,7 +43,7 @@ "```\n", "conda install -c patrikhlobil pandas-bokeh\n", "```\n", - "---\n" + "---" ] }, { @@ -68,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -96,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -112,22 +110,9 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "with plt.style.context('seaborn-whitegrid'): # context manager for styling the figure\n", " \n", @@ -150,20 +135,9 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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Ge+nSperbt68k6d1339Wjjz6qyZMnKy0tTWVlZT02IAAgXKfhtixLgwcPliRt27ZN06ZNU0FBgebNm6ePP/64p+YDAHxPp+Fub29XW1ubJOntt9/W2LFjQ9+zLMv+yQAAEXX6y8nCwkLdcsstGjJkiPr166fLLrtM0nd39EtLS+uxAQEA4ToNd2lpqcaNG6fm5mZdddVVobe9t7e3a8mSJT02IAAgXJcvBxw9enSHbcOGDbNrFgBADGL6sGAAQO9BuAHAMIQbAAxDuAHAMIQbAAxDuAHAMIQbAAxDuAHAMIQbQJf+c88inB6n43hG/SAFAGc2p9OpZcuWxXuMhLF06dJT3gdn3ABgGMINAIYh3ABgGMINAIYh3ABgGMINAIYh3ABgGMINAIYh3ABgGMINAIYh3ABgGMINAIYh3ABgGMINAIYh3ABgGFvDXVtbq4KCAuXn56uioqLD9zdv3qyioiIVFRXppptu0p49e+wcBwASgm3htixL5eXlWrNmjaqqqrR161bt378/bM3555+v9evXa8uWLSotLdWSJUvsGgcAEoZt4fb5fMrMzFRGRoaSk5NVWFio6urqsDU/+clPNGjQIEnS6NGj1dTUZNc4AJAwbAu33++X2+0OPXa5XPL7/Z2u37hxo66++mq7xgGAhGHbZ04Gg8EO2xwOR8S1u3bt0saNG7Vhw4ao+w0EAqqvr49phpycnJjWIXaxHvtY8RydfjxHvd+pNsy2cLvd7rBLH36/X+np6R3W7dmzR4sXL9azzz6rIUOGRN1vSkoK/yPFEce+9+M56v1O9Tmy7VJJbm6uGhoa1NjYqNbWVlVVVcnj8YSt+eyzz3TnnXfqkUce0bBhw+waBQASim1n3E6nU2VlZSopKZFlWSouLlZ2drYqKyslSV6vV0899ZS+/vprLVu2TJKUlJSkV155xa6RACAh2BZuScrLy1NeXl7YNq/XG/p6xYoVWrFihZ0jAEDC4Z2TAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhrE13LW1tSooKFB+fr4qKio6fP/AgQOaNm2aRo0apeeee87OUQAgYTjt2rFlWSovL9fatWvlcrk0depUeTweZWVlhdYMHjxYixYtUnV1tV1jAEDCse2M2+fzKTMzUxkZGUpOTlZhYWGHQA8dOlQ//vGP5XTa9u8HACQc24rp9/vldrtDj10ul3w+3ynvNxAIqL6+Pqa1OTk5p/zzEC7WYx8rnqPTj+eo9zvVhtkW7mAw2GGbw+E45f2mpKTwP1Iccex7P56j3u9UnyPbLpW43W41NTWFHvv9fqWnp9v14wDgjGFbuHNzc9XQ0KDGxka1traqqqpKHo/Hrh8HAGcM2y6VOJ1OlZWVqaSkRJZlqbi4WNnZ2aqsrJQkeb1eNTc3q7i4WEePHlWfPn30wgsvaNu2bUpLS7NrLAAwnq0v58jLy1NeXl7YNq/XG/r6nHPOUW1trZ0jAEDC4Z2TAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhiHcAGAYwg0AhrE13LW1tSooKFB+fr4qKio6fD8YDGr58uXKz89XUVGR6urq7BwHABKCbeG2LEvl5eVas2aNqqqqtHXrVu3fvz9sTW1trRoaGrRjxw49+OCD+v3vf2/XOACQMGwLt8/nU2ZmpjIyMpScnKzCwkJVV1eHramurtbkyZPlcDg0evRoHT58WIcOHbJrJABICE67duz3++V2u0OPXS6XfD5fl2vcbrf8fr/S09M73W8gEFB9fX3Mc9x4443dmBpd6c5x7w6eo9OH56j3685z5HQ6lZ2d3XH76RzovwWDwQ7bHA5Ht9d83+jRo09pLgAwnW2XStxut5qamkKPI51Jf39NU1NTl2fbAAAbw52bm6uGhgY1NjaqtbVVVVVV8ng8YWs8Ho9effVVBYNBvf/++zrrrLMINwBEYdulEqfTqbKyMpWUlMiyLBUXFys7O1uVlZWSJK/Xq7y8PO3cuVP5+fnq37+/Vq5cadc4AJAwHMFIF5oBAL0W75wEAMMQbgAwjG3XuBHdwoUL9eabb2ro0KHaunVrvMfB93z++ee677779MUXX6hPnz668cYbdeutt8Z7LHxPIBDQ9OnT1draKsuyVFBQoLvuuiveY9mKa9xx9O6772rAgAFasGAB4e6FDh06pObmZo0cOVJHjx5VcXGxnnrqKWVlZcV7NPyXYDCo48ePKzU1VSdPntTNN9+sRYsWJfR7PrhUEkeXX365Bg0aFO8x0In09HSNHDlSkpSWlqbhw4fL7/fHeSp8n8PhUGpqqiSpra1NbW1tUd/IZzrCDcTg008/VX19vS655JJ4j4IILMvSpEmTdOWVV+rKK69M+OeJcANRHDt2THfddZceeOABpaWlxXscRJCUlKRNmzZp586d8vl82rt3b7xHshXhBrpw8uRJ3XXXXSoqKtKECRPiPQ6iGDhwoH7605/q73//e7xHsRXhBjoRDAa1aNEiDR8+XLNmzYr3OOhES0uLDh8+LEk6ceKE3nrrLQ0fPjzOU9mLV5XE0d1336133nlHX331lYYOHao777xTv/71r+M9Fv6f9957T9OnT9cFF1ygPn2+O8e5++67lZeXF+fJ8N/27Nmj+++/X5ZlKRgM6tprr9WcOXPiPZatCDcAGIZLJQBgGMINAIYh3ABgGMINAIYh3ABgGMINYzU3N2v+/Pm65pprdP311+v222/XRx991On6Tz/9VDfccEPE7y1atEj79+8/5Zk8Ho9aWlpOeT9AV7itK4wUDAY1Z84cTZ48WY8//rgkqb6+Xl9++aWGDRvW7f2tWLHidI8I2IZww0i7du2S0+mU1+sNbcvJyZH03b1FZs+ercOHD6utrU1z587VNddcI+m7u8ctWLBAH374oYYNG6aHH35Y/fv314wZM3TfffcpNzdXl156qWbOnKm//e1v6tevn55++mmdffbZYT//2LFjWr58uT744ANJ0pw5c1RQUBC2Zvbs2WpqalIgENDMmTM1bdo0WZalRYsW6YMPPpDD4VBxcbFuu+02vfjii3rppZeUlJSkrKys0D9GQCSEG0bat29f6Jar35eSkqKnnnpKaWlpamlp0bRp0zR+/HhJ0kcffaQVK1ZozJgxWrhwoTZs2KDf/OY3YX/++PHjuuSSSzR//nw98sgjevnllzV79uywNU8//bTS0tK0ZcsWSdI333zTYY6VK1dq8ODBOnHihKZOnaoJEybo4MGD8vv9ofuv/+et2hUVFaqpqVFycnJoG9AZrnEj4QSDQa1atUpFRUWaNWuW/H6/vvjiC0nSD3/4Q40ZM0aSNHHiRP3zn//s8Of79u2rX/7yl5KkUaNG6eDBgx3WvP3225o+fXrocaT7qq9bt04TJ07UjTfeqM8//1wff/yxMjIy1NjYqAcffFC1tbWhuw1eeOGFuueee7Rp0yYlJSWd+kFAQiPcMFJ2drbq6uoifm/Lli1qaWnRK6+8ok2bNunss89WIBCQpA432I90w/2+ffuGtvfp00eWZXVYEwwGu7xZ/+7du/XWW2/pz3/+szZv3qyLL75YgUBAgwYN0qZNm3TFFVdow4YNWrRokaTvzrhvvvlm1dXVacqUKWpra4vtQOCMRLhhpLFjx6q1tVUvv/xyaJvP59M777yjI0eOaOjQoerbt6927doVdsb82Wef6V//+pckqaqqKnT23V1XXXWV1q9fH3r8/UslR44c0aBBg9S/f38dOHBA77//vqTv7mQXDAZVUFCguXPn6sMPP1R7e7s+//xzjR07Vvfee6+OHDmi48eP/09z4czANW4YyeFwaPXq1Vq5cqUqKiqUkpKi8847Tw888ICysrJUWlqqKVOmKCcnJ+wWnyNGjNBf/vIXlZWV6Uc/+lHYLze7o7S0VOXl5brhhhvUp08fzZkzJ+x+3VdffbVeeuklFRUVadiwYaHPPzx06JAWLlyo9vZ2Sd/dbdCyLN177706evSogsGgbrvtNg0cOPB/PzhIeNwdEAAMw6USADAM4QYAwxBuADAM4QYAwxBuADAM4QYAwxBuADDM/wFSVEdFS6WcVAAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "with sns.axes_style(\"whitegrid\"): # context manager for styling the figure\n", " \n", @@ -206,40 +180,40 @@ "source": [ "* When your data consists of only **1 categorical variable**, such as\n", "\n", - "| ID | variable 1 | variable 2 | variabel ... | \n", - "|------------|-------------| ---- | ----- |\n", - "| 1 | 0.2 | 0.8 | ... |\n", - "| 2 | 0.3 | 0.1 | ... |\n", - "| 3 | 0.9 | 0.6 | ... |\n", - "| 4 | 0.1 | 0.7 | ... |\n", - "| ... | ... | ... | ...|\n", + " | ID | variable 1 | variable 2 | variabel ... | \n", + " |------------|-------------| ---- | ----- |\n", + " | 1 | 0.2 | 0.8 | ... |\n", + " | 2 | 0.3 | 0.1 | ... |\n", + " | 3 | 0.9 | 0.6 | ... |\n", + " | 4 | 0.1 | 0.7 | ... |\n", + " | ... | ... | ... | ...|\n", "\n", - "the added value of using Seaborn approach is LOW. Pandas `.plot()` will probably suffice.\n", + " the added value of using Seaborn approach is LOW. Pandas `.plot()` will probably suffice.\n", "\n", "* When working with **timeseries data** from sensors or continuous logging, such as\n", "\n", - "| datetime | station 1 | station 2 | station ... | \n", - "|------------|-------------| ---- | ----- |\n", - "| 2017-12-20T17:50:46Z | 0.2 | 0.8 | ... |\n", - "| 2017-12-20T17:50:52Z | 0.3 | 0.1 | ... |\n", - "| 2017-12-20T17:51:03Z | 0.9 | 0.6 | ... |\n", - "| 2017-12-20T17:51:40Z | 0.1 | 0.7 | ... |\n", - "| ... | ... | ... | ...|\n", + " | datetime | station 1 | station 2 | station ... | \n", + " |------------|-------------| ---- | ----- |\n", + " | 2017-12-20T17:50:46Z | 0.2 | 0.8 | ... |\n", + " | 2017-12-20T17:50:52Z | 0.3 | 0.1 | ... |\n", + " | 2017-12-20T17:51:03Z | 0.9 | 0.6 | ... |\n", + " | 2017-12-20T17:51:40Z | 0.1 | 0.7 | ... |\n", + " | ... | ... | ... | ...|\n", "\n", - "the added value of using a grammar of graphics approach is LOW. Pandas `.plot()` will probably suffice.\n", + " the added value of using a grammar of graphics approach is LOW. Pandas `.plot()` will probably suffice.\n", "\n", "* When working with different experiments, different conditions, (factorial) **experimental designs**, such as\n", "\n", - "| ID | origin | addition (ml) | measured_value | \n", - "|----|-----------| ----- | ------ |\n", - "| 1 | Eindhoven | 0.3 | 7.2 |\n", - "| 2 | Eindhoven | 0.6 | 6.7 |\n", - "| 3 | Eindhoven | 0.9 | 5.2 |\n", - "| 4 | Destelbergen | 0.3 | 7.2 |\n", - "| 5 | Destelbergen | 0.6 | 6.8 |\n", - "| ... | ... | ... | ...|\n", + " | ID | origin | addition (ml) | measured_value | \n", + " |----|-----------| ----- | ------ |\n", + " | 1 | Eindhoven | 0.3 | 7.2 |\n", + " | 2 | Eindhoven | 0.6 | 6.7 |\n", + " | 3 | Eindhoven | 0.9 | 5.2 |\n", + " | 4 | Destelbergen | 0.3 | 7.2 |\n", + " | 5 | Destelbergen | 0.6 | 6.8 |\n", + " | ... | ... | ... | ...|\n", "\n", - "the added value of using Seaborn approach is HIGH. Represent your data [`tidy`](http://www.jeannicholashould.com/tidy-data-in-python.html) to achieve maximal benefit!\n", + " the added value of using Seaborn approach is HIGH. Represent your data [`tidy`](http://www.jeannicholashould.com/tidy-data-in-python.html) to achieve maximal benefit!\n", "\n", "* When you want to visualize __distributions__ of data or __regressions__ between variables, the added value of using Seaborn approach is HIGH." ] @@ -271,7 +245,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -324,7 +298,7 @@ "| Works well with Pandas | Works well with Pandas |\n", "| Built on top of [Matplotlib](https://matplotlib.org/) | Built on top of [Vega-lite](https://vega.github.io/vega-lite/) |\n", "| Python-clone of the R package `ggplot` | Plot specification to define a vega-lite 'JSON string' |\n", - "| Static plots | Web/interactive plots |\n" + "| Static plots | Web/interactive plots |" ] }, { @@ -347,30 +321,9 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import plotnine as p9\n", "\n", @@ -394,32 +347,9 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import plotnine as p9\n", "\n", @@ -448,22 +378,9 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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FCxeuBlZ3ut3w8PA9ADNmzLjHoXP1Qrt+ZF/rTsOpw1Uet3zd9LeI2AX4D2B7YAHwypTS6eNs8wKqP9yfBgwB/5VSOm4CpQ+U/a1z/myb+qbCDTMA7wAScBNwJnBoWZbnAhRFcXdRFDsDlGX5AFAAL6QavfsmcHBZlp5GkaSpZy7VjBjvzGkcEY8FfggsB7YDPg4cExGv7luFkjo28JFHgHranb3arNug6flvgZ0noSxJ0gSklM6kGhAgIusytLcDf0opHVQ/vyYidgDeC/x3P2qU1LkpER4lSQJ2BM5qWvZjYP+ImJ1SGm7eICJazYzxCOCO/pTYmQMPPHDekiVL+PznPz/v6KOPHnQ508L5558/d5tttuGqq66au2jRIu/s79w8YCillPr1AoZHSdJUsTlwS9OyW6h+V21KdWlTs65mxpgsRx99NHVo9G7rTIsWLRr90kvSurcl8Jd+7dzwKEmaSppHS6LN8lHNM2PMA27885//zIYbOmildctdd93Fox/9aOjznf2GR0nSVHEz1ehjo82AB4DbW22QUnrIzBij11ZuuOGGhkepT6bK3daSJF0C7Na07MXAZa2ud5Q0GIZHSVJfRMQGEbFtRGxbL3ps/Xyrev2yiDi5YZPjgMdExJER8ZSI2A/YH/jk5FYuaSyetpYk9csOPPSjY0evTfwK1YdBLAC2Gl2ZUro+IvYAPk01/+8Q8O6UktP0SFOI4VGS1BcppfMZ43OGU0qLWyy7AHhW/6qSNFGetpYkSVI2w6MkSZKyGR4lSZKUzfAoSZKkbIZHSZIkZTM8SpIkKZvhUZIkSdkMj5IkScpmeJQkSVI2w6MkSZKyGR4lSZKUzfAoSZKkbIZHSZIkZTM8SpIkKZvhUZIkSdkMj5IkScpmeJQkSVI2w6MkSZKyGR4lSX0TEQdExPURcV9EXB4RO4/Tft+IuDIi7o2ImyLixIjYZLLqlTQ+w6MkqS8iYm/gKOBwYDtgOXBmRGzVpv3zgZOBE4CnAXsBzwa+NBn1SspjeJQk9cvBwAkppS+llK5JKR0E/BlY0qb9c4E/ppSOSSldn1L6H+ALwA6TU66kHIZHSVLPRcR6wPbAWU2rzgJ2arPZxcCWEbFHVB4FvAb4wRivMyciNhx9APN6UL6kMRgeJUn9sCkwE7ilafktwOatNkgpXQzsC5wG3A/cDKwE3jXG6xwC3NnwuHEiRUsan+FRktRPqel5tFhWrYh4KnAM8J9Uo5YvAR4LHDfG/pcBGzU8tpxgvZLGMWvQBUiS1kq3ASOsOcq4GWuORo46BLgopfT/6ue/ioh7gOUR8aGU0k3NG6SUVgOrR59HxIQLlzQ2Rx4lST2XUrofuBzYrWnVblTXNrbycODBpmUj9b+mQmmKcORRktQvRwJfjYjLgEuAtwJbUZ+GjohlwBYppTfV7b8PfDEilgA/BhZQTfXzs5TS0CTXLqkNw6MkqS9SSqfVE3wfShUErwL2SCndUDdZQBUmR9ufFBHzgHcCn6K6WeZc4P2TWbeksRkeJUl9k1I6Fji2zbrFLZZ9BvhMn8uSNAFe8yhJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm59t3cbw8PACYEEXmz559N/h4eEeVqR11fDw8LParLKvdWHjjTeeu2rVKubNm/fM4eHhewZdzzQyLfrb+eefP3fRokWDLkNaqxke23sbcNgEtv9arwrROu/ycdbb1zowa9YsNt54Y4ALB13LNDWl+9s222wz6BKktZ7hsb0vAGUX2z2Z6ofrvsBv27QZLwxIjbZvszynr6nJAw88MHfVqlUXzps3b5dZs2Y58phvWvS3q666ai7+YSD1leGxjdmzZ98E3NTpdg2nc347e/bsX/S0KK2T2vUj+1p3VqxYsSHAX//61ysXLlx416DrmS6mS39btGjRhoOuQVrbecOMJEmSshkeJUmSlM3wKEmSpGyGR0lS30TEARFxfUTcFxGXR8TO47SfExGHR8QNEbE6Iq6LiP0mq15J4/OGGUlSX0TE3sBRwAHARVRToJ0ZEU9NKf2pzWbfBB4F7A/8AdgMf1dJU4r/ISVJ/XIwcEJK6Uv184MiYndgCXBIc+OIeAnwAuBxKaU76sV/nIxCJeXztLUkqeciYj2qOUrPalp1FrBTm80K4DLgfRHxl4j4fUR8MiIeNsbrzImIDUcfwLxe1C+pPUceJUn9sCkwE7ilafktwOZttnkc8HzgPuCV9T6OBR4BtLvu8RAm9mlgkjrkyKMkqZ9S0/NosWzUjHrdvimln6WUfkh16nvxGKOPy4CNGh5bTrxkSWNx5FGS1A+3ASOsOcq4GWuORo66CfhLSunOhmXXUAXOLYFrmzdIKa0GVo8+j4gJlCwphyOPkqSeSyndD1wO7Na0ajfg4jabXQQsjIgNGpY9EXgQuLHnRUrqiiOP0lpsn332aXd6UHDn+E3WLaeeemqvh+2OBL4aEZcBlwBvBbYCjgOIiGXAFimlN42WAHwYODEiDqO65vH/AV9OKf2tx7VJ6pLhUZLUFyml0yJiE+BQYAFwFbBHSumGuskCqjA52v7uiNgN+AzVXde3U837+KFJLVzSmAyPkqS+SSkdS3XHdKt1i1ss+y1rnuqWNIV4zaMkSZKyGR4lSZKUzfAoSZKkbIZHSZIkZTM8SpIkKZvhUZIkSdkMj5IkScpmeJQkSVI2w6MkSZKyGR4lSZKUzfAoSZKkbIZHSZIkZTM8SpIkKZvhUZIkSdkMj5IkScpmeJQkSVI2w6MkSZKyGR4lSZKUzfAoSeqbiDggIq6PiPsi4vKI2Dlzu+dFxAMRcUWfS5TUIcOjJKkvImJv4CjgcGA7YDlwZkRsNc52GwEnAz/pd42SOmd4lCT1y8HACSmlL6WUrkkpHQT8GVgyznZfAE4FLhnvBSJiTkRsOPoA5k20aEljMzxKknouItYDtgfOalp1FrDTGNu9BXg88JHMlzoEuLPhcWPHxUrqiOFRktQPmwIzgVualt8CbN5qg4j4J+AIYN+U0gOZr7MM2KjhsWVX1UrKNmvQBUiS1mqp6Xm0WEZEzKQ6VX1YSun32TtPaTWwumE/XZYpKZfhUZLUD7cBI6w5yrgZa45GQnWt4g7AdhHx2XrZDCAi4gHgxSmlc/tVrKR8nraWJPVcSul+4HJgt6ZVuwEXt9jkLuDpwLYNj+OA39Vf/7QvhUrqmCOPkqR+ORL4akRcRnXn9FuBrahCIRGxDNgipfSmlNKDwFWNG0fErcB9KaWrkDRlGB4lSX2RUjotIjYBDgUWUIXDPVJKN9RNFlCFSUnTiOFRktQ3KaVjgWPbrFs8zrZLgaU9L0rShHjNoyRJkrIZHiVJkpRtSpy2LopiPnA88FKqO+4OL8uy5WmOhm0WAycCS8qyPK7fNUqSJGnqjDx+lirILgReBny0KIpd2zUuimIT4P/SdGeeJEmS+mvg4bEoirnAXsCHyrJcVZblL4GTgP3G2OxTwCeB2/tfoSRJkkYNPDwCTwSiLMurG5ZdAWzTqnFRFIvqbU7oe2WSJEl6iKlwzeMGVNc5NlpJ9VFVD1EUxRzgc8AbyrJMRVH0raihoaE5wJxOt5s/f/7cmTNnMjIyMnfFihUb9qE0rWOGhoZa9iP7mnqtXV+D6dPfDjzwwHlHH330oMuQ1mpTITzeDTT/INoIWNWi7fuBc+pT2/12CHBYpxutXLly9MsLe1mM1ml3tlpoX1MftOxrMH3625IlSzA8Sv01FcLj74FUFMVTyrK8pl62La1vhnkhsG1RFPvWzzcCdiiKYqeyLN/U47qWUX20Vkfmz5//zJkzZ144MjKyy8qVK69s06ztD2iphY1aLbSvqQ9a9jXI7m8D9/nPf34ecOOg65DWZgMPj2VZ3lMUxbep7rB+C/A4YDHw2hbN9+Khp5K/BXwP+GKv61q4cOFqYHWn2w0PD98DMGPGjHsWLlzYfDpe6li7fmRfU6+N1Y+mS39z1FHqv4GHx9o7qALgTVTXPx5aluW5AEVR3A28tCzL5WVZrmjcqCiK1cDKsiy961qSJGkSTInwWJblSqpRxVbrNhhju0V9KkmSJEktTIWpeiRJkjRNGB4lSZKUzfAoSZKkbIZHSZIkZTM8SpIkKZvhUZLUNxFxQERcHxH3RcTlEbHzGG1fFRFnR8SKiLgrIi6JiN0ns15J4zM8SpL6IiL2Bo4CDge2A5YDZ0bEVm022QU4G9gD2B44D/h+RGzX/2ol5ZoS8zxKktZKBwMnpJS+VD8/qB5JXAIc0tw4pXRQ06IPRMSewMuBX/azUEn5ssNjRDwIpNz2KaWZXVUkSZr2ImI9qtHDI5pWnQXslLmPGcA84I4x2szhoR9bO6+zSiV1qpORx/fxj/A4C3gnMEL12dK3AJsDe1KdCv9MD2uUJE0/mwIzqX4/NBr9fZHjPcBc4JtjtDkEOKzj6iR1LTs8ppQ+Ofp1RHwCuAJ4RUpppGH5v1OFyUf2sEZJ0vTVfMYqWixbQ0S8HlgK7JlSunWMpsuAIxuezwNu7LBGSR3o9oaZxcDnGoMjQP38c8CbJ1iXJGl6u43q7FTzKONmrDka+RD1jTYnAK9NKZ0zVtuU0uqU0l2jD2DVBGqWlKHb8PgwYOs267YG1u9yv5KktUBK6X7gcmC3plW7ARe3264ecTwJ2Cel9IO+FSipa93ebX068ImI+BtwekrpzojYCHgl1SmE03tTniRpGjsS+GpEXAZcArwV2Ao4DiAilgFbpJTeVD9/PXAycCBwaUSMjlr+LaV052QXL6m1bsPjO4CHA18GvhwRw8Dset3pVDfTSJLWYSml0yJiE+BQYAFwFbBHSumGuskCqjA56m1Uv5c+Vz9GfYXqcilJU0BX4TGltAp4TUQ8GfhnqmtabgJ+nlK6pof1SZKmsZTSscCxbdYtbnq+aBJKkjRBE5okPKX0W+C3PapFkiRJU1zXH08YEbMj4u0RcUJEnBUR/1Qv3zsintK7EiVJkjRVdDXyGBGPA86hms/xSmBH/jGr/y7AS4C39KJASZIkTR3djjweA6wAHgssopr0ddQFVAFSkiRJa5lur3lcBLw+pXRbRDR/hvXNVHfQSZIkaS3T7cjjAzx0tLHRo4C7u9yvJEmSprBuw+MFwHsiYnbDshQRQTUJ7E8mXJkkSZKmnG5PW7+f6uOlrgG+R/Uh9+8AtgH+CXhOT6qTJEnSlNLVyGM9v+P2wEXA64ER4GXAH4DnpJSu61mFkiRJmjK6niQ8pXQ98OYe1iJJkqQprquRx4g4IiKe0etiJEmSNLV1e8PMW4BfRsTVEfHBiHh8L4uSJEnS1NRteFxA9SkylwLvAX4fET+LiAMjwjkeJUmS1lLd3jDzYErp7JTSflTzOr4KuA74GPDniHCqHkmSpLVQtyOPf5dSGk4pfQ/YF3gj1SfMLJrofiVJkjT1dH239aiIeB7VdD2vAR4JXAEcNdH9SpIkaerpKjxGxHZUgXFvYEuq+R2PA76eUvpd78qTJEnSVNLtyOPlwF+A06gC4+W9K0mSJElTVbfXPO4KbJVSeq/BUZLUTkQcEBHXR8R9EXF5ROw8TvsX1O3ui4j/jYi3T1atkvJ0e7f1BSml1OtiJElrj4jYm+oa+MOB7YDlwJkRsVWb9o8Ffli32w74OHBMRLx6UgqWlCX7tHVElMB7UkrX1l+PJaWU9pxYaZKkae5g4ISU0pfq5wdFxO7AEuCQFu3fDvwppXRQ/fyaiNgBeC/w3/0uVlKeTq55nAfMrL/eEHDkUZLUUkSsB2wPHNG06ixgpzab7Vivb/RjYP+ImJ1SGm7xOnOAOQ2L5gHcdddd3ZQtTWuT1e+zw2NKadeGrxf1pRpJ0tpiU6oBh1ualt8CbN5mm83btJ9V7++mFtscAhzWvPDRj350J7VKa5tHAH1Lkt1O1fPklNJve12MJGmt03yWKlosG699q+WjlgFHNjyfB9xINY3cqswa++bAAw+ct2TJkhs///nPb3n00Ufn1DOl6u/ChOs///zzn7nNNttceNVVV+2yaNGiK3ta3fjWluN/Rz9fpNupeq6OiCuBU4FvpJT+3MOaJEnT323ACGuOMm7GmqOLo25u0/4B4PZWG6SUVgOrR59HjGZNVqWUBn7uemhoCID3ve99q4466qhx65lq9XeqF/UPDw/fA7DTTjvdM9nHYC06/n3V7VQ9ewK/AT4MXB8RyyNiSURs2rvSJEnTVUrpfqo5gXdrWrUbcHGbzS5p0f7FwGWtrneUNBjdTtXz/ZTSG6j+ItwHWEF12mAoIs6MiDf2sEZJ0vR0JPBvEbFfRDwlIj4NbEX1iWRExLKIOLmh/XHAYyLiyLr9fsD+wCcnvXJJbXU78ghASum+lNI3U0qvogqSbwOeDpzUg9okSdNYSuk04CDgUOAKYBdgj5TSDXWTBVRhcrT99cAewKK6/YeBd6eUOpmmZzXwERpOZU8z1j9Y1p+h22seH6Keh+t1VJ91vZDqlLYkaR2XUjoWOLbNusUtll0APGsCr7caWNrt9oNm/YNl/Xm6Do8R8VTg9VSB8QnADcApwKkppV/3pjxJkiRNJd1O1fMr4GlU1zp+C3hzSumSXhYmSZKkqafbkcfLgfcAP0kpPdjDeqaM4eHhBVTX43TqyaP/Dg97c6Ambnh4uN0pPPuaemqMvgb2t65svPHGc1etWsW8efOeOToFjcY1ob42e/bsX/S2HDXrODxGxPrAJsD9a2twrL2NFp9a0IGv9aoQrfMuH2e9fU29Ml5fA/tbR2bNmsXGG28McOGga5mGuu1rkzPZ4Tqs4/CYUrovIl4AfLoP9UwlXwDKLrZ7MlWH3xdo9yk8OT+gpVHbt1luX1OvtetrkNff+uL5z3/+XldeeeWb7r///k0f/vCHX7fXXnt96vjjj/9lu/b777//s77zne8cfO+99z5+vfXWW7Htttt+Zfny5Q+5Y7soihdecMEFB9x3331brr/++jfuuuuunzv99NPP63XtDzzwwNxjjjnmwqVLl960evXqTcarf88999z1kksu2evuu+9+0oMPPjh77ty5/7v77rt/4dRTT/37pWEvetGLXr58+fKlzdteffXVOz7hCU+4v9fvoZPjv99++21/yimnHN+8fOnSpa/+wAc+8MfR5+Mc/572tYg4APgPqrOJvwEOSiktb9P2JODNLVZdnVJ6Wt1mMXBiizYPSyndN9F6G2rZharu7alqf2VK6fRxtnkB1RRZTwOGgP9KKR3X1ObVwEeBxwPXAR9MKX23o9pSGutTotoW9y3g2pTSBzreeC1Xn/a5HNi+3dD5Pvvs0/lB1zrr1FNPbflXtH1Nvdaur0Fef+uHiNgb+CpwAHAR1VmhfwOemlL6U4v2jwWuAr5INQjwPKq7vV8/OuVPROwILKeaCui7wCuB/wSen1L6aS/r32yzzRavXLnyxHnz5r3rjjvu+ElG/UdR/dI/D1gJvAV4L/DPKaVf1m0WA0cDT2rcNqV0cy9rr1+r0+O/qK79STz0s5VXpJRG6jZjHv9e9rUu6t8IeFjDolnAlcBnUkpL6zaLmYTjHxEvpeq/vwD+m3HC42T2/W6veTwROC4iNgDOBG6l6XNHU0pecyBJmqiDgRNSSl+qnx8UEbsDS4BDWrR/O/CnlNJB9fNr6unk3kv1CxiquSfPTiktq58vq0dsDqKaRaRn7rjjjnfus88+HHHEEScvXLjwrvHqb6h71AciYk/g5cAvH9q092GxhU6P/6hbU0or26w7iEk6/nRYf0rpTuDO0ecR8QpgY9Ycaez78U8pnUmVsXI/dnDS+n63k4SfQfWh4e8EfgD8DPh5/bis/leSpK5FxHpUp+zOalp1FrBTm812bNH+x8AOETF7nDbt9tmViFhvZGRk2xe84AXNq8aqv3kfM4B5wB1NqzaIiBsi4saIOCMitpt4xWu8djfHf9QvI+KmiPhJROzatG7Sjj/d1z9qf+CchontR/X9+Hdh0vp+tyOPzR1BkqRe2xSYCdzStPwWYPM222zepv2sen83jdGm3T67tSkwc9NNN21e3slrvQeYC3yzYdlvgcXAr4ENgQOBiyLimSmlaydScJNujv9NwFupTjvPAd4I/CQiFqWURm8amtTj3+1rRcQC4KVUH8PcaLKOf6cmre93FR7rTwCQJGkyNF+7Gy2Wjde+eXmn++xai1OOWa8VEa+n+rSQPVNKt44uTyldClza0O4iquvi3gW8e+IVryH7WKWUfgf8rmHRJRHxaKpTp413nE/a8Z/Aay2muu709IfsbPKPfycmpe9P6LOtJUnqo9uAEdYcFdmMNUdPRt3cpv0DwO3jtGm3z27dBoysWLGiefm4r1Xf6HEC8NqU0jljta2nzfs58E/dl9pSN8e/lUt5aG2Tevy7ea2oEv9+wFdTSmPewd7H49+pSev7XYXHiHgwIkbGenSzX0mSRtW/tC8HdmtatRtwcZvNLmnR/sXAZSml4XHatNtnV1JK98+cOfOKCy9cY4rHseofHXE8CdgnpfSD8V6nDjrbUp2W7Jkuj38r2/HQ2ibt+NN9/S+g+ujlE8Z7nX4d/y5MWt/v9prH97HmEOcj6oIeBXymy/1KktToSOCrEXEZ1S++twJbAccBRMQyYIuU0pvq9scB74yII6mmLNmR6qaHxjtJjwYujIj3A98D9gT+BXh+r4t/xCMe8dmvf/3rJ55xxhlvuOOOO84br/46OJ5MdR3dpRExOkr0t/pOYCLiMKrRvGuprrl7N1V4eUev66fD4x8RBwF/pJpPcT3gDcCr68eoSTv+ndbfYH/gpymlq5p3OFnHv57R5gkNix4bEdsCd6SU/jTIvt/tNY+fbLPqgxFxCtXBlCRpQlJKp0XEJsChVBMlXwXs0XD36wKqMDDa/vqI2IPqgyzeQTVn4rtH57mr21wcEa8DPkY1WfJ1wN69nuMR4IorrvjOSSeddOKHPvSh99c1jVk/1TyEs4DP1Y9RX6G6Bg9gPnA81enHO6mm8NklpfSzXtff6fGnCoyfBLYA/kYVIv81pfTDhn1O2vHvov7RuR5fTRXgW5nP5Bz/HajmzBx1ZP3vaF8YWN/vapLwMXcY8WLg5JRSr++amhacuFm95iThmixTcZLw6W5oaGhDqoCxUT3Po8ZhX5v6+nHDzBOpbo2XJEnSWqar09YRcXCLxesBTwH2Ak6dSFGSJEmamrq9YabVNY+rgRupLsb8aNcVSZIkacrq9oYZ54eUJElaBxkCJUmSlC07PEbEphHxjBbLnxER346I39QfgP7y3pYoSZKkqaKTkcdlVDPe/11EPAZYTjXJ5N+AbYDvRsQuvSpQkiRJU0cn4fF5wNealv07sAHVBKA7AFtTzbr+/p5UJ0mSpCmlk/C4BdXM7I1eDlyRUjoLIKX0N6qPJlzj9LYkSZKmv07CY6Lh86wj4lHAY4ELmtr9Bdh04qVJkiRpqukkPP6O6sOzR72MKkye1dRuAbBignVJkiRpCupknsdjgJMjYmPgZmAJ8AfgnKZ2uwO/7k15kiRJmkqyw2NK6WsR8WjgncB8qg8tPyCl9MBom4jYjOo6yMN6XKckSZKmgI4+YSaldARwxBjrbwUeNdGiJEmSNDX5CTOSJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGwd3W0tSVI7++yzTxq/1TrrzkEXMNWceuqpMega1B1HHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpRt1qALACiKYj5wPPBS4C7g8LIsj23R7rnAR4Ad6kWXAgeVZXntJJUqSZK0TpsqI4+fpQqyC4GXAR8timLXFu02Br4MPA5YAFwFlJNVpCRJ0rpu4COPRVHMBfYCtivLchXwy6IoTgL2A85rbFuW5ZlN234KeF9RFJuUZXn7JJUsSZK0zpoKI49PBKIsy6sbll0BbJOx7QuAmw2OkiRJk2PgI4/ABlTXOTZaCcwba6OiKB5Hdbr7Xf0oamhoaA4wp9Pt5s+fP3fmzJmMjIzMXbFixYZ9KE3rmKGhoZb9yL6mXmvX18D+pt7r18+2hQsXNmcK9dhUCI93A82dYyNgVbsNiqLYEjgbOKIsy2/2qa5DgMM63WjlypWjX17Yy2K0Truz1UL7mvqgZV8D+5v6ol8/26LL7ZRpKoTH3wOpKIqnlGV5Tb1sW6qbYdZQFMUWVNdCfrEsy0/3sa5lwJGdbjR//vxnzpw588KRkZFdVq5ceWWbZm1/QEstbNRqoX1NfdCyr4H9TX0xkZ9tGqCBh8eyLO8piuLbVHdYv4XqTurFwGub2xZFsRA4HzilLMsj+lnXwoULVwOrO91ueHj4HoAZM2bc49C5eqFdP7KvqdfG6kf2N/WaP9umr4GHx9o7gC8CN1Fd/3hoWZbnAhRFcTfw0rIslwP/B3gC8B9FUfxHw/ZPLcvyT5NcsyRJ0jpnSoTHsixXUk3X02rdBg1ff4RqknBJkiQNwFSYqkeSJEnThOFRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRshkdJkiRlMzxKkiQpm+FRkiRJ2QyPkiRJymZ4lCRJUjbDoyRJkrIZHiVJkpTN8ChJkqRsswZdwFQ1PDy8AFjQxaZPHv13eHi4hxVpXTU8PPysNqvsa+qpMfoa2N/UY/362TZ79uxfdF2Ushge23sbcNgEtv9arwrROu/ycdbb19Qr4/U1sL+pd/r1sy263E6ZDI/tfQEou9juyVQdfl/gt23a5PyAlkZt32a5fU291q6vgf1NvTeRn20aIMNjG7Nnz74JuKnT7RqG2H/r0Ll6oV0/sq+p18bqR/Y39Zo/26Yvb5iRJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCnbrEEX0KmiKOYDxwMvBe4CDi/L8tiBFiVJkrSOmI4jj5+lCr0LgZcBHy2KYtfBliRJkrRumFYjj0VRzAX2ArYry3IV8MuiKE4C9gPOG2RtkiRJ64JpFR6BJwJRluXVDcuuAA7u9QsNDQ3NAeZ0ut38+fPnzpw5k5GRkbkrVqzYsNd1ad0zNDTUsh/Z19Rr7foa2N/Ue/362bZw4cK7Jl6dxhIppUHXkK0oip2B75ZluWnDspcDny7L8gm9fK2hoaGlwGG93KckSeqvhQsXxqBrWNtNt5HHu4Hmv0I2Alb14bWWAUd2utH8+fOfOXPmzAtHRkZ2Wbly5ZV9qGttNQ+4EdiS/nw/1zr2ta7Z17pgf+ua/a1D9rWpb7qFx98DqSiKp5RleU29bFvgql6/0MKFC1cDqzvdbnh4+B6AGTNm3OPQeb6hoaHRL1d53PLY17pjX+uO/a079rfO2demvml1t3VZlvcA36a6w3peURTPBBYDJw60MEmSpHXEtAqPtXcACbgJOBM4tCzLcwdbkiRJ0rphup22pizLlVTT9UiSJGmSTceRR0mSJA2I4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKFimlQdcgSZKkacKRR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKEmSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElStlmDLkDrtqIo3gksBp4OfLcsy9cNtiKtrYqimAN8DngRsCnwJ+DjZVl+baCFaa1VFMXxwL8C84A7gOPLsvz4YKuSJs6RRw3aEPAx4IuDLkRrvVlU/e1FwEbA24Bji6LYcaBVaW12FPCEsiw3BHYG3lAUxV6DLUmaOEceNVBlWX4HoCiKbalGg6S+KMvyHuDQhkX/UxTFRcBOwCWDqUprs7Isr25a9CDwT4OoReolw6OkdVJRFHOBHYCjB12L1l5FUSwD3g08HLgBOGWwFUkT52lrSeucoigCOBH4GXDWgMvRWqwsy0OADYDnUAXHvw62ImniDI+S1il1cDwO2ALYuyzLNOCStJYryzKVZflzYDWwdMDlSBPmaWtJ64w6OH4O2A74l/o6SGmyzAKeMOgipIkyPGqgiqKYRdUPZwEziqJYHxgpy3J4sJVpLfVZ4LnAi8qyvGvQxWjtVRTFRkABfA+4G9gRWAJ8dJB1Sb1geNSgfQg4rOH5XsBXqOZ+lHqmKIrHAAdQnTr8c1EUo6s+7tx76oNE9XPsGKrftX8BPkX1B4w0rUVKXu4jSZKkPN4wI0mSpGyGR0mSJGUzPEqSJCmb4VGSJEnZDI+SJEnKZniUJElSNsOjJEmSshkeJUmSlM3wKKljEbFHRPwoIm6PiPsj4oaIODYiHt/hfpZGxN0Z7U6KiKu6r7ijmhZFRIqIHSbj9SRpuvHjCSV1JCI+BnwQ+C7wNuBWYGvgzcA5wGP78LIfBeb2Yb+SpA4ZHiVli4iXUAXHZSmlDzSsuhA4OSJe3o/XTSld14/9SpI652lrSZ14L3ALcFirlSml749+HRFvioj/iYg7IuKvEXF+RDyn1XYR8eyI+FlE3BcR10TEy5rWP+S0dUQsrk8tPysizoyIeyLi2oh4U86bqGv7Zf16t0XEDyPiMWO0f09E/Dwi7oyIWyPijIh4YlObp9X7uT0i7o2I30XE+3LXS9J0YXiUlCUiZgHPA85JKQ1nbLI1cDKwF7AP8GfgwubQBcwGTgO+ArwK+APw3YjYJuM1TgHOAl4BXAmcFBFPHed9/Ef9WpfXr7c/cC3wyDE22xL4LLAn8G9UPzsvjohHNLQpgY3r/f0r8Ekeeqp9vPWSNC142lpSrk2A9alC4LhSSv85+nVEzADOBp4NLAYaT3mvB3wspfTluu2PqQLkB6hC51g+m1I6tt7uUqpQ9irg6laNI2IjYClwfErpbQ2rvjfOe/n3hn3MrN/LrcBrgOMjYlPgccBBDaOv5zVsM+Z6SZpOHHmUlCvqf1NW44inRMR3I+IWYAQYBp4ENI88QnXzTbXzlEaoRumem/EyZzVst4oq2G45RvsdgYcDJ2Ts++8i4rkRcXZE3A48ANwLbMA/3svtwA3Asoh4c0Q01zDeekmaNgyPknLdBtwHbDVew4iYRxXsHgMcDOxMNep4JdXoZaPhlNJfm5bdCizIqGll0/P7W+y/0Sb1v0MZ+wYgIraiei8zqe4ufx7Ve7l19LVSSgnYHbgG+Bzw54i4PCJ2yVkvSdOJp60lZUkpPRAR/wP8S0TMHue6xx2pRgBfllK6cnRhfdr4xqa2syNi46YAuRlwU69qb3B7/e/CFnW08xKqUcZXpZRWwt+v/2y83pGU0u+AvSJiNrAT8HHg+xGxRUrp7vHWT/B9SdKkceRRUic+BTwKOLTVyoa7pB9W/3t/w7qdqG6iaeWVDe1mAgXw0wnW2solVKec39LBNg+jOlXfGJZfS5s/vlNKwymlC4AjgA2pgmr2ekma6hx5lJQtpfSjiDgc+FBEPAX4OtXp28cAb6S6BvAM4FLgbuBzEXEEsAXVjSp/abHb++v9rQ9cDxxANWq5rA/13xkRHwE+UYfU06n+iN4V+HpK6bIWm51b/3tiRHwBeCrVlEUrRxtExDOogvVpwHXARsAhwB+B68Zb38v3KEn9ZniU1JGU0oci4hLg3cAXgXlU1xCeDfx73eaWiNiLajqa7wG/B94OvL/FLoeB11NdC/h0qgD56pTSr/pU/39FxIq61jcDq6hGJG9t0/7XEfEWqrktzwCuoLrL+lsNzW6uH4dQBeU7geXAG1JKIxEx5vpev0dJ6qeoruOWJEmSxuc1j5IkScpmeJQkSVI2w6MkSZKyGR4lSZKUzfAoSZKkbIZHSZIkZTM8SpIkKZvhUZIkSdkMj5IkScpmeJQkSVI2w6MkSZKy/X9j2850E0SbsAAAAABJRU5ErkJggg==\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "my_plt_version = myplot.draw(); # extract as Matplotlib Figure\n", "\n", @@ -497,10 +414,8 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "tags": [] - }, + "execution_count": null, + "metadata": {}, "outputs": [], "source": [ "import altair as alt" @@ -515,72 +430,9 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - "" - ], - "text/plain": [ - "alt.Chart(...)" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "(alt.Chart(titanic) # 1. DATA \n", " .mark_bar() # 2. GEOMETRY, geom_*\n", @@ -617,72 +469,9 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - "" - ], - "text/plain": [ - "alt.Chart(...)" - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "brush = alt.selection(type='interval')\n", "\n", @@ -749,7 +538,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -765,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -774,392 +563,18 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"5021\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error(url) {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (let i = 0; i < css_urls.length; i++) {\n", - " const url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error.bind(null, url);\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\": \"XypntL49z55iwGVUW4qsEu83zKL3XEcz0MjuGOQ9SlaaQ68X/g+k1FcioZi7oQAc\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\": \"bEsM86IHGDTLCS0Zod8a8WM6Y4+lafAL/eSiyQcuPzinmWNgNO2/olUF0Z2Dkn5i\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\": \"TX0gSQTdXTTeScqxj6PVQxTiRW8DOoGVwinyi1D3kxv7wuxQ02XkOxv0xwiypcAH\"};\n", - "\n", - " for (let i = 0; i < js_urls.length; i++) {\n", - " const url = js_urls[i];\n", - " const element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error.bind(null, url);\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://unpkg.com/tabulator-tables@4.9.3/dist/js/tabulator.js\", \"https://unpkg.com/moment@2.27.0/moment.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\", \"https://unpkg.com/@holoviz/panel@^0.11.3/dist/panel.min.js\"];\n", - " var css_urls = [\"https://unpkg.com/tabulator-tables@4.9.3/dist/css/tabulator_simple.min.css\"];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"5021\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"5021\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\": \"XypntL49z55iwGVUW4qsEu83zKL3XEcz0MjuGOQ9SlaaQ68X/g+k1FcioZi7oQAc\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\": \"bEsM86IHGDTLCS0Zod8a8WM6Y4+lafAL/eSiyQcuPzinmWNgNO2/olUF0Z2Dkn5i\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\": \"TX0gSQTdXTTeScqxj6PVQxTiRW8DOoGVwinyi1D3kxv7wuxQ02XkOxv0xwiypcAH\"};\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://unpkg.com/tabulator-tables@4.9.3/dist/js/tabulator.js\", \"https://unpkg.com/moment@2.27.0/moment.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.2.min.js\", \"https://unpkg.com/@holoviz/panel@^0.11.3/dist/panel.min.js\"];\n var css_urls = [\"https://unpkg.com/tabulator-tables@4.9.3/dist/css/tabulator_simple.min.css\"];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"5021\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "output_notebook()" ] }, { "cell_type": "code", - "execution_count": 58, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
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s/rlbHBA/mqT+R/GLJL5asP/LwGXYFyK0/kF8s+cWStz8rpeLsw2eoP3npJjEIrKw/WoIH80T9qz/ZzvdT46WrP5zx0k1iEKg/VjvfT42Xrj9BfrHkF0uuP2GCB/NE/bM/olScffgMqz/N27JWxwSvPy3Bg3mi/q0/x2kDnTbQqT85tMh2vp+qP65lrY4JHqw/CKwcWmQ7rz9/l24Sg8CqP+GJ+jdCGbU/0KNwPQrXsz8VS36x5BezP1YdEzyYJ7I/8Las1THBoz9YV4Dcay6kP6abxCCwcqg/iUFg5dAiqz81XrpJDAKrP8dpA5020Kk/qgC511xIqj+iVJx9+AyrP/Y3Qhm9Las/2c73U+Olqz+JQWDl0CKrP3tBYOXQIqs/VOOlm8QgsD8pXI/C9SisP1YdEzyYJ6o/TnH24TPsqj9WHRM8mCeqP1pzIWlKxak/eekmMQisrD9rA5020GnHP1qCB/NE/as/Gz7DrgC5pz/w1HjpJjGoP4relrU6JrA//iqHFtnOzz/YFSD3mgvtP+i0gU4b6Oo/AbnXXEia1D8ta3VM8GDGPylcj8L1KMA/olScffgMuz/clrU6Jni4P63Idr6fGrc/mzbQaQOdtj/fXnMhaUq1P1sBcq+5kLQ/ZdgVIPeasz+iVJx9+AyzPzVeukkMArM/NV66SQwCsz83iUFg5dCyP2xZq2OCB7M/zD58hl0Bsj+GiIiIiIiwPyUGgZVDi6w/iV8s+cWSrz800GkDnTawP2ig0wY6bbA/aKDTBjptsD8AAAAAAACwP9yWtTomeLA/tNdcSJpSsT8aoYzelrWyP4izD59hV7g/pH8jlNHbuj9l5/up8dK1P70RyuhtWbM/GHYFyL3msj9y2kCnDXSyP2RKxdmHz7g/djBP1L8Rwj8K16NwPQq/P5fgwTxR/7Y/ZwOdNtBpsz9SxwQP5omyP4rtfD81XrI/qNUxwYN5sj92ME/UvxGyP/YoXI/C9bA/LCRNqTj7sD+gGi/dJAaxP2IfPsOuALE/gAfzRP0bsT+4LWt1TPCwP4RdAXKvubA/3Ja1OiZ4sD8X6LSBThuwP03jpZvEILA/n5vEILBysD/YQKcNdNqwPyr5xZJfLLE/R2IQWDm0sD9qy1odEzywP+6aC0lTKq4/eekmMQisrD+aqH8jlNGrP4GVQ4ts56s/0SLb+X5qrD8CSVMqzj6sPylcj8L1KKw/XtgVIPeaqz9SxwQP5omqP8dpA5020Kk/tgLkXnMhqT8fo7dlrY6pP5HtfD81Xqo/UKtjggfzpD/jw2fYFSCnP99tWatjgqc/BIPAyqFFpj9acyFpSsWpP5HtfD81Xqo/hzSl4uzDpz+Dz7ArQO6lP4/gwTxR/6Y/ZnVM8GCeqD+c8dJNYhCoP+rSTWIQWLE/wwQP5on6pz/HWh0TPJinP2IfPsOuAKk/LCRNqTj7sD8+pw102kDHP65H4XoUrs8//RuhjN6W2z9bAXKvuZDMP10s+cWSX7w/5d8IZfS2tD8iTak4+/CxP4IyelvW6rA/ZnVM8GCesD8xJngwT9SvP0o5tMh2vq8/2d3d3d3drT9WLPnFkl+sP4GVQ4ts56s/EFg5tMh2rj+zOiZ4ME+0P2rLWh0TPLg/YYIH80T9sz9I4XoUrkexP7Ks1THBg7E/ZDvfT42Xtj8j6t8IZfS+P1e6SQwCK7c/3SQGgZVDsz9YSJpScfaxP1YdEzyYJ7I/TDeJQWDluD/rCpB7zYXEP8M8Uf9GKMM/DjyYJ+rfuD+tuZA0peK0P6cpFWcfPrM/GqGM3pa1sj8iXI/C9Si0P9YVIPeaC8E/iyW/WPKLxT/9Riijt2XBP7YC5F5zIbk/D9nO91PjtT8gMQisHFq0PxH1b4QyerM/ObTIdr6fsj9eyS+W/GKxP54cWmQ7368/vHSTGARWrj/y8Bl2BcitP23n+6nx0q0/KWt1TPBgrj+4HoXrUbiuP7x0kxgEVq4/xSCwcmiRrT8pXI/C9SisPyPb+X5qvKQ/eyOU0duypj9YZmZmZmamPwJJUyrOPqw/hyW/WPKLpT9eyS+W/GKpP1Ys+cWSX6w/RSijt2Wttj/TXEiaUnGmP3WTGARWDq0/gaQpFWcfrj+VYVeA3GuuP6oPn2FXgKw/Yi4kTak4qz/dJAaBlUOrP42XbhKDwKo/ObTIdr6fqj+uVscED+apP28wT9S/Eao/6SYxCKwcqj/VeOkmMQisP+6LJb9Y8qs/4hdLfrHktz+UplScffi8P6jVMcGDeaI/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/f3mi/o1Qpj9SxwQP5omqP5NFtvP91Kg/9BuhjN6WpT/nKFyPwvWoP4/R27JWx6Q/Vh0TPJgnqj8OLbKd76emP8uwK0DuNac/wwQP5on6pz9eyS+W/GKpPw48mCfq36g/K6Xi7MNnqD9vIWlKxdmnPzenDXTaQKc/Vg4tsp3vpz/n+6nx0k2iP99tWatjgqc/pqqqqqqqqj9xhDJ6W9bKPzsMAiuHFqk/nPHSTWIQqD8X6LSBThuoP76uALnXXKg/P2IQWDm0qD/+415zIWmqP57+jVBGb6s/qPP91Hjppj++rgC511yoP+t+arx0k6g/KVyPwvUorD9ooNMGOm2wP/yp8dJNYrA/BFYOLbKdrz89Gb0ta3WsP/7jXnMhaao/5yhcj8L1qD/w1HjpJjGoP4PelrU6Jqg/RLgehetRqD8/YhBYObSoP9NrLiRNqag/f4iIiIiIqD9qy1odEzyoP3fNhaQpFac/rEkMAiuHpj8nQO41F5KmP/zWo3A9Cqc/48Nn2BUgpz/HWh0TPJinP4/gwTxR/6Y/CNnO91PjpT/8x73mQtKkP2wUrkfheqQ/bBSuR+F6pD83mCfq3wilPzeYJ+rfCKU/CNnO91PjpT/bCGX0tqylP0xVVVVVVaU/vKFFtvP9pD/8x73mQtKkP6jkF0t+saQ/oDj78Bl2pT/XslbHBA+mPyuW/GLJL6Y/rEkMAiuHpj+8oUW28/2kP5ZDi2zn+6k/bzBP1L8Rqj+P76fGSzepP4c0peLsw6c/uDxR/0Yooz+kjgkezBOlP7hLN4lBYKU/N5gn6t8IpT8ML90kBoGlPzeYJ+rfCKU/47SBThvopD83mCfq3wilP7yhRbbz/aQ/N5gn6t8IpT/4ca+5kDSlP4/R27JWx6Q/P0REREREpD+05kLSlIqjP835fmq8dKM/dcDKoUW2oz9xarx0kxikPz9ERERERKQ/GTEIrBxapD+c0wY6baCjP2ADnTbQaaM/ZFmrY4IHoz+LbOf7qfGiPyUzMzMzM6M/zfl+arx0oz9crY4JHsyjP3sjlNHbsqY/SPBgnqh/oz/FPnyGXQGiP8DobVmrY6I/O99PjZduoj8UzBP1b4SiP4ts5/up8aI/nNMGOm2goz8dhxbZzvejP/C2rNUxwaM/DCD3mgtJoz/jpZvEILCiP1CcffgMu6I/TEZvy1odoz9EmlJx9uGjPx2HFtnO96M/oDj78Bl2pT9YV4Dcay6kP4/C9Shcj6I/pH8jlNHboj+o1THBg3miP7ySXyz5xaI/JTMzMzMzoz9EmlJx9uGjP7CQNKXi7KM/Id0kBoGVoz8U2/l+arykP0SaUnH24aM/rCtA7jUXoj/sUbgeheuhP5MYBFYOLaI/ZFmrY4IHoz9aHRM8mCfGP7TIdr6fGq8/DjyYJ+rfqD8K5on6N0KpP+PSTWIQWKk/y7ArQO41pz9gEoPAyqGlP9eyVscED6Y/ctpApw10sj81baDTBjq1P788Uf9GKLM/RtS/EcrorT9qy1odEzyoP9NcSJpScaY/+HGvuZA0pT8AHswT9W+kPz9ERERERKQ/tOZC0pSKoz+LbOf7qfGiP+Olm8QgsKI/O99PjZduoj8QdgXIveaiP7g8Uf9GKKM/mH34DLsCpD9sFK5H4XqkPxTb+X5qvKQ/M0IZvS1rpT877jUXkqakPxTME/VvhKI/wOhtWatjoj+4PFH/RiijPx2HFtnO96M/GTEIrBxapD/FTWIQWDmkP6R/I5TR26I/oCkVZx8+oz8/NV66SQyiP8DobVmrY6I/j8L1KFyPoj/0DLsC5F6jP6w6JngwT6Q/K4cW2c73oz8/NV66SQyiPzvfT42XbqI/7FG4HoXroT/n+6nx0k2iPwAP5on6N6I/EHYFyL3moj/fT42XbhKjP4ts5/up8aI/GTEIrBxapD/+415zIWmqP+6LJb9Y8qs/8uEz7AqQqz9aggfzRP2rP1Ys+cWSX6w/TnH24TPsqj+kne+nxkunP7TmQtKUiqM/9BuhjN6WpT9I8GCeqH+jP8P1KFyPwqU/kyfq3whlpD+o1THBg3miP/QMuwLkXqM/g3mi/o1Qyj9MRm/LWh2jP6wrQO41F6I/30+Nl24Soz/N+X5qvHSjP/hiyS+W/KI/O99PjZduoj9sBci95kKiP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/g7MNn2BXAP0MZvS1rdeY/meDBPFH/5T9qvHSTGATcPymyne+nxsc/d82FpCkVtz/pRP0boYyuPwI6baDTBqo/hzSl4uzDpz/nGXYFyL2mPwwv3SQGgaU/xU1iEFg5pD/4YskvlvyiP2ivuZA0paI/uDxR/0Yooz/N+X5qvHSjP/C2rNUxwaM/RJpScfbhoz/RItv5fmq8P1jyiyW/WNA/hxbZzvdT0T9p5/up8dLFP440peLsw78/I+rfCGX0vj/Jdr6fGi+1PylrdUzwYK4/tgLkXnMhqT/nGXYFyL2mPwwv3SQGgaU/xU1iEFg5pD/N+X5qvHSjP835fmq8dKM/WFeA3GsupD+o5BdLfrGkP5Mn6t8IZaQ/GTEIrBxapD/wtqzVMcGjP835fmq8dKM/hxbZzvdToz9gA5020GmjP/C2rNUxwaM/HYcW2c73oz8dhxbZzvejP/C2rNUxwaM/oCkVZx8+oz+LbOf7qfGiP4ts5/up8aI/i2zn+6nxoj/4YskvlvyiP2ADnTbQaaM/zfl+arx0oz9kWatjggejP4/C9Shcj6I/O99PjZduoj8730+Nl26iPzvfT42XbqI/VPKLJb9Yoj8730+Nl26iPzvfT42XbqI/rCtA7jUXoj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT9YSJpScfahPzvfT42XbqI/bAXIveZCoj/n+6nx0k2iP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT8/NV66SQyiP1CcffgMu6I/qNUxwYN5oj+sK0DuNReiP6wrQO41F6I/7FG4HoXroT9YSJpScfahP7CQNKXi7KM/DCD3mgtJoz/fXnMhaUqlP7T1KFyPwqU/RKk4+/AZpj+gKRVnHz6jP+Olm8QgsKI/O99PjZduoj8730+Nl26iP/y411xImqI/O99PjZduoj/A6G1Zq2OiP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/xT58hl0Boj8730+Nl26iPzvfT42XbqI/O99PjZduoj8730+Nl26iP8U+fIZdAaI/WEiaUnH2oT8730+Nl26iP/y411xImqI/FMwT9W+Eoj+gKRVnHz6jP4ts5/up8aI/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT8ZIiIiIiKiPzvfT42XbqI/aK+5kDSloj+c0wY6baCjP8mjcD0K16M/vJJfLPnFoj+PwvUoXI+iP4ts5/up8aI/JTMzMzMzoz/fT42XbhKjP4ts5/up8aI/uDxR/0Yooz/4ca+5kDSlP2RZq2OCB6M/7FG4HoXroT/sUbgeheuhP1hImlJx9qE/f4iIiIiIqD8/NV66SQyyP0bUvxHK6K0/QX6x5BdLrj9iLiRNqTirP7CfGi/dJKY/62CeqH8jpD9I8GCeqH+jP835fmq8dKM/DCD3mgtJoz/8uNdcSJqiP2Roke18P6U/PQrXo3A9qj+WQ4ts5/upP5NFtvP91Kg/astaHRM8qD+gR+F6FK6nP/QqhxbZzqc/rkfhehSupz+HJb9Y8oulP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP6R/I5TR26I/N4lBYOXQoj8AD+aJ+jeiPwAP5on6N6I/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT9acyFpSsWpP5Mn6t8IZaQ/CuaJ+jdCsT9eukkMAiu/P6oAuddcSLo/aJHtfD81tj+VUnH24TOsPwIrhxbZzqc/Vg4tsp3vpz/rYJ6ofyOkP/QboYzelqU/y7ArQO41pz+gOPvwGXalPwAezBP1b6Q/i3vNhaQppT9GtvP91HipP2yg0wY6bcg/YAOdNtBpoz+gKRVnHz6jP7CfGi/dJKY/Gy/dJAaBvT8xCKwcWmTDP8dLN4lBYL0/2c73U+Olsz+uVscED+apP5iM3pa1OqY/VAFyr7mQpD+YffgMuwKkP0xGb8taHaM/46WbxCCwoj8730+Nl26iPzvfT42XbqI/O99PjZduoj83iUFg5dCiP4ts5/up8aI/qNUxwYN5oj8730+Nl26iPzvfT42XbqI/WEiaUnH2oT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT+o1THBg3miP7pn2BUg96o/it6WtTomsD+qALnXXEiqP5iM3pa1OqY/kyfq3whlpD+gOPvwGXalP/DFkl8s+aU/qPP91Hjppj/wxZJfLPmlP6jkF0t+saQ/oCkVZx8+oz9or7mQNKWiPzvfT42XbqI/O99PjZduoj8730+Nl26iPzvfT42XbqI/PzVeukkMoj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/5/up8dJNoj8730+Nl26iP8mjcD0K16M/qvHSTWIQqD/N27JWxwSvP4PPsCtA7rU/cK+5kDSlsj/ewTxR/0awP1Ys+cWSX6w/PRm9LWt1rD8I2c73U+OlP4/C9Shcj6I//LjXXEiaoj/sUbgeheuhP+xRuB6F66E/rCtA7jUXoj83iUFg5dCiPxB2Bci95qI/EHYFyL3moj8730+Nl26iPyHdJAaBlaM/315zIWlKpT9kWatjggejP835fmq8dKM/uDxR/0Yooz+LbOf7qfGiPxB2Bci95qI/FNv5fmq8pD/A91PjpZukP+Olm8QgsKI/AA/mifo3oj/sUbgeheuhP+f7qfHSTaI/O99PjZduoj8730+Nl26iPzvfT42XbqI/O99PjZduoj8730+Nl26iPzvfT42XbqI/j8L1KFyPoj+4PFH/RiijP835fmq8dKM/ZFmrY4IHoz8h3SQGgZWjP+IXS36x5L8/8Yslv1jy9j/ziyW/WLIRQFVVVVVV1RFAj8L1KFwPC0DGkl8s+cUAQN/d3d3d3f4/cT0K16PwAkCTXyz5xRIJQBzotIFOGwhAwFjyiyW//T810GkDnTbiP1OcffgMu9Q/f2q8dJMY0D+bNtBpA53KP3tb1uqY4MU/fT81XrpJxD9sWatjggfDPyajt2WtjsE/7tJNYhBYwT/NzMzMzMzAPyuW/GLJL74/OlH/Riijvz9RKs4+fIa9P0SLbOf7qbk/OCZ4ME/Utz9D/RuhjN62P/WaC0lTKrY/VYDcay4ktT/KItv5fmq0P9YVIPeaC7E/nMQgsHJosT8UrkfhehSuP2Q730+Nl64/psh2vp8arz8pa3VM8GCuP+6aC0lTKq4/qvHSTWIQsD/pJjEIrByqP4lBYOXQIqs/AC2yne+npj+c4uzDZ9ilP4c0peLsw6c/EpKmVJx9qD9mdUzwYJ6oP2aEMnpb1qo/O/0boYzepj8j6t8IZfSmP+cZdgXIvaY/qPP91Hjppj+HNKXi7MOnP5zx0k1iEKg/RLgehetRqD8rpeLsw2eoP9fBPFH/Rqg/L/vwGXYFqD/XwTxR/0aoP5S1OiZ4MLc/SgwCK4cWxT+DeaL+jVDQP57vp8ZLN80/j8L1KFyPxj8gIiIiIiK6P+Z8PzVeurE/hzSl4uzDpz+c0wY6baCjP0xVVVVVVaU/sJA0peLsoz+c4uzDZ9ilPz9TKs4+fKY/hyW/WPKLpT/fT42XbhKjP8U+fIZdAaI/PzVeukkMoj9QnH34DLuiP4cW2c73U6M/rCtA7jUXoj99bOf7qfGiP+Olm8QgsKI/daL+jVBGvz+1OiZ4ME/SPw7mifo3QtE/3SQGgZVDwz/4U+Olm8S4P0u4HoXrUbg/ZxKDwMqhtT8uT9S/EcqwP9TqmODBPLE/QOF6FK5HsT9JfrHkF0u2PyPb+X5qvLw/h8+wK0DuwT+mqqqqqqq6Pw2fYVeA3LM/YOXQItv5rj9WHRM8mCeqP76uALnXXKg/pJ3vp8ZLpz8K9W+EMnqrPwJJUyrOPqw/qPP91Hjppj/PBjptoNOmP99PjZduEqM/RJpScfbhoz8dhxbZzvejP5h9+Ay7AqQ/w/UoXI/CpT/nCpB7zYWkP99PjZduEqM/eyOU0duypj81fIZdAXKvP9NNYhBYObw/mVJx9uEzxD8BnTbQaQPFP7SBThvotNU/dEzwYJ6o7T8HOm2g0wbsP+nfCGX0ttw/Bx7ME/VvyD/aay4kTam4P2XYFSD3mrM/Y56ofyOUsT/8uNdcSJqyP5zi7MNn2KU/ukkMAiuHpj+AB/NE/RuxP7gta3VM8Lg/hfo3Qhm9rT8jCKwcWmSrP1Ys+cWSX6w/6TUXkqZUrD/jw2fYFSCnP8u/Ecrobak/CKwcWmQ7rz9/iIiIiIioPxKDwMqhRaY/O/0boYzepj/6fmq8dJOoPwafYVeA3Ks/rEkMAiuHpj+PwvUoXI+iP6R/I5TR26I/8Las1THBoz/fT42XbhKjPzeJQWDl0KI/fWzn+6nxoj8K16NwPQqnP/LSTWIQWKk/P1Mqzj58pj+TNtBpA52mPxTME/VvhKI/AA/mifo3oj/sUbgeheuhPw4tsp3vp6Y/+HGvuZA0pT8SoYzelrWqP9eyVscED6Y/aL6fGi/dpD/A6G1Zq2OiP8U+fIZdAaI/DCD3mgtJoz8zMzMzMzOjPwAtsp3vp6Y/g96WtTomqD+05kLSlIqjP/QMuwLkXqM/PQrXo3A9wj+LirMPn2GnP+xRuB6F66E/PzVeukkMoj9QnH34DLuiP2ADnTbQaaM//LjXXEiaoj8nMQisHFqkPyR4ME/Uv7E/f2q8dJMYpD9vEoPAyqGlP5ebxCCwcqg/CLsC5F5zsT82+/AZdgWwP99ecyFpSqU/tOZC0pSKoz8AD+aJ+jeiP+xRuB6F66E/aK+5kDSloj8UzBP1b4SiP2Roke18P6U/oEW28/3U0D+2rNUxwYPbP06Nl24Sg9I/ZmZmZmbm8T/RaQOdNlATQJ020GkDXR5AR+F6FK4HGECkcD0K12MQQBERERERkQRA7FG4HoXr/j9VVVVVVVX6P/8boYzeluk/WYDcay4k3T+jKRVnHz7ZPzCW/GLJL9Y/uKzVMcGD1T8meDBP1L/TP6Xi7MNn2NE/HcwT9W+E0D+J+jdCGb3JP+Dsw2fYFcg/KVyPwvUoxD+oHFpkO9/DP/WaC0lTKsY/gAfzRP0bxT9D/RuhjN7CPzKl4uzDZ8A/SPBgnqh/oz+iY4IH80StP6RwPQrXo7g/Y7x0kxgEtj+cxCCwcmi5P0bF2YfPsLM/vzxR/0Youz9ooNMGOm24P6JFtvP91Mg/62CeqH8jtD/l3whl9LasP5VhV4Dca64/6KfGSzeJsT89CtejcD2yP7YgsHJoka0/0r8RyuhtsT+icmiR7XyvPw48mCfq37A/RIts5/upsT/I6G1Zq2OyP+XQItv5frI/TnH24TPssj/I6G1Zq2OyP5huEoPAyrE/1iQGgZVDsz+1Za2OCR60P+f7qfHSTbo/c2iR7Xw/xT+R7Xw/NV7KPzpR/0Yoo78//UYoo7dltT/KItv5fmq0P4JBYOXQIrM/pH8jlNHbsj98seQXS36xP0oqzj58hq0/yYWkKRVnrz85w64AudesPzVeukkMAqs/dZMYBFYOrT9q2kCnDXSqPy/dJAaBlcM/Gui0gU4bxD+ONKXi7MO3Pxzb+X5qvLQ/sqzVMcGDsT+NtTomeDCvP4GkKRVnH64/N5gn6t8IpT8AHswT9W+kP1CrY4IH86Q/ZnVM8GCeqD/ByqFFtvOtP+XfCGX0tqw/+ICVQ4tspz9acyFpSsWpP5Mn6t8IZaQ/uEs3iUFgpT8rlvxiyS+mP76uALnXXKg/thHK6G1Zqz+NplScffisP4aIiIiIiLA/efgMuwLkrj9I/0Yoo7elP1pkO99Pjac/DjyYJ+rfqD/6jVBGb8uqP7pn2BUg96o/d9xrLiRNqT9MZDvfT42nP8u/Ecrobak/f2q8dJMYpD9MRm/LWh2jP2ADnTbQaaM/cWq8dJMYpD9iHz7DrgCpP6JUnH34DKs/x1odEzyYpz9I/0Yoo7elP9CUirMPn7E/u+ZC0pSKsz9q2kCnDXSqP6wrQO41F6I/5wqQe82FpD+o5BdLfrGkP4clv1jyi6U/i3vNhaQppT9BGb0ta3XAP1yPwvUoXK8/UJx9+Ay7oj9YV4Dcay6kP76fGi/dJKY/17JWxwQPpj9xarx0kxikP28haUrF2ac/vKFFtvP9pD8ML90kBoGlPxfotIFOG6g/yYWkKRVnrz8xJngwT9SvP9nO91Pjpas/+ICVQ4tspz/0KocW2c6nPxkxCKwcWqQ/UKtjggfzpD+R/GLJL5asP90z7AqQe60/SPBgnqh/oz/jpZvEILCiP/zHveZC0qQ/VAFyr7mQpD+pY4IH80TFPycxCKwcWrw/QwwCK4cWuT+8dJMYBFbjPzfQaQOdtgtAzczMzMzMEkC5HoXrUbgQQH+x5BdL/ghA7+7u7u7uAUD1KFyPwvX5P7xJDAIrh+4/a3VM8GCe5D9fLPnFkl/gP7uQNKXi7N8/UI2XbhKD2j//jVBGb8vUP6uqqqqqqtI/uB6F61G40j8fzBP1b4TSP3npJjEIrNI/jZduEoPA0j83Qhm9LWvRP/tiyS+W/M4/x5JfLPnFyj/61HjpJjHIP440peLsw8c/5m1Zq2OCxz9jZmZmZmbGP4WkKRVnH8Y/82+EMnpbxj/E2YfPsCvEP64AuddcSMI/dZMYBFYOwT/d3d3d3d3BP6bi7MNn2ME/rNUxwYN5wj9Y8oslv1jCP9NNYhBYOcQ/bstaHRM8xD+DeaL+jVDCP3N3d3d3d7c/ZErF2YfPuD+6WPKLJb+4P+rSTWIQWLk/47SBThvovD93vp8aL928P3QFyL3mQro/tNdcSJpSuT9KG+i0gU67P+XQItv5ftY/VlVVVVXVBEDkF0t+seQLQHsUrkfh+gJA5RdLfrHk9D9ImlJx9uHrP6k4+/AZduU/IiIiIiIi4z+RNKXi7MPhP5gn6t8IZeA/q2OCB/NE3T9jV4Dcay7aP0NERERERNg/4XoUrkfh2D8uJE2pOPvUP4XrUbgehdE/72CeqH8jzD8AAAAAAADMP4relrU6Jsw/2msuJE2pzD+6SQwCK4fOPzltoNMGOs0/ZmZmZmZmxj/2KFyPwvXAP7M6JngwT8A/9ihcj8L1wD/14TPsCpDDP1pkO99PjcM/dEzwYJ6owz+AB/NE/RvBP6RwPQrXo8A/9P3UeOkmwT9bq2OCB/PAP05iEFg5tMA/dZMYBFYOwT9Z1uqY4MHAP9YVIPeaC8E/001iEFg5wD/TTWIQWDm8P3CvuZA0pbo/V7pJDAIrtz+JUEZvy1q1P8SSXyz5xbI/PqcNdNpAtz+YffgMuwK8PzeJQWDl0Lo/wwQP5on6tz+sHFpkO9+3P5+M3pa1OrY/epVDi2znsz+VUnH24TO0P0Uoo7dlrbY/nNMGOm2gsz8EZfS2rNWxP2Xn+6nx0rU/ICIiIiIisj+c0wY6baCzP37cay4kTbE/MHpb1uqYsD8/NV66SQyyPzMzMzMzM7M/j8L1KFyPsj8c2/l+ary0P0jhehSuR7E/hF0Bcq+5sD/umgtJUyquP0Jvy1odE6w/hfo3Qhm9rT9G1L8RyuitP/7yRP0boaw/5e7u7u7urj9WDi2yne+nP2IfPsOuAKk/vq4AuddcqD/ufD81XrqpP5HtfD81Xqo/jZduEoPAqj+F61G4HoWrP4GkKRVnH64/9BuhjN6WpT/4gJVDi2ynPz9TKs4+fKY/sJ8aL90kpj89Gb0ta3WsP4GVQ4ts56s/ObTIdr6fqj8CSVMqzj6sP+PDZ9gVIKc/XskvlvxiqT9vIWlKxdmnP1hmZmZmZqY/OcOuALnXrD82+/AZdgWwP2iR7Xw/Na4/2c73U+Olqz9iHz7DrgCpP+kmMQisHKo/WFeA3GsupD+TJ+rfCGWkP+coXI/C9ag/aKDTBjptsD9I4XoUrkexPwisHFpkO68/5dAi2/l+qj85tMh2vp+qP0Jvy1odE6w/iUFg5dAiqz/l3whl9LasPyG/WPKLJa8/sHJoke18rz+VYVeA3GuuP5VScfbhM6w/sqzVMcGDsT/Vh8+wK0C+P+YmMQisHMo/dnd3d3d3zz9P/0Yoo7fFPzpg5dAi27k/FVpkO99PtT8YdgXIveayP4RdAXKvubA/qg+fYVeArD/DE/VvhDKqP+GJ+jdCGa0/aKDTBjptsD/pJjEIrByqP4lQRm/LWq0/uEs3iUFgpT/TXEiaUnGmP4/gwTxR/6Y/hzSl4uzDpz+wcmiR7XyvPxVLfrHkF7M/9P3UeOkmsT9acyFpSsWxP6RwPQrXo7A/5dAi2/l+sj9U8oslv1iyP3YwT9S/EbI/OcOuALnXtD8Sg8DKoUXCP09Gb8taHcc/sHJoke18vz9l5/up8dK1P/nwGXYFyLU/C0lTKs4+0D820GkDnTbhP+wKkHvNheU/jSW/WPKL9D9J4XoUrkfyP7y7u7u7u/g/TxvotIFO+z+kcD0K16P7P36x5BdLfvM/FPVvhDJ66j+RplScffjhPyvOPnyGXeA/pSkVZx8+2z9+I5TR27LYP1XHBA/midQ/aJHtfD811D/9YskvlvzSP+iY4ME8Uc8/fPgMuwLkzj9+I5TR27LQP+Lsw2fYFdA/ZdgVIPeayz8ZWmQ730/JP+01F5KmVMg/46WbxCCwxj+3SQwCK4fGPxrotIFOG8g/N0IZvS1ryT/78Bl2BcjTP/vwGXYFyN0/bS4kTak47j9xPQrXo3D8PxAREREREe4//WLJL5b84D8IrBxaZDvbP3npJjEIrNg/2/l+arx04T+4HoXrUbj/Pylcj8L1qANAFK5H4XoU+z+M3pa1OibsP6NFtvP91Oc/veZC0pSK4z+3HoXrUbjiP519+Ay7At4/n6h/I5TR2z9vEoPAyqHTP4AjlNHbstI/CR7ME/Vv0j8CK4cW2c7RP73mQtKUitM/XI/C9Shc1T+xK0DuNRfUP1jyiyW/WNI/AiuHFtnO0T+/5kLSlIrRP23n+6nx0uw/4XoUrkfhAkBz2kCnDXQCQB6F61G4nvQ/JE2pOPvw5z/MzMzMzMziPxi9LWt1TOE/ZfS2rNUx4j8Bcq+5kDTiP7sC5F5zIeE/PJgn6t8I4D+Nl24Sg8DeP7SBThvotN0/6SYxCKwc3j+gGi/dJAbbP8UgsHJokdk/PCZ4ME/U2T9z2kCnDXTYPy1rdUzwYNg/fYZdAXKv2T8AK4cW2c7XP2Q730+Nl9Y/3SQGgZVD1z8IZfS2rNXVP30/NV66SdQ/ugLkXnMh0z/b+X5qvHTTP3YFyL3mQtQ/rBxaZDvf0z9kyS+W/GLRP8KuALnXXMw/3d3d3d3dzT/P91PjpZvMP8a95kLSlM4/sHJoke18zz/fT42XbhLVP10Bcq+5kNo/SOF6FK5H1T8EVg4tsp3LP+WJ+jdCGck/zczMzMzMyD9mZmZmZmbKPxaSplScfcg/lyfq3whlyD8aoYzelrXGP+NecyFpSsU/TmIQWDm0xD8q+cWSXyzFP2xZq2OCB8M/gU4b6LSBxj+sHFpkO9/HP/9xr7mQNMk/5/up8dJNyj800GkDnTbIP1sBcq+5kMg/VOOlm8QgyD93vp8aL93IP3npJjEIrMg/sQ+fYVeAyD+NUEZvy1rJP1Eqzj58hsk/dEzwYJ6oxz90Bci95kLGP4QW2c73U8c/9wy7AuRexz/vGXYFyL3GP+8ZdgXIvcY/sp3vp8ZLxz/bslbHBA/GP0K28/3UeMU/it6WtTomxD/KWh0TPJjDP4FOG+i0gcI/NV66SQwCwz9pLiRNqTjDP4XrUbgehcM/z/dT46WbxD9RcfbhM+zGP98IZfS2rNM/e82FpCkV4j8JZfS2rNXgP4QyelvW6tQ/7AqQe82F5T+QwvUoXI8BQE8b6LSBzgBAjZduEoPA6j8LHswT9W/eP+0KkHvNhdo/0SLb+X5q1j/lifo3QhnXP5HtfD81XtQ/xNmHz7Ar1D/HSzeJQWDTP06Nl24Sg9I/o7dlrY4J1j9soNMGOm3WPwwCK4cW2dQ/1DHBg3mi0j8o6t8IZfTSP9S/EcrobdM/5/up8dJN0j8gPsOuALnRP1pkO99Pjdk/FSD3mgtJ4j8OLbKd76fhP9v5fmq8dNs/LPnFkl8s1z+c76fGSzfVPxt2Bci95tI/001iEFg52j+YbhKDwIoBQBdLfrHkFw9AodMGOm0gCkD2KFyPwnUDQHsUrkfh+gZAZmZmZmamEECx5BdLfjEJQIXrUbgehQFAQacNdNpA+D9+seQXS37zP0maUnH24fA/mW4Sg8DK6j/JL5b8YsnnP4frUbgeheY/n6h/I5RR9D8b6LSBTtsSQBSuR+F6VBdAAQAAAAAAGkCdNtBpA90XQFhVVVVVVQxAXY/C9ShcBUD8YskvlnwDQLgehetRuP4/VVVVVVVV9j/QaQOdNtAKQASdNtBpwxdAVVVVVVVVF0CPwvUoXA8QQFyPwvUoPCRAzczMzMxMMEAjIiIiIuI3QDMzMzMzczlAiIiIiIioOUAhIiIiIgI5QLu7u7u7WzRAzczMzMzMKkBmZmZmZgYiQIiIiIiI6CJABzptoNMGIUDNzMzMzAwXQIFOG+i0gQ5A6LSBThtoCEBxPQrXo/AFQHE9CtejcAJAVVVVVVVV9j8BAAAAAAD0PxdLfrHkF/I/SgwCK4cW8D/ziyW/WPLrP9QGOm2g0+k/09uyVscE5z+Iz7ArQO7kP58aL90kBuM/TxvotIFO4z+gGi/dJAbiP++nxks3ieA/NxeSplSc4D/9qfHSTWLgP1Y5tMh2vt8/OW2g0wY63z+PUEZvy1rdPxXZzvdT490/EmcfPsOu3D8/NV66SQzcP+zDZ9gVINs/A5020GkD2z/tNReSplTaPz/uNReSptg/qX8jlNHb1j9UDi2yne/XP9LbslbHBNc/3LJWxwQP1j9cukkMAivVP55hV4Dca9Q/xSCwcmiR0z/7N0IZvS3TP8/3U+Olm9I/es2FpCkV0z/2U+Olm8TSP2OCB/NE/dE/PFH/Riij0T9kO99PjZfQPzMzMzMzM88/R1Mqzj58zj9p5/up8dLNPxzME/VvhM4/Vg4tsp3v0T9VVVVVVVXRP7TIdr6fGtE/pLdlrY4J0D8C5F5zIWnOP2T0tqzVMdE/ggfzRP0b0T91kxgEVg7RP5/TBjptoNE/QKcNdNpA0T9FRERERETQP166SQwCK88/ukkMAiuH0D+DwMqhRbbPP/FE/RuhjM4/p38jlNHbzj8TIPeaC0nPP8EgsHJokc0/EoPAyqFFyj8m6t8IZfTGP6ljggfzRMk/JurfCGX0yj/xRP0boYzKP/Z+arx0k8w/W7pJDAIrzz+Ksw+fYVfQP+f7qfHSTdA/K4cW2c73zz8H80T9G6HSPxKDwMqhRdY/84slv1jy1z/UBjptoNPWP6WbxCCwcuE/0WkDnTbQ8D/4U+Olm8TlP1nyiyW/WNw/0LArQO412z8fsHJoke3WP/hT46WbxNo/6wqQe82F7j9kyS+W/GLpP9BpA5020N8/XQFyr7mQ4D8Bcq+5kDTsP9S/Ecrobew/dwXIveZC4z/lifo3QhnfP6uqqqqqqtw/o7dlrY4J3D/W6pjgwTzbP5t9+Ay7Ato/7Xw/NV664z+ZUnH24TPsP6GM3pa1Oug/xK4Auddc4z/xYJ6ofyPeP0B8hl0Bcts/m1Jx9uEz2j/BPFH/RijXP3cFyL3mQtY/8Bl2Bci91D9g5dAi2/nSP+F6FK5H4dI/m334DLsC1D9hV4Dcay7SP8yFpCkVZ9E/BQ/mifo30j9tWatjggfRP9Ei2/l+atA/ZDvfT42Xzj/n+6nx0k3OP7gehetRuM4/k9HbslbHzD+4HoXrUbjKPwLkXnMhaco/gAfzRP0byT87mCfq3wjJP9NNYhBYOcg/sQ+fYVeAyD81F5KmVJzJP1NVVVVVVck/IyIiIiIiyj+kt2WtjgnKPx1aZDvfT8k/vljyiyW/yD+K3pa1OibIP/XhM+wKkMc/ukkMAiuHxj8qQO41F5LGP6Pi7MNn2MU/EjyYJ+rfxD8PyuhtWavDP5KKsw+fYcM/jZduEoPAwj/zb4QyelvCP64AuddcSMI/1hUg95oLwT+411xImlLBP3cFyL3mQsI/kkOLbOf7wT++WPKLJb/APx4GgZVDi7w/BFYOLbKdtz/KE/VvhDK6PyuHFtnO97s/CuaJ+jdCuT//ca+5kDS9P6c4+/AZdsE/TdS/EcrowT9zaJHtfD/BP9IGOm2g08I/t5A0peLswz8R9W+EMnrDPwGdNtBpA8U/l+DBPFH/xj9IN4lBYOXMP6AaL90kBuQ/WPKLJb9YAECBThvotAEKQEjhehSuRw9AXyz5xZIfEEBY8oslv9gLQI/C9ShcDw1AKVyPwvUoBUASEREREZECQJFfLPnFEgFASgwCK4cW8j8RERERERHrPyFpSsXZh+Y/QacNdNpA5D9jO99PjZfiPz98hl0BcuA/nDbQaQOd3D+WtTomeDDbP1Nx9uEz7No/dkzwYJ6o2T+lKRVnHz7ZP3L24TPsCtg/8NJNYhBY1z+xK0DuNRfWP8uhRbbz/dQ/q6qqqqqq1D9lrY4JHszTPwIrhxbZztM/jVBGb8ta0z+ZUnH24TPSP7eQNKXi7M8/1hUg95oLzT8QWDm0yHbOP8vobVmrY84/pVScffgMzz+dYVeA3GvOP90kBoGVQ88/AiuHFtnOyz++nxov3STOPwqQe82FpM0/+fAZdgXIzT8ozj58hl3NP9TqmODBPM0/XI/C9Shc0T+EMnpb1urWP1OcffgMu9w/A5020GkD3z/XzvdT46XdP3D24TPsCtw/r+QXS36x2j9b1uqY4MHYP+htWatjgtc/u7u7u7u71z9yIWlKxdnVP4izD59hV9Q/1L8Ryuht0z9YObTIdr7RP9QxwYN5os4/yC+W/GLJyz8wT9S/EcrQP1eA3GsuJNE/gU4b6LSBzj/E2YfPsCvMPwisHFpkO8c/oykVZx8+xz8z7AqQe83FP8paHRM8mMM/Gy/dJAaBxT8BnTbQaQPFP7JWxwQP5sU/7xl2Bci9xj8cEzyYJ+rHP8yFpCkVZ8c/zz58hl0Bxj8welvW6pjEP/7UeOkmMcQ/p38jlNHbwj/ufD81XrrBP4lQRm/LWr0/exSuR+F6wD877jUXkqa8PxKDwMqhRb4/tvP91Hjpwj/rCpB7zYXEP/+411xImsY/IpTR27JWwz/CZ9gVIPfCP1jyiyW/WMI/BFYOLbKdwz9xPQrXo3DFP8Jn2BUg98Y/Q0REREREyD8NdNpApw3QPx+F61G4nvE/cT0K16PwCUBdj8L1KNwIQKuqqqqqqvY/n4zelrU67j/ByqFFtvPmP0HuNReSpuE/peLsw2fY4D8Sg8DKoUXeP9bqmODBPNs/Qots5/up1z8DnTbQaQPZP6UpFWcfPtU/11xImlJx0j+UirMPn2HTPw4tsp3vp9Q/WmQ730+N0z/sfD81XrrTP2fYFSD3mtM/yb3mQtKU0j+Y4ME8Uf/QP3WTGARWDs0/QHyGXQFyzz+/PFH/RijPP9uyVscED9A/+/AZdgXI0T8QWDm0yHbQP93d3d3d3c0/xNmHz7AryD/xiyW/WPLHPwwCK4cW2cY/V6tjggfzxD+4HoXrUbi+P6Pi7MNn2MU/aErF2YfPzD/DPFH/RijLP7bz/dR46co/kkOLbOf7yT+9yqFFtvPJP0K28/3UeMk/27JWxwQPyj89CtejcD3QP7HkF0t+sdA/PcOuALnX0D/8qfHSTWLQP+Olm8QgsNA/ImlKxdmH0T+DwMqhRbbRP3ii/o1QRtM/q2OCB/NE1T+eGi/dJAbVP2L0tqzVMdU/g3mi/o1Q1D+J+jdCGb3TPyd4ME/Uv9M/hxbZzvdT0z+IiIiIiIjSP0/UvxHK6NE/kl8s+cWS0T+cxCCwcmjRP1vW6pjgwdA/p38jlNHb0D9GKKO3Za3QP8m95kLSlNA/4hdLfrHkzz9mZmZmZmbQP4FOG+i0gc4/gjJ6W9bqzD/Hkl8s+cXKP5GmVJx9+MQ/9wy7AuRewz9+I5TR27LGP2Dl0CLb+cI/nah/I5TRxz/t7u7u7u7KP+p8PzVeusk/KVyPwvUoyD/0/dR46SbJP5GmVJx9+Mg/wq4AuddcyD9SuB6F61HIP1odEzyYJ8o/DLsC5F5zyT8m6t8IZfTKP4N5ov6NUMo/BfNE/RuhyD95ME/UvxHKP/IoXI/C9cg/QNKUirMPxz83iUFg5dDKP8EgsHJokck/FGcfPsOuyD+MCR7ME/XHPzb78Bl2Bcg/1XjpJjEIyD+1Za2OCR7IP6MpFWcfPsc/kaZUnH34yD8ozj58hl3JP7as1THBg8k/dwXIveZCyj8ePsOuALnLPypA7jUXks4/2kCnDXTa0j+j/o1QRm/dP5WKsw+fYec/nxov3SQG6z/BPFH/RijrPxFYObTIdus/sHJoke187D+/WPKLJb/sPxzotIFOG+0/TmIQWDm07j91kxgEVg7wPxP1b4Qyeuk/qDj78Bl24z8X2c73U+PgPwRWDi2ynd8/2ofPsCtA3j9LqTj78BnePyJNqTj78N0/lm4Sg8DK3T81F5KmVJzdP39qvHSTGN4/F9nO91Pj3T8lBoGVQ4veP+Lsw2fYFeA/lUOLbOf74D+CB/NE/RviP4jPsCtA7uI/Lmt1TPBg4T/pJjEIrBzePxfZzvdT49s/Tak4+/AZ2j/DZ9gVIPfYP68AuddcSNg/djBP1L8R2D9Fb8taHRPYPyd4ME/Uv9c/ay4kTak41z+F61G4HoXXPwQP5on6N9g/001iEFg52D/tCpB7zYXYP0Yoo7dlrdg/7zUXkqZU2D+DwMqhRbbXP3zNhaQpFdc/sw+fYVeA1j/PPnyGXQHWP9nO91PjpdU/QHyGXQFy1T/YFSD3mgvVPyz5xZJfLNU/Sn6x5BdL1D84+/AZdgXUPzxR/0Yoo9M/lIqzD59h0z/YFSD3mgvTP7wta3VM8NI//WLJL5b80j9Apw102kDTP7oC5F5zIdM/bRKDwMqh0z8lTak4+/DdP4lBYOXQIuc/TH6x5BdL6D8tsp3vp8brP9ejcD0K1wJAm5mZmZmZDkAHOm2g04YEQD0K16NwPfc/V4Dcay6k8D8szj58hl3tP7aBThvotPM/6LSBThvo8z/NzMzMzEwBQAGdNtBpA/4//WLJL5b88z+TXyz5xZLzP6cNdNpAp/0/EBERERER+D9/seQXS37yP/YoXI/C9e8/cT0K16Nw8z8L16NwPQr0P7M6JngwT+8/CR7ME/Vv6j/hehSuR+HnP+kmMQisHOY/3GsuJE2p5D/z/dR46SbjP1xImlJx9u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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[11697]},\"Time\":{\"__ndarray__\":\"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- } - ], + "outputs": [], "source": [ "p = figure(x_axis_type=\"datetime\", plot_height=200, plot_width=600)\n", "p.line(x='Time', y='LS06_347', source=source_data)\n", @@ -1283,7 +643,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1292,64 +652,9 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
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gj9gXQFyr7mAP4GFpCkVZ38/eekmMQisfD9/4uzDZ9h1PwIb6LSBTns/GQRWDi2yfT/fx73mQtKEPz+tjgkezIM/i2zn+6nxgj+eK0DuNReCP2BdAXKvuYA/wuWJ+jdCeT+4HoXrUbh+P5zEILByaIE/Le41F5KmhD+POiZ4ME+EP7DqmODBPIE/3Zw20GkDfT8G6SYxCKx8PxDQaQOdNoA/Tp6ofyOUgT8730+Nl26CP43TBjptoIM/2/l+arx0gz+N0wY6baCDP3sUrkfheoQ/PYIH80T9ez9gXQFyr7lwPwB4ME/Uv3E//kypOPvweT97FK5H4XqEP3/i7MNn2IU/UAXIveZCgj89Rm/LWh2DP0dJDAIrh3Y/Q3vNhaQpdT9gXQFyr7lwPz+tjgkezHM/P62OCR7Mgz/R1qNwPQqHP43TBjptoIM/nitA7jUXgj9De82FpCl1P4pMqTj78Gk/YF0Bcq+5cD+jYJ6ofyN0Py3uNReSpoQ/jzomeDBPhD+4HoXrUbh+P2BdAXKvuYA/XjJ6W9bqeD8ERm/LWh1zPzvfT42XbnI/O99PjZducj+w6pjgwTyBPyuHFtnO94M/jdMGOm2ggz8CG+i0gU57P1pkO99PjXc/H/0boYzedj9/4uzDZ9h1PyaZmZmZmXk/UAXIveZCgj8730+Nl26CP1724TPsCoA/eekmMQisfD89ggfzRP17P8Llifo3Qnk/45X8Yskvdj+BhaQpFWd/PwB4ME/Uv4E/nitA7jUXgj/hanVM8GB+P8Llifo3Qnk/H/0boYzedj/8qfHSTWJwP6Ngnqh/I3Q/+n5qvHSTeD99e82FpCmFP43TBjptoIM//Knx0k1igD89ggfzRP17P4OwK0DuNXc/f+Lsw2fYdT8iy1odEzx4P74XS36x5Hc/3WCeqH8jhD+N0wY6baCDPxzSlIqzD38/fbdlrY4Jfj+DsCtA7jV3P4d+arx0k3g/vhdLfrHkdz+dZ9gVIPd6PyP5xZJfLKk/TmIQWDm0sD956SYxCKysP7pn2BUg95o//kypOPvwiT99e82FpCmFP06eqH8jlIE/O99PjZdugj+h+X5qvHSDP9/HveZC0oQ/nMQgsHJogT+gkl8s+cWCP3npJjEIrHw/JpmZmZmZeT+Hfmq8dJN4PwRGb8taHXM/YsQgsHJogT8rhxbZzveDP/4QEREREYE/AhvotIFOez+gkl8s+cVyP/yp8dJNYnA/nMQgsHJocT/fx73mQtJ0P54rQO41F4I/Tp6ofyOUgT99t2Wtjgl+P43TBjptoIM/nMQgsHJogT/bNReSplSMP8U+fIZdAZI/fXvNhaQphT89Rm/LWh2DP1AFyL3mQoI/AHgwT9S/gT+eK0DuNReCP8dLN4lBYKU/jdMGOm2ggz8730+Nl26CPzvfT42XboI/7x/3mgtJgz+POiZ4ME+EP43TBjptoIM/exSuR+F6hD9e9uEz7AqAPzm0yHa+n3o/3Zw20GkDfT9gXQFyr7mAP+2411xImoI/exSuR+F6hD/hanVM8GB+PwB4ME/Uv4E//kypOPvweT+Hfmq8dJN4P2IAuddcSHo/eekmMQisfD/tuNdcSJqCPzG8dJMYBIY/7bjXXEiagj8730+Nl26CP+djO99PjXc/AHgwT9S/cT/8qfHSTWJwPwB4ME/Uv3E/EjeJQWDlgD8/rY4JHsyDP1g5tMh2vn8/2c73U+Olez8AeDBP1L9xP3npJjEIrGw/uB6F61G4bj+gkl8s+cVyP6CSXyz5xYI/2/l+arx0gz/ZzvdT46V7P4GFpCkVZ28/E35qvHSTaD9LF0t+seRnP/yp8dJNYnA/O99PjZducj9gXQFyr7mAPzm0yHa+n3o/YF0Bcq+5cD8k9uEz7ApwPxN+arx0k2g/yoEH80T9az8ERm/LWh1zP74XS36x5Hc/uB6F61G4fj+HJb9Y8oulP6abxCCwcrA/bCOU0duyhj8c0pSKsw9/PxzSlIqzD38//Knx0k1igD/8qfHSTWKAP6CSXyz5xYI/jzomeDBPhD9MN4lBYOWAP3npJjEIrHw/uB6F61G4bj8k9uEz7ApwPwgUrkfhenQ/qvHSTWIQiD99e82FpCmFP74XS36x5Ic/oJJfLPnFgj+eK0DuNReCP40Pn2FXgIw/P+kmMQisjD9/4uzDZ9iFP/4QEREREYE/Tp6ofyOUgT+BSQwCK4eGPyuHFtnO94M//kypOPvwiT/+EBERERGBP92cNtBpA30/eekmMQisfD956SYxCKx8P+FqdUzwYH4/arx0kxgEhj81mlJx9uGTP3npJjEIrKw//Knx0k1ikD/NCGX0tqyFP43TBjptoIM/QRSuR+F6hD+POiZ4ME+EP54rQO41F4I/ENBpA502gD85tMh2vp96P14yelvW6ng/XjJ6W9bqeD/8qfHSTWKAPxDQaQOdNoA/XvbhM+wKgD9gXQFyr7mAP+FqdUzwYH4/nWfYFSD3ej8f/RuhjN52P9v5fmq8dHM//Knx0k1icD+gkl8s+cVyP4GFpCkVZ38/2c73U+Olez9/4uzDZ9h1P6Ngnqh/I3Q/O99PjZducj/8qfHSTWJwP9v5fmq8dHM/oTUXkqZUfD8c0pSKsw9/P/yp8dJNYoA/JpmZmZmZeT8G6SYxCKx8Pxsv3SQGgXU/h35qvHSTeD+Hfmq8dJN4PyaZmZmZmXk/YgC511xIej/sUbgeheuBP0FQRm/LWn0/pQNWDi2yfT9kK0DuNRdyPwRGb8taHXM/o2CeqH8jdD8IFK5H4Xp0PyLLWh0TPHg//hARERERgT+hNReSplR8P92cNtBpA30/AHgwT9S/cT8oxCCwcmhxP9v5fmq8dHM/xBARERERcT/C5Yn6N0J5P1g5tMh2vn8/IstaHRM8eD/C5Yn6N0J5PzvfT42XbnI/YF0Bcq+5cD/8qfHSTWJwP6CSXyz5xXI/oTUXkqZUfD9Onqh/I5SBP0FQRm/LWn0/P62OCR7Mcz8bL90kBoF1P14yelvW6ng/IstaHRM8eD8iy1odEzx4Pz2CB/NE/Xs/3Zw20GkDfT/Gs8h2vp96P+djO99PjXc/45X8Yskvdj+Hfmq8dJN4P6E1F5KmVHw/avgMuwLkjj/Afmq8dJOIP2BdAXKvuYA/roN5ov6NgD/hanVM8GB+P8Llifo3Qnk/H/0boYzedj/jlfxiyS92P14yelvW6ng/WDm0yHa+fz+4HoXrUbh+PxzSlIqzD38/XvbhM+wKgD/EEBERERFxP0FQRm/LWm0/U7PIdr6faj9gXQFyr7lwP3npJjEIrHw/GQRWDi2yfT+DsCtA7jV3P4OwK0DuNXc/ObTIdr6faj+NdzBP1L9hPxN+arx0k2g//Knx0k1icD9YObTIdr5/PxkEVg4tsn0/P62OCR7Mcz8Jt2WtjgluPxN+arx0k2g/g7ArQO41Zz+4HoXrUbhuP5zEILByaHE/GQRWDi2yfT8iy1odEzx4P2QrQO41F3I/nMQgsHJocT/8qfHSTWJwP0FQRm/LWm0/JPbhM+wKcD8AeDBP1L9xP7gehetRuH4/52M730+Ndz+nLt0kBoF1P8QQEREREXE/YF0Bcq+5cD/8qfHSTWJwPz+tjgkezHM/38e95kLSdD+BhaQpFWd/P92cNtBpA30/P62OCR7Mcz+4HoXrUbhuP0FQRm/LWm0/yoEH80T9az/8qfHSTWJwPzvfT42XbnI/roN5ov6NgD/C5Yn6N0J5P6CSXyz5xXI/gYWkKRVnbz8Tfmq8dJNoPxN+arx0k2g/gYWkKRVnbz8oxCCwcmhxP2BdAXKvuYA/roN5ov6NgD9/4uzDZ9h1P4OwK0DuNXc/YF0Bcq+5cD8Tfmq8dJNoPxN+arx0k2g/uB6F61G4bj/ZzvdT46V7P4GFpCkVZ38/f+Lsw2fYdT8k9uEz7ApwPzm0yHa+n2o/AhvotIFOaz/8qfHSTWJwPwB4ME/Uv3E/fbdlrY4Jfj/8qfHSTWKAP6cu3SQGgXU/Gy/dJAaBdT9LF0t+seRnP0N7zYWkKWU/E35qvHSTaD8AeDBP1L9xP1724TPsCoA/nMQgsHJogT9iALnXXEh6PwIb6LSBTns/CbdlrY4Jbj85tMh2vp9qP5zEILByaHE/aPl+arx0cz++F0t+seR3P+2411xImoI/gYWkKRVnfz8Jt2WtjgluPwoTPJgn6o8/i4qzD59hlz85tMh2vp96P+djO99PjXc/eekmMQisfD+amZmZmZl5Pzm0yHa+n5o/3WCeqH8jlD99t2Wtjgl+P0N7zYWkKXU/38e95kLSdD8f/RuhjN52P3npJjEIrHw/g7ArQO41dz8/rY4JHsxzP/yp8dJNYnA/AhvotIFOaz+4HoXrUbhuP3/i7MNn2HU/vhdLfrHkdz/dnDbQaQN9Pz1Gb8taHYM/oJJfLPnFgj/dnDbQaQN9PyT24TPsCnA/ObTIdr6faj/KgQfzRP1rP/yp8dJNYnA/AhvotIFOez+w6pjgwTyBP6E1F5KmVHw/4Wp1TPBgfj9gXQFyr7lwPwvi7MNn2GU/E35qvHSTaD8CG+i0gU5rPyLLWh0TPHg/Tp6ofyOUgT89ggfzRP17PwbpJjEIrHw/ObTIdr6faj8Tfmq8dJNoPxN+arx0k2g/JPbhM+wKcD89ggfzRP17P+xRuB6F64E/XjJ6W9bqeD8f/RuhjN52P0sXS36x5Gc/zKyOCR7MYz/C5Yn6N0JpPzvfT42XbnI/45X8Yskvdj+BhaQpFWd/P+FqdUzwYH4/yoEH80T9az9LF0t+seRnP4pMqTj78Gk//Knx0k1icD9kK0DuNRdyPz2CB/NE/Xs/IstaHRM8eD/EEBERERFxP4GFpCkVZ28/H/0boYzedj956SYxCKx8P4OwK0DuNXc/wuWJ+jdCeT9e9uEz7AqAPxkEVg4tsn0/vhdLfrHkdz/EEBERERFxP/yp8dJNYnA/O99PjZducj/jlfxiyS92P2IAuddcSHo/P62OCR7Mgz85w64Aude8P6SOCR7ME5U/7poLSVMqrj/tuNdcSJqCP2BdAXKvuXA/BEZvy1odcz8iy1odEzx4P4GFpCkVZ38/AHgwT9S/gT/dnDbQaQN9P51n2BUg93o/P62OCR7Mcz8Jt2WtjgluP7gehetRuG4/f+Lsw2fYdT/hanVM8GB+P06eqH8jlIE/YgC511xIej96hl0Bcq+5PxKDwMqhRZY/XvbhM+wKgD/CMcGDeaKeP91gnqh/I4Q/roN5ov6NgD+eK0DuNReCPz2CB/NE/Xs/JpmZmZmZeT9/4uzDZ9h1P5zEILByaHE//Knx0k1icD9o+X5qvHRzPwgUrkfhenQ/XvbhM+wKgD8CG+i0gU57P2BdAXKvuYA/2/l+arx0cz956SYxCKxsP2BdAXKvuXA/nMQgsHJocT8CG+i0gU57Pzm0yHa+n3o/P62OCR7Mcz/EEBERERFxPyT24TPsCnA/eekmMQisbD/8qfHSTWJwPwRGb8taHXM/PYIH80T9ez+DsCtA7jV3P2BdAXKvuXA/gYWkKRVnbz9De82FpCllP0sXS36x5Gc/JPbhM+wKcD+cxCCwcmhxPxDQaQOdNoA/vhdLfrHkdz+cxCCwcmhxP/yp8dJNYnA/SxdLfrHkZz/C5Yn6N0JpPyjEILByaHE/o2CeqH8jdD+ug3mi/o2AP3npJjEIrHw/IstaHRM8eD8/rY4JHsxzP8qBB/NE/Ws/QVBGb8tabT/jlfxiyS92P0dJDAIrh3Y//hARERERgT/LoUW28/2EP2IAuddcSHo/ObTIdr6fej++F0t+seR3P2IAuddcSHo//kypOPvweT8mmZmZmZl5PwB4ME/Uv4E/sOqY4ME8gT8/rY4JHsyDP3sUrkfhenQ/AHgwT9S/cT8Jt2WtjgluP6Ngnqh/I3Q/XvbhM+wKgD/NRP0boYyOP80IZfS2rIU/GQRWDi2yfT/ZzvdT46V7P4OwK0DuNXc/38e95kLSdD9/4uzDZ9h1P6CSXyz5xXI/YF0Bcq+5gD99t2Wtjgl+PyLLWh0TPHg/BEZvy1odcz+S6CYxCKxsP/yp8dJNYnA/ukkMAiuHdj/ZzvdT46V7PxDQaQOdNoA/HNKUirMPfz9eMnpb1up4PyaZmZmZmXk/H/0boYzedj+S6CYxCKxsP4OwK0DuNXc/3Zw20GkDfT+yUbgeheuBP5GhRbbz/YQ/O99PjZdugj8t7jUXkqaEP8Llifo3Qnk/kugmMQisbD9o+X5qvHRzPxsv3SQGgXU/AhvotIFOez99e82FpCmFP4ts5/up8YI/nMQgsHJogT8vVVVVVVWFP0FQRm/LWn0/45X8Yskvdj+Hfmq8dJN4P0FQRm/LWn0/7bjXXEiagj/C5Yn6N0J5P54rQO41F4I/YF0Bcq+5cD+cxCCwcmhxPwB4ME/Uv3E/2/l+arx0cz9gXQFyr7mAP4ts5/up8YI/uB6F61G4jj8ba3VM8GCOP+OV/GLJL3Y/oJJfLPnFcj8ERm/LWh1zP/yp8dJNYnA/PYIH80T9ez9e9uEz7AqAPyaZmZmZmXk/AhvotIFOaz9De82FpCllP0FQRm/LWm0/Gy/dJAaBdT956SYxCKx8PwB4ME/Uv4E/roN5ov6NgD99t2Wtjgl+P+djO99PjXc/38e95kLSdD8f/RuhjN52P4d+arx0k3g/IstaHRM8eD9BUEZvy1p9P8Llifo3Qnk/oJJfLPnFcj+gkl8s+cVyP2BdAXKvuXA/ZCtA7jUXcj+Hfmq8dJN4P4d+arx0k3g/Tp6ofyOUgT+POiZ4ME+EPyUkTak4+5A/g8DKoUW2oz89ggfzRP2LPzm0yHa+n3o/ZCtA7jUXcj/8qfHSTWJwP3sUrkfhenQ/2c73U+Olez/b+X5qvHRzP4OwK0DuNXc/ikypOPvwaT+KTKk4+/BpP/yp8dJNYnA//Knx0k1icD9kK0DuNRdyP1724TPsCoA/ukkMAiuHdj9iALnXXEh6P/T91HjpJqE/AklTKs4+nD8bL90kBoGFP9nO91PjpXs/eekmMQisfD/hanVM8GB+P2bO91PjpXs/Zs73U+Olez/C5Yn6N0JpPxN+arx0k2g/CbdlrY4Jbj/nYzvfT413P51n2BUg93o/QVBGb8tafT9/4uzDZ9h1PxN+arx0k2g/E35qvHSTaD+4HoXrUbhuPwRGb8taHXM/IstaHRM8eD+Hfmq8dJN4P14yelvW6ng/f+Lsw2fYdT8730+Nl26CP2JM8GCeqJ8/ENBpA502gD+DsCtA7jV3Pz2CB/NE/Xs/Zs73U+Olez8rhxbZzveDP/4QEREREYE/IstaHRM8eD+jYJ6ofyN0P/yp8dJNYnA//Knx0k1icD8AeDBP1L9xP1724TPsCoA/uB6F61G4fj8/rY4JHsxzPwgUrkfhenQ/QVBGb8tabT8CG+i0gU5rP/yp8dJNYnA/Q3vNhaQpdT+hNReSplR8P1AFyL3mQoI/WDm0yHa+fz8730+Nl26CPyeLbOf7qZE/7bjXXEiakj8rhxbZzveDP2CZmZmZmYk/PUZvy1odgz8/rY4JHsyDPxkEVg4tsn0/QVBGb8tafT9kK0DuNRdyP7gehetRuG4/QVBGb8tabT9gXQFyr7lwP51n2BUg93o/nitA7jUXgj8ZBFYOLbJ9P2BdAXKvuYA/AHgwT9S/cT+cxCCwcmhxP7qFpCkVZ48/3Zw20GkDfT+BhaQpFWd/P6CSXyz5xYI/3Zw20GkDfT8ERm/LWh1zPwIb6LSBTms/JPbhM+wKcD9gXQFyr7lwPz+tjgkezHM/eekmMQisfD8ZBFYOLbJ9Px/9G6GM3nY/wuWJ+jdCeT9De82FpCl1PyaZmZmZmXk/uB6F61G4fj956SYxCKx8PxzSlIqzD38//Knx0k1igD/8qfHSTWKAP4GFpCkVZ38/sOqY4ME8gT8K16NwPQqHPy/dJAaBlbs/d+kmMQis3D/v7u7u7u7kP5X8YskvlsA/olScffgMqz8R9W+EMnqzP17JL5b8Yrk/VCrOPnyGxT/iF0t+seS3P1TjpZvEIKA/3X5qvHSTmD+m9Shcj8KVP5V/I5TR25I//Knx0k1ikD87G+i0gU6LP9nO91PjpYs/rr8RyuhtiT8f/RuhjN6GP0oMAiuHFok/6SYxCKwcij/Pb4QyeluGPx2W/GLJL4Y/YgC511xIej++F0t+seR3PxkEVg4tsn0/eekmMQisfD/8qfHSTWKAP4ts5/up8YI/gYWkKRVnfz9De82FpCl1P/yp8dJNYnA/ObTIdr6fej/dnDbQaQN9P1g5tMh2vn8/XvbhM+wKgD+w6pjgwTyBP3npJjEIrHw/py7dJAaBdT+KTKk4+/BpPyT24TPsCnA/P62OCR7Mcz+dZ9gVIPd6P323Za2OCX4/eekmMQisfD9HSQwCK4d2P9v5fmq8dHM/xBARERERcT/jlfxiyS92Pz+tjgkezHM/YgC511xIej+4HoXrUbh+P323Za2OCX4/vhdLfrHkdz9aZDvfT413P9v5fmq8dHM/H/0boYzedj++F0t+seSHP6aqqqqqqqo/kzbQaQOdlj+uVscED+apP6RwPQrXo5A/i2zn+6nxgj/dnDbQaQN9PxzSlIqzD38//Knx0k1igD/hanVM8GB+PxDQaQOdNoA/nMQgsHJogT8Q0GkDnTaAPxkEVg4tsn0/YgC511xIej/fx73mQtJ0PwgUrkfhenQ/YgC511xIej/8qfHSTWKAPz+tjgkezIM/YgC511xIej8ZBFYOLbJ9P/yp8dJNYoA/qvHSTWIQuD9iLiRNqTibP2r4DLsC5I4/TtpApw10ij/PqxxaZDuPPwoTPJgn6o8/38e95kLShD/fx73mQtKEP74XS36x5Ic/9DltoNMGmj+eK0DuNReSP1g5tMh2vo8/yXa+nxovjT+uvxHK6G2JPz1Gb8taHYM/O99PjZdugj8AeDBP1L+BP0EUrkfheoQ/y6FFtvP9hD/dYJ6ofyOEPz+tjgkezIM/roN5ov6NgD9YObTIdr5/PyaZmZmZmXk//Knx0k1igD/sUbgeheuBP54rQO41F4I/7bjXXEiagj+LbOf7qfGCP1g5tMh2vn8//Knx0k1igD8v7AqQe82lPwa9LWt1TJA/dc+wK0DulT+F61G4HoWrP23n+6nx0sE/O99PjZduuj8MIPeaC0mjPzm0yHa+n5o/7bjXXEiakj8rw64AudeMP6xY8oslv4g/rFjyiyW/iD99t2WtjgmOP81E/RuhjI4//OWJ+jdCiT+sWPKLJb+IP43TBjptoIM/nMQgsHJogT+eK0DuNReCP+Eu3SQGgYU/+n5qvHSTiD85tMh2vp+KPzG8dJMYBIY/f+Lsw2fYhT+4HoXrUbh+P92cNtBpA30/eekmMQisfD956SYxCKx8P1AFyL3mQoI/TtpApw10ij+8sCtA7jWHP4ts5/up8YI/XjJ6W9bqeD8bL90kBoF1P4d+arx0k3g/AhvotIFOez+yUbgeheuBP6xY8oslv4g/jdMGOm2ggz85tMh2vp96P3npJjEIrHw/eekmMQisfD+Hfmq8dJN4P323Za2OCX4/TDeJQWDlgD/dYJ6ofyOEP1AFyL3mQoI/3Zw20GkDfT97FK5H4Xp0Pxsv3SQGgXU/PYIH80T9ez8CG+i0gU57PwB4ME/Uv4E/7x/3mgtJgz/+EBERERGBP3npJjEIrHw/2/l+arx0cz+dZ9gVIPd6P06eqH8jlIE/sOqY4ME8gT8dlvxiyS+GP51n2BUg94o/bCOU0duyhj/NCGX0tqyFP7DqmODBPIE/sOqY4ME8gT9sBci95kKSP07aQKcNdIo/gUkMAiuHhj9eMnpb1uqIP486JngwT4Q/jzomeDBPhD9YObTIdr5/P6E1F5KmVHw/UJx9+Ay7sj/bNReSplScPycxCKwcWrQ/U2Q730+Ntz9hggfzRP2zPw4t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Application\",\"version\":\"2.3.2\"}};\n", - " var render_items = [{\"docid\":\"4f6d2c64-f553-4049-b0f9-43bc6a6dc3ed\",\"root_ids\":[\"5538\"],\"roots\":{\"5538\":\"1e0b1cd5-c585-47a7-a9a2-7f5200cd811e\"}}];\n", - " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", - "\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " embed_document(root);\n", - " } else {\n", - " var attempts = 0;\n", - " var timer = setInterval(function(root) {\n", - " if (root.Bokeh !== undefined) {\n", - " clearInterval(timer);\n", - " embed_document(root);\n", - " } else {\n", - " attempts++;\n", - " if (attempts > 100) {\n", - " clearInterval(timer);\n", - " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", - " }\n", - " }\n", - " }, 10, root)\n", - " }\n", - "})(window);" - ], - "application/vnd.bokehjs_exec.v0+json": "" - }, - "metadata": { - "application/vnd.bokehjs_exec.v0+json": { - "id": "5538" - } - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "p = figure(x_axis_type=\"datetime\", plot_height=200, plot_width=600)\n", "p.line(x='Time', y='L06_347', source=source_data)\n", @@ -1394,65 +699,9 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": {}, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.holoviews_exec.v0+json": "", - "text/html": [ - "
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\n", - "" - ], - "text/plain": [ - ":NdOverlay [Variable]\n", - " :Curve [Time] (value)" - ] - }, - "execution_count": 63, - "metadata": { - "application/vnd.holoviews_exec.v0+json": { - "id": "5867" - } - }, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import hvplot.pandas\n", "\n", @@ -1468,20 +717,9 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "bokeh.plotting.figure.Figure" - ] - }, - "execution_count": 64, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import holoviews as hv\n", "\n", @@ -1522,7 +760,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1540,895 +778,9 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - 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bb1dn/O4FX3xx/Js8tSPaVnZU8zqpyLadHcYPRZh1f0ds3XF8vf6AI1NatR0/29t3xhe/Ni727uvofWzwpTfEsuV9v+PbY3N+G6cMmRCnDr02Th16bXzxa+PipHPGx/ceeTIivO0NDsfb3iAfb3uDMimt2o6fiIjRU+6Oh2Y/HY1Gd8xbsDgGDb8+Go3uiIiYt2BxbNnWfsDn+DM/cPSMH8jH+IEyKa1aj5/1m7bEiIkz4+QhE+LicdPjjZVrej926tBrY2nb2wd8jvEDR8/4gXyMHyiT0qr1+GlGVR1s44cSGD+Qj/EDZVJa/TZ+fvP7JUdl3oLF/XVJTamqg238UALjB/IxfqBMSqvfxs9XL5rU6/SLJ8ffDRobn/vqqDh16LVx0jnj44SBI+Pvzx4XX//Wzf11SU2pqoNt/FAC4wfyMX6gTEory9ve5jyzMGbc83i079jd+9iWbe1x852PxNx5C3Nc0jFX1cE2fiiB8QP5GD9QJqWVZfwMvHBS7Nm7/4DHt7fvjNOGTcxwRcdeVQfb+KEExg/kY/xAmZRWlvFzypAJsXb9hwc8/va7H8QpQyZkuKJjr6qDbfxQAuMH8jF+oExKK8v4mXHP4/HViybFPQ/PiZ8/9Xz84qnn456H58TACyfFtFmP5rikY66qg238UALjB/IxfqBMSivL+OnsasQTv3ouRkycGYMvvSHOuHhKDL/y9njw8aeio6MzxyUdc1UdbOOHEhg/kI/xA2VSWv6en8SqOtjGDyUwfiAf4wfKpLSyjZ///O1LMWLizDjzkikREbFvf0c8+PhT0dVo5LqkY6qqg238UALjB/IxfqBMSivL+HnsF7+NMy+ZEo88MS9OGDgyIj75VtfDRt8S9/5obo5LOuaqOtjGDyUwfiAf4wfKpLSyjJ/Thk2M1WvWR0T0jp+IiHUbPooz/+m6HJd0zFV1sI0fSmD8QD7GD5RJaWUZP39/9rjo7u6JiL7jZ+++jvjCoLE5LumYq+pgGz+UwPiBfIwfKJPSyjJ+ho+fEf/1+1ci4tPx09PTEz+c/VRcNPa2HJd0zFV1sI0fSmD8QD7GD5RJaWUZP0vb3o6/P3tcXHbNHXHCwJFxzbTvx9f+9z/HgMFXxJJlb+W4pGOuqoNt/FAC4wfyMX6gTEor23d7W7fho/jh7Kfi2zMfiRn3PB6P/eK3se3jnbku55ir6mAbP5TA+IF8jB8ok9LKMn7u/dHcWLl6XY6fuulVdbCNH0pg/EA+xg+USWllGT+XXvWdOGHgyPj6t26OH85+Kt7/4MMcl9GUqjrYxg8lMH4gH+MHyqS0sr3tbfPWj+M//vP3MXrK3fH5My6Pi8dNj3/7+bOx8aNtuS7pmKrqYBs/lMD4gXyMHyiT0so2fv7/2nfsjl8/uyi+efUdfb719fFQVQfb+KEExg/kY/xAmZRW9vHzxso18f1HfxnDRt8SXxg0Nq6Zel/uS/pMVXWwjR9KYPxAPsYPlElpZRk/r/z5zbjjvp/GGRdPiRPPGhNXfft78czvXo7de/bluJykqjrYxg8lMH4gH+MHyqS0soyfE88cHVfedG88Nf+PsWv38f2LWNXBNn4ogfED+Rg/UCallWX87Ny1J8dPW0lVHWzjhxIYP5CP8QNlUlr9Nn4m3fqDeOe99b3/+3COp6o62MYPJTB+IB/jB8qktPpt/My8/4lYu/7D3v99OMdTVR1s44cSGD+Qj/EDZVJaWd729tKrbdHVaOT4qZteVQfb+KEExg/kY/xAmZRWnm94cNaY+Ifzr4nb750df/7L29HT05PjMppSVQfb+KEExg/kY/xAmZRWlvGze8+++M3vl8SU6Q/EgMFXxOkXT45/efDnsXzlezkuJ6mqDrbxQwmMH8jH+IEyKa3sf8np/o7OeP6Py+LmOx+Jfzj/mhh86Q25L+kzVdXBNn4ogfED+Rg/UCallX38dDUa8cqf34yZ9z8R5152U3zl/KtzX9JnqqqDbfxQAuMH8jF+oExKK8v42bN3f/zuhdfixjsejlOGTIgvn3dV3HL3T+KPf1p+3H0jhKoOtvFDCYwfyMf4gTIprSzj5wuDxsYpQybEtFmPxqIlx/d3fqvqYBs/lMD4gXyMHyiT0soyfm6/5/HYsauMX7yqDrbxQwmMH8jH+IEyKa0s4+cr518da9ZtyvFTN72qDrbxQwmMH8jH+IEyKa0s4+fXzy6Kcf/83Zj33OL47zfeieUr3+vjeKqqg238UALjB/IxfqBMSivL+Dlh4MjDOp6q6mAbP5TA+IF8jB8ok9LKMn527d4b+zs6D+l4qqqDbfxQAuMH8jF+oExKK/vf85OzdRs+ipGT7opThkyIC8fcGkvbVh30eW+tej++MeH/xEnnjI/zRk6NRUvaej9W1cE2fiiB8QP5GD9QJqWVZfwMG33LIZ034tv9dh0jJs6Mx+fOj0ajOxYtaYuBF06Kzq6+33a7p6cnzrxkSjzzu5ejp6cn/vDysjjpnPG9v0NV1cE2fiiB8QP5GD9QJqWVZfw88asF/8Nz8S8P/jzO/sYN8cSvnuuXa9i6fUcMGDy+z98xdNHY2+LVZSv6PG/f/o54av4f+zz2hUFj44ONmyPC+IHDMX4gH+MHyqS0Wuptb+s3bYkrb7q3X36upW2r4oJR0/o8dt2MB2POMwsP+TmdXY34+VPPx7DRt0R3d09EGD9wOMYP5GP8QJmUVkuNn4iIwZfe2C8/z8uvLY/h42f0eWzarEdj9tz5B33+H15eFp/76qg485Ip8cbKNb2Pd3Z1N11HZ3csWJT/xgmpJk/tiLfe6azkdVKVPfu7jB+KMOv+jti9ryv7awpoLqWVZfysXf/hAVa990H87JfPxVnDr++Xa1i2fFWcN3Jqn8emTH8gnpz3wiE/p9HojpdfWx7/eME1sfHDrRER8dHH+yrxW7/zQwEmT+2I/16xv7LXSRU+/Hif8UMRZt3fEZu25X9NAc2ltFrq7/n5h/OviQWL/twv17C9fWd88WvjYu++jt7HBl96Qyxb3vc7vm3Z1h7znlvc57FvXXtn/Ob3SyLC297gcLztDfLxtjcok9LKMn62bGs/wI5de/r9OkZPuTsemv10NBrdMW/B4hg0/PpoND757cR5CxbHlm3tsb19Z5x0zvh48ZXXIyJi5ep18aVzr4xV730QEcYPHI7xA/kYP1AmpdXv46fR6I49e/f3+fGCRX+OXz+7KD7cvL1fr2X9pi0xYuLMOHnIhLh43PQ+f5bn1KHXxtK2tyMiYtGStrhg1LT40rlXxlnDr49fPPV87/OqOtjGDyUwfiAf4wfKpLT6dfx8sHFzDL70xpg7b2HvY1d/+774/BmXx5e/flUMGDw+Vryztj8vKbmqDrbxQwmMH8jH+IEyKa1+HT9Tpj8Y42+8J7Zu3xEREUvb3o6/GzQ23lu7MXp6emLqXT+Oq799X39eUnJVHWzjhxIYP5CP8QNlUlr9On5OGTIhVq5e1/vjex6eE5Nv+0Hvj1e8sza+fN5V/XlJyVV1sI0fSmD8QD7GD5RJafXr+Pn8GZdH+47dvT++7Jo744lfLej98UdbPo6/PWN0f15SclUdbOOHEhg/kI/xA2VSWv06fk4bNjHefveT75K2Y9eeOPHM0b3fNS0i4s2318Rpwyb25yUlV9XBNn4ogfED+Rg/UCal1a/j58bvPByTbv1BrF6zPqbNejQuGDWtz8enf/exuGaqP/OzYavxQxmMH8jH+IEyKa1+HT/rN22Js79xQ5wwcGR8+byr+vyFot/53k/j7waNjba33u3PS0quqoNt/FAC4wfyMX6gTEqr3/+en65GI9Zv2hIdHZ19Hn/xldf7vAXueKmqg238UALjB/IxfqBMSqvfx09pVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsYPlElpGT+JVXWwjR9KYPxAPsfj+Hlvw75Y/g4c/1a+v7+y15/SMn4Sq+oGYPxQAuMH8jkex8/St/bFDTP2x9U3dsBx7bcv7o/1W/dU8jpRWsZPYlXdAIwfSmD8QD7H5fh5c19M/LbXH8e/ZxcaP62a8ZNYVTcA44cSGD+Qj/ED+Rg/rZvxk1hVNwDjhxIYP5CP8QP5GD+tm/GTWFU3AOOHEhg/kI/xA/kYP62b8ZNYVTcA44cSGD+Qj/ED+Rg/rZvxk1hVNwDjhxIYP5CP8QP5GD+tm/GTWFU3AOOHEhg/kI/xA/kYP62b8ZNYVTcA44cSGD+Qj/ED+Rg/rZvxk1hVNwDjhxIYP5CP8QP5GD+tm/GTWFU3AOOHEhg/kI/xA/kYP62b8ZNYVTcA44cSGD+Qj/ED+Rg/rZvxk1hVNwDjhxIYP5CP8QP5GD+tm/GTWFU3AOOHEhg/kI/xA/kYP62b8ZNYVTcA44cSGD+Qj/ED+Rg/rVutx8+6DR/FyEl3xSlDJsSFY26NpW2rDvq81e9viMuuuTNOOmd8fP1bN8cLi1/v/VhVNwDjhxIYP5CP8QP5GD+tW63Hz4iJM+PxufOj0eiORUvaYuCFk6Kzq3HA884bOTUenzs/enp64qVX22LA4Cti776OiDB+4HCMH8jH+IF8jJ/WrbbjZ+v2HTFg8Pjoanw6di4ae1u8umxFn+d1NRox5+k/9BlFJ50zPtau/zAijB84HOMH8jF+IB/jp3Wr7fhZ2rYqLhg1rc9j1814MOY8s/Cwn9f21rtx+sWTe0fTpm3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eDBP1L9xP3npJjEIrGw/uB6F61G4bj+gkl8s+cVyP6CSXyz5xYI/2/l+arx0gz/ZzvdT46V7P4GFpCkVZ28/E35qvHSTaD9LF0t+seRnP/yp8dJNYnA/O99PjZducj9gXQFyr7mAPzm0yHa+n3o/YF0Bcq+5cD8k9uEz7ApwPxN+arx0k2g/yoEH80T9az8ERm/LWh1zP74XS36x5Hc/uB6F61G4fj+HJb9Y8oulP6abxCCwcrA/bCOU0duyhj8c0pSKsw9/PxzSlIqzD38//Knx0k1igD/8qfHSTWKAP6CSXyz5xYI/jzomeDBPhD9MN4lBYOWAP3npJjEIrHw/uB6F61G4bj8k9uEz7ApwPwgUrkfhenQ/qvHSTWIQiD99e82FpCmFP74XS36x5Ic/oJJfLPnFgj+eK0DuNReCP40Pn2FXgIw/P+kmMQisjD9/4uzDZ9iFP/4QEREREYE/Tp6ofyOUgT+BSQwCK4eGPyuHFtnO94M//kypOPvwiT/+EBERERGBP92cNtBpA30/eekmMQisfD956SYxCKx8P+FqdUzwYH4/arx0kxgEhj81mlJx9uGTP3npJjEIrKw//Knx0k1ikD/NCGX0tqyFP43TBjptoIM/QRSuR+F6hD+POiZ4ME+EP54rQO41F4I/ENBpA502gD85tMh2vp96P14yelvW6ng/XjJ6W9bqeD/8qfHSTWKAPxDQaQOdNoA/XvbhM+wKgD9gXQFyr7mAP+FqdUzwYH4/nWfYFSD3ej8f/RuhjN52P9v5fmq8dHM//Knx0k1icD+gkl8s+cVyP4GFpCkVZ38/2c73U+Olez9/4uzDZ9h1P6Ngnqh/I3Q/O99PjZducj/8qfHSTWJwP9v5fmq8dHM/oTUXkqZUfD8c0pSKsw9/P/yp8dJNYoA/JpmZmZmZeT8G6SYxCKx8Pxsv3SQGgXU/h35qvHSTeD+Hfmq8dJN4PyaZmZmZmXk/YgC511xIej/sUbgeheuBP0FQRm/LWn0/pQNWDi2yfT9kK0DuNRdyPwRGb8taHXM/o2CeqH8jdD8IFK5H4Xp0PyLLWh0TPHg//hARERERgT+hNReSplR8P92cNtBpA30/AHgwT9S/cT8oxCCwcmhxP9v5fmq8dHM/xBARERERcT/C5Yn6N0J5P1g5tMh2vn8/IstaHRM8eD/C5Yn6N0J5PzvfT42XbnI/YF0Bcq+5cD/8qfHSTWJwP6CSXyz5xXI/oTUXkqZUfD9Onqh/I5SBP0FQRm/LWn0/P62OCR7Mcz8bL90kBoF1P14yelvW6ng/IstaHRM8eD8iy1odEzx4Pz2CB/NE/Xs/3Zw20GkDfT/Gs8h2vp96P+djO99PjXc/45X8Yskvdj+Hfmq8dJN4P6E1F5KmVHw/avgMuwLkjj/Afmq8dJOIP2BdAXKvuYA/roN5ov6NgD/hanVM8GB+P8Llifo3Qnk/H/0boYzedj/jlfxiyS92P14yelvW6ng/WDm0yHa+fz+4HoXrUbh+PxzSlIqzD38/XvbhM+wKgD/EEBERERFxP0FQRm/LWm0/U7PIdr6faj9gXQFyr7lwP3npJjEIrHw/GQRWDi2yfT+DsCtA7jV3P4OwK0DuNXc/ObTIdr6faj+NdzBP1L9hPxN+arx0k2g//Knx0k1icD9YObTIdr5/PxkEVg4tsn0/P62OCR7Mcz8Jt2WtjgluPxN+arx0k2g/g7ArQO41Zz+4HoXrUbhuP5zEILByaHE/GQRWDi2yfT8iy1odEzx4P2QrQO41F3I/nMQgsHJocT/8qfHSTWJwP0FQRm/LWm0/JPbhM+wKcD8AeDBP1L9xP7gehetRuH4/52M730+Ndz+nLt0kBoF1P8QQEREREXE/YF0Bcq+5cD/8qfHSTWJwPz+tjgkezHM/38e95kLSdD+BhaQpFWd/P92cNtBpA30/P62OCR7Mcz+4HoXrUbhuP0FQRm/LWm0/yoEH80T9az/8qfHSTWJwPzvfT42XbnI/roN5ov6NgD/C5Yn6N0J5P6CSXyz5xXI/gYWkKRVnbz8Tfmq8dJNoPxN+arx0k2g/gYWkKRVnbz8oxCCwcmhxP2BdAXKvuYA/roN5ov6NgD9/4uzDZ9h1P4OwK0DuNXc/YF0Bcq+5cD8Tfmq8dJNoPxN+arx0k2g/uB6F61G4bj/ZzvdT46V7P4GFpCkVZ38/f+Lsw2fYdT8k9uEz7ApwPzm0yHa+n2o/AhvotIFOaz/8qfHSTWJwPwB4ME/Uv3E/fbdlrY4Jfj/8qfHSTWKAP6cu3SQGgXU/Gy/dJAaBdT9LF0t+seRnP0N7zYWkKWU/E35qvHSTaD8AeDBP1L9xP1724TPsCoA/nMQgsHJogT9iALnXXEh6PwIb6LSBTns/CbdlrY4Jbj85tMh2vp9qP5zEILByaHE/aPl+arx0cz++F0t+seR3P+2411xImoI/gYWkKRVnfz8Jt2WtjgluPwoTPJgn6o8/i4qzD59hlz85tMh2vp96P+djO99PjXc/eekmMQisfD+amZmZmZl5Pzm0yHa+n5o/3WCeqH8jlD99t2Wtjgl+P0N7zYWkKXU/38e95kLSdD8f/RuhjN52P3npJjEIrHw/g7ArQO41dz8/rY4JHsxzP/yp8dJNYnA/AhvotIFOaz+4HoXrUbhuP3/i7MNn2HU/vhdLfrHkdz/dnDbQaQN9Pz1Gb8taHYM/oJJfLPnFgj/dnDbQaQN9PyT24TPsCnA/ObTIdr6faj/KgQfzRP1rP/yp8dJNYnA/AhvotIFOez+w6pjgwTyBP6E1F5KmVHw/4Wp1TPBgfj9gXQFyr7lwPwvi7MNn2GU/E35qvHSTaD8CG+i0gU5rPyLLWh0TPHg/Tp6ofyOUgT89ggfzRP17PwbpJjEIrHw/ObTIdr6faj8Tfmq8dJNoPxN+arx0k2g/JPbhM+wKcD89ggfzRP17P+xRuB6F64E/XjJ6W9bqeD8f/RuhjN52P0sXS36x5Gc/zKyOCR7MYz/C5Yn6N0JpPzvfT42XbnI/45X8Yskvdj+BhaQpFWd/P+FqdUzwYH4/yoEH80T9az9LF0t+seRnP4pMqTj78Gk//Knx0k1icD9kK0DuNRdyPz2CB/NE/Xs/IstaHRM8eD/EEBERERFxP4GFpCkVZ28/H/0boYzedj956SYxCKx8P4OwK0DuNXc/wuWJ+jdCeT9e9uEz7AqAPxkEVg4tsn0/vhdLfrHkdz/EEBERERFxP/yp8dJNYnA/O99PjZducj/jlfxiyS92P2IAuddcSHo/P62OCR7Mgz85w64Aude8P6SOCR7ME5U/7poLSVMqrj/tuNdcSJqCP2BdAXKvuXA/BEZvy1odcz8iy1odEzx4P4GFpCkVZ38/AHgwT9S/gT/dnDbQaQN9P51n2BUg93o/P62OCR7Mcz8Jt2WtjgluP7gehetRuG4/f+Lsw2fYdT/hanVM8GB+P06eqH8jlIE/YgC511xIej96hl0Bcq+5PxKDwMqhRZY/XvbhM+wKgD/CMcGDeaKeP91gnqh/I4Q/roN5ov6NgD+eK0DuNReCPz2CB/NE/Xs/JpmZmZmZeT9/4uzDZ9h1P5zEILByaHE//Knx0k1icD9o+X5qvHRzPwgUrkfhenQ/XvbhM+wKgD8CG+i0gU57P2BdAXKvuYA/2/l+arx0cz956SYxCKxsP2BdAXKvuXA/nMQgsHJocT8CG+i0gU57Pzm0yHa+n3o/P62OCR7Mcz/EEBERERFxPyT24TPsCnA/eekmMQisbD/8qfHSTWJwPwRGb8taHXM/PYIH80T9ez+DsCtA7jV3P2BdAXKvuXA/gYWkKRVnbz9De82FpCllP0sXS36x5Gc/JPbhM+wKcD+cxCCwcmhxPxDQaQOdNoA/vhdLfrHkdz+cxCCwcmhxP/yp8dJNYnA/SxdLfrHkZz/C5Yn6N0JpPyjEILByaHE/o2CeqH8jdD+ug3mi/o2AP3npJjEIrHw/IstaHRM8eD8/rY4JHsxzP8qBB/NE/Ws/QVBGb8tabT/jlfxiyS92P0dJDAIrh3Y//hARERERgT/LoUW28/2EP2IAuddcSHo/ObTIdr6fej++F0t+seR3P2IAuddcSHo//kypOPvweT8mmZmZmZl5PwB4ME/Uv4E/sOqY4ME8gT8/rY4JHsyDP3sUrkfhenQ/AHgwT9S/cT8Jt2WtjgluP6Ngnqh/I3Q/XvbhM+wKgD/NRP0boYyOP80IZfS2rIU/GQRWDi2yfT/ZzvdT46V7P4OwK0DuNXc/38e95kLSdD9/4uzDZ9h1P6CSXyz5xXI/YF0Bcq+5gD99t2Wtjgl+PyLLWh0TPHg/BEZvy1odcz+S6CYxCKxsP/yp8dJNYnA/ukkMAiuHdj/ZzvdT46V7PxDQaQOdNoA/HNKUirMPfz9eMnpb1up4PyaZmZmZmXk/H/0boYzedj+S6CYxCKxsP4OwK0DuNXc/3Zw20GkDfT+yUbgeheuBP5GhRbbz/YQ/O99PjZdugj8t7jUXkqaEP8Llifo3Qnk/kugmMQisbD9o+X5qvHRzPxsv3SQGgXU/AhvotIFOez99e82FpCmFP4ts5/up8YI/nMQgsHJogT8vVVVVVVWFP0FQRm/LWn0/45X8Yskvdj+Hfmq8dJN4P0FQRm/LWn0/7bjXXEiagj/C5Yn6N0J5P54rQO41F4I/YF0Bcq+5cD+cxCCwcmhxPwB4ME/Uv3E/2/l+arx0cz9gXQFyr7mAP4ts5/up8YI/uB6F61G4jj8ba3VM8GCOP+OV/GLJL3Y/oJJfLPnFcj8ERm/LWh1zP/yp8dJNYnA/PYIH80T9ez9e9uEz7AqAPyaZmZmZmXk/AhvotIFOaz9De82FpCllP0FQRm/LWm0/Gy/dJAaBdT956SYxCKx8PwB4ME/Uv4E/roN5ov6NgD99t2Wtjgl+P+djO99PjXc/38e95kLSdD8f/RuhjN52P4d+arx0k3g/IstaHRM8eD9BUEZvy1p9P8Llifo3Qnk/oJJfLPnFcj+gkl8s+cVyP2BdAXKvuXA/ZCtA7jUXcj+Hfmq8dJN4P4d+arx0k3g/Tp6ofyOUgT+POiZ4ME+EPyUkTak4+5A/g8DKoUW2oz89ggfzRP2LPzm0yHa+n3o/ZCtA7jUXcj/8qfHSTWJwP3sUrkfhenQ/2c73U+Olez/b+X5qvHRzP4OwK0DuNXc/ikypOPvwaT+KTKk4+/BpP/yp8dJNYnA//Knx0k1icD9kK0DuNRdyP1724TPsCoA/ukkMAiuHdj9iALnXXEh6P/T91HjpJqE/AklTKs4+nD8bL90kBoGFP9nO91PjpXs/eekmMQisfD/hanVM8GB+P2bO91PjpXs/Zs73U+Olez/C5Yn6N0JpPxN+arx0k2g/CbdlrY4Jbj/nYzvfT413P51n2BUg93o/QVBGb8tafT9/4uzDZ9h1PxN+arx0k2g/E35qvHSTaD+4HoXrUbhuPwRGb8taHXM/IstaHRM8eD+Hfmq8dJN4P14yelvW6ng/f+Lsw2fYdT8730+Nl26CP2JM8GCeqJ8/ENBpA502gD+DsCtA7jV3Pz2CB/NE/Xs/Zs73U+Olez8rhxbZzveDP/4QEREREYE/IstaHRM8eD+jYJ6ofyN0P/yp8dJNYnA//Knx0k1icD8AeDBP1L9xP1724TPsCoA/uB6F61G4fj8/rY4JHsxzPwgUrkfhenQ/QVBGb8tabT8CG+i0gU5rP/yp8dJNYnA/Q3vNhaQpdT+hNReSplR8P1AFyL3mQoI/WDm0yHa+fz8730+Nl26CPyeLbOf7qZE/7bjXXEiakj8rhxbZzveDP2CZmZmZmYk/PUZvy1odgz8/rY4JHsyDPxkEVg4tsn0/QVBGb8tafT9kK0DuNRdyP7gehetRuG4/QVBGb8tabT9gXQFyr7lwP51n2BUg93o/nitA7jUXgj8ZBFYOLbJ9P2BdAXKvuYA/AHgwT9S/cT+cxCCwcmhxP7qFpCkVZ48/3Zw20GkDfT+BhaQpFWd/P6CSXyz5xYI/3Zw20GkDfT8ERm/LWh1zPwIb6LSBTms/JPbhM+wKcD9gXQFyr7lwPz+tjgkezHM/eekmMQisfD8ZBFYOLbJ9Px/9G6GM3nY/wuWJ+jdCeT9De82FpCl1PyaZmZmZmXk/uB6F61G4fj956SYxCKx8PxzSlIqzD38//Knx0k1igD/8qfHSTWKAP4GFpCkVZ38/sOqY4ME8gT8K16NwPQqHPy/dJAaBlbs/d+kmMQis3D/v7u7u7u7kP5X8YskvlsA/olScffgMqz8R9W+EMnqzP17JL5b8Yrk/VCrOPnyGxT/iF0t+seS3P1TjpZvEIKA/3X5qvHSTmD+m9Shcj8KVP5V/I5TR25I//Knx0k1ikD87G+i0gU6LP9nO91PjpYs/rr8RyuhtiT8f/RuhjN6GP0oMAiuHFok/6SYxCKwcij/Pb4QyeluGPx2W/GLJL4Y/YgC511xIej++F0t+seR3PxkEVg4tsn0/eekmMQisfD/8qfHSTWKAP4ts5/up8YI/gYWkKRVnfz9De82FpCl1P/yp8dJNYnA/ObTIdr6fej/dnDbQaQN9P1g5tMh2vn8/XvbhM+wKgD+w6pjgwTyBP3npJjEIrHw/py7dJAaBdT+KTKk4+/BpPyT24TPsCnA/P62OCR7Mcz+dZ9gVIPd6P323Za2OCX4/eekmMQisfD9HSQwCK4d2P9v5fmq8dHM/xBARERERcT/jlfxiyS92Pz+tjgkezHM/YgC511xIej+4HoXrUbh+P323Za2OCX4/vhdLfrHkdz9aZDvfT413P9v5fmq8dHM/H/0boYzedj++F0t+seSHP6aqqqqqqqo/kzbQaQOdlj+uVscED+apP6RwPQrXo5A/i2zn+6nxgj/dnDbQaQN9PxzSlIqzD38//Knx0k1igD/hanVM8GB+PxDQaQOdNoA/nMQgsHJogT8Q0GkDnTaAPxkEVg4tsn0/YgC511xIej/fx73mQtJ0PwgUrkfhenQ/YgC511xIej/8qfHSTWKAPz+tjgkezIM/YgC511xIej8ZBFYOLbJ9P/yp8dJNYoA/qvHSTWIQuD9iLiRNqTibP2r4DLsC5I4/TtpApw10ij/PqxxaZDuPPwoTPJgn6o8/38e95kLShD/fx73mQtKEP74XS36x5Ic/9DltoNMGmj+eK0DuNReSP1g5tMh2vo8/yXa+nxovjT+uvxHK6G2JPz1Gb8taHYM/O99PjZdugj8AeDBP1L+BP0EUrkfheoQ/y6FFtvP9hD/dYJ6ofyOEPz+tjgkezIM/roN5ov6NgD9YObTIdr5/PyaZmZmZmXk//Knx0k1igD/sUbgeheuBP54rQO41F4I/7bjXXEiagj+LbOf7qfGCP1g5tMh2vn8//Knx0k1igD8v7AqQe82lPwa9LWt1TJA/dc+wK0DulT+F61G4HoWrP23n+6nx0sE/O99PjZduuj8MIPeaC0mjPzm0yHa+n5o/7bjXXEiakj8rw64AudeMP6xY8oslv4g/rFjyiyW/iD99t2WtjgmOP81E/RuhjI4//OWJ+jdCiT+sWPKLJb+IP43TBjptoIM/nMQgsHJogT+eK0DuNReCP+Eu3SQGgYU/+n5qvHSTiD85tMh2vp+KPzG8dJMYBIY/f+Lsw2fYhT+4HoXrUbh+P92cNtBpA30/eekmMQisfD956SYxCKx8P1AFyL3mQoI/TtpApw10ij+8sCtA7jWHP4ts5/up8YI/XjJ6W9bqeD8bL90kBoF1P4d+arx0k3g/AhvotIFOez+yUbgeheuBP6xY8oslv4g/jdMGOm2ggz85tMh2vp96P3npJjEIrHw/eekmMQisfD+Hfmq8dJN4P323Za2OCX4/TDeJQWDlgD/dYJ6ofyOEP1AFyL3mQoI/3Zw20GkDfT97FK5H4Xp0Pxsv3SQGgXU/PYIH80T9ez8CG+i0gU57PwB4ME/Uv4E/7x/3mgtJgz/+EBERERGBP3npJjEIrHw/2/l+arx0cz+dZ9gVIPd6P06eqH8jlIE/sOqY4ME8gT8dlvxiyS+GP51n2BUg94o/bCOU0duyhj/NCGX0tqyFP7DqmODBPIE/sOqY4ME8gT9sBci95kKSP07aQKcNdIo/gUkMAiuHhj9eMnpb1uqIP486JngwT4Q/jzomeDBPhD9YObTIdr5/P6E1F5KmVHw/UJx9+Ay7sj/bNReSplScPycxCKwcWrQ/U2Q730+Ntz9hggfzRP2zPw4tsp3vp6Y/4Ja1OiZ45T8xT9S/EcrnP+Lsw2fYFdY/ZdgVIPeawz/fT42XbhK7P90z7AqQe7U/kpmZmZmZsT/0/dR46SaxP7YRyuhtWas/2xdLfrHkpz9/eaL+jVCmP8D3U+Olm6Q/YAOdNtBpoz9U8oslv1iiPy3QaQOdNqA/2zUXkqZUnD8bTak4+/CZP8MT9W+EMpo/M1H/Riijlz8EkqZUnH2YP9NrLiRNqZg/5SqHFtnOlz+sOiZ4ME+UP/T91HjpJpE/2zUXkqZUjD8rw64AudeMP1724TPsCpA/avgMuwLkjj/N6pjgwTyRP+UMuwLkXpM/ptdcSJpSkT+LqH8jlNGLP9HWo3A9Coc/bCOU0duyhj9eMnpb1uqIPw6l4uzDZ4g/641QRm/Lij+LqH8jlNGLP2wjlNHbsoY/bCOU0duyhj+RoUW28/2EP74XS36x5Ic/nAC511xIij85tMh2vp+KPzm0yHa+n4o/71uPwvUojD/+TKk4+/CJP8B+arx0k4g/mpmZmZmZiT/VlrU6JniQP1yPwvUoXK8/ukkMAiuHlj/VlrU6JniQP1g5tMh2vo8/ObTIdr6fij+uvxHK6G2JPww+w64AuYc/wH5qvHSTiD/Afmq8dJOIPww+w64AuYc/XMtaHRM8iD8QDAIrhxaJPx/9G6GM3oY/boqzD59hhz9vEoPAyqGlP3Wx5BdLfqE/nitA7jUXkj/8qfHSTWKQPwoTPJgn6o8/WDm0yHa+jz/ZzvdT46WLP9HWo3A9Coc/jzomeDBPhD99e82FpCmFP4FJDAIrh4Y/rr8RyuhtiT9O2kCnDXSKP0xzIWlKxYk/fXvNhaQphT+N0wY6baCDP06eqH8jlIE/jdMGOm2ggz99e82FpCmFP4FJDAIrh4Y/DqXi7MNniD9eMnpb1uqIPylcj8L1KIw/zQhl9LashT+cxCCwcmiBPxsv3SQGgYU/Mbx0kxgEhj+BSQwCK4eGP6rx0k1iEIg//OWJ+jdCiT/fx73mQtKEPx/9G6GM3oY/GQRWDi2yfT99t2Wtjgl+P323Za2OCX4/XvbhM+wKgD/R1qNwPQqHPzm0yHa+n4o/fXvNhaQphT8AeDBP1L+BPzvfT42XbnI/52M730+Ndz956SYxCKx8P92cNtBpA30/fXvNhaQphT/pJjEIrByKP43TBjptoIM/nMQgsHJogT/C5Yn6N0J5PxzSlIqzD38/HNKUirMPfz+LbOf7qfGCP2wjlNHbsoY/cPHSTWIQiD/b+X5qvHSDP4lBYOXQIos/7FG4HoXrgT+POiZ4ME+EPy9VVVVVVYU/gUkMAiuHhj9cy1odEzyIP+kmMQisHIo/DqXi7MNniD+LbOf7qfGCP/4QEREREYE/kaFFtvP9hD+BSQwCK4eGPy9VVVVVVYU/P62OCR7Mgz9KDAIrhxaJP9s1F5KmVIw/DD7DrgC5hz8OpeLsw2eIP9FApw102qA/N4lBYOXQoj/BILByaJHJPx/3mgtJU9o/J3gwT9S/xT+lVJx9+AzHP+01F5KmVMQ/1iQGgZVDuz+zOiZ4ME+0P2Z1TPBgnrA/6UT9G6GMrj+yu7u7u7urP65WxwQP5qk/17JWxwQPpj9EmlJx9uGjP3Wx5BdLfqE/TDeJQWDloD+c0wY6baCjP9NNYhBYOaQ/j8L1KFyPoj9or7mQNKWiP6RwPQrXo6A/YOXQItv5nj/rjVBGb8uaP/Q5baDT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KXU/o2CeqH8jdD/dnDbQaQN9P9nO91PjpXs/BEZvy1odcz/8qfHSTWJwP4pMqTj78Gk/xBARERERcT8bL90kBoF1PxzSlIqzD38/4Wp1TPBgfj+4HoXrUbh+P4OwK0DuNXc/P62OCR7Mcz9/4uzDZ9h1P4d+arx0k3g/g7ArQO41dz+Hfmq8dJN4P51n2BUg93o/2c73U+Olez89ggfzRP17P14yelvW6ng/oJJfLPnFcj8iy1odEzx4PzvfT42XbnI//kypOPvweT/dnDbQaQN9P9nO91PjpXs/WmQ730+Ndz8/rY4JHsxzPz+tjgkezHM/Gy/dJAaBdT9De82FpCl1PxkEVg4tsn0/XvbhM+wKgD/ZzvdT46V7PxkEVg4tsn0/vhdLfrHkdz8iy1odEzx4P3/i7MNn2HU/ZCtA7jUXcj9De82FpCl1P2BdAXKvuYA/uB6F61G4fj/jlfxiyS92PzvfT42XbnI/ObTIdr6faj8k9uEz7ApwPz+tjgkezHM/38e95kLSdD+BhaQpFWd/P6E1F5KmVHw/R0kMAiuHdj8ERm/LWh1zPwvi7MNn2GU/CbdlrY4Jbj/EEBERERFxP2j5fmq8dHM/AhvotIFOez/nYzvfT413P/yp8dJNYnA/JPbhM+wKcD/EEBERERFhPwIb6LSBTms//Knx0k1icD8AeDBP1L9xP5qZmZmZmXk/Zs73U+Olez/jlfxiyS92PyT24TPsCnA/jXcwT9S/YT8k9uEz7ApwPwRGb8taHXM/JpmZmZmZeT8CG+i0gU57P92cNtBpA30/H/0boYzedj8730+Nl25yPwB4ME/Uv3E/ZCtA7jUXcj+cxCCwcmhxP9nO91PjpXs/ObTIdr6fej9MN4lBYOWAP1724TPsCoA/wuWJ+jdCeT+DsCtA7jV3PwRGb8taHXM/P62OCR7Mcz8ERm/LWh1zP74XS36x5Hc/P62OCR7Mcz9De82FpCl1P6Ngnqh/I3Q/g7ArQO41dz/6fmq8dJN4P4lBYOXQIps/fbdlrY4Jjj9gXQFyr7mAP2BdAXKvuYA/2c73U+Olez8f/RuhjN52P5zEILByaHE/P62OCR7Mcz97FK5H4Xp0P0dJDAIrh3Y/ObTIdr6fej9BUEZvy1p9P3npJjEIrHw/g7ArQO41dz/C5Yn6N0J5P3npJjEIrHw/nMQgsHJocT9kK0DuNRdyP+OV/GLJL3Y/wuWJ+jdCeT/b+X5qvHRzP/yp8dJNYnA/ikypOPvwaT8CG+i0gU5rP/yp8dJNYnA/ZCtA7jUXcj8bL90kBoF1P6E1F5KmVHw/YgC511xIej/b+X5qvHRzP0FQRm/LWm0/JPbhM+wKcD/fx73mQtJ0P74XS36x5Hc/JpmZmZmZeT9/4uzDZ9h1P0dJDAIrh3Y/ukkMAiuHdj8iy1odEzx4P1pkO99PjXc/H/0boYzedj/ZzvdT46V7P6E1F5KmVHw/45X8Yskvdj+BhaQpFWdvP/yp8dJNYnA/YF0Bcq+5cD8730+Nl25yP/yp8dJNYnA/BEZvy1odcz++F0t+seR3P9v5fmq8dHM/vhdLfrHkdz/6fmq8dJN4P0FQRm/LWm0//Knx0k1icD/b+X5qvHRzP+OV/GLJL3Y//kypOPvweT99t2Wtjgl+P9v5fmq8dHM/ZCtA7jUXcj8k9uEz7ApwP4mp8dJNYnA//Knx0k1icD/8qfHSTWJwP7pJDAIrh3Y/YgC511xIej+jYJ6ofyN0P5zEILByaHE/AHgwT9S/cT+BhaQpFWdvPzvfT42XbnI//kypOPvweT9/4uzDZ9h1P8Llifo3Qnk/38e95kLSdD8ERm/LWh1zP3npJjEIrGw/gYWkKRVnbz8AeDBP1L9xP2QrQO41F3I/PYIH80T9ez+hNReSplR8P7pJDAIrh3Y/PYIH80T9ez+Hfmq8dJN4P6E1F5KmVHw/I/nFkl8sqT/8qfHSTWKQP4FJDAIrh4Y/nitA7jUXgj+6SQwCK4eWP/yp8dJNYpA/2/l+arx0gz/sUbgeheuBP/5MqTj78Ik/K4cW2c73gz8Q0GkDnTaAP3npJjEIrHw/TtpApw10ij9MN4lBYOWQPy9VVVVVVYU/y6FFtvP9hD/vH/eaC0mDPxDQaQOdNoA/ENBpA502gD/dnDbQaQN9P92cNtBpA30/2c73U+Olez8CG+i0gU57P6E1F5KmVHw/ObTIdr6fij/b+X5qvHSDP4luEoPAyqE/O99PjZdukj+LbOf7qfGCP7gehetRuH4/XjJ6W9bqeD9kK0DuNRdyP3npJjEIrHw/nWfYFSD3ej956SYxCKx8P/5MqTj78Hk/+n5qvHSTeD+6SQwCK4d2P4OwK0DuNXc/g7ArQO41dz/C5Yn6N0J5P2IAuddcSHo/vhdLfrHkdz+DsCtA7jV3P6cu3SQGgXU/P62OCR7Mcz8CG+i0gU5rP/yp8dJNYnA/ZCtA7jUXcj/8qfHSTWJwP+OV/GLJL3Y/nWfYFSD3ej97FK5H4Xp0PzvfT42XbnI/wuWJ+jdCaT+4HoXrUbhuPyLLWh0TPHg/nWfYFSD3ej/+TKk4+/B5P+djO99PjXc/XjJ6W9bqeD8f/RuhjN52P5qZmZmZmXk/nWfYFSD3ej89ggfzRP17P0dJDAIrh3Y/2c73U+Olez/C5Yn6N0J5P51n2BUg93o/ukkMAiuHdj/C5Yn6N0J5P9nO91PjpXs/Q3vNhaQpdT/+TKk4+/B5P3npJjEIrHw//hARERERgT/8qfHSTWKAP4lfLPnFkp8/uoWkKRVnnz8U6t8IZfSWPyuHFtnO95M/wNmHz7ArsD81baDTBjq1P2wFyL3mQqI/aJHtfD81jj8vVVVVVVWFPzvfT42XboI/AHgwT9S/gT+BSQwCK4eGP317zYWkKYU/Mbx0kxgEhj+N0wY6baCDPyeLbOf7qZE/rDomeDBPlD+BSQwCK4eGPwrXo3A9Coc/QRSuR+F6hD+LbOf7qfGCP+2411xImoI/Er9Y8oslnz9q2kCnDXSaPz2CB/NE/Ys/UAXIveZCgj+gkl8s+cWCPz2CB/NE/Xs/eekmMQisfD+4HoXrUbh+P/4QEREREYE/uB6F61G4fj9/4uzDZ9h1P2BdAXKvuXA/38e95kLSdD+nLt0kBoF1P14yelvW6ng/gYWkKRVnfz/b+X5qvHSDP8Kp8dJNYoA/QVBGb8tafT9Onqh/I5SBP7DqmODBPIE//hARERERgT+cxCCwcmiBP92cNtBpA30/JpmZmZmZeT8CG+i0gU57P/5MqTj78Hk/38e95kLSdD8730+Nl25yP2IAuddcSHo/BEZvy1odcz8f/RuhjN52P8Llifo3Qnk//kypOPvweT8bL90kBoF1P4mp8dJNYnA/nMQgsHJocT9/4uzDZ9h1P4GFpCkVZ38/XvbhM+wKgD9BUEZvy1p9P7gehetRuH4/QVBGb8tafT+w6pjgwTyBP7DqmODBPIE/uB6F61G4jj8bL90kBoGFP66DeaL+jYA/2c73U+Olez956SYxCKx8P6E1F5KmVHw/vhdLfrHkdz85tMh2vp96P6E1F5KmVHw//Knx0k1igD9Onqh/I5SBP/zlifo3Qok/1XjpJjEIrD+q8dJNYhCoPyUkTak4+5A/rFjyiyW/iD8f/RuhjN6GP0EUrkfheoQ/8YYW2c73gz8/rY4JHsyDP7JRuB6F64E/TDeJQWDlgD/C5Yn6N0J5P7DqmODBPIE/PUZvy1odgz8OWmQ730+tP5wAuddcSJo/YJmZmZmZiT8gZDvfT42HP2wjlNHbsoY/H/0boYzehj/fx73mQtKEP0EUrkfheoQ/QRSuR+F6hD8vN4lBYOWQP/T91HjpJpE/HZb8Yskvhj9Onqh/I5SBP4ts5/up8YI/ENBpA502gD+w6pjgwTyBPz+tjgkezIM/DqXi7MNniD+uvxHK6G2JP9/HveZC0oQ/3WCeqH8jhD9BjZduEoOgP8u/EcrobZk/e1BGb8tajT9O2kCnDXSKP66/EcrobYk//kypOPvwiT9eMnpb1uqIP4FJDAIrh4Y/WDm0yHa+jz89CtejcD26P3e+nxov3bw/AB7ME/VvpD/j4TPsCpCbP0UQWDm0yJY/g8DKoUW2kz/N6pjgwTyRP1TjpZvEIJA/XvbhM+wKkD87G+i0gU6LPxtrdUzwYI4/7fRvhDJ6iz/pJjEIrByKP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP7ywK0DuNYc/wH5qvHSTiD9cy1odEzyIP89vhDJ6W4Y/2/l+arx0gz/b+X5qvHSDP54rQO41F4I/O99PjZdugj+POiZ4ME+EP8uhRbbz/YQ/i2zn+6nxgj/+EBERERGBP6E1F5KmVHw/XvbhM+wKgD8730+Nl26CP/yp8dJNYoA/Tp6ofyOUgT99e82FpCmFPwB4ME/Uv4E/TDeJQWDlgD+hNReSplR8P+FqdUzwYH4/uB6F61G4fj9YObTIdr5/PxzSlIqzD38/exSuR+F6hD+LbOf7qfGCPxDQaQOdNoA/4Wp1TPBgfj+ug3mi/o2AP06eqH8jlIE/sOqY4ME8gT/vH/eaC0mDPyuHFtnO94M/2/l+arx0gz9QBci95kKCP1AFyL3mQoI/2/l+arx0gz8v7AqQe82lPzNR/0Yoo5c/nAC511xIij+kcD0K16OQP+GY4ME8UZ8/y78RyuhtmT9Onqh/I5SRP4lBYOXQIos/IGQ730+Nhz+BSQwCK4eGP4FJDAIrh4Y/H/0boYzehj99e82FpCmFP486JngwT4Q/uB6F61G4fj9e9uEz7AqAP/yp8dJNYoA//Knx0k1igD8AeDBP1L+BP9v5fmq8dIM/nMQgsHJogT8CG+i0gU57P7DqmODBPIE/7x/3mgtJgz8730+Nl26CP+8f95oLSYM/zQhl9LashT8gZDvfT42HP31dAXKvuZA/9P3UeOkmkT/LoUW28/2kPxS9LWt1TKA/dc+wK0DulT+qD59hV4CcP4GVQ4ts55s/7bjXXEiakj9WSsXZh8+QP40Pn2FXgIw/DqXi7MNniD/85Yn6N0KJP4uofyOU0Ys/G2t1TPBgjj87G+i0gU6LPylcj8L1KIw//kypOPvwiT9uirMPn2GHP8B+arx0k4g//OWJ+jdCiT+sWPKLJb+IP5wAuddcSIo/ObTIdr6fij/FPnyGXQGSPy0qzj58ho0/gUkMAiuHhj9uirMPn2GHP4FJDAIrh4Y/ObTIdr6fmj9U46WbxCCQP8vd3d3d3Y0/YPS2rNUxoT8GvS1rdUyQP92cNtBpA40/umfYFSD3qj/rb4QyeluWP+xRuB6F65E/fV0Bcq+5kD9WSsXZh8+QP8u/Ecrobak/FL0ta3VMsD+8g3mi/o2gP1zLWh0TPJg/VmiR7Xw/lT+2TWIQWDmUP2bAyqFFtpM/5Qy7AuRekz+FJ+rfCGWUP2ZmZmZmZqY/K8OuALnXnD8G2/l+aryUP2RZq2OCB5M/xT58hl0Bkj9e9uEz7AqQPwoTPJgn6o8/uB6F61G4jj8c0pSKsw+PP40Pn2FXgIw/THMhaUrFiT9aZDvfT42HP8B+arx0k4g/mpmZmZmZiT9w8dJNYhCIP5qZmZmZmYk/DD7DrgC5hz+8sCtA7jWHP07aQKcNdIo/2c73U+Oliz85tMh2vp+KP9nO91PjpYs/6SYxCKwcij/Afmq8dJOIP/zlifo3Qok/boqzD59hhz9McyFpSsWJP0xzIWlKxYk/vLArQO41hz8OpeLsw2eIP8B+arx0k4g//OWJ+jdCiT++F0t+seSHPww+w64AuYc/rr8RyuhtiT8OpeLsw2eIPww+w64AuYc/gUkMAiuHhj8OpeLsw2eIP8B+arx0k4g/rFjyiyW/iD+8sCtA7jWHP8B+arx0k4g/rr8RyuhtiT85tMh2vp+KP07aQKcNdIo/ObTIdr6fij89ggfzRP2LP+kmMQisHIo/ObTIdr6fij8lJE2pOPuQP43TBjptoJM/nWfYFSD3ij9uirMPn2GHP80IZfS2rIU/bCOU0duyhj/hLt0kBoGFP3/i7MNn2IU/4S7dJAaBhT89Rm/LWh2DP/GGFtnO94M/kaFFtvP9hD8bL90kBoGFP89vhDJ6W4Y/vLArQO41hz/Pb4QyeluGP4FJDAIrh4Y/gUkMAiuHhj9O2kCnDXSKP7TmQtKUipM/nWfYFSD3ij/85Yn6N0KJP3Dx0k1iEIg/Le41F5KmhD9KDAIrhxaJPx/9G6GM3oY/qvHSTWIQiD/hLt0kBoGFP1AFyL3mQoI/kaFFtvP9hD8vVVVVVVWFPzvfT42XboI/nitA7jUXgj/sUbgeheuBPz1Gb8taHYM/gUkMAiuHhj/NCGX0tqyFP486JngwT4Q/gUkMAiuHhj9/4uzDZ9iFPx/9G6GM3oY/HZb8Yskvhj97FK5H4XqEP43TBjptoIM/gUkMAiuHhj8f/RuhjN6GP+Eu3SQGgYU/HZb8Yskvhj9/4uzDZ9iFP2wjlNHbsoY/L1VVVVVVhT+BSQwCK4eGP4FJDAIrh4Y/boqzD59hhz9uirMPn2GHPx/9G6GM3oY/gUkMAiuHhj9sI5TR27KGP2wjlNHbsoY/RvKLJb9Ykj+N0wY6baCTP3Wx5BdLfpE/k1ScffgMmz/+TKk4+/CJPxsv3SQGgYU/fXvNhaQphT9eMnpb1uqIP/5MqTj78Ik/wH5qvHSTiD8QDAIrhxaJPylcj8L1KIw/nAC511xIij9O2kCnDXSKP+uNUEZvy4o/+n5qvHSTiD/Afmq8dJOIP8B+arx0k4g/XMtaHRM8iD+amZmZmZmJP6xY8oslv4g/SgwCK4cWiT+q8dJNYhCIP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP74XS36x5Ic/nWfYFSD3ij8KEzyYJ+qPP3npJjEIrIw/XMtaHRM8iD8gZDvfT42HPx2W/GLJL4Y/gUkMAiuHhj/Pb4QyeluGP1pkO99PjYc/HZb8Yskvhj/pJjEIrByKP14yelvW6og/vhdLfrHkhz+BSQwCK4eGPxAMAiuHFok/K6Xi7MNnmD+FRbbz/dSYP2iR7Xw/NY4//kypOPvwiT+JQWDl0CKLP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP66/EcrobYk/ObTIdr6fij+05kLSlIqTP3tQRm/LWp0/dc+wK0DulT9mwMqhRbaTPzvfT42XbpI/VOOlm8QgkD8rw64AudeMP8l2vp8aL40/71uPwvUojD+JQWDl0CKLP9s1F5KmVIw/3Zw20GkDjT9sXyz5xZKPP2r4DLsC5I4/XvbhM+wKkD8730+Nl26SPy0qzj58ho0/OxvotIFOiz+dZ9gVIPeKP8B+arx0k4g/TtpApw10ij+cALnXXEiKP66/EcrobYk/boqzD59hhz8f/RuhjN6GP7pJDAIrh4Y/3WCeqH8jhD9uirMPn2GHP317zYWkKYU/8YYW2c73gz8f/RuhjN6GP6rx0k1iEIg/z2+EMnpbhj8MPsOuALmHPw6l4uzDZ4g/boqzD59hhz/Afmq8dJOIPyBkO99PjYc/wH5qvHSTiD9eMnpb1uqIPx2W/GLJL4Y/QRSuR+F6hD8vVVVVVVWFP486JngwT4Q/3WCeqH8jhD/vH/eaC0mDP8uhRbbz/YQ/arx0kxgEhj+RoUW28/2EPwrXo3A9Coc/38e95kLShD+N0wY6baCDP0EUrkfheoQ/QRSuR+F6hD99e82FpCmFP3/i7MNn2IU/f+Lsw2fYhT8f/RuhjN6GPyBkO99PjYc/z2+EMnpbhj8xvHSTGASGP9/HveZC0oQ/H/0boYzehj8dlvxiyS+GP4FJDAIrh4Y/jzomeDBPhD+POiZ4ME+EP91gnqh/I4Q/gUkMAiuHhj8MPsOuALmHP0xGb8taHbM/47SBThvotD9jvHSTGAS+P9ejcD0K18M/K4cW2c73sz/FILByaJGtPw48mCfq36g/P1Mqzj58pj83mCfq3wilP6w6JngwT6Q//tR46SYxsD/XXEiaUnHCP8mFpCkVZ7c/TmIQWDm0yD+PwvUoXI/CP5KKsw+fYbc/9Ay7AuResz/YQKcNdNqwP99PjZduErM/yXa+nxovtT/Jdr6fGi+9P2IfPsOuALk/Y62OCR7Msz8sJE2pOPuwP7TIdr6fGq8/JRVnHz7Drj85w64AudesP6a5kDSl4qw/1XjpJjEIrD+aqH8jlNGrPyajt2WtjrE/pqqqqqqqsj+EXQFyr7m4PzMzMzMzM8c/EBERERERxT/JhaQpFWe/P7Ks1THBg7k/aJHtfD81tj+aqH8jlNGzP5ZDi2zn+7E/vIN5ov6NsD8hv1jyiyWvP6aqqqqqqqo/Dkt+seQXqz956SYxCKysP65lrY4JHqw/CvVvhDJ6qz+JQWDl0CKrP2IuJE2pOKs/jZduEoPAqj/pJjEIrByqP4/vp8ZLN6k/vq4AuddcqD9IDi2yne+nP6Sd76fGS6c/I+rfCGX0pj8lFWcfPsOuPw5LfrHkF6s/02suJE2pqD9QukkMAiunPzNCGb0ta6U/+HGvuZA0pT9sFK5H4XqkPxkxCKwcWqQ/9Ay7AuReoz/b+X5qvHSjP6AaL90kBqE/cVvW6pjgoT8/NV66SQyiP0jwYJ6of6M/nNMGOm2goz+LbOf7qfGiP8U+fIZdAaI/cVvW6pjgoT91seQXS36hP/Cnxks3iaE/8KfGSzeJoT/jpZvEILCiPz81XrpJDKI/dbHkF0t+oT9Ei2zn+6mhP3Fb1uqY4KE/8KfGSzeJoT8AD+aJ+jeiP5MYBFYOLaI/fV0Bcq+5oD8730+Nl26iPz81XrpJDKI/GSIiIiIioj91ov6NUEavPzuYJ+rfCMU/n4zelrU6wj8jIiIiIiLGPyPb+X5qvLw/vSCwcmiRtT+R7Xw/NV6yP9prLiRNqbA/gaQpFWcfrj+e/o1QRm+rP8MT9W+EMqo/BpB7zYWkqT/XwTxR/0aoP1LW6pjgwaw/Rrbz/dR4qT+HNKXi7MOnPz9TKs4+fKY/hyW/WPKLpT+Le82FpCmlP7yhRbbz/aQ/EIXrUbgepT/jtIFOG+ikP1hXgNxrLqQ/bzBP1L8Rqj89CtejcD2qPzvuNReSpqQ/P0REREREpD/wtqzVMcGjP0jwYJ6of6M/UJx9+Ay7oj8UzBP1b4SiP6wrQO41F7I/rBxaZDvfrz933GsuJE2pPx+U0duyVqc/zwY6baDTpj/4ca+5kDSlP6A4+/AZdqU/ZGiR7Xw/pT+Le82FpCmlPxkxCKwcWqQ/4ZjgwTxRnz9U46WbxCCgP1g5tMh2vp8/c6QpFWcfnj+6haQpFWefPznSlIqzD58/Prbz/dR4sT9U8oslv1i6PwwCK4cW2bY/exSuR+F6wD95+Ay7AuS+P0upOPvwGbY/jZduEoPAsj+EXQFyr7mwP7x0kxgEVq4/LbKd76fGqz+P76fGSzepP/iAlUOLbKc/P1Mqzj58pj/0G6GM3palP2i+nxov3aQ/FNv5fmq8pD8EZfS2rNWxP99PjZduEtE/U1VVVVVV1z/0/dR46SbXP1mrY4IH894/GXYFyL3m1D9MN4lBYOXeP3GvuZA0pdo/irMPn2FX0j/ZzvdT46XRP0NERERERNo/iM+wK0Du0T/D9Shcj8LJP+hC0pSKs8c/BFYOLbKdyz9DRERERETIP/cMuwLkXsM/I9v5fmq8wD/dM+wKkHu9P8oT9W+EMro/OlH/Riijtz8aoYzelrW6P9mHz7ArQMY/OlH/Riijzz+4HoXrUbjCPydA7jUXkr4/VccED+aJzj8Bcq+5kDTVPxi9LWt1TMg/h8+wK0DuxT+nfyOU0dvCP2LJL5b8YsU/7TUXkqZUwD+5u7u7u7u7P85pA5020Lk/yOhtWatjuj9QjZduEoPQP3k/NV66ScQ/f3mi/o1Qvj+Nl24Sg8C6P5HtfD81Xro/AZ020GkDyT/hehSuR+HKP5qZmZmZmck/koqzD59hwz8zMzMzMzPDP1WA3GsuJL0/fLHkF0t+uT9xTPBgnqi3P9sIZfS2rL0/rNUxwYN5wj8/RERERES8PwcezBP1b7w/ocZLN4lBuD9JfrHkF0u2PwXzRP0bobQ/fMDKoUW2sz8DuddcSJqyPwRl9Las1bE/BGX0tqzVsT9wr7mQNKWyP3FM8GCeqK8/pH8jlNHbsj++rgC511y4P8w+fIZdAbo/n4zelrU6tj/Z3d3d3d21P4AH80T9G7k/WEiaUnH2uT+79Shcj8K1P05x9uEz7LI/WnMhaUrFsT/WFSD3mguxP4izD59hV7A/cUzwYJ6orz/N27JWxwSvP/nwGXYFyMU/VccED+aJyj+YbhKDwMrJPyjOPnyGXcU/R1Mqzj58xj+V/GLJL5bAP9prLiRNqbg/qWOCB/NEtT/wtqzVMcGzPzMzMzMzM7M/\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[11697]},\"__x__values\":{\"__ndarray__\":\"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fPsO+P/cMuwLkXsM/mpmZmZmZxT8nMQisHFrMP7VlrY4JHsg/w/UoXI/CzT9VxwQP5onOPwrXo3A9Css/6nw/NV66xT/0RP0boYzGPzTQaQOdNsg/BjptoNMGwj/KE/VvhDLKPwOBlUOLbMs/oozelrU6yj+YbhKDwMrNP1WA3GsuJM0/qvHSTWIQzD8MAiuHFtnKP0P9G6GM3so/zSLb+X5qyD+wcmiR7XzHP2yg0wY6bcw/w0s3iUFgxT/mbVmrY4K/P27LWh0TPMQ/k9HbslbHyD/61HjpJjHIP6gcWmQ738c/vHSTGARWvj9iEFg5tMjCPx/ME/VvhMo/BoGVQ4tsxz+cGi/dJAbFPxqhjN6WtcI/GQRWDi2yxT+yrNUxwYPJPwGdNtBpA80/TrgehetRzD8ta3VM8GDGP+8ZdgXIvcY/opvEILByxD+ONKXi7MPHP/T91HjpJsE/pQ102kCnyT8vlvxiyS/KP3sUrkfhesg/n4zelrU6wj/I6G1Zq2PGPwwCK4cW2cI/wSCwcmiRxT8O5on6N0LFP4RdAXKvucQ/K4cW2c73xz81F5KmVJzBP+kmMQisHMY/XnMhaUrFzT+lVJx9+AzDPwcezBP1b8A/2msuJE2pwD/ByqFFtvPBP9YVIPeaC8k/NReSplScxT9g5dAi2/nGP45Di2zn+7k/rbmQNKXiwD/l0CLb+X7CP/nwGXYFyME/dnd3d3d3wz/bslbHBA/KP8gvlvxiycc/q44JHswTxT+rjgkezBPBPywkTak4+8A/WmQ730+Nvz8JSVMqzj7AP5S1OiZ4MMM/7e7u7u7uwj9nA5020GnDPz/uNReSpsQ/+yqHFtnOtz/ZzvdT46W7P9dcSJpSccI/uB6F61G4vj9qdUzwYJ7IPw4tsp3vp9I/lrU6Jngw2z+oxks3iUHYPwnzRP0bodQ/x73mQtKU0D8Sg8DKoUXKP0x+seQXS8I/XI/C9Shcxz+4HoXrUbjGPzKl4uzDZ8g/AFYOLbKdxz/HWh0TPJi/PxS9LWt1TLA/FpKmVJx9xD8bL90kBoHBP70RyuhtWcM/iyW/WPKLxT94W9bqmODBP+iY4ME8UcM/jZduEoPAyj+VUnH24TO8P26EMnpb1ro/xJJfLPnFsj9aHRM8mCfCP7as1THBg8E/L5b8Yskvwj/L6G1Zq2PCP+WJ+jdCGcE/FpKmVJx9wD+HJb9Y8ou9Px/ME/VvhMI/exSuR+F6wD+DwMqhRbbDP/2NUEZvy8I/EyD3mgtJwz8bPsOuALm/P8mFpCkVZ7c/835qvHSTuD/GveZC0pS6P9dcSJpSccI/mQtJUyrOvj8K5on6N0K5Pwy7AuRec8E/ZmZmZmZmvj/hifo3Qhm1P3n4DLsC5LY/SOF6FK5HuT97W9bqmODBP5fgwTxR/74/o+Lsw2fYvT/0/dR46SbBP4lBYOXQIrs/V6tjggfztD9GxdmHz7C7PywkTak4+7A/8UT9G6GMwj+ZC0lTKs6+P5s20GkDncI/Q/0boYzewj8tsp3vp8a7P2cSg8DKobU/DBERERERuT/pJjEIrBy6Pyr5xZJfLME/4hdLfrHkwz8sJE2pOPu4Pwi7AuRec7k/FVpkO99PvT+LbOf7qfG6P/y411xImro/CUlTKs4+vD9pLiRNqTi7P6/kF0t+scA/WwFyr7mQwD/1mgtJUyq+Pz9ERERERLw/JQaBlUOLvD+411xImlLBP9dcSJpSccY/szomeDBPyD9Z1uqY4MHEP/WaC0lTKsY/HBM8mCfqwz8QERERERHBP5lScfbhM8A/mQtJUyrOvj/Zh8+wK0DCP95rLiRNqcA/BfNE/RuhvD+bNtBpA53CPyVcj8L1KMA/2/l+arx0uz8twYN5ov61P1TjpZvEILg/7yhcj8L1uD956SYxCKzAP4n6N0IZvcE/XI/C9Shcvz8daUrF2Ye/P2OtjgkezLM/vSCwcmiRtT+kfyOU0duyP9nO91Pjpas/Q/0boYzevj/RaQOdNtDBP4GkKRVnH74/315zIWlKtT+DsCtA7jV3v7Kd76fGS6c/kfxiyS+WtD85w64Aude0P0P9G6GM3rY/sbmQNKXiwD9uy1odEzzAP8CDeaL+jcA/RIts5/upuT/ZzvdT46WzP3hb1uqY4LE/QmDl0CLbuT/Vh8+wK0C+P+3u7u7u7r4/mzbQaQOdvj+uVscED+a5P5VScfbhM7w/SX6x5BdLtj9LuB6F61GwP6aqqqqqqrI/EQRWDi2ytT//gJVDi2y/P9TqmODBPLk/yiLb+X5qvD8GOm2g0wbKP+f7qfHSTbI/umfYFSD3qj/bCGX0tqylP7Ks1THBg7k/USrOPnyGvT+W76fGSze5PxMREREREbE/lVJx9uEzrD/MPnyGXQGyP6JUnH34DLs/FUt+seQXsz9bAXKvuZDAP0jhehSuR7k/YJ6ofyOUwT8vlvxiyS/CP6G3Za2OCbY/9ZoLSVMqvj9FKKO3Za2+P5fgwTxR/74/wIN5ov6NwD81F5KmVJzBP9mHz7ArQMI/kxgEVg4twj81baDTBjq9P8oi2/l+arw//3GvuZA0vT/KE/VvhDK6Px+U0duyVr8/ToDcay4krT/6jVBGb8uqPzjQaQOdNsw/iUFg5dAisz+9EcrobVmzP0//Riijt7U/eyOU0duytj/Bdr6fGi+9P7SBThvotME/zczMzMzMtD+3kDSl4uyzP0u4HoXrUbg/olScffgMqz+GiIiIiIiwP6JUnH34DLM/NNBpA502uD/Xo3A9CtezP7yDeaL+jbg/7xl2Bci9tj8rhxbZzvezP6oAuddcSLI/AC2yne+npj8Gn2FXgNyrP6AaL90kBrk/anVM8GCewD9U8oslv1i6P6JUnH34DLs/5m1Zq2OCtz86Uf9GKKO3P+rDZ9gVILc/RtS/EcrorT8bPsOuALm3P2GCB/NE/bM/7oslv1jyuz/Xo3A9Cte7P0MMAiuHFrk/cukmMQistD+c0wY6baCzP0jwYJ6of7M/DjyYJ+rfuD/P91PjpZu8P3qGXQFyr7k/TEZvy1odsz/2fmq8dJPAP2LJL5b8YsE/oBov3SQGwT8WkqZUnH3AP17JL5b8Yrk/SPBgnqh/uz8v7AqQe829P7EPn2FXgLQ/kyfq3whltD/hifo3Qhm1Pyr5xZJfLLk/6JjgwTxRtz+6WPKLJb+4P28Sg8DKob0/RsXZh8+wuz9wr7mQNKW6P5H8Yskvlrw/SZpScfbh1T8Bcq+5kDThP02pOPvwGdQ/0r8RyuhtyT9+I5TR27LGP788Uf9GKLs/rwC511xI0D83Qhm9LWvXP+f7qfHSTc4/puLsw2fYzT/CrgC511zIP4cW2c73U8c/LWt1TPBgxj9TnH34DLvGPzgmeDBP1L8/1hUg95oLuT/LsCtA7jW/P9eyVscED74/qWOCB/NEvT+F+jdCGb29P19mZmZmZrY/rbmQNKXiwD9Fb8taHRPAP7ByaJHtfL8/vzxR/0Youz8iTak4+/C5P+tgnqh/I7w/Vg4tsp3vtz+JUEZvy1q9P8uhRbbz/bw/7e7u7u7uvj/7KocW2c63P+GJ+jdCGbU/9Ay7AuResz/7G6GM3pa1PwXzRP0bobw/sHJoke18vz//ca+5kDS9P/C2rNUxwbs/vSCwcmiRtT/ffD81XrqpP4RdAXKvubA/xS+W/GLJrz/kQtKUirO3P/Y3Qhm9Lbs/n4zelrU6tj/2Riijt2WtP2ig0wY6bbA/wiLb+X5qrD+bRbbz/dSwP+XfCGX0trQ/JQaBlUOLvD92ME/UvxG6P83bslbHBLc/ZErF2YfPuD8dWmQ730+tPxTME/VvhJI/G2t1TPBgnj8MIPeaC0mjP5ELSVMqzq4/O+41F5KmpD9oke18PzW+P0upOPvwGbY/RJpScfbhsz/8uNdcSJqiPyHdJAaBlaM/x0s3iUFgpT/aehSuR+GyPyr5xZJfLLk/VYDcay4ktT8MuwLkXnPFP8CDeaL+jcA/olScffgMsz/OaQOdNtCxPz628/3UeLE/ZdgVIPeasz9MRm/LWh27Pw/ZzvdT47U/Y7x0kxgEtj+TGARWDi2yP5MYBFYOLaI/fXvNhaQplT9cnqh/I5ShP6JyaJHtfK8/bxKDwMqhwT+q8dJNYhDAP3QFyL3mQro/iVBGb8tarT+kcD0K16OwP/NE/RuhjOU/NdBpA532F0C/WPKLJX8VQHd3d3d39wFAagOdNtBp9D+N3pa1OqbwPx+F61G4HuE/pw102kCn1T9KN4lBYOXSP/+NUEZvy9A/4TPsCpB70T+Isw+fYVfEPwGdNtBpA8U/iF0Bcq+51D8GgZVDi2zLP/4qhxbZzss/awOdNtBpyz+pqqqqqqrKPzHBg3mi/sk/Gy/dJAaBxT8aoYzelrXCPzPsCpB7zcU/sQ+fYVeAwD+DsCtA7jV3P8w+fIZdAcI/0SLb+X5qwD8WkqZUnH3EP1NVVVVVVcE/JurfCGX0wj8hsHJoke28P3qGXQFyr7k/GHYFyL3msj+kcD0K16O4PyPq3whl9LY/h8+wK0DuwT8hv1jyiyW/P2q8dJMYBL4/PqcNdNpAvz/LoUW28/20P6AaL90kBrE/V6tjggfztD9iEFg5tMi2P8oT9W+EMro/X0iaUnH2uT+HFtnO91O7P6oAuddcSLo/E9nO91PjzT800GkDnTa4P1pzIWlKxbE/O99PjZdusj91ov6NUEa/P/1VDi2ynbc/olScffgMuz8QZx8+w664P5H8Yskvlrw/DZ9hV4Dcsz92ME/UvxGyP7eQNKXi7LM/CLsC5F5zuT9dLPnFkl+0P85pA5020LE/tNdcSJpSuT8F80T9G6G0P7pY8oslv7A/it6WtTomsD/4U+Olm8SwP6JFtvP91Lg/CuaJ+jdCuT/HWh0TPJi3P/sboYzelrU/9Ay7AuResz8gIiIiIiKyP9CUirMPn7E/+n5qvHSTsD8v7AqQe821P6UcWmQ737c/17JWxwQPtj/wtqzVMcGzP99PjZduErM/PRm9LWt1rD++rgC511yoP05x9uEz7LI//4CVQ4tstz8HLbKd76e2P/NvhDJ6W7Y/4OzDZ9gVuD8xCKwcWmSzP7ByaJHtfK8/4ZjgwTxRrz/JhaQpFWevP1e6SQwCK7c/nu+nxks3sT+F+jdCGb2tP2xZq2OCB7M/c3d3d3d3pz9I4XoUrkexP/ZGKKO3Za0/MSZ4ME/Urz+JUEZvy1q1P2Xn+6nx0rU/szomeDBPvD/HSzeJQWDBPyJNqTj78Lk/boQyelvWsj/nCpB7zYW0PzB6W9bqmLA/FVpkO99PtT/vGXYFyL22P+GJ+jdCGbU/I/nFkl8sqT850pSKsw+vP8oT9W+EMrI/WDm0yHa+tz+Isw+fYVfAP9uyVscED8I/OW2g0wY6wT8030+Nl266P9v5fmq8dLs/6SYxCKwc7j/MWh0TPJj4P4slv1jyi90/+JoLSVMqzj+MCR7ME/XHP3tb1uqY4M0/UI2XbhKDwD+Isw+fYVfAP9OUirMPn8E/A8i95kLSxD807AqQe83hPwisHFpkO+I/Q0RERERE1j+95kLSlIrVP/+411xImtA/xgQP5on6xz/IL5b8YsnHPzdCGb0ta8E/XI/C9Shcvz9OcfbhM+y6Py1rdUzwYMI/+sWSXyz5wT/RMcGDeaK+P9eyVscED7Y/8KfGSzeJuT8AAAAAAACwP/LSTWIQWLE/AAAAAAAAuD9N1L8Ryui9P7TIdr6fGr8/8Las1THBuz9oke18PzW2P8DobVmrY6I/Lk/UvxHKuD9RKs4+fIa9P0xGb8taHbM/boQyelvWuj+gGi/dJAbBP3yx5BdLfsk/c9pApw100D9A0pSKsw/HP6UNdNpAp70/7f3UeOkmuT9sWatjgge7P6ud76fGS78/vp8aL90kvj9JfrHkF0u+PyBpSsXZh8c/HveaC0lTwj9gnqh/I5TBPyjOPnyGXbk/mG4Sg8DKuT9raJHtfD+9PxEEVg4tsrU/mQtJUyrOvj+kfyOU0du6PylrdUzwYLY/3ULSlIqzrz800GkDnTawP+Olm8QgsLI/c3d3d3d3vz84JngwT9S3P6G3Za2OCb4/uB6F61G4vj8xF5KmVJy1P37cay4kTbE/jZduEoPAsj+9EcrobVmzP5+M3pa1OrY/S6k4+/AZtj/hehSuR+GqP7EPn2FXgLQ/MHpb1uqYsD/y8Bl2BcitPzpg5dAi27E/IDEIrBxatD/g7MNn2BW4P0diEFg5tLg/KVyPwvUorD+BhaQpFWdvP4pMqTj78Gm/1XjpJjEIrD9SuB6F61GwP5VhV4Dca64/Ll66SQwCsz8PyuhtWauzP9v5fmq8dLM/LcGDeaL+rT/bCGX0tqylP7YRyuhtWas/LCRNqTj7sD9Ei2zn+6mxP9LO91PjpbM/IlyPwvUotD9OcfbhM+yqPwPIveZC0rQ/FK5H4XoUwj8nMQisHFrAP7ySXyz5xaI/cVvW6pjgoT/l0CLb+X6yP6jVMcGDebI/pI4JHswTpT8zb8taHROcP3OkKRVnH54/vRHK6G1Zsz9KDAIrhxapP91RuB6F66E/kfxiyS+WtD/hifo3Qhm1P+rSTWIQWLE/BFYOLbKdrz8R9W+EMnqzP0ob6LSBTqs/9CqHFtnOpz/81qNwPQqnP7Ks1THBg7E/5/up8dJNuj8JWDm0yHa2P7efGi/dJLY/SOF6FK5HsT9KKs4+fIatPzVeukkMAqs/x1odEzyYpz8o3SQGgZWzP+xRuB6F67k/iVBGb8tarT/y0k1iEFixP7g8Uf9GKKM/sJ8aL90kpj/4U+Olm8SgPyl6W9bqmKA/gjJ6W9bqsD8K16NwPQq3P9V46SYxCLQ/boQyelvWsj9t9uEz7AqwP/LSTWIQWLE/9kYoo7dlrT82+/AZdgWwP99PjZduEsc/lyfq3whl2D/IL5b8YsnPP2XYFSD3msM/WxBYObTItj9S1uqY4MGsP4aIiIiIiLA/PSijt2Wtrj94W9bqmOC5P2rLWh0TPLg/cUzwYJ6otz9eukkMAiu3P3QFyL3mQrI/hyW/WPKLpT97I5TR27KmP7p2vp8aL60/0THBg3mitj/31HjpJjG4P/1GKKO3ZbU/7FG4HoXruT/uiyW/WPKrP3OGXQFyr6k/4ZjgwTxRnz8pelvW6pigPzb78Bl2BbA/aKDTBjptuD/hmODBPFGvP83bslbHBK8/WoIH80T9qz8QWDm0yHa2P5iM3pa1OqY/sIFOG+i0oT+2AuRecyGxP+IXS36x5Lc/kG4Sg8DKuT8sJE2pOPuwPx73mgtJU7I/YBKDwMqhpT+TRbbz/dSoP2D0tqzVMaE/vIN5ov6NsD9JfrHkF0u2P26EMnpb1rI/vr3mQtKUqj/fXnMhaUqlPxBnHz7DrqA/VOOlm8Qg3j9kggfzRP3kP8TZh8+wK94/pzj78Bl2xT8QZx8+w664P7CBThvotLk/ZwOdNtBpsz89KKO3Za2uPydP1L8Ryqg/8Las1THBoz+3kDSl4uyzPzb78Bl2Bbg/gAfzRP0bsT+0yHa+nxq3P4GkKRVnH7Y/+FPjpZvEoD/A6G1Zq2OiPxKDwMqhRaY/O99PjZdusj/jpZvEILC6PwAAAAAAALg/dZMYBFYOtT8R9W+EMnqzP28haUrF2ac/xT58hl0Boj+Bsw+fYVegP+lE/RuhjK4/TmIQWDm0sD9G1L8RyuitPw5LfrHkF6s/rgC511xIwj/Q27JWxwTLP6BhV4Dca8I/jAkezBP1tz+CMnpb1uq4P/p+arx0k7g/ubu7u7u7sz97I5TR27K2PwI6baDTBro/8KfGSzeJwT9mdUzwYJ64P03UvxHK6LU/dBSuR+F6tD88i2zn+6m5P65WxwQP5rk/c3d3d3d3tz9HUyrOPnzCP9ejcD0K18c/GL0ta3VMxD9Ei2zn+6nBPwIrhxbZzr8/ubu7u7u7uz+uR+F6FK63P+cKkHvNhbQ/QmDl0CLbsT/LsCtA7jWnP17JL5b8Yqk/ke18PzVeqj9iHz7DrgCxP9s1F5KmVJw/CbdlrY4Jbr8VqfHSTWJgP1yPwvUoXK8/PRm9LWt1rD+W76fGSzexP3sUrkfheqQ/hxbZzvdTsz/qw2fYFSC3P8MED+aJ+rc/boQyelvWuj/dJAaBlUPLP3LaQKcNdLI/BfNE/RuhtD/N27JWxwS3P3qGXQFyr7k/j9HbslbHvD/fT42XbhK7Pyr5xZJfLLk/EfVvhDJ6sz+o1THBg3miP0j/Riijt6U//Me95kLSpD/mfD81XrqxP90kBoGVQ7M/ObTIdr6fsj81fIZdAXKvP1LHBA/miao/iV8s+cWSnz+kfyOU0duiP/DFkl8s+aU/jZduEoPAqj+TGARWDi2yPx73mgtJU7I/DjyYJ+rfsD9q2kCnDXSqP5zEILByaKE/FL0ta3VMoD9g9Las1TGhP+k1F5KmVKw/pH8jlNHbsj96hl0Bcq+xP7yDeaL+jbA/y78RyuhtqT8K16NwPQqXP8uhRbbz/ZQ//Me95kLSlD/rfmq8dJOoP/yp8dJNYrA/gaQpFWcfrj/clrU6JniwP/LSTWIQWKk/byFpSsXZpz8zYOXQItupP7yDeaL+jaA/x0s3iUFgpT99PzVeukmsP0mNl24Sg7A/MSZ4ME/Urz8nT9S/EcqoP6SOCR7ME6U/zxUg95oLqT8q+cWSXyy5P9YVIPeaC7k/CKwcWmQ7tz/jpZvEILCyP2ig0wY6bbA/CNnO91PjpT+wgU4b6LShP6ApFWcfPqM/i4qzD59hpz/clrU6JniwP+Olm8QgsLo/JHgwT9S/uT/hifo3Qhm1P5ELSVMqzq4//NajcD0Kpz9mhDJ6W9aqP5zx0k1iEKg/RtS/EcrorT/0/dR46SaxPxKSplScfbA/KWt1TPBgrj9OgNxrLiStP6oPn2FXgJw/2c73U+Olmz+sK0DuNReiP/LhM+wKkKs/9jdCGb0tsz9bAXKvuZC0PxkTPJgn6q8/TdS/EcrowT8pa3VM8GC+P5KZmZmZmbk/qWOCB/NEtT+75kLSlIqzP7VlrY4JHrQ/RsXZh8+wsz/A2YfPsCuwP17JL5b8Yqk/72CeqH8jyD9NYhBYObTiPxm9LWt1TOI/+H5qvHST0D/t7u7u7u7GPwisHFpkO88/YYIH80T9yz+QbhKDwMq5P7Ks1THBg7E/IlyPwvUotD877jUXkqa0P2k9CtejcL0/EfVvhDJ6wz+Dz7ArQO69P7CBThvotLk/FfVvhDJ6xz91kxgEVg7BPwctsp3vp7Y/X1eA3GsutD/3xZJfLPm1P/QboYzelqU/jXcwT9S/UT8bGui0gU5bv5zEILByaKE/VB8+w64AmT+HFtnO91OjP/DFkl8s+aU/kxgEVg4tsj/dM+wKkHu1P/zHveZC0qQ/Yh8+w64AsT9tLiRNqTjLP9v5fmq8dKM/wNmHz7AroD9sBci95kKiPyr5xZJfLLE/aJHtfD81tj/l7u7u7u6uP4GkKRVnH64/NvvwGXYFsD+2AuRecyGpP6SOCR7ME6U/RJpScfbhoz9BfrHkF0uuP2cDnTbQabM/UtbqmODBrD/PFSD3mgupP5h9+Ay7AqQ/tNdcSJpSoT+yu7u7u7ubP31dAXKvuaA/YOXQItv5rj+aqH8jlNGzP/LSTWIQWLE/SOF6FK5HsT9mZmZmZmamPxK/WPKLJZ8/FMwT9W+Eoj9YZmZmZmamPxtcj8L1KKw/+FPjpZvEsD8daUrF2YevP1Ys+cWSX6w/L+wKkHvNpT/TTWIQWDmUPx2W/GLJL5Y/e1BGb8tanT/4ca+5kDSlPxkEVg4tsq0/umfYFSD3qj9mdUzwYJ6oP7qFpCkVZ58/lX8jlNHbkj9zpCkVZx+eP6wrQO41F6I/atpApw10qj/WFSD3mguxPzb78Bl2BbA/4Yn6N0IZrT8IyuhtWaujP9OJ+jdCGZ0/dc+wK0DulT8nMQisHFqkP1hImlJx9rE/AA/mifo3uj86Uf9GKKO/P26EMnpb1ro/sHJoke18rz+RC0lTKs6eP4P8Yskvlpw/WoIH80T9mz+VUnH24TOsP7gehetRuK4/CbdlrY4JXj/8qfHSTWJwv3sUrkfheoS/bCOU0duyhr9BUEZvy1ptP4uofyOU0Ys/9BuhjN6WpT8ozj58hl2xP421OiZ4MK8/2c73U+Olqz+gKRVnHz6jP2ig0wY6baA/YgC511xIej9YSJpScfahP/LwGXYFyJ0/uC1rdUzwsD+gGi/dJAahP0jwYJ6of6M/bAXIveZCoj/wtqzVMcGjPxDQaQOdNoA/N4lBYOXQoj8AAAAAAACgP7nKoUW287U/DCD3mgtJoz+RC0lTKs6uPxaSplScfcQ/bxKDwMqhtT97Mnpb1uqYP/zlifo3Qpk/8MWSXyz5pT/pNReSplSsPylrdUzwYK4/H4XrUbgepT+011xImlKhPznhehSuR6E/4+Ez7AqQmz+05kLSlIqTP99PjZduEqM/02suJE2pqD+HJb9Y8oulP/QboYzelqU/uC1rdUzwoD/bNReSplSMP66/EcrobYk/7fRvhDJ6iz8QdgXIveaiP65H4XoUrqc/46WbxCCwoj8bPsOuALmnP4cW2c73U6M/641QRm/Lmj8EdNpApw2UP91gnqh/I4Q/j8L1KFyPoj/2N0IZvS2zP8UgsHJoka0/tgLkXnMhqT+yne+nxkunP9FApw102qA/dbHkF0t+oT/nCpB7zYWkP7K7u7u7u6s/A8i95kLStD98wMqhRbazP8HKoUW2860/17JWxwQPpj99e82FpCmVP9nO91PjpZs/9oLAyqFFlj91seQXS36hPylrdUzwYK4//LjXXEiasj/OeOkmMQi0P90kBoGVQ6s/62CeqH8jpD+uVscED+apP0F+seQXS54/qNUxwYN5oj+q8dJNYhDWP8m95kLSlPE/kDSl4uzD9j8Sg8DKoUXSP5TEILByaLk/l+DBPFH/tj8/RERERES0P1pzIWlKxbk/ctpApw10sj85tMh2vp96PyjEILByaHE/LbKd76fGqz933GsuJE2pP88GOm2g06Y/DBERERERoT/jpZvEILCyPzEIrBxaZLM/GHYFyL3msj+lDXTaQKe1P6oPn2FXgKw/Gy/dJAaBlT8QWDm0yHaeP/zHveZC0qQ/ppvEILBysD+YjN6WtTqmP4GVQ4ts56s/uC1rdUzwsD9RKs4+fIa1P4uKsw+fYZc/PUZvy1odkz+kjgkezBOlPxfotIFOG6g/fLHkF0t+sT+AB/NE/RuxPy/dJAaBlbM/dc+wK0DulT9sI5TR27KWPxkEVg4tsn0/04n6N0IZnT9c6SYxCKycP+XQItv5frI/KWt1TPBgrj8JSVMqzj60P99ecyFpSqU/JSRNqTj7kD+8sCtA7jWHP/T91HjpJpE/XJ6ofyOUoT9t5/up8dK1P6SOCR7ME6U/UrgehetRsD/mbVmrY4LDP2Z1TPBgnrg/6UT9G6GMrj9Ei2zn+6mhP5kaL90kBrE/mH34DLsCtD82+/AZdgW4P9Ei2/l+aqw/CKwcWmQ7nz/A2YfPsCugP0SLbOf7qaE/THMhaUrFmT9YSJpScfahPz+tjgkezHM//Knx0k1iQD8+4OzDZ9hFP0N7zYWkKXW/WDm0yHa+f7/6fmq8dJNov8vd3d3d3Z0/VkrF2YfPkD9BfrHkF0ueP5iM3pa1OqY/L90kBoGVoz8j+cWSXyyZP4Un6t8IZZQ/exSuR+F6lD+0BA/mifqXP0xVVVVVVaU/sqzVMcGDsT/l0CLb+X6qP5NFtvP91Kg//OWJ+jdCmT87G+i0gU6LP0byiyW/WJI/XMtaHRM8mD83iUFg5dCiP4izD59hV7A/kpmZmZmZuT/fCGX0tqzJP8u/Ecrobak/UtbqmODBnD9DxwQP5omaP5HtfD81Xpo/62CeqH8jpD/w1HjpJjGoP+F6FK5H4ao/6SYxCKwcsj8/NV66SQyiP/5MqTj78Ik/FOrfCGX0lj/pRP0boYyeP5M20GkDnaY/eekmMQisrD/Tay4kTamoPznSlIqzD68/qMZLN4lBoD/rb4QyeluWP7TXXEiaUqE/gZVDi2znmz8730+Nl26iP2Z1TPBgnqg//vJE/RuhrD8pa3VM8GCuP8mUirMPn6E/TDeJQWDlgD9De82FpCl1v2IAuddcSHq/nK8rQO41V7/8qfHSTWJgP/yp8dJNYjA/GxrotIFOS78KEzyYJ+qfPzEIrBxaZJs/gYWkKRVnfz8CSVMqzj6cPylcj8L1KJw/TnH24TPsqj/fT42XbhKjP+F6FK5H4ao/xrPIdr6fej9Onqh/I5SRP43TBjptoJM/ptdcSJpSkT99t2Wtjgl+P3kH80T9G6E/L90kBoGVoz8AD+aJ+jeiP7Ks1THBg6k/PYIH80T9iz8OpeLsw2eIPz1Gb8taHZM/30+Nl24Soz9WLPnFkl+sP9NrLiRNqag/sQ+fYVeAxD9LuB6F61G4PzNR/0Yoo5c/0UCnDXTaoD8UvS1rdUygPzm0yHa+n5o/6UT9G6GMnj9g5dAi2/meP6ApFWcfPrM/L/vwGXYFqD/6fmq8dJOoP9Ei2/l+aqw/TGQ730+Npz/hehSuR+GqP0bUvxHK6K0/Bp9hV4Dcqz9OcfbhM+yqPyPq3whl9KY/qOQXS36xpD9Cb8taHROsPy2yne+nxqs/J0DuNReSpj/uiyW/WPKrP/N+arx0k7A/GHYFyL3msj/4gJVDi2ynPyl6W9bqmKA/O99PjZduoj9I4XoUrkehP5ELSVMqzp4/hQkezBP1rz+dYVeA3Gu2P19XgNxrLsA/p0fhehSutz+F61G4HoWzP9nO91Pjpas/l5vEILByqD8SkqZUnH2oPzsb6LSBTps/CbdlrY4JXr++F0t+seR3v8l2vp8aL42/4Wp1TPBgfr/EEBERERFhv+xRuB6F64E/K8OuALnXnD8EdNpApw2kP/hiyS+W/KI/BHTaQKcNpD8UzBP1b4SiP9nsw2fYFaA/K4cW2c73gz/wtqzVMcGjP5MYBFYOLZI/aJHtfD81rj8OS36x5BerP2aEMnpb1qo/sCYxCKwcij/pJjEIrByKP323Za2OCX4/WmQ730+Nlz956SYxCKyMPx+yne+nxqs/xJJfLPnFsj/6nDbQaQOdPxK/WPKLJZ8/Zs73U+Olez97FK5H4XqEP26Ksw+fYYc/xT58hl0Bkj+8g3mi/o2gP8/3U+Olm6Q/i3vNhaQppT/Jdr6fGi+NPxtNqTj78Kk/jdMGOm2gkz8v3SQGgZWjP81E/RuhjI4/02suJE2pqD9I4XoUrkehP323Za2OCY4/8vAZdgXInT8mmZmZmZl5P1724TPsCpA/LdBpA502kD/N6pjgwTyRP2xfLPnFko8/EFg5tMh2nj8MERERERGhPz9iEFg5tKg/4ZjgwTxRnz/VlrU6JniQP4ts5/up8ZI/02suJE2pmD9sBci95kKiP+FqdUzwYH4/CvVvhDJ6mz8ML90kBoGlP9WWtTomeJA/exSuR+F6dL/6fmq8dJNoPx+U0duyVqc/i2zn+6nxkj+eK0DuNReSP6ljggfzRME/p0fhehSuvz87G+i0gU6LP1724TPsCoA/3Zw20GkDfT+0Itv5fmqcP5iM3pa1OqY/sJA0peLsoz/4U+Olm8SgP0oMAiuHFok/tAQP5on6lz8QWDm0yHaeP8HKoUW2850/sru7u7u7mz9sBci95kKiP4/C9Shcj6I/mH34DLsCpD+iRbbz/dSYP+30b4Qyeos/FL0ta3VMoD/Jdr6fGi+dP32ZmZmZmZk/G02pOPvwmT95B/NE/RuhPydP1L8Ryqg/RJpScfbhoz+yne+nxkuXP54rQO41F5I/LSrOPnyGjT9EqTj78BmWP/QMuwLkXqM/6UT9G6GMnj8EkqZUnH2YP0xzIWlKxYm/xT58hl0Bkr9Onqh/I5SRvwisHFpkO4+/eekmMQisjL85tMh2vp9qvx1Fb8taHUM/AiuHFtnOpz85tMh2vp+aPwm3Za2OCW4/g96WtTommD8f/RuhjN52v/qcNtBpA50/nOLsw2fYlT/jw2fYFSCXP0w3iUFg5ZA/fV0Bcq+5kD9eMnpb1uqIP2q8dJMYBJY/uB6F61G4jj+oxks3iUGgP6xY8oslv5g//hARERERkT+iY4IH80SdP31OG+i0gbY/PUZvy1odkz+Bsw+fYVegP4EW6LSBTju/c2iR7Xw/lT+6haQpFWefP0F+seQXS54/YOXQItv5nj/8qfHSTWJwv7ySXyz5xZI/ukkMAiuHZr+4LWt1TPCgP8MT9W+EMpo/WoIH80T9qz+udJMYBFauPxkiIiIiIqI/kyfq3whlpD+sWPKLJb+IP395ov6NUKY/z2+EMnpbhj/NCGX0tqyVPzvuNReSpqQ/38e95kLSdD+2AuRecyGpPxB2Bci95qI/4Wp1TPBgfj9g9Las1TGhP4EW6LSBTjs/EHYFyL3moj8bTak4+/CZP/Cnxks3iaE/pI4JHswTpT8G6SYxCKx8PzvfT42XbpI/YF0Bcq+5gL+yUbgeheuBP9v5fmq8dIM//Me95kLSpD9eMnpb1up4P0SLbOf7qZE/zKyOCR7MYz8K2ezDZ9glP4pMqTj78Gk/38e95kLSdD/fx73mQtKEPyP5xZJfLKk/SPBgnqh/oz8K16NwPQqXP3npJjEIrGw/eekmMQisfD8iy1odEzx4P0N7zYWkKXU/XjJ6W9bqiD87DAIrhxapP99ecyFpSqU/0SLb+X5qnD+iY4IH80SdPz7g7MNn2EW/fbdlrY4Jjj8bGui0gU5Lv5ELSVMqzp4/aJHtfD81nj+gKRVnHz6jPwoTPJgn6p8/f+Lsw2fYhT95B/NE/RuhP5yvK0DuNVc/EGcfPsOuoD/pRP0boYyePwisHFpkO48/17JWxwQPpj/VtIFOG+iUPy83iUFg5ZA/CbdlrY4Jbj+R7Xw/NV6aP2iR7Xw/NY4/AHgwT9S/gT8AeDBP1L9xvydA7jUXkqY/roN5ov6NgD+ND59hV4CMP4pMqTj78Fm/FMwT9W+Ekj/NRP0boYyOP+2411xImpI/MQisHFpkmz/sUbgeheuRP/C2rNUxwaM//Knx0k1iML/vW4/C9SiMPx1Fb8taHUO/avgMuwLkjj8KEzyYJ+qfP06eqH8jlIE/uB6F61G4jj9eMnpb1uqIP3Noke18P5U/nitA7jUXkj/jpZvEILCSP7Ks1THBg6k/bAXIveZCoj/sUbgeheuhP+F6FK5H4Zo/CvVvhDJ6mz99PzVeukm0P6w6JngwT5Q/i2zn+6nxkj+dZ9gVIPeKP1TjpZvEIJA/FMwT9W+Ekj88tWWtjglOP3Noke18P5U/Fy/dJAaByT8nQO41F5KmP2JM8GCeqJ8/kQtJUyrOnj8ZBFYOLbKdPxTq3whl9JY/WoIH80T9mz9I8GCeqH+jP4ts5/up8bI/yXa+nxovwT8rhxbZzvfDP5X8YskvlsA/M0IZvS1rtT/clrU6JniwPywkTak4+7A/MqXi7MNnuD9mdUzwYJ64P4PPsCtA7r0/1hUg95oLuT/dJAaBlUOzPxkTPJgn6q8/WDm0yHa+rz+mqqqqqqqqP2rLWh0TPKg/bFmrY4IHzz+PwvUoXI/YPz0K16NwPdQ/gU4b6LSBxj9kO99PjZe+PyuHFtnO97s/qXJoke18tz8v3SQGgZWzP99tWatjgqc/ZFmrY4IHoz8AAAAAAACgP8IxwYN5op4/WDm0yHa+nz+6dr6fGi+tP06A3GsuJK0/ezJ6W9bqqD933GsuJE2pP/vwGXYFyNE/KKO3Za2O1z+SNKXi7MPRP47elrU6JsQ/0THBg3mivj/HWh0TPJi3P57+jVBGb7M/CvVvhDJ6qz+JUEZvy1qtP8uwK0DuNac/UscED+aJqj/dQtKUirOvPyJNqTj78LE/atpApw10qj/LvxHK6G2pPxb3mgtJU6o/48Nn2BUgpz/y4TPsCpCrPyUVZx8+w64/vq4AuddcsD9l2BUg95qzP0w3iUFg5bA/KVyPwvUorD+4HoXrUbieP4uKsw+fYZc/nOLsw2fYlT+2TWIQWDmUP1LW6pjgwZw/okW28/3UqD+011xImlKhP4lBYOXQIqs/nNMGOm2goz+8sCtA7jWXPx2W/GLJL5Y/Trx0kxgElj91z7ArQO6VP1QBcq+5kKQ/VPKLJb9Yoj8KEzyYJ+qfPxkEVg4tso0/uB6F61G4fj8dlvxiyS+GPw6l4uzDZ4g/bF8s+cWSjz9Cb8taHROsP7Kd76fGS6c/2/l+arx0oz9sXyz5xZKPP6oPn2FXgJw/K8OuALnXnD8ZBFYOLbKdPxCF61G4HqU/bef7qfHSrT+qALnXXEiqP4relrU6JrA/nPHSTWIQqD9ooNMGOm2gP+tvhDJ6W6Y/+pw20GkDnT9KDAIrhxaZPwauR+F6FK4/wwQP5on6pz+DsCtA7jVnP7ySXyz5xZK/nAC511xIir/8qfHSTWKAvzv9G6GM3pY/eekmMQisnD/y8Bl2BcidP3FqvHSTGKQ/ZwOdNtBpuz+0yHa+nxq/P3tQRm/LWp0/wjHBg3minj9xW9bqmOChP2Dl0CLb+Z4/nNMGOm2goz9gEoPAyqGlPzvfT42XbqI/dbHkF0t+kT+m9Shcj8KVP6rx0k1iEJg/atpApw10mj9UPQrXo3CdP4/vp8ZLN6k/c4ZdAXKvqT/rYJ6ofyOkP+f7qfHSTaI/uoWkKRVnnz/sUbgeheuhP2324TPsCqA/FL0ta3VMoD9I/0Yoo7elP99ecyFpSqU/XLx0kxgEpj8lJE2pOPugP/QboYzelqU/pHA9CtejsD9kSsXZh8+wP3hb1uqY4LE/R2IQWDm0sD+R/GLJL5asPx+U0duyVqc/48Nn2BUglz/pJjEIrByaP8l2vp8aL50/g8+wK0DupT+c4uzDZ9ilP998PzVeuqk/QmDl0CLbqT/TTWIQWDmkP9WWtTomeKA/PTeJQWDloD8Eg8DKoUWmPwwv3SQGgaU/CNnO91PjpT8SsHJoke2sPwAAAAAAALA/dAXIveZCsj9TVVVVVVW1P7VlrY4JHrQ/vRHK6G1Zsz+F61G4HoWzP8Jn2BUg97I/RJpScfbhsz90Bci95kKyP4lBYOXQIqs/+o1QRm/Lqj+mqqqqqqqqP57+jVBGb6s/PQrXo3A9qj+JQWDl0CKrP/ZVDi2yna8/6SYxCKwcqj8bPsOuALmnP/QboYzelqU/O99PjZduoj/FPnyGXQGiP4ts5/up8ZI/PzVeukkMoj/nKFyPwvWoP0bF2YfPsKs/oDj78Bl2pT/ZzvdT46WbP4uKsw+fYZc/AAAAAAAAoD/wp8ZLN4mhPyHOPnyGXaE/Yi4kTak4qz/j0k1iEFipPxTME/VvhKI/jfHSTWIQmD+Le82FpCmlP31OG+i0ga4/sJA0peLsoz8AAAAAAACgP9ejcD0K16M/J0/UvxHKqD+YbhKDwMqhP/4QEREREYG/roN5ov6NkL8UzBP1b4SSv3tQRm/LWo2/IxeSplScnT8AAAAAAACgP1pkO99Pjac/9P3UeOkmoT85tMh2vp+qP7TmQtKUipM/IxeSplScnT8/UyrOPnymP1TyiyW/WKI/GQRWDi2yjT8OPJgn6t+oP/qNUEZvy6o/KWt1TPBgyj8pa3VM8GCuPx+jt2Wtjqk/aKDTBjptoD9I4XoUrkehP+PSTWIQWKk/fU4b6LSBrj89Gb0ta3W0P6RwPQrXo8w/ay4kTak41T+YtTomeDDPPzEIrBxaZMM/UscED+aJuj/JhaQpFWe3P8daHRM8mLc/r+QXS36xtD81baDTBjqtP+58PzVeuqk/ng102kCnrT9GxdmHz7CrP3WTGARWDq0/aKDTBjptsD/2N0IZvS2zP7NJDAIrh7Y/UXH24TPswj/RItv5fmrmP/VvhDJ6W+Y/iM+wK0Du0z/JzMzMzMzIPwstsp3vp8Y/FK5H4XoUwj/Vh8+wK0C+PxMg95oLSbs/DjyYJ+rfuD9QnH34DLu6P5t9+Ay7AsA/9ZoLSVMqwj/Jdr6fGi/FP3RM8GCeqMc/27JWxwQPwj9JfrHkF0u+PwPIveZC0rw/CUlTKs4+wD956SYxCKy8P3yx5BdLfrk/j8L1KFyPuj8+tvP91Hi5P9nd3d3d3bU/VYDcay4ktT+79Shcj8K1P9yWtTomeLg/A3KvuZA0wT+e76fGSzfFP6KbxCCwcsQ/PQrXo3A9wj/dJAaBlUO7P/Y3Qhm9LbM/pzj78Bl2tT/MTWIQWDm0PyAiIiIiIrI/XJ6ofyOUsT8HLbKd76e2P+cKkHvNhbQ/bef7qfHSrT9YV4Dcay6kP+coXI/C9ag/okW28/3UsD+kcD0K16OwP3FM8GCeqK8/XJ6ofyOUsT9wr7mQNKWyP421OiZ4MK8/vq4AuddcqD/dM+wKkHutP3tBYOXQIqs/xSCwcmiRrT+NtTomeDCvP26EMnpb1rI/futRuB6Fsz+amZmZmZmxP/hxr7mQNKU/EpKmVJx9sD+mm8QgsHKwP6wcWmQ7368/5e7u7u7urj8sJE2pOPuwP8w+fIZdAbI/RsXZh8+wsz+VYVeA3GuuP4/gwTxR/6Y/daL+jVBGrz+uVscED+axP7YC5F5zIbk/Gz7DrgC5vz/bslbHBA/CPyAiIiIiIro/fU4b6LSBtj9l5/up8dK1P1nl0CLb+bY/TdS/EcrotT/g7MNn2BW4P7EPn2FXgMA/YskvlvxixT9jrY4JHszDP9WHz7ArQL4/Vh0TPJgnuj9ooNMGOm24PxkTPJgn6rc/82+EMnpbtj/DBA/mifq/PwY6baDTBso/Q/0boYzeyj8ePsOuALnDP+IXS36x5L8/XI/C9Shcvz+Dz7ArQO69PwcezBP1b7w/EfVvhDJ6wz+1Za2OCR7IP+01F5KmVMQ/tvP91Hjpvj+R/GLJL5a8P0bF2YfPsLs/yOhtWatjuj9dLPnFkl+8P28haUrF2b8/6JjgwTxRvz8Lg8DKoUW+PxfotIFOG7g/rBxaZDvftz+nR+F6FK63Pw/ZzvdT47U/pzj78Bl2tT+v8/3UeOm2P2Xn+6nx0rU/IDEIrBxatD91ov6NUEa3P0u4HoXrUbg/7yhcj8L1uD8uT9S/Ecq4P4relrU6Jrg/cUzwYJ6otz+tyHa+nxq3Pzb78Bl2Bbg/WdbqmODBtD/7G6GM3pa1P7m7u7u7u7M/ShvotIFOsz/OaQOdNtCxPwXzRP0bobQ/EQRWDi2ytT92ME/UvxGyPwAP5on6N7I/jZduEoPAsj/y4TPsCpCzPxzME/VvhLI/6SYxCKwcsj+Le82FpCm1PyJNqTj78Lk/LCRNqTj7uD9ooNMGOm24P1yPwvUoXLc/2msuJE2puD+QXyz5xZK3P3n4DLsC5LY/EGcfPsOuuD8welvW6pi4P/Y3Qhm9LbM/futRuB6Fsz8xF5KmVJy1P8bMzMzMzLQ/2c73U+Oluz99PzVeuknSPxjZzvdT49k/nah/I5TRzz+CMnpb1urEP9yWtTomeMg/6yYxCKwc0D8X2c73U+PJP5JDi2zn+8U/Q0REREREyD9XxwQP5onSPycxCKwcWuE/NV66SQwC8j9SuB6F61ECQJx9+Ay7Avc/0SLb+X5q4z9EtvP91HjbPwOdNtBpA9c/FGcfPsOu2D8lBoGVQ4vcP7dlrY4JHt4/z8zMzMzM2j9bHRM8mCfWP1H/Riijt9M/Rrbz/dR40T+oxks3iUHQP/FE/RuhjM4/HBM8mCfqyz8QERERERHJP8CDeaL+jcg/5ELSlIqzxz/9jVBGb8vGPy2yne+nxsc/S/Bgnqh/xz8Sg8DKoUXGPz5g5dAi28U/vRHK6G1Zwz83Qhm9LWvJP5iZmZmZmdE/b1mrY4IH0T+fjN6WtTrOP/iaC0lTKso/XEiaUnH2yT9KfrHkF0vSPw8tsp3vp+U/VVVVVVVV9z+wcmiR7Xz2P3E9CtejcOQ/p1ScffgM4D+EeaL+jVDcPxfZzvdT498/7zUXkqZU5j+pfyOU0dviP0jhehSuR90/g8DKoUW23z/hwTxR/0bnP7Od76fGS+U/NHpb1uqY3j/PItv5fmraPwAAAAAAANo/A+RecyFp2D/pJjEIrBzWPx4+w64AudM/dEzwYJ6o0T+t1THBg3nQP4cW2c73U88/OPvwGXYF0D+j4uzDZ9jNP1Eqzj58hsk/OlH/Riijxz+tuZA0peLIP86wK0DuNcs/t2Wtjgke0D9Z8oslv1jQP3OvuZA0pc4/szomeDBPzD8+pw102kDHPzJeukkMAsM/JQaBlUOLxD/CZ9gVIPfGP3YwT9S/EcY/tvP91Hjpxj9E0pSKsw/HP+p8PzVeusk/4hdLfrHkyz84JngwT9TLP86wK0DuNcs/gZVDi2zn0T8lBoGVQ4vWPwPkXnMhadQ/nX34DLsC0j8dzBP1b4TQPwOdNtBpA9E/LbKd76fG1T96zYWkKRXVPwisHFpkO9U/gcDKoUW22T8Rg8DKoUXYP4Dcay4kTdU/d+kmMQis2D/w0k1iEFjbP5X8YskvltY/TGIQWDm01D//Riijt2XTP4/C9Shcj9I//PAZdgXI2T//1HjpJjHnP/OLJb9Y8uU/9uEz7AqQ4T90IWlKxdndP0REREREROM/EZ9hV4Dc7T8YBFYOLbLmP+ltWatjguE/ov6NUEZv4D+95kLSlIrgPxwTPJgn6uQ/Qxm9LWt15D+pOPvwGXbgP2fYFSD3mts/fPgMuwLk2D8/NV66SQzYP3IhaUrF2dc/1jHBg3mi1j/xiyW/WPLTP2+EMnpb1tQ/tPP91Hjp1j8bL90kBoHgP/EZdgXIveU/NKXi7MNn4T9Db8taHRPeP6BFtvP91No/uNdcSJpS1T+T7Xw/NV7UP3Z3d3d3d9M/exSuR+F61D+hjN6WtTrUP86wK0DuNdM/B8i95kLS1D97W9bqmODVPzomeDBP1NM/3whl9Las0z9NG+i0gU7VP0NERERERNg/kHvNhaQp6j+tjgkezBPxP+uY4ME8UeY/A5020GkD4T+MCR7ME/XdP/0boYzeltk/BFYOLbKd2T+rjgkezBPZP/nFkl8s+dU/zczMzMzM0j9dSJpScfbVP+nfCGX0ttQ/CKwcWmQ70z/dJAaBlUPRP/nwGXYFyM0/+TdCGb0tzz/RItv5fmrQPxI8mCfq38w/+TdCGb0tzz8IrBxaZDvPPxlLfrHkF88/3sE8Uf9GzD/Ag3mi/o3IP1nW6pjgwcw/LbKd76fGyz98seQXS37JP0TSlIqzD8s/xr3mQtKUyj/GBA/mifrHP9nO91Pjpcc/fT81XrpJyD/hM+wKkHvFP+7STWIQWMU/it6WtTomxD+411xImlLFP9dcSJpSccY/+Knx0k1ixD8dWmQ730/BP4IyelvW6sA/aErF2YfPwD9/arx0kxjAPwisHFpkO78/zrArQO41wz/MPnyGXQHGP/2NUEZvy8I/Q0REREREwD9VgNxrLiS9PyuHFtnO97s/qNUxwYN5uj9DRERERETAP/fFkl8s+cE/pVScffgMwz81F5KmVJzBP/7UeOkmMcA/ZDvfT42Xwj8FrBxaZDvDPwwCK4cW2cI/QNKUirMPwz9g5dAi2/nCP6+d76fGS8M/0NuyVscEwz++nxov3STCPxsv3SQGgcE/N0IZvS1rwT/RItv5fmrAP0P9G6GM3r4/qWOCB/NEvT8K16NwPQq/P3E9CtejcL0/Ib9Y8osltz9GxdmHz7CzP9eyVscED7Y/Y62OCR7Muz/vGXYFyL22PzNCGb0ta7U/m0W28/3UuD9YObTIdr63P5qofyOU0bs/sHJoke18vz91ov6NUEa/P8KuALnXXMA/mVJx9uEzwD9jvHSTGAS+P8oT9W+EMsI/LWt1TPBgwj9mZmZmZmbCPxkTPJgn6r8/obdlrY4Jwj8j6t8IZfS+P9v5fmq8dLs/mVJx9uEzwD9iyS+W/GLBP1CNl24Sg8A/C3TaQKcNwD9xTPBgnqi/P4aIiIiIiMA/bstaHRM8wD85baDTBjrBP/k3Qhm9LcM/m334DLsCxD/P91PjpZvEP1DjpZvEIMQ/9ihcj8L1xD9w9uEz7ArEP6MpFWcfPsM/mLU6Jngwwz+/PFH/RijDP5KKsw+fYcM/wRHK6G1Zwz9vEoPAyqHBP3LaQKcNdMI/82+EMnpbwj+V/GLJL5bAPxKDwMqhRcI/B9ejcD0Kwz+28/3UeOnCP6MpFWcfPsM/Cy2yne+nxj+WmZmZmZnJPxeSplScfeA/yC+W/GLJ/j9XVVVVVVUAQDttoNMGOv8/A5020GkDA0CF61G4HoUDQFnyiyW/WP4/c9pApw108z96zYWkKRXtP7x0kxgEVug/Q4ts5/up5D9Zq2OCB/PiP9NNYhBYOeI/35a1OiZ44T/7qfHSTWLiP5020GkDneE/yuhtWatj4D8MAiuHFtneP0//Riijt90/89JNYhBY3T9vEoPAyqHdP3sUrkfhet4/j3vNhaQp3z8fzBP1b4TcP+81F5KmVNo/ldHbslbH2D/jM+wKkHvXP76fGi/dJNY/PzVeukkM1j+PwvUoXI/SP6AaL90kBtE/Y4IH80T90T91kxgEVg7TP1QOLbKd79E/JQaBlUOL0j9QjZduEoPSPyKU0duyVtM/vp8aL90k2j/QsCtA7jXkPyR4ME/Uv+8/c6+5kDSl8D8zelvW6pjrP4UW2c73U+Y/G+i0gU4b9z9z2kCnDXQBQOF6FK5H4fU/1uqY4ME88D9/arx0kxjxP3E9CtejcPM/bRKDwMqh7j+yne+nxkvtP1urY4IH8+s/YZ6ofyOU6D8TyuhtWavlP9KUirMPn+M/DElTKs4+4j+FpCkVZx/hP1pkO99Pjd8/ivo3Qhm93T8UZx8+w67cP7mQNKXi7Ns/U5x9+Ay72D8uJE2pOPvUP7as1THBg9M/RP0boYze0j8YvS1rdUzSP6dUnH34DNM/001iEFg51D+Pe82FpCnTP6abxCCwctI//tR46SYx0j+gRbbz/dTSPzJ6W9bqmNI/DXTaQKcN0j98+Ay7AuTQP7m7u7u7u88/mVJx9uEz0D9cSJpScfbNP7x0kxgEVso/CUlTKs4+yD+sHFpkO9/HP3ii/o1QRsc/3whl9LasyT9w9uEz7ArMP4AH80T9G80/Bx7ME/VvzD8LHswT9W/MP9TqmODBPM0/aef7qfHSyT8T2c73U+PFPwaBlUOLbMc/pLdlrY4Jyj/iF0t+seTLP3D24TPsCsg/g8DKoUW2xz+X4ME8Uf/GP73KoUW288U/jAkezBP1wz/5N0IZvS3DP52ofyOU0cc/IpTR27JWxz+rjgkezBPFP0EZvS1rdcQ/3Ja1OiZ4xD/xiyW/WPLDPz81XrpJDMI/pHA9CtejwD/oUbgehevBP+ZtWatjgsM/Bx7ME/VvwD/rYJ6ofyO8Pz0K16NwPbo/nv6NUEZvuz9y2kCnDXTCPy+W/GLJL8o/exSuR+F6zD+EXQFyr7nEP5RuEoPAysE/5/up8dJNwj8IZfS2rNXBP7gehetRuMI/yb3mQtKUwj+2rNUxwYPBP34jlNHbssI/vzxR/0Yowz8JSVMqzj7EP2XYFSD3msM/qaqqqqqqwj8YdgXIvebCPxKDwMqhRcI/sCtA7jUXwj95ME/UvxHCPyd4ME/Uv8E/VYDcay4kwT9Xq2OCB/PAPwPIveZC0sA/UI2XbhKDwD8YvS1rdUzAP97BPFH/RsA/gjJ6W9bqwD+v5BdLfrHAP0YMAiuHFsE/ftxrLiRNwT93vp8aL93AP8/3U+Olm8A/vljyiyW/wD8YvS1rdUzAPx+F61G4HsE/pzj78Bl2wT+FpCkVZx/CP1XHBA/micI/wmfYFSD3wj8vlvxiyS/CPyJNqTj78ME/l+DBPFH/wj9G/RuhjN7CP00b6LSBTsM/GHYFyL3mwj9A0pSKsw/DP/tiyS+W/MI/djBP1L8Rwj9TVVVVVVXBP5+M3pa1OsI/ScXZh8+wwz96zYWkKRXHP7ByaJHtfMc/YYIH80T9xz++WPKLJb/EP52ofyOU0cM/XSz5xZJfxD8YvS1rdUzEP0yNl24Sg8Q/6wqQe82FxD/5N0IZvS3DP5KKsw+fYcM/f2q8dJMYxD9dLPnFkl/EPwcezBP1b8Q/kkOLbOf7xT+TGARWDi3GP+8ZdgXIvcY/9ihcj8L1zD/P91PjpZvgP1G4HoXrUeg/xwQP5on64T9OYhBYObTcP6ebxCCwcuA/46WbxCCw6T/tw2fYFSDoP7tJDAIrh+I/X0iaUnH23T8LHswT9W/aPySU0duyVtk/54n6N0IZ2T8pXI/C9SjYP/iaC0lTKtg/1873U+Ol1z/D9Shcj8LVP28Sg8DKodU/fT81XrpJ1D8IrBxaZDvTP97d3d3d3dE/OW2g0wY60T8GgZVDi2zRP2yg0wY6bcw/qX8jlNHb1D9aZDvfT43PPyr5xZJfLM0/xr3mQtKUyj83Qhm9LWvNPxrotIFOG8w/l+DBPFH/zj8zMzMzMzPPP/7UeOkmMcw/X0iaUnH2yT+411xImlLJP/IoXI/C9cg/r53vp8ZLxz9KDAIrhxbFP1nW6pjgwcg/rkfhehSuxz+TGARWDi3GP7M6JngwT8Q/jAkezBP1wz89CtejcD3CP/+411xImsI/vzxR/0Yowz+Hz7ArQO7FPwlJUyrOPsg/pvHSTWIQxD/ZzvdT46XDP13l0CLb+cI/T0Zvy1odwz8xwYN5ov7BP5s20GkDncI/OCZ4ME/Uwz/D9Shcj8LFP0SLbOf7qcU/7xl2Bci9yj9wy1odEzzaP04b6LSBTuM/EjyYJ+rf3D9cj8L1KFzXPx3ME/VvhNY/ukkMAiuH1j/KWh0TPJjVP6cNdNpAp9M/3GsuJE2p0j+5kDSl4uzRPwisHFpkO9E/ZvS2rNUx0T9DRERERETQP0B8hl0Bcs8/o+Lsw2fYzT+iRbbz/dTMPxH1b4Qyess/5/up8dJNyj8DyL3mQtLIPwOBlUOLbMc/zIWkKRVnxz+QUEZvy1rJP4LrUbgehcc/EBERERERxT+f0wY6baDDPyJNqTj78ME/6JjgwTxRvz/Jdr6fGi/BP41QRm/LWsU/sHJoke18xz+bffgMuwLIPwQP5on6N8o/q44JHswTzT9EtvP91HjRP0bhehSuR9M/vHSTGARW0j89mCfq3wjTP1VVVVVVVdE/VOOlm8Qg0D/BEcrobVnPP06pOPvwGc4/oykVZx8+0T+uR+F6FK7RP68AuddcSNY/Hz7DrgC55D+nDXTaQKf5PyIiIiIiogFAIyIiIiIi+j8s+cWSXyzyP6uqqqqqquw/LWt1TPBg5z/K6G1Zq2PkP/dT46WbxOE/rwC511xI4D+tjgkezBPfP2LJL5b8Yt0/TfBgnqh/3T8/7jUXkqbaP3E9CtejcNc/uUkMAiuH1j9lrY4JHszXPzomeDBP1Nc/K4cW2c731T9TcfbhM+zUPxAREREREdU/3GsuJE2p1D/obVmrY4LTP1WcffgMu9I/0pSKsw+f0z8s+cWSXyzTP/JE/RuhjNI/slbHBA/m0T/VeOkmMQjQP98IZfS2rM0/ukkMAiuH0D+pOPvwGXbRP2IQWDm0yNI/MJb8Yskv2D94ov6NUEbfP4ddAXKvueU/Uf9GKKM38T9iV4Dca67wP7SBThvotO8/T9S/Ecro7T8wT9S/EcrnP/VvhDJ6W+U//o1QRm/L4j9jEFg5tMjgP1nyiyW/WOE/bxKDwMqh4T9gnqh/I5TgP4HAyqFFtt8/eKL+jVBG3z83F5KmVJzdP6jx0k1iENo/mODBPFH/1D8Pn2FXgNzXP9Ei2/l+atg/j8L1KFyP2D9Y8oslv1jYP2t1TPBgnuE/1E1iEFg57D9x9uEz7ArpP7XIdr6fGuA/SAwCK4cW3T+uR+F6FK7dPwAAAAAAANw/9eEz7AqQ2z9TcfbhM+zcP/RvhDJ6W9g/I9v5fmq81j/cslbHBA/WPxSuR+F6FNY/Z62OCR7M1T8FD+aJ+jfUP78RyuhtWdM/4TPsCpB70z/DILByaJHTP4ts5/up8dI/NKXi7MNn0j8lTak4+/DTP86wK0DuNdM/d76fGi/d0j8Pn2FXgNzTP5tScfbhM9g/ukkMAiuH3j936SYxCKzcP8w+fIZdAdg/ME/UvxHK1j8tsp3vp8bVP2VmZmZmZtQ//RuhjN6W0z93vp8aL93SP5X8YskvltI/1XjpJjEI0j85baDTBjrRPx73mgtJU84/1OqY4ME8zT8hBoGVQ4vMP1K4HoXrUcw/DZ9hV4Dcyz/jXnMhaUrNP2etjgkezMs/sp3vp8ZLyz9AfIZdAXLLP/1GKKO3Zck/CpB7zYWkyT/zb4QyelvKP2IQWDm0yMo/arx0kxgEyj9ecyFpSsXJP+nfCGX0tsg/JL9Y8oslxz8iTak4+/DFPwisHFpkO8M/uB6F61G4vj+cGi/dJAbFP2nn+6nx0sU/es2FpCkVxz8+YOXQItvBPxfZzvdT48U/iLMPn2FXxD84JngwT9TDP6+d76fGS8M/87as1THBwz/3DLsC5F7DP5KKsw+fYcM/XxBYObTIwj9k9Las1THBP0bF2YfPsLs/ObTIdr6fuj+ht2Wtjgm+P7wta3VM8MQ/415zIWlKxT8CK4cW2c7DP2kuJE2pOMM/8UT9G6GMwj8bL90kBoHBP/hT46WbxMA/+FPjpZvEwD9ecyFpSsXBP7dJDAIrh8I/gZVDi2znwz+3kDSl4uzDP/+411xImsI/szomeDBPxD8HHswT9W/EP/yp8dJNYsQ/4TPsCpB7xT+8dJMYBFbGPwt02kCnDcQ/CUlTKs4+wD8IZfS2rNXBP3E9CtejcME/OW2g0wY6wT97FK5H4XrAP/IoXI/C9cQ/v+ZC0pSKwz/pJjEIrBzCP2nn+6nx0sE/koqzD59hwz/GBA/mifrDP4IyelvW6sQ/MHpb1uqYxD/HSzeJQWDFP2XYFSD3msc/HveaC0lTxj8dWmQ730/JP6zVMcGDeco/b1mrY4IHyz8ED+aJ+jfKP6ljggfzRMk/P+41F5KmyD8LdNpApw3IP26EMnpb1sY//UYoo7dlwT+QXyz5xZLDP/+411xImsI/iyW/WPKLwT9cSJpScfbBP6/kF0t+scQ/m334DLsCxD9A0pSKsw/DP27LWh0TPMA/aErF2YfPwD93vp8aL93AP5GmVJx9+MA/OW2g0wY6wT8R9W+EMnrDPxrotIFOG8Q/7TUXkqZUxD/mbVmrY4LDP/FE/RuhjMI/c2iR7Xw/wT+SirMPn2HDPwwCK4cW2cI/82+EMnpbyj8+pw102kDLPxP1b4QyetM/J79Y8osl7D8nMQisHFrxP6h/I5TR2+Y/wRHK6G1Z4T+K+jdCGb3fP1cOLbKd7+c/6ELSlIqz7T85tMh2vp/mP6scWmQ73+M/wvUoXI/C4j9rvHSTGAThPwaBlUOLbOE/ay4kTak44D9aZDvfT43fP3z4DLsC5N4/jlBGb8ta4D/MhaQpFWfdP30/NV66SeA/CKwcWmQ75j8UrkfhehT2P6cNdNpAp/U/9v3UeOkm8T8cWmQ730/rPxM8mCfq3+Y/0NuyVseE8j/ntIFOG+j8P+F6FK5H4fM/AQAAAAAA8T+411xImlLtP6BhV4Dca+o/qA102kCn5z8Sg8DKoUXlP+98PzVeuuI/d76fGi/d4D/Ag3mi/o3eP1TjpZvEIN4/TRvotIFO3T8VZx8+w67jPyA+w64Aueg/v58aL90k4z9w9uEz7AreP/+NUEZvy9w//Knx0k1i3j+WbhKDwMrfPzomeDBP1P4//GLJL5Z8D0AFOm2g04YKQFVVVVVV1RBAddpApw20FEAHOm2g00YRQON6FK5HYQxA6LSBThtoCkBTuB6F69EDQAGdNtBpA/8/HOi0gU4b+D+uR+F6FK7zPzlCGb0ta+0/uwLkXnMh6j840GkDnTboP4MH80T9G+Y/Z5HtfD815D8fzBP1b4TmP5HtfD81XuQ/R2/LWh0T4z/ntIFOG+jeP9gVIPeaC90/PcOuALnX3D99PzVeuknaP1dVVVVVVds/TxvotIFO3z+Pl24Sg8DcP7jXXEiaUts/001iEFg52j/glrU6JnjaP3QhaUrF2dk/eDBP1L8R2D/dJAaBlUPXP5GmVJx9+Ng/o7dlrY4J1j+95kLSlIrTP65H4XoUrtE/5dAi2/l+0D9SuB6F61HMPzm0yHa+n84/Qrbz/dR4zT/yRP0boYzSP4/C9Shcj9A/ke18PzVe0D8klNHbslbRP0dTKs4+fNI/nO+nxks31T8K16NwPQrVP9bqmODBPNU/Di2yne+n1D/6fmq8dJPSP0CnDXTaQNE/jVBGb8tazT8fhetRuB7NP4relrU6Jsw/FyD3mgtJyz9cSJpScfbJP3hb1uqY4M0/2msuJE2pzD+kt2WtjgnOP5fgwTxR/8o/7JjgwTxRyz9I4XoUrkfJP2Dl0CLb+cY/+2LJL5b8xj+8dJMYBFbKP9ejcD0K18c/ONBpA502yD+im8QgsHLIP9YVIPeaC8k/+2LJL5b8xj8GOm2g0wbGP5huEoPAysU/s+QXS36xyD9nA5020GnHP8paHRM8mMc/0XjpJjEIxD/tNReSplTEPymyne+nxsM/PqcNdNpAwz8/7jUXkqbEP2p1TPBgnsg/Q/0boYzexj/6fmq8dJPIP32GXQFyr8U/HVpkO99PxT/OaQOdNtDFPz5g5dAi28U/CGX0tqzVxT/Zh8+wK0DGP7m7u7u7u8c/FyD3mgtJxz+8dJMYBFbGPyajt2WtjsU/MHpb1uqYwD+AB/NE/RvBP7VlrY4JHsQ/gZVDi2znxz8jIiIiIiLGP7SBThvotMU/anVM8GCexD916SYxCKzEPxaSplScfcQ/Hj7DrgC5wz9l2BUg95rDP7SBThvotMU/zD58hl0Bxj+RplScffjEPxi9LWt1TMQ/KvnFkl8sxT/9Riijt2XFP29oke18P8U/aErF2YfPxD/qw2fYFSDHP7gehetRuMY/Lk/UvxHKxD8ypeLsw2fAP3fNhaQpFb8/m334DLsCwD8rhxbZzve7PwrXo3A9Cr8/6FG4HoXrwT9hggfzRP3DP2NXgNxrLsQ/7FG4HoXrwT8dWmQ730/BP497zYWkKcE/tWWtjgkewD+8LWt1TPDAP/hT46WbxMA/m334DLsCwD/FL5b8Ysm/PwGsHFpkO7c/cUzwYJ6otz8K5on6N0K5P3sUrkfhesA/z/dT46WbwD9VxwQP5onCP7Kd76fGS8M/7KfGSzeJwT91kxgEVg69P/C2rNUxwbs/+o1QRm/Luj9jO99PjZfeP28Sg8DKodE/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/30+Nl24Syz9mZmZmZmbCP4XrUbgehcM/Uv9GKKO3yT/ufD81XrrJP1odEzyYJ8Y/7TUXkqZUxD+6AuRecyHFPy+W/GLJL8Y/wmfYFSD3wj+Pe82FpCnBP5X8YskvlsA/KM4+fIZdwT8SPJgn6t/APy5P1L8RysA/72CeqH8jwD+v5BdLfrHAPyG/WPKLJb8/uB6F61G4vj9g5dAi2/m+P+ZtWatjgr8/5m1Zq2OCvz88fIZdAXK/P9hApw102sA/NvvwGXYFwD84JngwT9S/P+O0gU4b6Lw/wcqhRbbzvT//Riijt2XRP5kn6t8IZeI/VscED+aJ5D8FD+aJ+jfgP6H+jVBGb9c/oYzelrU60j8NdNpApw3QP0dTKs4+fM4/+xuhjN6W1z/vNReSplTgPxAREREREds/P8OuALnX1j/5xZJfLPnVP+F6FK5H4dI/F9nO91Pj1z8ywYN5ov7gP/Cnxks3id0/3GsuJE2p2D9R/0Yoo7fXPyGwcmiR7dY/6bSBThvo1D8MuwLkXnPVPxHK6G1Zq9U/dgXIveZC1D9Ei2zn+6nfPyUGgZVDi+E/LPnFkl8s3T+dqH8jlNHZPy2yne+nxtc/bKDTBjpt1j+M3pa1OibSP8jobVmrY84/zBP1b4Qy0D/hehSuR+HSPxdLfrHkF9M/ULgehetR0j+jKRVnHz7PP5zEILByaM0/Vg4tsp3v0z/XzvdT46XVP+iY4ME8UdM/zrArQO410z92Bci95kLUP7EPn2FXgNY/w/UoXI/C2z+vR+F6FK7kP0vF2YfPsN0/iYiIiIiI4z9BYOXQItvpP+EIZfS2rPA/68Nn2BUg7D+bxCCwcmjrP8ERyuhtWeU/W9bqmODB4T9QjZduEoPePydcj8L1KNo/1L8Ryuht1z+tjgkezBPVP9V46SYxCNg/1873U+Ol1z9vhDJ6W9bQPxBYObTIdtY/3LJWxwQP2D9R/0Yoo7fTP2Q730+Nl9A/s1bHBA/m0T/obVmrY4LTP8uhRbbz/cw/8kT9G6GM0D/MPnyGXQHSP+9gnqh/I8g/dEzwYJ6oxz82+/AZdgXMP/hT46WbxMg/YVeA3Gsu0D/7G6GM3pbNP+7STWIQWMk/7FG4HoXryT/5xZJfLPnVPzHBg3mi/sk/pHA9CtejzD/3DLsC5F7RP2DJL5b8YtM/YOXQItv50D+SirMPn2HPP4IyelvW6sw/NvvwGXYFyD/wp8ZLN4nBP3WTGARWDsE/ciFpSsXZwz/P91PjpZvIP+f7qfHSTco/szomeDBPxD9/seQXS37FP3sUrkfhesQ/3SQGgZVDwz9k9Las1THFPzeJQWDl0MI/XrpJDAIrxz/4qfHSTWLEPzMzMzMzM8M/Gy/dJAaBxT97arx0kxjEP1XHBA/micI/eekmMQiswD9uy1odEzzAP788Uf9GKMM/D3TaQKcNxD8ED+aJ+jfCPzMzMzMzM8M/xNmHz7ArxD/JveZC0pTCP28Sg8DKocE/fT81XrpJwD8WkqZUnH3EP+ynxks3icU/Gui0gU4bxD+uR+F6FK7DP+F6FK5H4cI/M+wKkHvNwT8IZfS2rNXBP1WA3GsuJME/of6NUEZvwz8IrBxaZDvDP0upOPvwGcI/XEiaUnH2wT8OLbKd76e+P2Q730+Nl74/wq4AuddcwD8uT9S/EcrAP8HKoUW288E/vp8aL90kwj8v7AqQe829P6rx0k1iEMA/2whl9LasvT/QlIqzD5+5P3FM8GCeqLc/X2ZmZmZmtj9cj8L1KFy/PyUGgZVDi8A/5d8IZfS2vD8lBoGVQ4vAP/7jXnMhabo/AjptoNMGuj+OQ4ts5/u5P26EMnpb1ro/Qm/LWh0TvD/jtIFOG+i8P0upOPvwGb4/ZwOdNtBpuz+wgU4b6LS5P7efGi/dJLY/kfxiyS+WtD8aoYzelrWyP26EMnpb1ro/ocZLN4lBuD+yrNUxwYOpP/NvhDJ6W74/5/up8dJNuj+TJ+rfCGW0Pz0K16NwPbI/eoZdAXKvsT9TZDvfT423P/sboYzelr0/wwQP5on6tz/31HjpJjG4P1erY4IH87Q/qMZLN4lBsD++rgC511ywP10s+cWSX7Q/TEZvy1oduz+ZC0lTKs7OP90z7AqQe7U/H5TR27JWtz+9EcrobVmzP5VhV4Dca64/A8i95kLStD9vEoPAyqG1P65WxwQP5rk/jZduEoPAuj+lDXTaQKe1Pzx8hl0Bcrc/hetRuB6Fsz9q2kCnDXSqPwwREREREbE/u+ZC0pSKsz9cj8L1KFy3P7TIdr6fGrc/IlyPwvUotD8F80T9G6G0P4cW2c73U7M/6UT9G6GMrj9OcfbhM+yqP7LKoUW2860/q44JHswTtT/uiyW/WPKzP1yeqH8jlLE/SX6x5BdLtj9sWatjggezP/N+arx0k7A/LcGDeaL+rT/Jdr6fGi+tP5+M3pa1OrY//3GvuZA0tT+R7Xw/NV6yP5s20GkDnbY/kxgEVg4tsj8zYOXQItupP4uZmZmZmak/CvVvhDJ6qz8lFWcfPsO2P9K/Ecrobbk/CNnO91PjpT/op8ZLN4mxP06A3GsuJK0/I/nFkl8sqT+Nl24Sg8CqP90z7AqQe60/47SBThvotD/aay4kTam4P5bvp8ZLN7k/Y62OCR7Muz9I4XoUrkfJP8uhRbbz/bQ/kG4Sg8DKsT+6WPKLJb+wP0//Riijt7U/i3vNhaQptT8BnTbQaQO1P0xGb8taHbM/GHYFyL3msj9IDi2yne+nPw48mCfq36g/kfxiyS+WrD/Z3d3d3d21Pz0ZvS1rdaw/y78RyuhtqT/b+X5qvHSzP0F+seQXS64/8MWSXyz5pT9qy1odEzyoP0Jvy1odE6w/4hdLfrHktz/HWh0TPJi3Py2yne+nxrM/AjptoNMGsj85tMh2vp+qPxYGgZVDi6w/MqXi7MNnsD+EXQFyr7mwPwwCK4cW2bY/aT0K16NwtT/YQKcNdNqwPxs+w64Aubc/xWfYFSD3yj9VgNxrLiS1PxH1b4QyerM/BfNE/RuhtD+v8/3UeOm2PzNCGb0ta7U/wmfYFSD3sj/jpZvEILCyP/yp8dJNYrA/8NR46SYxqD+iVJx9+AyrP8DZh8+wK7A/cL6fGi/dtD/y4TPsCpCzP4AH80T9G7E/QwwCK4cWsT/2Riijt2WtP0bF2YfPsKs/Yj0K16NwrT9YObTIdr6vP+Dsw2fYFbg/PcOuALnXwD9wr7mQNKW6P9CUirMPn7E/qMZLN4lBsD8lFWcfPsOuPxSuR+F6FK4/LcGDeaL+rT81fIZdAXKvP7pY8oslv7A/xJJfLPnFsj8LdNpApw20P4lBYOXQIrM/DBERERERsT9G1L8RyuitP6oAuddcSKo/F+i0gU4bsD+RC0lTKs6uP5VhV4Dca64/ToDcay4krT8CSVMqzj6sP5zx0k1iEKg/oDj78Bl2pT9kaJHtfD+lPyG/WPKLJa8/FK5H4XoUrj+8dJMYBFauP2Q730+Nl64/SirOPnyGrT/6jVBGb8uqP+kmMQisHKo/5yhcj8L1qD+NtTomeDCvP97BPFH/RrA/GQRWDi2yrT/Vh8+wK0CuP4XrUbgehas/Vh0TPJgnqj+qALnXXEiqP88VIPeaC6k/4Yn6N0IZrT+iY4IH80StP6rx0k1iELA/1YfPsCtArj9SxwQP5omqP17JL5b8Yqk/pI4JHswTpT/DBA/mifqnP65lrY4JHqw/fU4b6LSBrj9WLPnFkl+sP0ob6LSBTqs/1YfPsCtArj9OcfbhM+yqP1CrY4IH86Q/KVyPwvUorD8iTak4+/CxPy5P1L8RyrA/2msuJE2psD8hv1jyiyWvP6a5kDSl4qw/321Zq2OCpz9aggfzRP2rP/7yRP0boaw/tMh2vp8arz/umgtJUyquPxtNqTj78Kk/rlbHBA/mqT8v+/AZdgWoP/hxr7mQNKU/O+41F5KmpD+Xm8QgsHKoP1YdEzyYJ6o/ZoQyelvWqj8W95oLSVOqPx+jt2Wtjqk/vHSTGARWrj8zMzMzMzOzP6ud76fGS7c/ZDvfT42Xtj/mfD81XrqxP4/R27JWx6Q/Vh0TPJgnsj9UEFg5tMimPw48mCfq37g/NXyGXQFyrz/RMcGDeaKuP/LhM+wKkKs/psh2vp8arz/DE/VvhDKqPwwREREREbE/vHSTGARWvj9iLiRNqTirP7gehetRuK4/Vg4tsp3vpz8bPsOuALmnP8Ii2/l+aqw/DjyYJ+rfqD9ovp8aL92kP9prLiRNqbA/CKwcWmQ7rz8IyuhtWaujP5h9+Ay7AqQ/JzEIrBxapD/U6pjgwTyxP+k1F5KmVKw/xU1iEFg5pD9S1uqY4MGsP8/3U+Olm7Q/VAFyr7mQpD8Sg8DKoUWmP0ob6LSBTqs/Yh8+w64AsT+iVJx9+AyrP4lQRm/LWq0/LcGDeaL+rT8nMQisHFq0P5zx0k1iEKg/Yi4kTak4qz8ZBFYOLbKtP0Jvy1odE6w/7poLSVMqrj/+8kT9G6GsP6oAuddcSKo/L/vwGXYFqD/rYJ6ofyOkP9NNYhBYOaQ/XrpJDAIrpz/fbVmrY4KnP0Jg5dAi26k/DCD3mgtJoz8X6LSBThuoPznSlIqzD68/f4iIiIiIqD/wtqzVMcGjP6jkF0t+saQ/L/vwGXYFqD+NplScffisPwAezBP1b6Q/x2kDnTbQqT91ov6NUEavP+PDZ9gVIKc/qOQXS36xpD9crY4JHsyjP3fcay4kTak/ppvEILByqD9YZmZmZmamP7pn2BUg96o/pqqqqqqqsj/fT42XbhKjPycxCKwcWqQ/VAFyr7mQpD/bF0t+seSnP7CfGi/dJKY/x2kDnTbQqT+JUEZvy1qtPy5P1L8RyrA/62+EMnpbpj9EqTj78BmmP395ov6NUKY/J0DuNReSpj/6fmq8dJOoP/DUeOkmMag/+pw20GkDrT+kne+nxkunP1g5tMh2vq8/tgLkXnMhqT8CSVMqzj6sP91C0pSKs68/qOQXS36xpD9MZDvfT42nP/7jXnMhaao/CuaJ+jdCqT9YSJpScfahPwAP5on6N6I/pH8jlNHboj9mdUzwYJ6wPxkEVg4tsq0/i3vNhaQppT/dM+wKkHutP/iAlUOLbKc/JQaBlUOLrD/A6G1Zq2OiP+O0gU4b6KQ/WmQ730+Npz8nQO41F5KmPxsv3SQGgaU/CtejcD0Kpz8czBP1b4TCP9v5fmq8dKM/WEiaUnH2oT+sK0DuNReiP0j/Riijt6U/C2X0tqzVyT9jyS+W/GLsPzzfT42Xbuo/TGIQWDm00D9TVVVVVVW9PzvuNReSprQ/1hUg95oLsT8ozj58hl2xP7695kLSlKo/Vh0TPJgnqj91ov6NUEavP+6aC0lTKq4/KVyPwvUorD+F61G4HoWrP0xkO99Pjac/pHA9CtejsD/hifo3QhmtPy/78Bl2Bag/ObTIdr6fqj9qvHSTGASmP1hImlJx9qE/P0REREREpD/rb4QyelumP0F+seQXS64/BFYOLbKdrz8W95oLSVOqP/Y3Qhm9Las/ng102kCnrT+iRbbz/dSwP+8ZdgXIvbY/jAkezBP1tz/Qo3A9CtezP19ImlJx9rE/Ib9Y8oslrz9kO99PjZeuP8a95kLSlLI/CtejcD0Ktz+GiIiIiIi4P9v5fmq8dLM/astaHRM8sD+K3pa1OiawP8Uvlvxiya8/NW2g0wY6rT9KG+i0gU6rPz9TKs4+fKY/P1Mqzj58pj/HaQOdNtCpPxb3mgtJU6o/bzBP1L8Rqj9CYOXQItupPz9iEFg5tKg/H5TR27JWpz+kne+nxkunP+coXI/C9ag/DC/dJAaBpT+qD59hV4CsPw5LfrHkF6s/d9xrLiRNqT8dWmQ730+tP1YdEzyYJ6o/16NwPQrXoz8UzBP1b4SiP2ivuZA0paI/6UT9G6GMrj8zUf9GKKOnPxTME/VvhKI/XK2OCR7Moz9kWatjggejP5MYBFYOLaI/GSIiIiIioj/sUbgeheuhP1pkO99Pjac/bzBP1L8Rqj+pcmiR7Xy3P7TXXEiaUrE/K4cW2c73oz9MVVVVVVWlP6w6JngwT6Q/exSuR+F6pD83iUFg5dCiP1CcffgMu6I/xT58hl0Boj9or7mQNKWiPzNCGb0ta6U/arx0kxgEpj+Dz7ArQO6lP4t7zYWkKaU/uB6F61G4rj+pY4IH80TBP7M6JngwT8w/5DPsCpB72T/pJjEIrBzGP70RyuhtWbM/3TPsCpB7rT+Xm8QgsHKoP0Jg5dAi26k/6SYxCKwcqj+sSQwCK4emP4PPsCtA7qU/L90kBoGVoz/sUbgeheuhP6R/I5TR26I/oDj78Bl2pT/clrU6JniwP3Noke18P7U/+pw20GkDrT8OS36x5BerP5zi7MNn2KU/NXyGXQFyrz+MCR7ME/W3P+Z8PzVeurE/zduyVscErz89Gb0ta3WsP17JL5b8Yqk/yhP1b4Qysj+fjN6WtTq+Pz9ERERERLw/7nw/NV66sT8IrBxaZDuvPyGwcmiR7aw/cT0K16NwrT+q8dJNYhCwP05x9uEz7Lo/vp8aL90kwj9l2BUg95q7P6JUnH34DLM/6JjgwTxRtz9/arx0kxi0P6R/I5TR27I/5/up8dJNsj9YSJpScfaxP4X6N0IZva0/z/dT46WbpD8QhetRuB6lPxTb+X5qvKQ/ZGiR7Xw/pT+kjgkezBOlP1LW6pjgwaw/NW2g0wY6rT8v7AqQe82lP30/NV66Saw/c3d3d3d3tz/Z3d3d3d21P6oAuddcSKo/vJJfLPnFoj/8uNdcSJqiP2RZq2OCB6M/mqh/I5TRqz/jpZvEILCiPydA7jUXkqY/Dkt+seQXqz8CWDm0yHauPznDrgC516w/Yh8+w64AqT+2AuRecyGpPxfotIFOG6g/ShvotIFOqz+uVscED+apP76uALnXXKg/AiuHFtnOpz8nT9S/EcqoPzv9G6GM3qY/CUlTKs4+tD+nR+F6FK63P2ADnTbQaaM/cWq8dJMYpD+sOiZ4ME+kP+f7qfHSTaI/315zIWlKpT9iEFg5tMimP3N3d3d3d6c/CMrobVmroz+gOPvwGXalP4ts5/up8aI//Me95kLSpD/rb4QyelumP5iM3pa1OqY/47SBThvopD87/RuhjN6mP3sjlNHbsqY/+HGvuZA0pT+kjgkezBOlPyPb+X5qvKQ/w/UoXI/CpT9YSJpScfahPxB2Bci95qI/x0s3iUFgpT+75kLSlIrHP6w6JngwT6Q/TEZvy1odoz+gKRVnHz6jPy/dJAaBlaM/HYcW2c73oz/nCpB7zYWkP3Noke18P6U/bAXIveZCoj/0DLsC5F6jP7TmQtKUiqM/RKk4+/AZpj9vME/UvxGqP6oAuddcSKo/sqzVMcGDqT8ALbKd76emP2i+nxov3aQ/uDxR/0Yooz+TGARWDi2iPzMzMzMzM6M/M0IZvS1rpT8AHswT9W+kP7T1KFyPwqU//Me95kLSpD9I8GCeqH+jP1hImlJx9qE/VPKLJb9Yoj/FPnyGXQGiP+O0gU4b6KQ/pH8jlNHboj+PwvUoXI+iP6SOCR7ME6U/aK+5kDSloj9or7mQNKWiP2wFyL3mQqI/7FG4HoXroT++nxov3SSmP/p+arx0k7A/hxbZzvdToz/FPnyGXQGiP5MYBFYOLaI/tPUoXI/CpT9sFK5H4XqkP6R/I5TR26I/uDxR/0Yooz/n+6nx0k2iPz81XrpJDKI/GSIiIiIioj9qy1odEzywPy2yne+nxrs/3SQGgZVDuz91ov6NUEa3P+6LJb9Y8qs/zfl+arx0oz9I8GCeqH+jP+xRuB6F66E/qNUxwYN5oj9MRm/LWh2jP6jVMcGDeaI/qNUxwYN5oj+kfyOU0duiP1CcffgMu6I/g8DKoUW2oz9sBci95kKiP6R/I5TR26I/cWq8dJMYpD8ML90kBoGlP+tgnqh/I6Q/+GLJL5b8oj+LbOf7qfGiP/C2rNUxwaM/7FG4HoXroT/fT42XbhKjP5iM3pa1OqY/9BuhjN6WpT8EdNpApw2kP4/C9Shcj6I/62CeqH8jpD+8kl8s+cWiPzvfT42XbqI//LjXXEiaoj+TRbbz/dSoP4/gwTxR/6Y/UKtjggfzpD+sK0DuNReiPzvfT42XbqI/SPBgnqh/oz/FPnyGXQGiP5MYBFYOLaI/K4cW2c73oz+c0wY6baCjP7g8Uf9GKKM/O99PjZduoj/FPnyGXQGiPwAP5on6N6I/kxgEVg4toj9kWatjggejP88VIPeaC6k/vKFFtvP9pD+sOiZ4ME+kP6jVMcGDeaI/AA/mifo3oj8ZIiIiIiKiP6wrQO41F6I/i2zn+6nxoj8v3SQGgZWjPz81XrpJDKI/AA/mifo3oj9YSJpScfahP+xRuB6F66E/WEiaUnH2oT9JxdmHz7DDPxsv3SQGgaU/j9HbslbHpD9YV4Dcay6kP6ApFWcfPqM/WFeA3GsupD9QnH34DLuiPwAP5on6N6I/9kYoo7dlrT89KKO3Za2uP8uwK0DuNac/+GLJL5b8oj8ZIiIiIiKiP7g8Uf9GKKM/bAXIveZCoj/jpZvEILCiP+xRuB6F66E/rCtA7jUXoj9crY4JHsyjP4/C9Shcj6I/WEiaUnH2oT/sUbgeheuhP+xRuB6F66E/5/up8dJNoj9U8oslv1iiPz81XrpJDKI/pH8jlNHboj/fT42XbhKjP1hXgNxrLqQ/O99PjZduoj+05kLSlIqjP/hiyS+W/KI/GSIiIiIioj+LbOf7qfGiP57vp8ZLN6k/hyW/WPKLpT9I/0Yoo7elPzeJQWDl0KI/UJx9+Ay7oj+LbOf7qfGiP+xRuB6F66E/i2zn+6nxoj8v+/AZdgWoP3sjlNHbsqY/tPUoXI/CpT+kfyOU0duiP7ySXyz5xaI/pH8jlNHboj/sUbgeheuhPzeJQWDl0KI/0JSKsw+fsT9JjZduEoO4P+XQItv5frI/KWt1TPBgrj9MN4lBYOWwP4ts5/up8bI/KM4+fIZdsT8rpeLsw2eoP8MT9W+EMqo/XrpJDAIrpz+eDXTaQKetP1QBcq+5kKQ/KVyPwvUorD8W95oLSVOqP/QMuwLkXqM/9wy7AuRewz/n+6nx0k2iPwwg95oLSaM/7FG4HoXroT+sOiZ4ME+kPzeJQWDl0KI/aK+5kDSloj+o1THBg3miP+Olm8QgsKI/i3vNhaQppT+8oUW28/2kPxTb+X5qvKQ/FMwT9W+Eoj9OYhBYObTAP3H24TPsCug/wMqhRbbz5D/ntIFOG+jaP4/R27JWx7w/8vAZdgXIrT/PBjptoNOmP6BH4XoUrqc/JzEIrBxapD9or7mQNKWiP/hiyS+W/KI/rCtA7jUXoj+LbOf7qfGiP5zTBjptoKM/7FG4HoXroT+8kl8s+cWiP1TyiyW/WKI/i2zn+6nxoj/LsCtA7jW3P/p+arx0k8w/DuaJ+jdCzT/QlIqzD5/BP3yx5BdLfrk/vzxR/0Youz+gGi/dJAaxPx+jt2Wtjqk/FNv5fmq8pD/jpZvEILCiP6wrQO41F6I/7FG4HoXroT8ZIiIiIiKiPzvfT42XbqI/O99PjZduoj9YSJpScfahP5MYBFYOLaI/AA/mifo3oj+05kLSlIqjPz81XrpJDKI/UJx9+Ay7oj/sUbgeheuhP+xRuB6F66E/AA/mifo3oj/sUbgeheuhP5MYBFYOLaI/01xImlJxpj8/RERERESkP/hiyS+W/KI/AA/mifo3oj9kWatjggejP2wUrkfheqQ/rCtA7jUXoj/rYJ6ofyOkPxKDwMqhRaY/f3mi/o1Qpj+09Shcj8KlP7ySXyz5xaI/j+DBPFH/pj8v+/AZdgWoPwwg95oLSaM/62+EMnpbpj8OS36x5BerP9eyVscED6Y/BHTaQKcNpD/n+6nx0k2iP/hiyS+W/KI/WFeA3GsupD/wtqzVMcGjPxKSplScfag/CvVvhDJ6qz9/eaL+jVCmP1CrY4IH86Q/oCkVZx8+oz8MIPeaC0mjP/hiyS+W/KI/5/up8dJNoj8v3SQGgZWjPxCF61G4HqU/zwY6baDTpj9MVVVVVVWlPwAP5on6N6I/GSIiIiIioj/0DLsC5F6jP4/C9Shcj6I/zfl+arx0oz8GkHvNhaSpP99ecyFpSqU/TFVVVVVVpT+LbOf7qfGiP6wrQO41F6I/rCtA7jUXoj/A6G1Zq2OiP8U+fIZdAaI/bAXIveZCoj83mCfq3wilP5Mn6t8IZaQ/i2zn+6nxoj/4YskvlvyiP+O0gU4b6KQ/MzMzMzMzoz8ML90kBoGlP6BH4XoUrqc/pJ3vp8ZLpz9UAXKvuZCkP8U+fIZdAaI/rCtA7jUXoj+4PFH/RiijP/y411xImqI/JTMzMzMzoz/TXEiaUnGmPxB2Bci95qI//LjXXEiaoj/sUbgeheuhP1hImlJx9qE/O99PjZduoj8ZIiIiIiKiP0xGb8taHaM/I/nFkl8sqT9YV4Dcay6kP6ApFWcfPqM/O99PjZduoj8ZIiIiIiKiP+xRuB6F66E/wOhtWatjoj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/8uNdcSJqiP8U+fIZdAaI/pH8jlNHboj/sUbgeheuhP1TyiyW/WKI/Id0kBoGVoz+HFtnO91OjP1hXgNxrLqQ/F9nO91PjpT9Cb8taHROsP/zHveZC0qQ/nNMGOm2goz+PwvUoXI+iPwAP5on6N6I/j8L1KFyPoj+8kl8s+cWiP6R/I5TR26I/AA/mifo3oj+gKRVnHz6jP/ZGKKO3Za0/ICIiIiIisj+YbhKDwMqxP31OG+i0ga4/mqh/I5TRqz8xCKwcWmSrPwaQe82FpKk/rkfhehSupz9/arx0kxikP7yhRbbz/aQ/YBKDwMqhpT83iUFg5dCiP4uKsw+fYac/k0W28/3UqD8730+Nl26iPyHdJAaBlaM/AC2yne+npj+wkDSl4uyjP2ADnTbQaaM/5/up8dJNoj++nxov3SSmPxb3mgtJU6o/rlbHBA/mqT9eukkMAiu3Pzb78Bl2BbA/wxP1b4Qyqj+kjgkezBOlP6SOCR7ME6U/tOZC0pSKoz8zUf9GKKOnP+cKkHvNhaQ/UKtjggfzpD/DBA/mifqnP1hXgNxrLqQ/+HGvuZA0pT+P4ME8Uf+mP3YwT9S/EcY/7FG4HoXroT9YSJpScfahP5MYBFYOLaI/szomeDBPtD+e/o1QRm+7P/y411xImrI/JQaBlUOLrD+o5BdLfrGkP8DobVmrY6I/xT58hl0Boj9MRm/LWh2jP1hmZmZmZqY/XK2OCR7Moz9U8oslv1iiP8DobVmrY6I/wOhtWatjoj/FPnyGXQGiPxkiIiIiIqI/j8L1KFyPoj/b+X5qvHSjPz81XrpJDKI/7FG4HoXroT/sUbgeheuhP8DobVmrY6I/j8L1KFyPoj9sBci95kKiP/p+arx0k6g/AC2yne+npj8UzBP1b4SiP6jVMcGDeaI/bAXIveZCoj8QdgXIveaiP6jVMcGDeaI/qNUxwYN5oj8AD+aJ+jeiP3XAyqFFtqM/qOQXS36xpD9ovp8aL92kP6R/I5TR26I/YAOdNtBpoz+TGARWDi2iP1TyiyW/WKI/PzVeukkMoj91wMqhRbajP2wUrkfheqQ/wOhtWatjoj8730+Nl26iP+Olm8QgsKI/TEZvy1odoz+kfyOU0duiP9eyVscED6Y//uNecyFpqj/l7u7u7u6uP5kLSVMqzrY/pH8jlNHbsj8dWmQ730+tP5ZDi2zn+6k/nOLsw2fYpT9I8GCeqH+jP5h9+Ay7AqQ/j9HbslbHpD9sFK5H4XqkP1TyiyW/WKI/AA/mifo3oj/jpZvEILCiP4/C9Shcj6I/eRbZzvdToz/wtqzVMcGjP8DobVmrY6I/j8L1KFyPoj+o1THBg3miPwAP5on6N6I/tOZC0pSKoz+PwvUoXI+iPzvuNReSpqQ/oCkVZx8+oz9gA5020GmjP2Roke18P6U/UJx9+Ay7oj9MRm/LWh2jP5M20GkDnaY/L90kBoGVoz/4YskvlvyiP8DobVmrY6I/xT58hl0Boj8/NV66SQyiP+xRuB6F66E/7FG4HoXroT+sK0DuNReiP+xRuB6F66E/7FG4HoXroT/sUbgeheuhPw/K6G1Zq7s/7nw/NV469z9OG+i0gQ4SQJb8YskvFhJALfnFkl8sC0AUrkfhepQAQFnyiyW/WP4/6LSBThvoAkDXo3A9CtcIQIiIiIiIiAdACtejcD0K/T9Di2zn+6nhPzxR/0Yoo9M/tWWtjgkezD9D/RuhjN7GP4ts5/up8cI/RIts5/upwT/clrU6JnjAPyPq3whl9L4/nv6NUEZvuz/9VQ4tsp23Py/sCpB7zbU/boQyelvWsj8lFWcfPsOuP+58PzVeurE/ke18PzVesj+9EcrobVmzP4AH80T9G7E/Lk/UvxHKsD877jUXkqa0P30/NV66Saw/8uEz7AqQqz89Gb0ta3WsP05x9uEz7Ko/AklTKs4+rD+JQWDl0CKrP3fcay4kTak/pH8jlNHbsj/A6G1Zq2OiP+xRuB6F66E/7FG4HoXroT9YSJpScfahPy/sCpB7zaU/N5gn6t8IpT/Jo3A9CtejP7hLN4lBYKU/j8L1KFyPoj8/NV66SQyiP+xRuB6F66E/wOhtWatjoj/jtIFOG+ikP5iM3pa1OqY/L90kBoGVoz8IyuhtWaujP1CrY4IH86Q/qNUxwYN5oj8ZMQisHFqkP3sjlNHbsrY/wq4AuddcxD/l0CLb+X7QPz6nDXTaQM8/7FG4HoXrxT/3xZJfLPm1PzNg5dAi26k/O/0boYzepj+c0wY6baCjP0xVVVVVVaU/sJA0peLsoz+c4uzDZ9ilPz9TKs4+fKY/hyW/WPKLpT/fT42XbhKjP8U+fIZdAaI/PzVeukkMoj9QnH34DLuiP4cW2c73U6M/rCtA7jUXoj99bOf7qfGiP+Olm8QgsKI/daL+jVBGvz+1OiZ4ME/SPw7mifo3QtE/3SQGgZVDwz/4U+Olm8S4P0u4HoXrUbg/ZxKDwMqhtT8uT9S/EcqwP9TqmODBPLE/QOF6FK5HsT9JfrHkF0u2PyPb+X5qvLw/h8+wK0DuwT+mqqqqqqq6Pw2fYVeA3LM/YOXQItv5rj9WHRM8mCeqP76uALnXXKg/pJ3vp8ZLpz8K9W+EMnqrPwJJUyrOPqw/qPP91Hjppj/PBjptoNOmP99PjZduEqM/RJpScfbhoz8dhxbZzvejP5h9+Ay7AqQ/w/UoXI/CpT/nCpB7zYWkP99PjZduEqM/eyOU0duypj81fIZdAXKvP9NNYhBYObw/mVJx9uEzxD8BnTbQaQPFP7SBThvotNU/dEzwYJ6o7T8HOm2g0wbsP+nfCGX0ttw/Bx7ME/VvyD/aay4kTam4P2XYFSD3mrM/Y56ofyOUsT/8uNdcSJqyP5zi7MNn2KU/ukkMAiuHpj+AB/NE/RuxP7gta3VM8Lg/hfo3Qhm9rT8jCKwcWmSrP1Ys+cWSX6w/6TUXkqZUrD/jw2fYFSCnP8u/Ecrobak/CKwcWmQ7rz9/iIiIiIioPxKDwMqhRaY/O/0boYzepj/6fmq8dJOoPwafYVeA3Ks/rEkMAiuHpj+PwvUoXI+iP6R/I5TR26I/8Las1THBoz/fT42XbhKjPzeJQWDl0KI/fWzn+6nxoj8K16NwPQqnP/LSTWIQWKk/P1Mqzj58pj+TNtBpA52mPxTME/VvhKI/AA/mifo3oj/sUbgeheuhPw4tsp3vp6Y/+HGvuZA0pT8SoYzelrWqP9eyVscED6Y/aL6fGi/dpD/A6G1Zq2OiP8U+fIZdAaI/DCD3mgtJoz8zMzMzMzOjPwAtsp3vp6Y/g96WtTomqD+05kLSlIqjP/QMuwLkXqM/PQrXo3A9wj+LirMPn2GnP+xRuB6F66E/PzVeukkMoj9QnH34DLuiP2ADnTbQaaM//LjXXEiaoj8nMQisHFqkPyR4ME/Uv7E/f2q8dJMYpD9vEoPAyqGlP5ebxCCwcqg/CLsC5F5zsT82+/AZdgWwP99ecyFpSqU/tOZC0pSKoz8AD+aJ+jeiP+xRuB6F66E/aK+5kDSloj8UzBP1b4SiP2Roke18P6U/oEW28/3U0D+2rNUxwYPbP06Nl24Sg9I/ZmZmZmbm8T/yiyW/WDITQJ020GkDXR5AR+F6FK4HGECkcD0K12MQQBERERERkQRA7FG4HoXr/j9VVVVVVVX6P/8boYzeluk/WYDcay4k3T+jKRVnHz7ZPzCW/GLJL9Y/uKzVMcGD1T8meDBP1L/TP6Xi7MNn2NE/HcwT9W+E0D+J+jdCGb3JP+Dsw2fYFcg/KVyPwvUoxD+oHFpkO9/DP/WaC0lTKsY/gAfzRP0bxT9D/RuhjN7CPzKl4uzDZ8A/SPBgnqh/oz+iY4IH80StP6RwPQrXo7g/Y7x0kxgEtj+cxCCwcmi5P0bF2YfPsLM/vzxR/0Youz9ooNMGOm24P6JFtvP91Mg/62CeqH8jtD/l3whl9LasP5VhV4Dca64/6KfGSzeJsT89CtejcD2yP7YgsHJoka0/0r8RyuhtsT+icmiR7XyvPw48mCfq37A/RIts5/upsT/I6G1Zq2OyP+XQItv5frI/TnH24TPssj/I6G1Zq2OyP5huEoPAyrE/1iQGgZVDsz+1Za2OCR60P3QFyL3mQro/c2iR7Xw/xT+R7Xw/NV7KPzpR/0Yoo78//UYoo7dltT/KItv5fmq0P4JBYOXQIrM/pH8jlNHbsj98seQXS36xP0oqzj58hq0/yYWkKRVnrz85w64AudesPzVeukkMAqs/dZMYBFYOrT9q2kCnDXSqPy/dJAaBlcM/Gui0gU4bxD+ONKXi7MO3Pxzb+X5qvLQ/sqzVMcGDsT+NtTomeDCvP4GkKRVnH64/N5gn6t8IpT8AHswT9W+kP1CrY4IH86Q/ZnVM8GCeqD/ByqFFtvOtP+XfCGX0tqw/+ICVQ4tspz9acyFpSsWpP5Mn6t8IZaQ/uEs3iUFgpT8rlvxiyS+mP76uALnXXKg/thHK6G1Zqz+NplScffisP4aIiIiIiLA/efgMuwLkrj9I/0Yoo7elP1pkO99Pjac/DjyYJ+rfqD/6jVBGb8uqP7pn2BUg96o/d9xrLiRNqT9MZDvfT42nP8u/Ecrobak/f2q8dJMYpD9MRm/LWh2jP2ADnTbQaaM/cWq8dJMYpD9iHz7DrgCpP6JUnH34DKs/x1odEzyYpz9I/0Yoo7elP9CUirMPn7E/u+ZC0pSKsz/+415zIWmqP6wrQO41F6I/5wqQe82FpD+o5BdLfrGkP4clv1jyi6U/i3vNhaQppT9BGb0ta3XAP1yPwvUoXK8/UJx9+Ay7oj9YV4Dcay6kP76fGi/dJKY/17JWxwQPpj9xarx0kxikP28haUrF2ac/vKFFtvP9pD8ML90kBoGlPxfotIFOG6g/yYWkKRVnrz8xJngwT9SvP9nO91Pjpas/+ICVQ4tspz/0KocW2c6nPxkxCKwcWqQ/UKtjggfzpD+R/GLJL5asP90z7AqQe60/SPBgnqh/oz/jpZvEILCiP/zHveZC0qQ/VAFyr7mQpD+pY4IH80TFPycxCKwcWrw/1hUg95oLuT/ErgC511zjPzfQaQOdtgtAEHTaQKfNEkC5HoXrUbgQQAAAAAAAAAlA7+7u7u7uAUD1KFyPwvX5P7xJDAIrh+4/a3VM8GCe5D9fLPnFkl/gP7uQNKXi7N8/UI2XbhKD2j//jVBGb8vUP6uqqqqqqtI/uB6F61G40j8fzBP1b4TSP3npJjEIrNI/jZduEoPA0j83Qhm9LWvRP/tiyS+W/M4/x5JfLPnFyj/61HjpJjHIP440peLsw8c/5m1Zq2OCxz9jZmZmZmbGP4WkKRVnH8Y/82+EMnpbxj/E2YfPsCvEP64AuddcSMI/dZMYBFYOwT/d3d3d3d3BP6bi7MNn2ME/rNUxwYN5wj9Y8oslv1jCP9NNYhBYOcQ/bstaHRM8xD+DeaL+jVDCP3N3d3d3d7c/ZErF2YfPuD+6WPKLJb+4P+rSTWIQWLk/47SBThvovD93vp8aL928P3QFyL3mQro/tNdcSJpSuT9KG+i0gU67P5w20GkDndY/1QY6baDTBEDkF0t+seQLQHsUrkfh+gJA5RdLfrHk9D9ImlJx9uHrP6k4+/AZduU/IiIiIiIi4z+RNKXi7MPhP5gn6t8IZeA/q2OCB/NE3T9jV4Dcay7aP0NERERERNg/4XoUrkfh2D8uJE2pOPvUP4XrUbgehdE/72CeqH8jzD8AAAAAAADMP4relrU6Jsw/2msuJE2pzD+6SQwCK4fOPzltoNMGOs0/ZmZmZmZmxj/2KFyPwvXAP7M6JngwT8A/9ihcj8L1wD/14TPsCpDDP1pkO99PjcM/dEzwYJ6owz+AB/NE/RvBP6RwPQrXo8A/9P3UeOkmwT9bq2OCB/PAP05iEFg5tMA/dZMYBFYOwT9Z1uqY4MHAP9YVIPeaC8E/001iEFg5wD/TTWIQWDm8P3CvuZA0pbo/V7pJDAIrtz+JUEZvy1q1P8SSXyz5xbI/PqcNdNpAtz+YffgMuwK8PzeJQWDl0Lo/wwQP5on6tz+sHFpkO9+3P5+M3pa1OrY/epVDi2znsz+VUnH24TO0P0Uoo7dlrbY/nNMGOm2gsz8EZfS2rNWxP2Xn+6nx0rU/ICIiIiIisj/SzvdT46WzP37cay4kTbE/MHpb1uqYsD8/NV66SQyyPzMzMzMzM7M/j8L1KFyPsj8c2/l+ary0P0jhehSuR7E/hF0Bcq+5sD/umgtJUyquP0Jvy1odE6w/hfo3Qhm9rT9G1L8RyuitP/7yRP0boaw/5e7u7u7urj9WDi2yne+nP2IfPsOuAKk/vq4AuddcqD/ufD81XrqpP5HtfD81Xqo/jZduEoPAqj+F61G4HoWrP4GkKRVnH64/9BuhjN6WpT/4gJVDi2ynPz9TKs4+fKY/sJ8aL90kpj89Gb0ta3WsP4GVQ4ts56s/ObTIdr6fqj8CSVMqzj6sP+PDZ9gVIKc/XskvlvxiqT9vIWlKxdmnP1hmZmZmZqY/OcOuALnXrD82+/AZdgWwP2iR7Xw/Na4/2c73U+Olqz9iHz7DrgCpP+kmMQisHKo/WFeA3GsupD+TJ+rfCGWkP+coXI/C9ag/aKDTBjptsD9I4XoUrkexPwisHFpkO68/5dAi2/l+qj85tMh2vp+qP0Jvy1odE6w/iUFg5dAiqz/l3whl9LasPyG/WPKLJa8/sHJoke18rz+VYVeA3GuuP5VScfbhM6w/sqzVMcGDsT/Vh8+wK0C+P+YmMQisHMo/dnd3d3d3zz9P/0Yoo7fFPzpg5dAi27k/FVpkO99PtT8YdgXIveayP4RdAXKvubA/qg+fYVeArD/DE/VvhDKqP+GJ+jdCGa0/aKDTBjptsD/pJjEIrByqP4lQRm/LWq0/uEs3iUFgpT/TXEiaUnGmP4/gwTxR/6Y/hzSl4uzDpz+wcmiR7XyvPxVLfrHkF7M/9P3UeOkmsT9acyFpSsWxP6RwPQrXo7A/5dAi2/l+sj9U8oslv1iyP3YwT9S/EbI/OcOuALnXtD8Sg8DKoUXCP09Gb8taHcc/sHJoke18vz9l5/up8dK1P/nwGXYFyLU/C0lTKs4+0D820GkDnTbhP+wKkHvNheU/jSW/WPKL9D9J4XoUrkfyP7y7u7u7u/g/TxvotIFO+z+kcD0K16P7P36x5BdLfvM/FPVvhDJ66j+RplScffjhPyvOPnyGXeA/pSkVZx8+2z9+I5TR27LYP1XHBA/midQ/aJHtfD811D/9YskvlvzSP+iY4ME8Uc8/fPgMuwLkzj9+I5TR27LQP+Lsw2fYFdA/ZdgVIPeayz8ZWmQ730/JP+01F5KmVMg/46WbxCCwxj+3SQwCK4fGPxrotIFOG8g/N0IZvS1ryT/78Bl2BcjTP/vwGXYFyN0/bS4kTak47j9xPQrXo3D8PxAREREREe4//WLJL5b84D8IrBxaZDvbP3npJjEIrNg/2/l+arx04T+4HoXrUbj/Pylcj8L1qANAFK5H4XoU+z99arx0kxjsP6NFtvP91Oc/veZC0pSK4z+3HoXrUbjiP519+Ay7At4/n6h/I5TR2z9vEoPAyqHTP4AjlNHbstI/CR7ME/Vv0j8CK4cW2c7RP73mQtKUitM/XI/C9Shc1T+xK0DuNRfUP1jyiyW/WNI/AiuHFtnO0T+/5kLSlIrRP23n+6nx0uw/4XoUrkfhAkBz2kCnDXQCQB6F61G4nvQ/JE2pOPvw5z/MzMzMzMziPxi9LWt1TOE/ZfS2rNUx4j8Bcq+5kDTiP7sC5F5zIeE/PJgn6t8I4D+Nl24Sg8DeP7SBThvotN0/6SYxCKwc3j+gGi/dJAbbP8UgsHJokdk/PCZ4ME/U2T9z2kCnDXTYPy1rdUzwYNg/fYZdAXKv2T8AK4cW2c7XP2Q730+Nl9Y/3SQGgZVD1z8IZfS2rNXVP30/NV66SdQ/ugLkXnMh0z/b+X5qvHTTP3YFyL3mQtQ/rBxaZDvf0z9kyS+W/GLRP8KuALnXXMw/3d3d3d3dzT/P91PjpZvMP8a95kLSlM4/sHJoke18zz/fT42XbhLVP10Bcq+5kNo/SOF6FK5H1T8EVg4tsp3LP+WJ+jdCGck/zczMzMzMyD9mZmZmZmbKPxaSplScfcg/lyfq3whlyD8aoYzelrXGP+NecyFpSsU/TmIQWDm0xD8q+cWSXyzFP2xZq2OCB8M/gU4b6LSBxj+sHFpkO9/HP/9xr7mQNMk/5/up8dJNyj800GkDnTbIP1sBcq+5kMg/VOOlm8QgyD93vp8aL93IP3npJjEIrMg/sQ+fYVeAyD+NUEZvy1rJP1Eqzj58hsk/dEzwYJ6oxz90Bci95kLGP4QW2c73U8c/9wy7AuRexz/vGXYFyL3GP+8ZdgXIvcY/sp3vp8ZLxz/bslbHBA/GP0K28/3UeMU/it6WtTomxD/KWh0TPJjDP4FOG+i0gcI/NV66SQwCwz9pLiRNqTjDP4XrUbgehcM/z/dT46WbxD9RcfbhM+zGP98IZfS2rNM/e82FpCkV4j8JZfS2rNXgP4QyelvW6tQ/7AqQe82F5T8NdNpAp40BQE8b6LSBzgBAjZduEoPA6j8LHswT9W/eP+0KkHvNhdo/0SLb+X5q1j/lifo3QhnXP5HtfD81XtQ/xNmHz7Ar1D/HSzeJQWDTP06Nl24Sg9I/o7dlrY4J1j9soNMGOm3WPwwCK4cW2dQ/1DHBg3mi0j8o6t8IZfTSP9S/EcrobdM/5/up8dJN0j8neDBP1L/RP1pkO99Pjdk/FSD3mgtJ4j8OLbKd76fhP9v5fmq8dNs/LPnFkl8s1z+c76fGSzfVPxt2Bci95tI/001iEFg52j8ZvS1rdYwBQBdLfrHkFw9AodMGOm0gCkD2KFyPwnUDQH+x5BdL/gZAZmZmZmamEECx5BdLfjEJQIXrUbgehQFAQacNdNpA+D9+seQXS37zP0maUnH24fA/mW4Sg8DK6j/Fkl8s+cXnP4frUbgeheY/n6h/I5RR9D8b6LSBTtsSQBSuR+F6VBdAAQAAAAAAGkCdNtBpA90XQFhVVVVVVQxAXY/C9ShcBUD8YskvlnwDQLgehetRuP4/VVVVVVVV9j/QaQOdNtAKQASdNtBpwxdAVVVVVVVVF0CPwvUoXA8QQMSSXyz5RSRAzczMzMxMMEAjIiIiIuI3QDMzMzMzczlAiIiIiIioOUAhIiIiIgI5QLu7u7u7WzRAzczMzMzMKkBmZmZmZgYiQIiIiIiI6CJABzptoNMGIUDNzMzMzAwXQIFOG+i0gQ5A6LSBThtoCEBxPQrXo/AFQHE9CtejcAJAVVVVVVVV9j8BAAAAAAD0PxdLfrHkF/I/SgwCK4cW8D/ziyW/WPLrP9QGOm2g0+k/09uyVscE5z8o6t8IZfTkP58aL90kBuM/TxvotIFO4z+gGi/dJAbiP++nxks3ieA/NxeSplSc4D/9qfHSTWLgP1Y5tMh2vt8/OW2g0wY63z+PUEZvy1rdPxXZzvdT490/EmcfPsOu3D8/NV66SQzcP+zDZ9gVINs/A5020GkD2z/tNReSplTaPz/uNReSptg/qX8jlNHb1j9UDi2yne/XP9LbslbHBNc/3LJWxwQP1j9cukkMAivVP55hV4Dca9Q/xSCwcmiR0z/7N0IZvS3TP8/3U+Olm9I/es2FpCkV0z/2U+Olm8TSP2OCB/NE/dE/PFH/Riij0T9kO99PjZfQPzMzMzMzM88/R1Mqzj58zj9p5/up8dLNPxzME/VvhM4/Vg4tsp3v0T9VVVVVVVXRP7TIdr6fGtE/pLdlrY4J0D8C5F5zIWnOP2T0tqzVMdE/ggfzRP0b0T91kxgEVg7RP5/TBjptoNE/QKcNdNpA0T9FRERERETQP166SQwCK88/ukkMAiuH0D+DwMqhRbbPP/FE/RuhjM4/p38jlNHbzj8TIPeaC0nPP8EgsHJokc0/EoPAyqFFyj8m6t8IZfTGP6ljggfzRMk/JurfCGX0yj/xRP0boYzKP/Z+arx0k8w/W7pJDAIrzz+Ksw+fYVfQP+f7qfHSTdA/K4cW2c73zz8H80T9G6HSPxKDwMqhRdY/84slv1jy1z/UBjptoNPWP6WbxCCwcuE/0WkDnTbQ8D/4U+Olm8TlP1nyiyW/WNw/0LArQO412z8fsHJoke3WP/hT46WbxNo/6wqQe82F7j9kyS+W/GLpP23n+6nx0t8/XQFyr7mQ4D8Bcq+5kDTsP9S/Ecrobew/dwXIveZC4z/lifo3QhnfP6uqqqqqqtw/o7dlrY4J3D/W6pjgwTzbP5t9+Ay7Ato/7Xw/NV664z+ZUnH24TPsP6GM3pa1Oug/xK4Auddc4z/xYJ6ofyPeP0B8hl0Bcts/m1Jx9uEz2j/BPFH/RijXP3cFyL3mQtY/8Bl2Bci91D9g5dAi2/nSP+F6FK5H4dI/m334DLsC1D9hV4Dcay7SP8yFpCkVZ9E/BQ/mifo30j9tWatjggfRP9Ei2/l+atA/ZDvfT42Xzj/n+6nx0k3OP7gehetRuM4/k9HbslbHzD+4HoXrUbjKPwLkXnMhaco/gAfzRP0byT87mCfq3wjJP9NNYhBYOcg/sQ+fYVeAyD81F5KmVJzJP1NVVVVVVck/IyIiIiIiyj+kt2WtjgnKPx1aZDvfT8k/vljyiyW/yD+K3pa1OibIP/XhM+wKkMc/ukkMAiuHxj8qQO41F5LGP6Pi7MNn2MU/EjyYJ+rfxD8PyuhtWavDP5KKsw+fYcM/jZduEoPAwj/zb4QyelvCP64AuddcSMI/1hUg95oLwT+411xImlLBP3cFyL3mQsI/kkOLbOf7wT++WPKLJb/APx4GgZVDi7w/H5TR27JWtz/KE/VvhDK6PyuHFtnO97s/CuaJ+jdCuT//ca+5kDS9P6c4+/AZdsE/TdS/EcrowT9zaJHtfD/BP9IGOm2g08I/t5A0peLswz8R9W+EMnrDPwGdNtBpA8U/l+DBPFH/xj9IN4lBYOXMP6AaL90kBuQ/WPKLJb9YAECBThvotAEKQEjhehSuRw9AXyz5xZIfEEBY8oslv9gLQI/C9ShcDw1AKVyPwvUoBUASEREREZECQJFfLPnFEgFASgwCK4cW8j8RERERERHrPyFpSsXZh+Y/QacNdNpA5D9jO99PjZfiPz98hl0BcuA/nDbQaQOd3D+WtTomeDDbP1Nx9uEz7No/dkzwYJ6o2T+lKRVnHz7ZP3L24TPsCtg/8NJNYhBY1z+xK0DuNRfWP8uhRbbz/dQ/q6qqqqqq1D9lrY4JHszTPwIrhxbZztM/jVBGb8ta0z+ZUnH24TPSP7eQNKXi7M8/1hUg95oLzT8QWDm0yHbOP8vobVmrY84/pVScffgMzz+dYVeA3GvOP90kBoGVQ88/AiuHFtnOyz++nxov3STOPwqQe82FpM0/+fAZdgXIzT8ozj58hl3NP9TqmODBPM0/XI/C9Shc0T+EMnpb1urWP1OcffgMu9w/A5020GkD3z/XzvdT46XdP3D24TPsCtw/r+QXS36x2j9b1uqY4MHYP+htWatjgtc/u7u7u7u71z9yIWlKxdnVP4izD59hV9Q/1L8Ryuht0z9YObTIdr7RP9QxwYN5os4/yC+W/GLJyz8wT9S/EcrQP1eA3GsuJNE/gU4b6LSBzj/E2YfPsCvMPwisHFpkO8c/oykVZx8+xz8z7AqQe83FP8paHRM8mMM/Gy/dJAaBxT8BnTbQaQPFP7JWxwQP5sU/7xl2Bci9xj8cEzyYJ+rHP8yFpCkVZ8c/zz58hl0Bxj8welvW6pjEP/7UeOkmMcQ/p38jlNHbwj/ufD81XrrBP4lQRm/LWr0/exSuR+F6wD877jUXkqa8PxKDwMqhRb4/tvP91Hjpwj/rCpB7zYXEP/+411xImsY/IpTR27JWwz/CZ9gVIPfCP1jyiyW/WMI/BFYOLbKdwz9xPQrXo3DFP8Jn2BUg98Y/Q0REREREyD8NdNpApw3QP28Sg8DKofE/7FG4HoXrCUBdj8L1KNwIQKuqqqqqqvY/n4zelrU67j/w7u7u7u7mP0HuNReSpuE/peLsw2fY4D8Sg8DKoUXeP9bqmODBPNs/Qots5/up1z8DnTbQaQPZP6UpFWcfPtU/11xImlJx0j+UirMPn2HTPw4tsp3vp9Q/WmQ730+N0z/sfD81XrrTP2fYFSD3mtM/yb3mQtKU0j+Y4ME8Uf/QP3WTGARWDs0/QHyGXQFyzz+/PFH/RijPP9uyVscED9A/+/AZdgXI0T8QWDm0yHbQP93d3d3d3c0/xNmHz7AryD/xiyW/WPLHPwwCK4cW2cY/V6tjggfzxD+4HoXrUbi+P6Pi7MNn2MU/aErF2YfPzD/DPFH/RijLP7bz/dR46co/kkOLbOf7yT+9yqFFtvPJP0K28/3UeMk/27JWxwQPyj89CtejcD3QP7HkF0t+sdA/PcOuALnX0D/8qfHSTWLQP+Olm8QgsNA/ImlKxdmH0T+DwMqhRbbRP3ii/o1QRtM/q2OCB/NE1T+eGi/dJAbVP2L0tqzVMdU/g3mi/o1Q1D+J+jdCGb3TPyd4ME/Uv9M/hxbZzvdT0z+IiIiIiIjSP0/UvxHK6NE/kl8s+cWS0T+cxCCwcmjRP1vW6pjgwdA/p38jlNHb0D9GKKO3Za3QP8m95kLSlNA/4hdLfrHkzz9mZmZmZmbQP4FOG+i0gc4/gjJ6W9bqzD/Hkl8s+cXKP5GmVJx9+MQ/9wy7AuRewz9+I5TR27LGP2Dl0CLb+cI/nah/I5TRxz/t7u7u7u7KP+p8PzVeusk/KVyPwvUoyD/0/dR46SbJP5GmVJx9+Mg/wq4AuddcyD9SuB6F61HIP1odEzyYJ8o/DLsC5F5zyT+LbOf7qfHKP4N5ov6NUMo/BfNE/RuhyD95ME/UvxHKP/IoXI/C9cg/QNKUirMPxz83iUFg5dDKP8EgsHJokck/FGcfPsOuyD+MCR7ME/XHPzb78Bl2Bcg/1XjpJjEIyD+1Za2OCR7IP6MpFWcfPsc/kaZUnH34yD8ozj58hl3JP7as1THBg8k/dwXIveZCyj8ePsOuALnLPypA7jUXks4/2kCnDXTa0j+j/o1QRm/dP8SuALnXXOc/nxov3SQG6z/BPFH/RijrPxFYObTIdus/sHJoke187D+/WPKLJb/sPxzotIFOG+0/TmIQWDm07j91kxgEVg7wPxP1b4Qyeuk/qDj78Bl24z8X2c73U+PgPwRWDi2ynd8/2ofPsCtA3j9LqTj78BnePyJNqTj78N0/lm4Sg8DK3T81F5KmVJzdP0vF2YfPsN0/CpB7zYWk3T9TcfbhM+zeP/fhM+wKkN8/jZduEoPA4D9bHRM8mCfhPy5rdUzwYOA/54n6N0IZ3T8s+cWSXyzbPzm0yHa+n9g/tIFOG+i01T+/yqFFtvPVP21Zq2OCB9c/hxbZzvdT1T8Sg8DKoUXSP03wYJ6of9M/S/Bgnqh/0z/qUbgehevTPy4kTak4+9Q/peLsw2fY1T8zMzMzMzPXPzvfT42XbtY/Z9gVIPea0z81XrpJDALTP+f7qfHSTdI/9G+EMnpb0j8WkqZUnH3SP4ts5/up8dI/+FPjpZvE0j8GgZVDi2zRPxBYObTIdtI/rkfhehSu0T88Uf9GKKPRP+7u7u7u7tA/gU4b6LSB0D8wlvxiyS/QPycxCKwcWtA/8Yslv1jyzz/9G6GM3pbRP76fGi/dJNI/3Ja1OiZ40j/tNReSplTeP5iZmZmZmec/l24Sg8DK6T+UXyz5xZLuP5b8YskvlgNAvljyiyW/D0ClcD0K16MEQFG4HoXrUfU/DAIrhxbZ7z9TKs4+fIbuP3XaQKcNdPQ/Sn6x5BdL9D/v7u7u7u4BQB+F61G4Hv8/TxvotIFO9D+x5BdLfrHzP6cNdNpAp/8/oNMGOm2g+D8UrkfhehTzPwvXo3A9CvE/yS+W/GLJ8z/ptIFOG+jzPyijt2WtDvA/2BUg95oL6j8klNHbslblPzn78Bl2BeQ/tvP91Hjp4z9n2BUg95riP1+6SQwCK+A/y6FFtvP92j/IL5b8YsnZP2q8dJMYBNw/H8wT9W+E2j8+fIZdAXLZP78RyuhtWds/F9nO91Pj2T8AK4cW2c7XP1TjpZvEINo/rBxaZDvf2T/PPnyGXQHaP5HtfD81Xto/IGlKxdmH2z+F61G4HoXiP6wcWmQ73+c/u0kMAiuH5j+DeaL+jVDpP2MQWDm0yOU/mwtJUyrO4T8v3SQGgZXdP1urY4IH89w/gwfzRP0b4j+EeaL+jVD5P0p+seQXSwJAN9BpA522B0CF61G4HsUVQDCW/GLJLxZApHA9CtcjGED3KFyPwvUgQHsUrkfhuiRAIyIiIiKiJEBoZmZmZmYeQNQGOm2gExVAw/UoXI+CGEAOdNpAp00UQK/kF0t+sQ5Ar0fhehQuCUCF61G4HgUHQOF6FK5H4QVAs+QXS36x/z8AAAAAAAAAQO/u7u7u7gNAH4XrUbge/z/hehSuR+H1PxhLfrHkF/M/MTMzMzMz8j+nDXTaQKfxP6DTBjptoPA/Xyz5xZJf7j+fqH8jlNHrP6Xi7MNn2Ok/1b8Ryuht5z/5xZJfLPnlP1BGb8taHeY/R7bz/dR45T/rCpB7zYXjP6DTBjptoOE/EcrobVmr4T/IBA/mifrgP9CwK0DuNeA/HcwT9W+E4D8XIPeaC0ngP4GVQ4ts598/TfBgnqh/3z9PG+i0gU7gP4slv1jyi98/2yQGgZVD3T+TGARWDi3eP4PAyqFFtt8/1uqY4ME83z+/yqFFtvPbP3sUrkfhetw/haQpFWcf2j9GKKO3Za3WP98IZfS2rNM/O99PjZdu1D/Ag3mi/o3UP0jhehSuR9U/sw+fYVeA1j9iyS+W/GLVPxUg95oLSdU/8Bl2Bci90j/VeOkmMQjSP5A0peLsw9E/hetRuB6F0z9Apw102kDVPx4+w64AudM/vOZC0pSK6z/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP+9gnqh/I+4/gU4b6LSB6z+j/o1QRm/mP/W2rNUxweI/KVyPwvUo4D8nMQisHFrePz81XrpJDN4/HOi0gU4b3j9KfrHkF0vePzMzMzMzM9s/7QqQe82F2D+NUEZvy1rXP8/3U+Olm9Y/DXTaQKcN1j/UvxHK6G3VP0bhehSuR9U/nX34DLsC1D+cxCCwcmjTPzEIrBxaZNM/7u7u7u7u0j/jpZvEILDQP9j5fmq8dM8/5dAi2/l+zj/WMcGDeaLQPyGwcmiR7dA/dgXIveZC0D+UtTomeDDPPyVNqTj78M0/6nw/NV66zT+3kDSl4uzLP+rDZ9gVIMs/dwXIveZCyj+V/GLJL5bMP/O2rNUxwcs/OlH/Riijyz9VxwQP5onKPzuYJ+rfCMk/2c73U+Olxz9uy1odEzzIP8TZh8+wK8g/ubu7u7u7xz95PzVeuknIPwLkXnMhacY/kxgEVg4txj9zr7mQNKXGP+3u7u7u7sY/UXH24TPsxj+1Za2OCR7IP41QRm/LWsk/Y62OCR7Mxz+XJ+rfCGXIP8CDeaL+jcg/rBxaZDvfxz9yIWlKxdnHPzKl4uzDZ8g/tIFOG+i0yT8730+Nl27KP9IGOm2g08o/6wqQe82FzD+8LWt1TPDMP3tb1uqY4M0/SlMqzj58zj9uhDJ6W9bOPyajt2Wtjs0/c2iR7Xw/zT8LdNpApw3MPzltoNMGOsk/4OzDZ9gVzD8neDBP1L/NP6Pi7MNn2M0/ftxrLiRNzT9P/0Yoo7fNP2Q730+Nl84/T0Zvy1odzz9D/RuhjN7OPwQP5on6N84/Fy/dJAaBzT/4U+Olm8TMP7uQNKXi7Ms/m334DLsCzD+q8dJNYhDMPylcj8L1KMw/rbmQNKXizD8hsHJoke3MPzgmeDBP1Ms/Q/0boYzeyj9b8oslv1jKP2LJL5b8Ysk/j3vNhaQpyT800GkDnTbIP30/NV66Scg/NvvwGXYFyD9nA5020GnHPyH3mgtJU8Y/xJJfLPnFxj+h/o1QRm/HP2p1TPBgnsg/DuaJ+jdCyT85baDTBjrJP2rLWh0TPMg/HVpkO99PxT+411xImlLBP0xGb8taHbs/27JWxwQPxj/XXEiaUnHGP1NVVVVVVcU/O+41F5KmvD9y2kCnDXTCP0EZvS1rdcQ/vljyiyW/xD+GiIiIiIjMP90kBoGVQ8s/pVScffgMyz8LdNpApw3IPwPIveZC0sg/98WSXyz5yT9JfrHkF0vKPz81XrpJDMo/E9nO91PjyT+nfyOU0dvKP+XQItv5fso/M+wKkHvNzT+vuZA0peLQPx3ME/VvhNQ/O99PjZdu3j8fhetRuB7fPyOU0duyVuI/dEzwYJ6o7j9QjZduEoPqP9dcSJpSceM/c2iR7Xw/2z8jIiIiIiLYP9mHz7ArQNY/okW28/3U1D+EMnpb1urUP3IhaUrF2dU/dwXIveZC1D8vCKwcWmTXP0NERERERNY/uZA0peLs0T/hehSuR+HQP5MYBFYOLdA/FSD3mgtJ0T8730+Nl27SP2iR7Xw/NdI//WLJL5b80D8DnTbQaQPRP9gVIPeaC9E/eqL+jVBG0T+aC0lTKs7QP57vp8ZLN9E/r7mQNKXi1D9PRm/LWh3VP6k4+/AZdtE/anVM8GCezD9qvHSTGATKPxsv3SQGgc0/h8+wK0DuzT+lVJx9+AzPP3ii/o1QRtE/B/NE/Ruh0D8QWDm0yHbOP1Nx9uEz7NA/NOwKkHvN0z/n+6nx0k3WPxl2Bci95tI/JzEIrBxa0D9iEFg5tMjQPwqQe82FpNE/EZ9hV4Dczz9TRm/LWh3LP0x+seQXS8Y/5ELSlIqzxz8GgZVDi2zHP5lScfbhM8g/LbKd76fGyz/CveZC0pTOP+ZtWatjgs8/S6k4+/AZyj/xRP0boYzKP9v5fmq8dMs/y6FFtvP9zD8keDBP1L/NPx/ME/VvhM4/Wh0TPJgnzj95PzVeuknMPwlJUyrOPsw/1OqY4ME8zT/P91PjpZvMPzgmeDBP1Ms/EoPAyqFFzj8+pw102kDPP4qzD59hV9A/EFg5tMh20D+Y4ME8Uf/YP65H4XoUruA/B6wcWmQ74D9Ei2zn+6ngP4/C9Shcj9w/T0Zvy1od2T9DRERERETWP42XbhKDwNQ/6SYxCKwc1D9AYOXQItvTP/+411xImtI/Q0RERERE0j+V0duyVsfSP44JHswT9dM/w2fYFSD31D/hM+wKkHvTP3QhaUrF2dM/rwC511xI0j8OLbKd76fQPx/3mgtJU9A/FK5H4XoU0D+JQWDl0CLPP/hT46WbxMw/4uzDZ9gV0D+EXQFyr7nIP1ecffgMu8o//3GvuZA0zT/HveZC0pTQP9V46SYxCNA/SFMqzj580D/ah8+wK0DQPwkezBP1b9A/bxKDwMqh0z/p3whl9DbyP0RERERExApA5BdLfrFkCEDziyW/WPL6P+m0gU4b6PY/zczMzMzM9T9xPQrXo3DwP+f7qfHSTeg/rkfhehSu5D8MAiuHFtnjP9v5fmq8dOI/bqDTBjpt4T9aZDvfT43hP9gVIPeaC+E/ZvS2rNUx4D+8LWt1TPDePwhl9Las1d0/gjJ6W9bq3D8LSVMqzj7cPylcj8L1KNw/x73mQtKU3D9jggfzRP3sP5X8YskvlgNAPQrXo3A9+T+rqqqqqqr0P9ijcD0K1/U/FyD3mgtJ8T8cWmQ730/sP3vNhaQpFek/MXpb1uqY5T9KxdmHz7DjP39qvHSTGOI/hHmi/o1Q4T+3rNUxwYPgP8T1KFyPwt8/UyrOPnyG4D+dffgMuwLlP7MPn2FXgOE/YRBYObTI3j8O5on6N0LdPxwv3SQGgds/F9nO91Pj2T9eukkMAivZPxcg95oLSdk/SCijt2Wt2D9wEoPAyqHXP7ArQO41F9Y/3LJWxwQP1j+hjN6WtTrWP2vn+6nx0tU/j8L1KFyP1D9cj8L1KFzTP32GXQFyr9M/TfBgnqh/1T8f95oLSVPWP5JfLPnFktM/tzomeDBP0D86CtejcD3OPwhl9Las1c0/5ELSlIqzzz8fzBP1b4TOPybq3whl9M4/iIiIiIiI0D9qdUzwYJ7MP2Dl0CLb+co/iyW/WPKLyT/pJjEIrBzKP80T9W+EMso/J3gwT9S/yT/BILByaJHJP/GLJb9Y8ss/tMh2vp8axz9LqTj78BnGP99PjZduEsc//Knx0k1iyD9iyS+W/GLJP3rNhaQpFcs/HBM8mCfqyz+jKRVnHz7LP4n6N0IZvck/6nw/NV66yT+nOPvwGXbFPygVZx8+w8Y/U1VVVVVVxT8QWDm0yHbGP4XrUbgehcc/VOOlm8QgyD/VeOkmMQjEP00b6LSBTsM/jjSl4uzDwz+xD59hV4DEP7TIdr6fGsM/sCtA7jUXwj/KE/VvhDLCPyJNqTj78MU/JHgwT9S/wT8asHJoke28P7Kd76fGS78/byFpSsXZvz9uy1odEzzEP/4qhxbZzsM/q44JHswTxT9NG+i0gU7HPyUGgZVDi8A/+2LJL5b8xj9L8GCeqH/DPyKU0duyVsc/30+Nl24Sxz8UZx8+w67IP8KuALnXXMw/XwFyr7mQzD8GOm2g0wbKPz3DrgC518g/ciFpSsXZxz+v5BdLfrHIP4FOG+i0gco/qMZLN4lBzD+v5BdLfrHMP/yp8dJNYsw/Y62OCR7Myz9bukkMAivLPwhl9Las1ck/ScXZh8+wxz+T0duyVsfIPzpR/0Yoo8c/GHYFyL3mxj/jpZvEILDGP5RuEoPAysE/1OqY4ME8wT8YdgXIvebCP1WA3GsuJMU/AZ020GkDxT+75kLSlIrHPwsezBP1b8g/uNdcSJpSyT+dqH8jlNHHP4XrUbgehcc/hoiIiIiIyD9oSsXZh8/IP10s+cWSX8g/+FPjpZvEyD+pqqqqqqrGP/1GKKO3ZcU/BoGVQ4tswz/b+X5qvHTDP4QW2c73U8M/eTBP1L8Rwj8Sg8DKoUXCP9K/EcrobcU/c76fGi/dxD8R9W+EMnrDP7ArQO41F8I/rBxaZDvfvz9HmlJx9uHDP1K4HoXrUcA/Ik2pOPvwwT9kO99PjZfGPzPsCpB7zcU/0NuyVscExz/fT42XbhLDP8a95kLSlMI/bef7qfHSwT9vIWlKxdm/P6mqqqqqqsI/Vg4tsp3vwz+lVJx9+AzDP6mqqqqqqsI/BfNE/RuhwD+ht2WtjgnCP3cFyL3mQsI/cT0K16NwwT9oke18PzXCP8Jn2BUg98I/XxBYObTIwj8qQO41F5LCPwQP5on6N8I/wcqhRbbzwT8WkqZUnH3AP/NvhDJ6W74/U1VVVVVVwT/b+X5qvHTDPw2fYVeA3MM/EBERERERwT/FILByaJHFP68AuddcSNI/jVBGb8ta1T//uNdcSJrOP4ts5/up8cY/T0Zvy1odwz/Ag3mi/o3AP0vwYJ6of8M/XI/C9Shcvz/b+X5qvHS7P+Z8PzVeurk/d76fGi/dvD+UtTomeDC/P26EMnpb1sI/82+EMnpbvj/LoUW28/3APzx8hl0Bcrc/BFYOLbKdtz+Nl24Sg8C6P9NNYhBYObw/s0kMAiuHvj/lifo3QhnBP7VlrY4JHrw/vC1rdUzwwD/1mgtJUyq2P28Sg8DKobU/NNBpA502uD8keDBP1L+5P90z7AqQe70/6SYxCKwcwj9QnH34DLu6P42mVJx9+Lw/BGX0tqzVuT877jUXkqa8P7Ks1THBg7k/f3mi/o1Qtj8dWmQ730+9PyGwcmiR7cA/mqh/I5TRuz+411xImlLBPyUGgZVDi7w/vRHK6G1Zuz/vGXYFyL22P65WxwQP5rk/OcOuALnXvD/qfD81XrrBP7TIdr6fGsM/C3TaQKcNyD+QXyz5xZLDP1yPwvUoXL8/2msuJE2pwD9TZDvfT42/P4lBYOXQIsM/9P3UeOkmyT+dYVeA3Gu+Pz/uNReSpsA/g8DKoUW2uz/2N0IZvS2zP8MED+aJ+rc/99R46SYxuD916SYxCKzAP+iY4ME8Ub8/u/UoXI/CvT+VUnH24TO8P0SaUnH24bs/zwY6baDTvj/kQtKUirO/Py/dJAaBlbs/+fAZdgXIvT/Jdr6fGi/BP5zEILByaME/k9HbslbHwD/vKFyPwvW4P51hV4Dca7Y/RSijt2Wttj/zb4Qyelu2P3sUrkfherw/N5gn6t8IvT/NzMzMzMzAP8mFpCkVZ78/XTvfT42Xtj+R7Xw/NV6yP7M6JngwT7Q/USrOPnyGtT/2N0IZvS27P5BfLPnFkr8/KM4+fIZduT9kO99PjZe+P19XgNxrLrQ/kyfq3whltD/WFSD3mgu5Px1pSsXZh78/dekmMQiswD+j4uzDZ9jBP/T91HjpJsE/WmQ730+Nvz9A0pSKsw+/P6gcWmQ738M/oGFXgNxrxj/ewTxR/0bEP97BPFH/RsQ/wq4AuddczD+V/GLJL5bQP99PjZduEss/JHgwT9S/xT+MCR7ME/XDP2xZq2OCB8M/lLU6Jngwwz88fIZdAXLDP+iY4ME8UcM/0NuyVscEwz+s1THBg3nCPz3DrgC518A/w/UoXI/CvT/VeOkmMQi8P0DSlIqzD78/U5x9+Ay7wj9Y8oslv1jCP93d3d3d3cE/oHA9CtejxD9fZmZmZma+P1g5tMh2vr8/001iEFg5vD9aZDvfT42/P/sboYzelsE/uNdcSJpSwT9uy1odEzzAPxBYObTIdr4/xr3mQtKUuj85tMh2vp+6P9sIZfS2rL0/8uEz7AqQuz8HHswT9W+8PzgXkqZUnL0/GIXrUbgevT/aay4kTam4P+cKkHvNhbw/EGcfPsOuuD/0/dR46Sa5P5zTBjptoLs/QNKUirMPvz9zaJHtfD/BPyUGgZVDi7w/L+wKkHvNvT/7G6GM3pa9P7oC5F5zIcE/N0IZvS1rwT9SuB6F61HAPw2uR+F6FL4/dZMYBFYOvT+NplScffi8P0Uoo7dlrb4//3GvuZA0tT+sHFpkO9+3PwXzRP0bobw/QNKUirMPtz+cxCCwcmi5P2xZq2OCB7s/0THBg3mitj9t9uEz7Aq4P5VScfbhM7Q/EFg5tMh2tj9l5/up8dK1PxMg95oLSbM/H5TR27JWtz++rgC511y4Pxzb+X5qvLQ/S7gehetRuD+/SzeJQWC1PxzME/VvhLI/+n5qvHSTsD+AB/NE/RuxP7Kd76fGS7c/y7ArQO41tz8gMQisHFq0P5TEILByaLk/DZ9hV4Dcsz90Bci95kKyP2ig0wY6bbA/hxbZzvdTsz9vIWlKxdm3P2ig0wY6bbg/FVpkO99PtT+o1THBg3m6PyAiIiIiIrI/AklTKs4+rD/A2YfPsCuwPwRl9Las1bE/RTeJQWDluD+aqH8jlNG7P28haUrF2bc//uNecyFpuj95+Ay7AuS2P9sIZfS2rLU/vHSTGARWtj91ov6NUEa3P4aIiIiIiLg/hoiIiIiIuD8YhetRuB61PyuW/GLJL7Y/5/up8dJNsj8pa3VM8GCuP31OG+i0ga4/qgC511xIsj86Uf9GKKO3P8mFpCkVZ7c/BfNE/RuhtD92PzVeukm0P/QMuwLkXrM/oCkVZx8+sz+YffgMuwK0P+cKkHvNhbQ/WxBYObTItj+kcD0K16O4P9sIZfS2rLU/obdlrY4Jtj+tuZA0peK0P0bF2YfPsLM/GqGM3pa1sj9nA5020GmzPwwCK4cW2bY/daL+jVBGtz92ME/UvxGyP4JBYOXQIrM/7poLSVMqrj8zYOXQItupPzpg5dAi27E/WDm0yHa+rz95+Ay7AuS2P0P9G6GM3rY//Knx0k1isD+Xm8QgsHKoP7YRyuhtWas/bfbhM+wKsD9iHz7DrgC5P2324TPsCrg/bzBP1L8Rqj+qD59hV4CsP4IyelvW6rA/Ks4+fIZd0T9/eaL+jVC2P8u/Ecrobak/AC2yne+npj+TRbbz/dSoP19XgNxrLrQ/GIXrUbgetT/dQtKUirOvPxqhjN6WtbI/ZnVM8GCeqD+HJb9Y8oulP0Jg5dAi26k/prmQNKXirD/vGXYFyL22P3E9CtejcLU/dj81XrpJtD+sK0DuNReyPxKSplScfag/WGZmZmZmpj+Le82FpCmlP/QqhxbZzqc/ctpApw10sj+BlUOLbOezP5H8Yskvlqw/pHA9CtejsD8bPsOuALmnP1hXgNxrLqQ/hzSl4uzDpz9WHRM8mCeqPzEIrBxaZLM/pQ102kCntT9t5/up8dKtP2D0tqzVMbE/FveaC0lTqj+gR+F6FK6nP7K7u7u7u6s/WEiaUnH2sT+v5BdLfrG0P5s20GkDnbY/y7ArQO41tz+pcmiR7Xy3P2D0tqzVMbE/HYcW2c73oz9YZmZmZmamP+cZdgXIvaY/PzVeukkMsj89Gb0ta3W0P6RwPQrXo7A/EFg5tMh2rj/0KocW2c6nP5zi7MNn2KU/QmDl0CLbqT8zUf9GKKOnP1qR7Xw/Na4/aT0K16NwtT86YOXQItuxP/LSTWIQWLE/gaQpFWcfrj/PFSD3mgupPxKSplScfag/DjyYJ+rfqD+W76fGSzexP/C2rNUxwbM/prmQNKXirD8ypeLsw2ewP1LW6pjgwaw//NajcD0Kpz8AHswT9W+kP4/R27JWx6Q/YPS2rNUxsT+amZmZmZmxP+GJ+jdCGa0/RIts5/upsT/ZzvdT46WrP8Ii2/l+aqw/XskvlvxiqT8GkHvNhaSpP+Xu7u7u7q4/umfYFSD3qj+LmZmZmZmpPz0K16NwPao/c4ZdAXKvqT+uVscED+axP9V46SYxCLQ/5/up8dJNuj+xHoXrUbi2P7CBThvotLk/0SLb+X5qvD+R7Xw/NV7GPyjOPnyGXck/uC1rdUzwuD+3nxov3SS2P7vmQtKUirM/WdbqmODBtD83iUFg5dC6PwRWDi2ynbc/OCZ4ME/Utz8uT9S/EcqwP42mVJx9+LQ/2ECnDXTasD/op8ZLN4mxP70gsHJokbU/TnH24TPssj/t/dR46SaxP+6LJb9Y8rM/9ihcj8L1sD+8g3mi/o2wP5ELSVMqzq4/2d3d3d3drT+sK0DuNReyP/yp8dJNYrA/PSijt2Wtrj+5u7u7u7uzP+8oXI/C9bA/cUzwYJ6orz/RMcGDeaKuPyUGgZVDi6w/Yh8+w64AsT/pRP0boYyuP9nO91Pjpas/astaHRM8sD8OS36x5BerP+PSTWIQWKk/18E8Uf9GqD8nT9S/EcqoP5+bxCCwcrA/vr3mQtKUqj+P4ME8Uf+mPz0oo7dlra4/ZmZmZmZmpj83mCfq3wilPzvuNReSpqQ//Me95kLSpD9JjZduEoOwP/7yRP0boaw/zwY6baDTpj/RMcGDeaKuPzsMAiuHFqk/kzbQaQOdpj/LsCtA7jWnP5iM3pa1OqY/ObTIdr6fsj81fIZdAXKvP4/vp8ZLN6k/PSijt2Wtrj8nQO41F5KmPwwg95oLSaM/O+41F5KmpD/dJAaBlUOrPwcezBP1b7Q/XskvlvxisT+0yHa+nxqvP6rx0k1iELA/17JWxwQPpj/Jo3A9CtejP0xkO99Pjac/JQaBlUOLrD9RKs4+fIa1P7M6JngwT7Q/sqzVMcGDsT+R7Xw/NV6yP9V46SYxCKw/H5TR27JWpz8pa3VM8GCuPzb78Bl2BbA/hpduEoPAsj+iVJx9+AyzP5VhV4Dca64/SirOPnyGrT+R7Xw/NV6qP6oAuddcSKo/TGQ730+Npz+kne+nxkunPxBnHz7DrrA/eoZdAXKvsT/hifo3QhmtP9CjcD0K17M/0JSKsw+fsT/2N0IZvS2rPwI6baDTBqo/RtS/EcrorT8rhxbZzvezPzPsCpB7zcE/L5b8Yskvwj/aay4kTanAP7x0kxgEVrY/AklTKs4+rD8/UyrOPnymP395ov6NUKY/XskvlvxisT+muZA0peKsPxKwcmiR7aw/AjptoNMGsj/pRP0boYyuP3syelvW6qg/g8+wK0DupT++rgC511yoP8DZh8+wK7A/UrgehetRsD+6dr6fGi+tPwwREREREbE/fT81XrpJrD8v7AqQe82lP6jz/dR46aY/WnMhaUrFqT/n+6nx0k2yP8l2vp8aL60/3ULSlIqzrz8v3SQGgZWzP9NcSJpScaY/CMrobVmroz83mCfq3wilP3fNhaQpFac/NvvwGXYFsD+at2WtjgmuP7Ks1THBg6k/ToDcay4krT/l3whl9LasP3OGXQFyr6k/TnH24TPsqj/pJjEIrByqP+6aC0lTKq4/FK5H4XoUrj+qD59hV4CsP2iR7Xw/Na4/bz81XrpJrD+uZa2OCR6sP0bF2YfPsKs/TnH24TPsqj/A2YfPsCuwP5zEILByaLE/+o1QRm/Lsj/kUbgeheuxP9TqmODBPLE/BpB7zYWksT850pSKsw+vPy3Bg3mi/q0/mG4Sg8DKsT8gIiIiIiKyPy5P1L8RyrA/BpB7zYWksT+iY4IH80StP8MT9W+EMqo/XLx0kxgEpj8X6LSBThuoP6abxCCwcrA/Rrbz/dR4sT8IrBxaZDvHP9K/Ecrobck/EFg5tMh2rj/FTWIQWDmkP3OGXQFyr6k/LbKd76fGqz9BfrHkF0uuP/sboYzelrU/T/9GKKO3tT8nMQisHFq8P/Wp8dJNYrg/TmIQWDm0sD+4LWt1TPCwP2XYFSD3mrM/+xuhjN6WvT9HYhBYObS4P8daHRM8mLc/UscED+aJuj/n+6nx0k2yPzenDXTaQKc/2xdLfrHkpz9q2kCnDXSqP8uwK0DuNbc/9jdCGb0tsz/+ASuHFtmuP+6LJb9Y8rM/aJHtfD81rj9vIWlKxdmnP+Dsw2fYFbA/UtbqmODBrD/uiyW/WPKzP4GkKRVnH7Y/lVJx9uEztD8JSVMqzj60P0jhehSuR7E/nhxaZDvfrz/hehSuR+GqP8dpA5020Kk/5wqQe82FtD/pJjEIrByyPxh2Bci95rI/6sNn2BUgtz8xCKwcWmSzP+F6FK5H4ao/0JSKsw+fsT9SuB6F61GwP17JL5b8YrE/CuaJ+jdCsT89CtejcD2yP4t7zYWkKbU/7FG4HoXrsT/Tay4kTamoP4PelrU6Jqg/1XjpJjEIrD9Z1uqY4MG0P9CUirMPn7E/EGcfPsOusD9FN4lBYOW4PwlJUyrOPrQ/mH34DLsCpD+TRbbz/dSoP5bvp8ZLN7E/epVDi2znsz/hifo3Qhm1P/fFkl8s+bU/CVg5tMh2tj84JngwT9S3P0l+seQXS7Y/01xImlJxtj/WFSD3mgu5P+RC0pSKs8c/9eEz7AqQwz9k9Las1THBP00b6LSBTsM/q44JHswTvT/iF0t+seS3P1CNl24Sg7g/ZDvfT42Xtj8RBFYOLbK9P7TXXEiaUrk/N4lBYOXQoj83iUFg5dCiP9NcSJpScaY/JVyPwvUoxD8ozj58hl3FP5/TBjptoMM/KWt1TPBgtj/nKFyPwvWoP+xRuB6F66E/2c73U+Olqz/TTWIQWDnWPzVeukkMAqs/oCkVZx8+oz9I8GCeqH+jP7gehetRuK4/5dAi2/l+qj+gR+F6FK6nP4PPsCtA7qU/xU1iEFg5pD93zYWkKRWnPzNR/0Yoo6c/c3d3d3d3pz+c8dJNYhCoP2IuJE2pOKs/x2kDnTbQqT+yu7u7u7urPydA7jUXkqY/DCD3mgtJoz/FPnyGXQGiP6wrQO41F6I/nv6NUEZvqz+yne+nxkunPwAezBP1b6Q/i4qzD59hpz+kjgkezBOlP6jVMcGDeaI/xT58hl0Boj/sUbgeheuhP4lBYOXQIqs/UKtjggfzpD+05kLSlIqjPzNR/0Yoo6c/YBKDwMqhpT+gKRVnHz6jPwjK6G1Zq6M/SPBgnqh/oz9q2kCnDXSqP/QboYzelqU/j9HbslbHpD83tvP91HipP/hxr7mQNKU/UJx9+Ay7oj+05kLSlIqjPxkxCKwcWqQ/d9xrLiRNqT9EuB6F61GoP99ecyFpSqU/pqqqqqqqqj+4SzeJQWClP7YC5F5zIak/DC/dJAaBpT8nQO41F5KmP2wUrkfheqQ/ZnVM8GCeqD89Gb0ta3WsPxKSplScfag/F+i0gU4bqD/TXEiaUnGmP5M20GkDnaY/8NR46SYxqD+aqH8jlNGrPz81XrpJDLI/835qvHSTsD9gnqh/I5TTPzLBg3mi/t8/nu+nxks3yT+5yqFFtvO1PznSlIqzD68/KWt1TPBgrj/Z3d3d3d2tPwJJUyrOPqw//vJE/RuhrD9xTPBgnqivP8F2vp8aL7U/6JjgwTxRtz9KG+i0gU6zP1sBcq+5kLQ/EGcfPsOusD8GkHvNhaSxP7p2vp8aL60/qgC511xIqj+kjgkezBOlP0xGb8taHaM/cWq8dJMYpD+muZA0peKsP2Z1TPBgnqg/LcGDeaL+rT/zfmq8dJOwP6oAuddcSKo/UJx9+Ay7oj9EmlJx9uGjPz9ERERERKQ/ZnVM8GCeqD++veZC0pSqPxb3mgtJU6o/CgRWDi2yrT+kcD0K16OwP+XQItv5fqo/OwwCK4cWqT9WHRM8mCeqPyUVZx8+w64/iLMPn2FXsD8welvW6piwP2iR7Xw/Na4/Yi4kTak4qz9MVVVVVVWlP6jkF0t+saQ/H5TR27JWpz9ooNMGOm2wP+kmMQisHKo/47SBThvopD9zd3d3d3enPxfotIFOG6g/x1odEzyYpz/HWh0TPJinP28haUrF2ac/pqqqqqqqqj/Vh8+wK0CuPwoEVg4tsq0/DAIrhxbZrj8lFWcfPsOuP8uwK0DuNac/I/nFkl8sqT+4SzeJQWClP7695kLSlKo/AC2yne+npj/jtIFOG+ikPxtNqTj78Kk/F9nO91PjpT/sUbgeheuhP6ApFWcfPqM/ULpJDAIrpz/dM+wKkHutP9Ei2/l+aqw/l5vEILByqD+VUnH24TOsP3fcay4kTak/pH8jlNHboj9UEFg5tMimP05x9uEz7Ko/TnH24TPssj+0gU4b6LTTP9S/EcrobdM/aS4kTak4xz9VgNxrLiS9P42XbhKDwLI/1YfPsCtArj+LirMPn2GnPyGwcmiR7aw/i5mZmZmZqT+D3pa1OiaoP+F6FK5H4ao/3TPsCpB7rT/JhaQpFWevPxkEVg4tsq0/kQtJUyrOrj+PwvUoXI+yP5HtfD81XrI/ZnVM8GCesD/mfD81XrqxPxSuR+F6FK4/cT0K16NwrT+aqH8jlNGrPwr1b4Qyeqs/wmfYFSD3sj/PBjptoNO2P8546SYxCLQ/EyD3mgtJsz81XrpJDAKrPy/dJAaBlaM/zfl+arx0oz9vIWlKxdmnP8dpA5020Kk/9kYoo7dlrT9t9uEz7AqwP91C0pSKs68/wcqhRbbzrT9e2BUg95qrP9Ei2/l+aqw/PSijt2Wtrj8pa3VM8GCuP5H8Yskvlqw/OcOuALnXrD9CYOXQItuxP6oAuddcSKo/vKFFtvP9pD+Dz7ArQO6lPz9TKs4+fKY/18E8Uf9GqD/XwTxR/0aoPzb78Bl2BbA/wNmHz7ArsD/JhaQpFWevPzNg5dAi26k/olScffgMqz/rfmq8dJOoP05x9uEz7Ko/olScffgMqz+e/o1QRm+rP4lfLPnFkq8/4Yn6N0IZrT+P76fGSzepPzNR/0Yoo6c/tPUoXI/CpT+2AuRecyGpPx+U0duyVqc/l5vEILByqD/ewTxR/0awP/QqhxbZzqc/j8L1KFyPoj8MIPeaC0mjP6w6JngwT6Q/y7ArQO41pz9xTPBgnqivP8F2vp8aL7U/o+Lsw2fYtT9dLPnFkl+0PwwREREREbE/jbU6Jngwrz9Cb8taHROsP90z7AqQe60/cUzwYJ6orz8AAAAAAACwP5qZmZmZmbE/TnH24TPsqj8bL90kBoGlPzeYJ+rfCKU/J0DuNReSpj9acyFpSsWxPxaSplScfcA/qgC511xIqj91ov6NUEavP9fBPFH/Rqg/GTEIrBxapD97I5TR27KmPzeYJ+rfCKU/RtS/EcrorT8EZfS2rNWxPyMIrBxaZKs/j++nxks3qT8ALbKd76emP7VlrY4JHrQ/L90kBoGVuz877jUXkqa0P/9xr7mQNLU/ObTIdr6fsj+yrNUxwYOxP+Olm8QgsLI/ToDcay4krT+P0duyVsekP+xRuB6F66E/j8L1KFyPoj9mdUzwYJ6oP2Roke18P6U/XrpJDAIrpz+qD59hV4CsP6c4+/AZdrU/jZduEoPAqj+2AuRecyGpP7yhRbbz/aQ/iUFg5dAiqz+WQ4ts5/upP4PelrU6Jqg/jZduEoPAqj8zQhm9LWulP6R/I5TR26I/PzVeukkMoj/sUbgeheuhP8daHRM8mKc/N5gn6t8IpT/4YskvlvyiP7g8Uf9GKKM/g8+wK0DupT9MRm/LWh2jPzMzMzMzM6M/VPKLJb9Yoj8dhxbZzvejPwAP5on6N6I/SP9GKKO3pT83pw102kCnP7M6JngwT7w/HBM8mCfqwz/sUbgeheuhP+xRuB6F66E/Rrbz/dR4qT+Le82FpCmlP5iM3pa1OqY/j+DBPFH/pj+gOPvwGXalP6jVMcGDeaI/7FG4HoXroT9sBci95kKiP0oMAiuHFqk/N6cNdNpApz9/arx0kxikP9NrLiRNqag/qOQXS36xpD9YV4Dcay6kP5zTBjptoKM/yaNwPQrXoz9YZmZmZmamPwAtsp3vp6Y/K6Xi7MNnqD9LuB6F61GwP65lrY4JHqw/oCkVZx8+oz+P0duyVsekP/zHveZC0qQ/qPP91Hjppj87/RuhjN6mP4t7zYWkKaU//uNecyFpqj8OPJgn6t+oP/y411xImqI/+ICVQ4tspz/w1HjpJjGoP1Ys+cWSX6w/olScffgMqz+JQWDl0CKrP06A3GsuJK0/i4qzD59hpz+05kLSlIqjP/QboYzelqU/XLx0kxgEpj/nKFyPwvWoP97BPFH/RrA/+FPjpZvEsD+2AuRecyGxP17YFSD3mqs/wOhtWatjoj+PwvUoXI+iPwwg95oLSaM/k0W28/3UqD+WQ4ts5/upP5iM3pa1OqY/jZduEoPAqj/LsCtA7jWnP3FqvHSTGKQ/N4lBYOXQoj+PwvUoXI+iP7YC5F5zIak/H4XrUbgepT+TJ+rfCGWkP3syelvW6qg//uNecyFpqj/TXEiaUnGmP/y411xImqI/46WbxCCwoj/4gJVDi2ynP+PSTWIQWKk/62+EMnpbpj/w1HjpJjGoP3CEMnpb1uc/ZMkvlvxi/T/7YskvlvzYPwwCK4cW2b4/t5A0peLssz/ewTxR/0awP7gehetRuK4/AklTKs4+rD8nT9S/EcqoP4/gwTxR/6Y/DC/dJAaBpT/A91PjpZukP9sIZfS2rKU/g96WtTomqD8DyL3mQtK0P7Pz/dR46cY/kpmZmZmZuT9kSsXZh8+wPwrmifo3Qqk/kyfq3whlpD8CK4cW2c6nP1CrY4IH86Q/mH34DLsCpD/nCpB7zYWkP/y411xImqI/qNUxwYN5oj8AD+aJ+jeiP+xRuB6F66E/fWzn+6nxoj+wkDSl4uyjPxB2Bci95qI/HYcW2c73oz+SQ4ts5/vJPzhCGb0ta+c/3GsuJE2p5D+4HoXrUbjQPz3DrgC518A/9ZoLSVMqtj9qy1odEzywP8DZh8+wK7A/NW2g0wY6rT/dM+wKkHutP06A3GsuJK0/kfxiyS+WrD9WLPnFkl+sPxfotIFOG7A/efgMuwLkrj/Tay4kTamoPy/78Bl2Bag/hyW/WPKLpT9MVVVVVVWlP/QMuwLkXqM/qPP91Hjppj87/RuhjN6mP1hXgNxrLqQ/XK2OCR7Moz8ZMQisHFqkPwjK6G1Zq6M//LjXXEiaoj8730+Nl26iPzeYJ+rfCKU/62+EMnpbpj9vIWlKxdm/P6zVMcGDecY/ubu7u7u7sz/0G6GM3palP1QBcq+5kKQ/P0REREREpD9kaJHtfD+lPzeYJ+rfCKU/sJ8aL90kpj/4ca+5kDSlPxwTPJgn6sM/kaZUnH34wD+amZmZmZmxP23n+6nx0q0/q44JHswTtT83iUFg5dC6P9hApw102rg/27JWxwQPwj+SmZmZmZm5P99tWatjgqc/qOQXS36xpD8Eg8DKoUWmP1pkO99Pjbc/okW28/3UxD+ONKXi7MPDPzpR/0Yoo7c/ng102kCnrT8GgZVDi2ynP0Jg5dAi26k/OwwCK4cWqT8bPsOuALmnP3+IiIiIiKg/RLgehetRqD/4gJVDi2ynP8/3U+Olm6Q/WEiaUnH2oT8zMzMzMzOjP8VNYhBYOaQ/aL6fGi/dpD/P91PjpZukP5ebxCCwcqg//Knx0k1isD/dJAaBlUOrPxb3mgtJU6o/P2IQWDm0qD+P4ME8Uf+mP+cKkHvNhaQ/WmQ730+Npz8COm2g0waqP5zEILByaLk/CKwcWmQ7vz9crY4JHsyjP5zTBjptoKM/pH8jlNHboj8ZMQisHFqkP6SOCR7ME6U/j9HbslbHpD+TJ+rfCGWkPz9ERERERKQ/oCkVZx8+oz+kfyOU0duiP0jwYJ6of6M/g8+wK0DupT/hehSuR+GqPxS9LWt1TLA/5d8IZfS2rD/PBjptoNOmP99ecyFpSqU/HYcW2c73oz8AHswT9W+kPxCF61G4HqU/sJA0peLsoz+05kLSlIqjP+cZdgXIvaY/i3vNhaQppT/0G6GM3palP+tgnqh/I6Q/BHTaQKcNpD+8oUW28/2kP1y8dJMYBKY/K5b8Yskvpj8ML90kBoGlP8D3U+Olm6Q/9Ay7AuReoz9kWatjggejP6R/I5TR26I/oDj78Bl2pT/XslbHBA+mP1CrY4IH86Q/GTEIrBxapD+kfyOU0duiP+f7qfHSTaI/7FG4HoXroT/sUbgeheuhPxKDwMqhRaY/62CeqH8jpD/8uNdcSJqiP1QQWDm0yKY/5wqQe82FpD8nMQisHFqkP5MYBFYOLaI/7FG4HoXroT8ZMQisHFqkP+O0gU4b6KQ//LjXXEiaoj/FPnyGXQGiP+xRuB6F66E/bAXIveZCoj/FPnyGXQGiP4/C9Shcj6I/9Ay7AuReoz8U2/l+arykP/zWo3A9Cqc/BpB7zYWkqT8rhxbZzvejP+xRuB6F66E/j8L1KFyPoj9YSJpScfahP7yhRbbz/aQ/mH34DLsCpD9U8oslv1iiP2wFyL3mQqI/17JWxwQPpj+c8dJNYhCoP7CfGi/dJKY/j++nxks3qT9/iIiIiIioP/iAlUOLbKc/RJpScfbhoz+HFtnO91OjP1TyiyW/WKI/7FG4HoXroT/sUbgeheuhP8U+fIZdAaI/hyW/WPKLpT+c4uzDZ9ilP0xGb8taHaM/nNMGOm2goz83iUFg5dCiPwrmifo3Qqk/Yh8+w64AqT++rgC511yoP3syelvW6qg//NajcD0Kpz8rhxbZzvejP+O0gU4b6KQ/j8L1KFyPoj8/NV66SQyiP/hiyS+W/KI/ZnVM8GCeqD/pJjEIrByyP7M6JngwT8A/5Yn6N0IZxT+gGi/dJAa5P0jwYJ6of7M/7oslv1jyqz+LirMPn2GnP2ASg8DKoaU/TFVVVVVVpT83mCfq3wilP2ADnTbQaaM/HYcW2c73oz+kfyOU0duiPxTME/VvhKI/7FG4HoXroT9YSJpScfahP/C2rNUxwaM/uDxR/0Yooz+8kl8s+cWiP+cKkHvNhaQ/TEZvy1odoz/sUbgeheuhP+xRuB6F66E/xT58hl0Boj9MRm/LWh2jP5h9+Ay7AqQ/K5b8Yskvpj+yrNUxwYOpP7ySXyz5xaI/FMwT9W+Eoj8zMzMzMzOjP1ytjgkezKM/2/l+arx0oz9xarx0kxikP+PDZ9gVIKc/pJ3vp8ZLpz877jUXkqakP2RZq2OCB6M/oCkVZx8+oz9or7mQNKWiP395ov6NUKY/ZGiR7Xw/pT++veZC0pSqP+rSTWIQWLE/qgC511xIuj9WDi2yne+/PxSuR+F6FMI/j8L1KFyP1D/NE/VvhDLrP7MrQO41F+s/MJb8Yskv1D8bL90kBoHBP3C+nxov3bQ/byFpSsXZpz/81qNwPQqnPzNR/0Yoo6c/nv6NUEZvqz/HaQOdNtCpP2ASg8DKoaU/L/vwGXYFqD+kfyOU0duiPwAP5on6N6I/aK+5kDSloj83iUFg5dCiP+O0gU4b6KQ/c2iR7Xw/pT8zQhm9LWulP99tWatjgqc/aK+5kDSloj9U8oslv1iiP6R/I5TR26I/O99PjZduoj/FTWIQWDmkP99PjZduEqM/yaNwPQrXoz8K5on6N0KpPwwg95oLSaM/P0REREREpD/8uNdcSJqiP+xRuB6F66E/xU1iEFg5pD9UAXKvuZCkP5iM3pa1OqY/XskvlvxiqT9WHRM8mCeqP0ob6LSBTqs/0THBg3mirj/DE/VvhDKqP8D3U+Olm6Q/kyfq3whlpD+TNtBpA52mP1QQWDm0yKY/vJJfLPnFoj+sK0DuNReiPz81XrpJDKI/7FG4HoXroT8dhxbZzvejP0jwYJ6of6M/wPdT46WbpD9iEFg5tMimP/hiyS+W/KI/GSIiIiIioj/8uNdcSJqiP/C2rNUxwaM/UrgehetRqD+P76fGSzepPxKhjN6Wtao/MQisHFpkqz9EqTj78BmmP1hImlJx9qE/7FG4HoXroT/FPnyGXQGiP+Olm8QgsKI/BHTaQKcNpD8/UyrOPnymP2ASg8DKoaU/AC2yne+npj/nKFyPwvWoP2rLWh0TPLA/NW2g0wY6tT9uWatjggfxPye/WPKLpQlA7FG4HoVrA0ARERERERHhPwGdNtBpA8k/AZ020GkDwT9qvHSTGAS+PzVeukkMArs/tWWtjgkewD+SXyz5xZLTP88+fIZdAdY/ZPS2rNUxzT9P/0Yoo7e9PxqhjN6WtbI/YPS2rNUxsT/n+6nx0k2yP8P1KFyPwrU/znjpJjEItD91kxgEVg6tP1Ys+cWSX6w/i3vNhaQppT8zQhm9LWulP2rLWh0TPKg/AklTKs4+rD+sHFpkO9/nP69H4XoUrvc/4E+Nl24S6T8/NV66SQzWP8a95kLSlMY/4OzDZ9gVwD8gIiIiIiK6P0mNl24Sg7g/UI2XbhKDuD+wcmiR7Xy3P4PPsCtA7rU/CuaJ+jdCuT8YhetRuB61P7pY8oslv7A/lWFXgNxrrj/A2YfPsCuwPzb78Bl2BbA/RTeJQWDlsD+eDXTaQKetP+8ZdgXIvcI/27JWxwQPyj+SirMPn2G/PzNCGb0ta7U/CLsC5F5zsT+LbOf7qfGyP3yx5BdLfrE/4OzDZ9gVsD89Gb0ta3WsP3syelvW6qg/8NR46SYxqD8QhetRuB6lP0xkO99Pjac/i5mZmZmZqT+VUnH24TOsP4IyelvW6rA/3Ja1OiZ4sD/w1HjpJjGoP4/R27JWx6Q/RKk4+/AZpj8j6t8IZfSmP5VhV4Dca64/QX6x5BdLrj8ALbKd76emP4lBYOXQIqs/17JWxwQPpj+8oUW28/2kP5Mn6t8IZaQ/f3mi/o1Qpj9Cb8taHROsP90kBoGVQ6s/Gz7DrgC5pz9KKs4+fIatP+cZdgXIvaY/vq4AuddcqD/HaQOdNtCpP8daHRM8mKc/1YfPsCtArj800GkDnTawP2aEMnpb1qo/1hUg95oLsT9/eaL+jVCmP/y411xImqI/pI4JHswTpT9mdUzwYJ6oP4GkKRVnH64/qvHSTWIQsD9q2kCnDXSqP2rLWh0TPLA/oCkVZx8+oz+YffgMuwKkP1TjpZvEILA/z/dT46WbvD9NG+i0gU7DP2YfPsOuAMU/ZdgVIPeauz/58Bl2Bci1P+k1F5KmVKw/6TUXkqZUrD/A2YfPsCuwPzeYJ+rfCKU/h10Bcq+5AEBPG+i0gc72P2VmZmZmZhtA3pa1Oib49D/gwTxR/0bSPzeJQWDl0NI/N4lBYOXQ0j83iUFg5dDSPzeJQWDl0NI/0pSKsw+f0T+Nl24Sg8CqP9NrLiRNqag/QmDl0CLbqT+3kDSl4uyzPzuYJ+rfCMU/Ik2pOPvwyT/GveZC0pTCPzb78Bl2Bbg/uljyiyW/sD+AB/NE/RuxP83MzMzMzKw/jZduEoPAqj9SxwQP5omqP/7yRP0boaw/rnSTGARWrj/WFSD3mguxP4IyelvW6rA/hoiIiIiIsD+at2WtjgmuP+GY4ME8Ua8/HWlKxdmHrz85w64AudesP6JjggfzRK0/MSZ4ME/Urz+iRbbz/dSwP2Q730+Nl64/c3d3d3d3pz87/RuhjN6mPx+jt2Wtjqk/hetRuB6Fqz8pa3VM8GCuP5VScfbhM6w/sqzVMcGDsT8BrBxaZDu3P7x0kxgEVq4/LbKd76fGqz+NplScffisP42XbhKDwKo/Yj0K16NwrT89Gb0ta3WsP+t+arx0k6g/nPHSTWIQqD+c8dJNYhCoP+k1F5KmVKw/kfxiyS+WrD8lBoGVQ4usPzm0yHa+n6o/WoIH80T9qz+F61G4HoWrP42mVJx9+Kw/+ICVQ4tspz8nT9S/EcqoP/QMuwLkXqM/oCkVZx8+oz/0G6GM3palPwSDwMqhRaY/g8+wK0DupT+D3pa1OiaoP9ejcD0K16M/RJpScfbhoz+05kLSlIqjP+xRuB6F66E/9Ay7AuReoz+gKRVnHz6jPxB2Bci95qI/RJpScfbhoz83iUFg5dCiP5zTBjptoKM/WEiaUnH2oT8AD+aJ+jeiPwwg95oLSaM/+GLJL5b8oj+TNtBpA52mP0xVVVVVVaU/aK+5kDSloj8730+Nl26iP4ts5/up8aI/GTEIrBxapD/PFSD3mgupP4/gwTxR/6Y/AjptoNMGqj9KG+i0gU6rP7ySXyz5xaI/TEZvy1odoz9MRm/LWh2jP/QMuwLkXqM/VAFyr7mQpD/rYJ6ofyOkP1ytjgkezKM/tOZC0pSKoz/4YskvlvyiP+k1F5KmVLQ/17JWxwQPvj+TJ+rfCGW8P/7jXnMhabI/4XoUrkfhqj/wxZJfLPmlPz9ERERERKQ/RJpScfbhoz9QnH34DLuiPzeJQWDl0KI/O+41F5KmpD/PFSD3mgupP2rLWh0TPKg/XskvlvxiqT+6WPKLJb+oP6jVMcGDeaI/HYcW2c73oz/8x73mQtKkP8D3U+Olm6Q/i3vNhaQppT9I/0Yoo7elP2ADnTbQaaM/tOZC0pSKoz83iUFg5dCiP9v5fmq8dKM/0U+Nl24Soz9I8GCeqH+jP/C2rNUxwaM/M0IZvS1rpT9MVVVVVVWlP0SaUnH24aM/5wqQe82FpD8X6LSBThuoP7CQNKXi7KM/GSIiIiIioj9MVVVVVVWlP3fcay4kTak/TnH24TPsqj++rgC511yoP9eyVscED6Y/N5gn6t8IpT/4ca+5kDSlPydA7jUXkqY/vq4AuddcqD/dJAaBlUOrPyul4uzDZ6g/ezJ6W9bqqD8730+Nl26iP/QMuwLkXqM/tOZC0pSKoz9kWatjggejPxKDwMqhRaY/VBBYObTIpj9EmlJx9uGjPz9TKs4+fKY/KvnFkl8ssT81XrpJDAKzP6wcWmQ7368/3TPsCpB7rT83pw102kCnP7pY8oslv6g/PSijt2Wtrj91ov6NUEavP9DbslbHBMs/RJpScfbhoz/nCpB7zYWkP2ADnTbQaaM/MzMzMzMzoz9gA5020GmjP7TmQtKUiqM/SPBgnqh/oz+kfyOU0duiP6R/I5TR26I/YAOdNtBpoz/jpZvEILCiP8mjcD0K16M/rDomeDBPpD/HWh0TPJinP/iAlUOLbKc/AA/mifo3oj+sK0DuNReiP5MYBFYOLaI/7FG4HoXroT/4YskvlvyiP395ov6NUKY/XK2OCR7Moz8Eg8DKoUWmPxkiIiIiIqI/kxgEVg4toj8QdgXIveaiPz81XrpJDKI/rDomeDBPpD+gOPvwGXalPwAP5on6N6I/UJx9+Ay7oj/0DLsC5F6jP5MYBFYOLaI/7FG4HoXroT8/NV66SQyiP8DobVmrY6I//LjXXEiaoj8AD+aJ+jeiP8DobVmrY6I/uDxR/0Yooz9U8oslv1iiP+xRuB6F66E/GSIiIiIioj/A6G1Zq2OiP8DobVmrY6I/PzVeukkMoj8/NV66SQyiP+O0gU4b6KQ/zmkDnTbQsT+e/o1QRm+zPx73mgtJU7I/wNmHz7ArsD8CSVMqzj6sP1CrY4IH86Q/bzBP1L8Rqj/pJjEIrBzOPyuHFtnO96M/VPKLJb9Yoj83iUFg5dCiP8P1KFyPwqU/wwQP5on6pz+F61G4HoWrP+Xu7u7u7q4/9BuhjN6WpT+P76fGSzepP/zWo3A9Cqc/UscED+aJqj+uZa2OCR6sP23n+6nx0q0/SirOPnyGrT/y8Bl2BcitP+k1F5KmVKw/4XoUrkfhqj/FILByaJGtP6oPn2FXgKw/lVJx9uEzrD9t5/up8dKtP+lE/RuhjK4/MSZ4ME/Urz89KKO3Za2uP83bslbHBK8/3Ja1OiZ4sD8MAiuHFtmuP/L//////68/XI/C9Shcrz+TGARWDi2yP6dH4XoUrrc/F+i0gU4bsD+mqqqqqqqyP/LwGXYFyK0/wwQP5on6pz+qALnXXEiqPx+jt2Wtjqk//uNecyFpqj/HaQOdNtCpP0S4HoXrUag/M0IZvS1rpT/w1HjpJjGoP1pkO99Pjac/IwisHFpkqz8+tvP91HixP7gta3VM8LA/wcqhRbbzrT9WLPnFkl+sPyGwcmiR7aw/cT0K16NwrT8EVg4tsp2vP8oT9W+EMrI/K5b8Yskvtj9KDAIrhxbBPy+W/GLJL8Y/KM4+fIZdxT/aay4kTanAP3YwT9S/Ebo/82+EMnpbtj83mCfq3wi1P5Mn6t8IZbQ/hetRuB6Fsz+amZmZmZmxP9K/EcrobbE/jkOLbOf7sT/4U+Olm8SwPzKl4uzDZ7A/Ib9Y8oslrz94W9bqmOCxPwi7AuRec7E/nMQgsHJosT++rgC511ywP2ig0wY6bbA/EpKmVJx9sD8xJngwT9SvP4lfLPnFkq8/uljyiyW/sD9JjZduEoOwP2rLWh0TPLA/c4ZdAXKvqT9iPQrXo3CtP9ExwYN5oq4/WnMhaUrFqT8j+cWSXyypP6JUnH34DKs/N7bz/dR4qT/fbVmrY4KnP9NcSJpScaY/d9xrLiRNqT9gA5020GmjPxkiIiIiIqI/YAOdNtBpoz/81qNwPQqnP6xJDAIrh6Y/EpKmVJx9qD+HFtnO91OjPy2yne+nxqs/HveaC0lTsj8iTak4+/CxP2iR7Xw/Na4/gjJ6W9bqsD/n+6nx0k2iP/QMuwLkXqM/AiuHFtnOpz8Gn2FXgNyrP42mVJx9+Kw/lkOLbOf7qT/4gJVDi2ynP4PPsCtA7qU/G02pOPvwqT8nT9S/EcqoP8UgsHJokb0/PqcNdNpAtz/D9Shcj8KlPydP1L8Ryqg//uNecyFpqj8dWmQ730+tP0F+seQXS64/JQaBlUOLrD/j0k1iEFipP2raQKcNdKo/AklTKs4+rD9q2kCnDXSqP7pY8oslv6g/RsXZh8+wsz9oSsXZh8/AP7ByaJHtfMM/yYWkKRVntz8welvW6piwP42XbhKDwKo/5xl2Bci9pj/DBA/mifqnP57+jVBGb6s/uC1rdUzwsD96lUOLbOezPzB6W9bqmLA/Vh0TPJgnsj81XrpJDAKrPzenDXTaQKc/RLgehetRqD+qALnXXEiqP/DUeOkmMag/x2kDnTbQqT8QdgXIveaiP+tgnqh/I6Q/9BuhjN6WpT87/RuhjN6mP6Sd76fGS6c/+ICVQ4tspz/wxZJfLPmlP6jz/dR46aY/MzMzMzMzoz/jpZvEILCiP1QBcq+5kKQ/DC/dJAaBpT/fbVmrY4KnP9sXS36x5Kc/YBKDwMqhpT/HWh0TPJinP2wUrkfheqQ/ZoQyelvWqj/PFSD3mgupP5ebxCCwcqg/F+i0gU4bqD9q2kCnDXSqP4XrUbgehas/it6WtTomsD/0b4QyelvQP28wT9S/Eao/9CqHFtnOpz8flNHbslanP8dpA5020Kk/Dkt+seQXqz+R7Xw/NV6qP6JUnH34DKs/02suJE2pqD/VeOkmMQisP8HKoUW2860/PQrXo3A9qj9wr7mQNKWyP/tiyS+W/MY/bVmrY4IH1T8Q5on6N0LTP2OtjgkezMc/98WSXyz5vT/Bdr6fGi+1PySHFtnO97M/yhP1b4Qysj8sJE2pOPuwP97BPFH/RrA/AAAAAAAAsD9OgNxrLiStPzEXkqZUnK0/PSijt2Wtrj9G1L8RyuitPyUGgZVDi6w/2msuJE2psD+oxks3iUGwP4dDi2zn+6k/zxUg95oLqT81baDTBjqtPxkEVg4tsq0/lkOLbOf7qT9iHz7DrgCpP9ExwYN5oq4/rlbHBA/mqT+amZmZmZmpPydA7jUXkqY/lkOLbOf7qT/LvxHK6G2pPw5LfrHkF6s/JQaBlUOLrD91ov6NUEavP4relrU6JrA/CvVvhDJ6qz9OcfbhM+yqPz0K16NwPao/Yi4kTak4qz+R/GLJL5asPxSuR+F6FK4/2msuJE2psD/umgtJUyquPylrdUzwYK4/nhxaZDvfrz800GkDnTawP7TIdr6fGq8/YOXQItv5rj9aggfzRP2rP/ZGKKO3Za0/9jdCGb0tqz+qALnXXEiqP2ASg8DKoaU/0THBg3mirj+at2WtjgmuP4UJHswT9a8/Lk/UvxHKsD+6WPKLJb+wP+Xu7u7u7q4/lVJx9uEzrD9Oj8L1KFyvP7TIdr6fGq8/3ULSlIqzrz/n+6nx0k2yP7yDeaL+jbA/CuaJ+jdCsT+TGARWDi2yPy5P1L8RyrA/qNUxwYN5sj/SvxHK6G2xP79LN4lBYLU/oCkVZx8+sz9jrY4JHsyzP03UvxHK6LU/kyfq3whltD/rYJ6ofyO0PyAxCKwcWrQ/cL6fGi/dtD97I5TR27K2P1NVVVVVVbU/4Yn6N0IZtT8pa3VM8GC2P2k9CtejcLU/RJpScfbhsz8X6LSBThuwP8a95kLSlLI/GrByaJHttD9TVVVVVVW1P9eyVscED7Y/R2IQWDm0uD8hv1jyiyW3P1erY4IH87Q/MReSplSctT9jrY4JHsyzPxfZzvdT47U/i3vNhaQptT+0yHa+nxq3P8Uvlvxiybc/YOXQItv5tj8lFWcfPsO2P8uwK0DuNbc/XI/C9Shctz/vGXYFyL22P4X6N0IZvbU/i3vNhaQptT9RKs4+fIa1P8uwK0DuNbc/j8L1KFyPuj/MPnyGXQG6P8mFpCkVZ7c/H5TR27JWtz/wtqzVMcGzPznDrgC517Q/jAkezBP1tz9PDi2yne+3P2IfPsOuALk/n5vEILByuD9cj8L1KFy3Pz81XrpJDLo/pqqqqqqquj9pLiRNqTi7P0dTKs4+fL4/lLU6Jngwvz/QlIqzD5+5Pz9ERERERLQ/FVpkO99PtT/6jVBGb8uyP1hImlJx9rE/30+Nl24Ssz/jpZvEILC6Pz628/3UeLk/cukmMQistD8COm2g0wayP99ecyFpSrU/Q/0boYzetj8rlvxiyS+2P1sQWDm0yLY/y7ArQO41tz92ME/UvxG6PwRWDi2ynbc/xKFFtvP9tD9dO99PjZe2P/FE/RuhjLY/DjyYJ+rfuD+5yqFFtvO1P3qGXQFyr7k/vq4AuddcuD+R/GLJL5a0P2Z1TPBgnrA/PQrXo3A9sj8xCKwcWmSzP8a95kLSlLI/9P3UeOkmsT8j6t8IZfS2PydA7jUXkrY/98WSXyz5tT97I5TR27K2P0P9G6GM3rY/I+rfCGX0tj/Z3d3d3d21PwGdNtBpA7U/9ZoLSVMqtj+bNtBpA522P3WTGARWDrU/4OzDZ9gVsD8GkHvNhaSxP4izD59hV7A/WEiaUnH2sT8Lg8DKoUW2Pw/K6G1Zq7M/bxKDwMqhtT8nQO41F5K2P37cay4kTbE/FVpkO99PtT+6WPKLJb+wP0bUvxHK6K0/N4lBYOXQsj/dM+wKkHu1P6Pi7MNn2LU/bFmrY4IHsz9acyFpSsWxPylrdUzwYL4/iLMPn2FXuD+9EcrobVmzP1CcffgMu7I/d82FpCkVtz/7KocW2c63P3fNhaQpFbc/R2IQWDm0uD877jUXkqa8PxMg95oLSbs/aJHtfD81tj9uhDJ6W9ayP9eyVscED7Y/s0kMAiuHtj+Dz7ArQO61P3LaQKcNdLI/aS4kTak4sz/rYJ6ofyO0Pxh2Bci95rI/3Ja1OiZ4sD8flNHbsla3P/WaC0lTKrY/ucqhRbbztT+6Z9gVIPeqP2aTGARWDq0/oBov3SQGsT9+3GsuJE2xP5bvp8ZLN7E/WDm0yHa+tz/t/dR46Sa5PyJNqTj78LE/IbByaJHtrD+FCR7ME/WvP/yp8dJNYrA/JHgwT9S/sT94W9bqmOCxP1nW6pjgwbQ/6SYxCKwcuj+BpCkVZx+2P9LO91PjpbM//uNecyFpsj9l5/up8dK1P/qNUEZvy7I/SgwCK4cWsT+qALnXXEi6PxKSplScfbg/+GLJL5b8sj+FCR7ME/WvP625kDSl4rQ/1YfPsCtAtj800GkDnTa4P2Dl0CLb+bY/Lk/UvxHKuD9HYhBYObS4P/nwGXYFyLU/znjpJjEItD9jvHSTGAS2Pw/K6G1Zq7M/LDMzMzMzsz8asHJoke20P08OLbKd77c/uljyiyW/uD82+/AZdgW4P6Px0k1iELg/efgMuwLktj82+/AZdgW4PzTQaQOdNrg/wNmHz7AruD93zYWkKRW3PwI6baDTBro/o/HSTWIQuD9uhDJ6W9ayPwPIveZC0rQ/wmfYFSD3sj9y2kCnDXSyP7NJDAIrh7Y/2c73U+Oluz+PwvUoXI+6PxkTPJgn6rc/j8L1KFyPuj8gIiIiIiK6P70RyuhtWbs/yOhtWatjuj+3kDSl4uy7P8/3U+Olm7w/17JWxwQPvj84JngwT9S3PzV8hl0Bcq8/O99PjZdusj+o1THBg3myP2kuJE2pOLM/3SQGgZVDsz8czBP1b4S6P1TyiyW/WLo/u/UoXI/CtT8EZfS2rNW5P8a95kLSlLo/xr3mQtKUuj9GxdmHz7C7P7VlrY4JHrw/hetRuB6Fuz8X6LSBThu4P0jwYJ6of7s/A8i95kLSwD956SYxCKzAP8Uvlvxiybc/ZnVM8GCesD/6jVBGb8uyPyuHFtnO97s/hxbZzvdTuz+F+jdCGb21P10730+Nl7Y/TEZvy1oduz/kUbgeheu5P31OG+i0gb4/qWOCB/NEwT8gIiIiIiLCP0EZvS1rdcQ/CKwcWmQ7wz92ME/UvxHCP8V2vp8aL8k/L90kBoGVyz/bslbHBA/KP+01F5KmVMw/iUFg5dAixz8h95oLSVPCP6/z/dR46bY/Bx7ME/VvtD8c2/l+ary0P4t7zYWkKbU/kfxiyS+WtD97I5TR27K2P6GM3pa1OtA/V8cED+aJ3D8/NV66SQzYP93d3d3d3ck/CGX0tqzVwT8HHswT9W+8P0diEFg5tLg/mzbQaQOdtj+bNtBpA522P6UNdNpAp7U/WwFyr7mQtD+o1THBg3myP5qofyOU0bM/gaQpFWcftj9pPQrXo3C1P+k1F5KmVLQ/iVBGb8tatT8gMQisHFq0PzvfT42XbrI/99R46SYxsD8daUrF2YevP4izD59hV7A/6TUXkqZUrD8xF5KmVJytP3yx5BdLfrE/YPS2rNUxsT/y8Bl2BcitP+F6FK5H4ao/ng102kCnrT/vKFyPwvWwPyAiIiIiIrI/EfVvhDJ6sz9pLiRNqTi7P76fGi/dJL4/6sNn2BUgtz/0DLsC5F6zPwAP5on6N7I//vJE/RuhrD+yrNUxwYOpP1YdEzyYJ6o/1hUg95oLsT+qALnXXEiyP3YwT9S/EbI/aS4kTak4sz+1Za2OCR60P9hApw102rg/2c73U+Ol0T+SXyz5xZLVPzgmeDBP1Ms/aef7qfHSwT9U8oslv1i6P70gsHJokbU//uNecyFpsj+fm8QgsHKwP4relrU6JrA/QX6x5BdLrj8keDBP1L+xPy5eukkMArM/KWt1TPBgrj/XwTxR/0aoP+kmMQisHKo/+qscWmQ7rz9FN4lBYOWwP+8oXI/C9bA/FUt+seQXsz90Bci95kKyPz0oo7dlra4/5/up8dJNsj/2N0IZvS2zP28haUrF2bc/vq4AuddcuD9WDi2yne+3PxfotIFOG7g/WEiaUnH2uT97I5TR27K2PzNCGb0ta7U/a2iR7Xw/tT/3xZJfLPm1P1dkO99Pjcs//RuhjN6W4T/bQKcNdNrmPycxCKwc2vQ/tIFOG+i07j/GSzeJQWDgPyzOPnyGXe4/JngwT9S/8D/5DLsC5F7jP0fhehSux/o/hetRuB4FB0CamZmZmZn9P4FOG+i0gQRA3d3d3d1dDkCbmZmZmZkHQH2x5BdLfvo/s1bHBA9m8D9bZDvfT43oPxeSplScfeU/XbpJDAIr4z8DuddcSJreP4+mVJx9+Nw/z/dT46Wb2j8zMzMzMzPZP1VVVVVVlQJAw/UoXI/CGkC1gU4b6PQTQJX8YskvlgdAK1yPwvUo/z9mZmZmZuYRQLHkF0t+cRpAWfKLJb9YIEBgLPnFkr8gQKcNdNpAZxZAPQrXo3A9CEDziyW/WPL2P6RwPQrXo/U/gk4b6LSB8z+eNtBpA530P3h3d3d3d/0/16NwPQrXAkAvlvxiyS8IQJX8YskvVhFA5BdLfrFkC0CkcD0K16P9P6HTBjptoPQ/BzptoNMG9T/9Yskvlvz0Pylcj8L1KPM/lvxiyS+W8z9SuB6F61H0P0SLbOf7qew/aNgVIPea7D9kyS+W/GL1P5uZmZmZmf4/odMGOm2gAEAXS36x5Bf7P93d3d3d3fc/dnd3d3d3/z8EnTbQaYMAQJw20GkDnfc/hOtRuB6F8j93Bci95kLtP2lKxdmHz+k/zYWkKRVn5z+d76fGSzfoPzEIrBxa5PQ/pHA9Ctej+D87baDTBjrzP68AuddcSOw/tIFOG+i06D/x0k1iEFjoP9W/Ecrobec/sLmQNKXi5z+oDXTaQKfmP/fhM+wKkOQ/CawcWmQ74j956SYxCKzgPzltoNMGOuA/7Hw/NV663z/DZ9gVIPfeP2CeqH8jlN0/2FxImlJx3D8qQO41F5LaP6MpFWcfPtk/Watjggfz2j98+Ay7AuTePxIRERERkfE/SeF6FK5H9j8DnTbQaQPsPwUP5on6N+U/uddcSJpS4T+EXQFyr7nePyz5xZJfLN8/QRm9LWt13j9oke18PzXcPxsv3SQGgds/HaGM3pa12j8DnTbQaQPbP5HtfD81Xto/+cWSXyz52T/+///////XPx+F61G4Htc/w2fYFSD31D9zr7mQNKXUP4ZdAXKvudQ/7TUXkqZU1D/34TPsCpDTP/0boYzeltE/7MNn2BUg0z+QCR7ME/XRP/hT46WbxNA/irMPn2FX0D/tRP0boYzOPzeJQWDl0M4/sCtA7jUXzj+2rNUxwYPNP8paHRM8mMs/7TUXkqZUzD8a6LSBThvMP/O2rNUxwcs/ScXZh8+wyz+DwMqhRbbLP4XrUbgehcs/pVScffgMzz/aQKcNdNrQP4ts5/up8co/GVpkO99PyT/tNReSplTIPzgmeDBP1Mc/FpKmVJx9yD+BlUOLbOfPP2ZmZmZmZto/I9v5fmq82D/fT42XbhLTPwisHFpkO9E/H8wT9W+E0D/bslbHBA/OP3qGXQFyr80/hxbZzvdTyz9YObTIdr7HP2etjgkezMc/VccED+aJyj9jV4Dcay7SP1fHBA/mido/L90kBoGV2z89w64AudfaP+e0gU4b6Ng/Mnpb1uqY1j/IL5b8YsnVPzJ6W9bqmNQ/dkzwYJ6o0z9iyS+W/GLTP57vp8ZLN9U/XrpJDAIr1T/hehSuR+HSP+NecyFpStM/nDbQaQOd1D/AWPKLJb/WP4QH80T9G/E/Xyz5xZJf7D8ZBFYOLbLzP1yPwvUoXPo/LbKd76fG8T8LkHvNhaTnP4XrUbgeheQ/i7MPn2FX4T+Y4ME8Uf/eP3L24TPsCt4/bstaHRM83j9fLPnFkl/ePz58hl0Bct0/+Qy7AuRe6T8yMzMzMzMDQK9H4XoUrvw/YleA3Gsu8D9b1uqY4MHoP0TSlIqzD+Y/vp8aL90k4j8VZx8+w67gP5+M3pa1Ot4/UI2XbhKD3D9CGb0ta3XiP0GnDXTaQAdAUrgehesREEC7u7u7u7v9P/tiyS+W/PY/9Shcj8L19j+LJb9Y8ov0PzltoNMGOvU/A5020GkD9T9Ei2zn+6ntP2X0tqzVMeg/uR6F61G45D+XbhKDwMriP5HtfD81XuE/zIWkKRVn2z9cj8L1KFzZPzcXkqZUnNs/G6GM3pa12j/DZ9gVIPfaPzCW/GLJL94/NewKkHvN4z+bUnH24TPjP7is1THBg98/I9v5fmq82j+DeaL+jVDYP4zelrU6Jtg/6JjgwTxR1z/J6G1Zq2PWP7uQNKXi7NU/SOF6FK5H1T/sw2fYFSDTPwisHFpkO9E/hDJ6W9bq0D+NUEZvy1rRP497zYWkKdE/gU4b6LSB0D8XIPeaC0nRP2FXgNxrLtA/Tak4+/AZ0D+xK0DuNRfQP73KoUW2880/bstaHRM8zD/PPnyGXQHKP7dJDAIrh8Y/VccED+aJyj800GkDnTbMP9uyVscED8o/sCtA7jUXyj9p5/up8dLJP8uhRbbz/cg/s+QXS36xyD/hehSuR+HGP2yg0wY6bcg/AZ020GkDyT9NG+i0gU7HPwhl9Las1cU/YJ6ofyOUxT/SBjptoNPGP2LJL5b8YsU/DLsC5F5zxT97FK5H4XrIP6/kF0t+scg/zrArQO41xz/clrU6JnjEP7bz/dR46b4/6TUXkqZUvD+0yHa+nxq/PydA7jUXkr4/J3gwT9S/wT9MfrHkF0vCP1g5tMh2vr8/F+i0gU4buD8j6t8IZfS+P2iR7Xw/Nb4/GHYFyL3muj800GkDnTa4Pxsv3SQGgb0/O5gn6t8IwT8xF5KmVJy9PxqhjN6Wtbo/f3mi/o1Qtj9/eaL+jVC2PwisHFpkO7c/V7pJDAIrtz+TJ+rfCGW8P/NvhDJ6W74/bFmrY4IHuz/aay4kTam4P0SLbOf7qbk/QwwCK4cWuT9/eaL+jVC2P4PPsCtA7rU/DjyYJ+rfuD8VS36x5Be7Pxs+w64Aubc/FUt+seQXsz94arx0kxi0P9CjcD0K17M/3SQGgZVDsz/OeOkmMQi0P7Ks1THBg7k/VOOlm8QguD8pXI/C9Si0P90kBoGVQ7M/tXSTGARWtj+9ILByaJG1PxSuR+F6FLY/efgMuwLktj+TGARWDi26PyAiIiIiIro/FUt+seQXuz+JUEZvy1q9P5lScfbhM8A/vHSTGARWwj9oSsXZh8/EP41QRm/LWsU/U5x9+Ay7zj8oo7dlrY7pP0VERERERPU/DZB7zYWk7z9b1uqY4MHiP2IQWDm0yNw/DAIrhxbZ2j90TPBgnqjZP+Olm8QgsNg/bVmrY4IH2z+85kLSlIroP1WcffgMu+4/WDm0yHa+6D9toNMGOm3qPw8tsp3vp+o/BVYOLbKd6z9rA5020GnpP1ScffgMu+Y/L90kBoGV4z9Bpw102kDiP9dcSJpSceI/K4cW2c734D9mHz7DrgDbP4/C9Shcj9o/s1bHBA/m2z8rhxbZzvfbPzxR/0Yoo9k/oYzelrU62D8wT9S/EcrUP4XrUbgehdE/Yskvlvxi0T+A3GsuJE3RP3DLWh0TPNI/3SQGgZVD0T9DGb0ta3XQP8a95kLSlM4/1XjpJjEIzD8QERERERHJP1CNl24Sg8g//3GvuZA0yT/MhaQpFWfLP6MpFWcfPss/qWOCB/NEyT8pXI/C9SjQP68AuddcSNI/7Hw/NV660T+EeaL+jVDQP5RfLPnFks8/GXYFyL3m0D+PUEZvy1rRP1mrY4IH89A/9P3UeOkm0T9ZgNxrLiTRP1VVVVVVVdE/SOF6FK5H0T8NdNpApw3SP75Y8oslv9Y/jgkezBP12T9N8GCeqH/fP90kBoGVQ+k/MU/UvxHK5j/6N0IZvS3gP9hcSJpScdo/FdnO91Pj1T9NqTj78BnYP+81F5KmVNg/0SLb+X5q1j/b+X5qvHTTP/JE/RuhjNQ/+zdCGb0t1T94ov6NUEbTP7mQNKXi7NE/a+f7qfHS0z9vEoPAyqHiP3VM8GCeqOI/3pa1OiZ42D96zYWkKRXVPxwTPJgn6tM/8WCeqH8j1D/HSzeJQWDTP5jgwTxR/9I/N4lBYOXQ0j9zaJHtfD/RPwG511xImtA/Sn6x5BdL0D9eukkMAivPPz0K16NwPc4/4TPsCpB7zT+XJ+rfCGXMP05iEFg5tMw/ke18PzVeyj+lDXTaQKfJP3XpJjEIrMg/exSuR+F6yD/5N0IZvS3HPylcj8L1KMg/opvEILByyD92d3d3d3fHP4IyelvW6sQ/Gui0gU4bxD8WkqZUnH3EP+iY4ME8UcM/obdlrY4Jwj+EXQFyr7nAP41QRm/LWsE/d76fGi/dwD8QERERERHBP/FE/RuhjL4/byFpSsXZvz+F+jdCGb29PxH1b4Qyers/tvP91Hjpwj+2rNUxwYPNP7Kd76fGS78/cK+5kDSluj91ov6NUEa3P8uwK0DuNbc/NvvwGXYFuD9Xq2OCB/O8P0DSlIqzD78/c3d3d3d3vz8rlvxiyS+2P0dTKs4+fLY/0THBg3mitj/TTWIQWDm0P7vmQtKUirM/5dAi2/l+qj9cnqh/I5SxPzeJQWDl0Lo/3SQGgZVDuz9zaJHtfD+1P7695kLSlKo/U1VVVVVVtT/JhaQpFWe3P9yWtTomeLg/XI/C9Shctz8nQO41F5K2P+6LJb9Y8rM/4XoUrkfhsj8WBoGVQ4usP2k9CtejcLU/0KNwPQrXsz/jpZvEILCyP3QFyL3mQrI/CLsC5F5zsT89KKO3Za2uP+xRuB6F67E/OdKUirMPrz/ffD81XrqpP1pzIWlKxak/qNUxwYN5sj/y4TPsCpC7P93d3d3d3cU/mzbQaQOdtj+kfyOU0duyP/T91HjpJrE/Ll66SQwCsz+R7Xw/NV6yP5HtfD81XrI/bFmrY4IHsz8zMzMzMzOzP9prLiRNqbA/JqO3Za2OsT/NzMzMzMysP0bUvxHK6K0/ObTIdr6fqj8nQO41F5KmP/QboYzelqU/HMwT9W+Esj8zMzMzMzOzP/Cnxks3ibE/KM4+fIZdsT8twYN5ov6tPz9TKs4+fKY/mIzelrU6pj8Eg8DKoUWmP0xGb8taHbM/tMh2vp8arz+VYVeA3GuuP6a5kDSl4qw/Bp9hV4Dcqz/6jVBGb8uqPzv9G6GM3qY/c3d3d3d3pz9cj8L1KFyvPz0oo7dlra4/4Yn6N0IZrT8OPJgn6t+oP/zWo3A9Cqc/XLx0kxgEpj8ALbKd76emPzenDXTaQKc/KM4+fIZdsT8EZfS2rNWxP2ig0wY6bbA/cUzwYJ6orz/g7MNn2BWwP4relrU6JrA/NNBpA502sD+CMnpb1uqwP9nO91PjpbM/koqzD59htz+W76fGSze5P/FT46WbxLg/V6tjggfzvD+TGARWDi3QP5SKsw+fYd8/o+Lsw2fY1T9qvHSTGATQPwaBlUOLbMc/h8+wK0DuxT8TyuhtWavHPzdCGb0ta8k/d76fGi/dyD+h/o1QRm/HP9yWtTomeMg/1OqY4ME8yT+GiIiIiIjIP34jlNHbssY/V2Q730+Nyz/5N0IZvS3VP2LJL5b8Ytk/ID7DrgC52z+LbOf7qfHiPyGwcmiR7eM/5DPsCpB73T+BThvotIHWP2Dl0CLb+dA/KaO3Za2O0T8nMQisHFrQPxSuR+F6FM4/L90kBoGVyz83iUFg5dDOP+XQItv5ftQ/j8L1KFyP1D8OLbKd76fSP4AjlNHbstI/Sn6x5BdL0j/8qfHSTWLSP18s+cWSX9I/bstaHRM80j+hjN6WtTrSP9V46SYxCNI/EFg5tMh20j8QERERERHXP/hT46WbxO0/rBxaZDvf6T94d3d3d3fgPxwTPJgn6ts/IGlKxdmH1z+95kLSlIrVP8E8Uf9GKNE/1DHBg3mizj/7YskvlvzKP/9xr7mQNMk/opvEILByyD9fSJpScfbJP5KKsw+fYcc/iLMPn2FXyD+XJ+rfCGXIP9QxwYN5oso/iUFg5dAiyz9cSJpScfbJP/GLJb9Y8sc/k9HbslbHyD9QjZduEoPIPyMiIiIiIsY/AZ020GkDxT8PyuhtWavHP42XbhKDwMY/PHyGXQFywz+fjN6WtTrCP6d/I5TR28Y/+xuhjN6WxT97FK5H4XrEP+7STWIQWMU/slbHBA/mxT9CtvP91HjFP4FOG+i0gcY/YOXQItv5xj8rhxbZzvfHPw2fYVeA3Mc/ROF6FK5HxT9jrY4JHszDP7M6JngwT8Q/6d8IZfS2xD+uR+F6FK7DP00b6LSBTsM/UI2XbhKDxD+WmZmZmZnFP+yY4ME8UcM/nu+nxks3wT9ecyFpSsXBP57vp8ZLN8E/6JjgwTxRvz99PzVeukm8P/Z+arx0k8A/hfo3Qhm9vT+dYVeA3Gu+P39qvHSTGLw/boQyelvWuj+bNtBpA522P395ov6NULY/q53vp8ZLtz/E2YfPsCvAP2p1TPBgnsA/01xImlJxvj8HLbKd76e2P4ts5/up8bI/ZDvfT42Xtj+LbOf7qfG6Pwrmifo3Qrk/ukkMAiuHvj+zOiZ4ME+8Pw4tsp3vp74/TdS/EcrovT/qw2fYFSC/P3n4DLsC5L4/n4zelrU6vj+j4uzDZ9i9PwuDwMqhRb4/daL+jVBGvz8pXI/C9Si8P37cay4kTbk/nMQgsHJouT9PDi2yne+3P4IyelvW6rg/Lk/UvxHKuD9KG+i0gU67P8l2vp8aL70/MzMzMzMzuz/1qfHSTWK4PwIrhxbZzrc/daL+jVBGtz//gJVDi2y3P/fUeOkmMbg/4OzDZ9gVuD800GkDnTa4PwRWDi2ynbc/koqzD59htz/aay4kTam4P4izD59hV7g/+f//////tz+GiIiIiIi4P1yeqH8jlLk/O99PjZduuj9DDAIrhxa5Pyr5xZJfLLk/zD58hl0Buj/WFSD3mgu5P2rLWh0TPLg/JHgwT9S/uT+3kDSl4uy7P5MYBFYOLbo/835qvHSTuD8MERERERG5P5kLSVMqzrY/PRm9LWt1tD/7KocW2c63P6HGSzeJQbg/fLHkF0t+uT+W76fGSze5P+xRuB6F67k/47SBThvovD8UZx8+w67QP8KuALnXXNY//7jXXEia1D9I4XoUrkfjP7pJDAIrB/Q/gU4b6LSB/D+QwvUoXI8KQIiIiIiICAhAQacNdNpAAEA30GkDnTb2P93d3d3d3fU/yi+W/GLJ9D+vR+F6FK7yP0jhehSuR+o/wBHK6G1Z5z+N3pa1OiblP79Y8oslv+I/ZfS2rNUx4T8UrkfhehThP2jYFSD3muA/mpmZmZmZ4D9zaJHtfD/fP7x0kxgEVus/U7gehetRCkBdj8L1KNwIQBzotIFOG/0/toFOG+i09D97FK5H4XryPz6nDXTaQO4/ldHbslbH5z+Qe82FpCnnP+j7qfHSTeI/KaO3Za2O4T8J80T9G6HiP/L91HjpJt8/mODBPFH/3j+SXyz5xZLdP1sdEzyYJ9w/GJKmVJx93D9jggfzRP3ZP7eQNKXi7Nk/g8DKoUW22T8Sg8DKoUXYPwJWDi2yndc/Qxm9LWt12D/jXnMhaUrXPyxA7jUXktY/E/VvhDJ60z86JngwT9TRP8gvlvxiydE/PzVeukkM0j+nDXTaQKfRP1Nx9uEz7NA/xSCwcmiRzT+bUnH24TPQP8paHRM8mMs/XnMhaUrFxT/7YskvlvzGP7M6JngwT8g/DuaJ+jdCyT9soNMGOm3MP85pA5020Mk/tMh2vp8ayz/qfD81XrrFP9IGOm2g08Y/EjyYJ+rfyD/mbVmrY4LHP/cMuwLkXsc/6d8IZfS2yD/RItv5fmrIP/nwGXYFyMU/e1vW6pjgxT8ZWmQ730/FP4AH80T9G8U/VYDcay4kxT9oSsXZh8/EP8dLN4lBYMU/nkW28/3UxD/LoUW28/3EP6jGSzeJQcA/RsXZh8+wuz/3xZJfLPm9P+RC0pSKs78/kF8s+cWSvz/lifo3QhnFP9v5fmq8dMM/vC1rdUzwxD//gJVDi2y3P3qGXQFyr7k/3sE8Uf9GwD8/NV66SQzCPzgmeDBP1MM/tWWtjgkexD8O5on6N0LFP6AaL90kBsU/YYIH80T9uz/bslbHBA/CP9hApw102sA/olScffgMuz87mCfq3wjBP7HIdr6fGsM//3GvuZA0wT/Ag3mi/o3APxsv3SQGgcE/mzbQaQOdwj/9Riijt2XBP8l2vp8aL8E/MzMzMzMzwz8PyuhtWavDP/WaC0lTKsI/xNmHz7ArwD+F61G4HoW7P63Idr6fGrc/BfNE/RuhvD85w64Aude0Pwi7AuRec7k/9jdCGb0tuz/omODBPFG3P45Di2zn+7k/+GLJL5b8sj9MN4lBYOWwP3QUrkfherQ/gjJ6W9bquD/kUbgeheu5P+Dsw2fYFbg/OlH/Riijtz+wgU4b6LS5P6ApFWcfPrM/NV66SQwCsz+YffgMuwK0P7TXXEiaUrE/f2q8dJMYtD8e95oLSVO6Pxsv3SQGgbU/tNdcSJpSuT8BnTbQaQO1P9nO91PjpbM/BGX0tqzVsT+CMnpb1uqwP9WHz7ArQLY/g8DKoUW2uz+hxks3iUG4P10s+cWSX7w/q53vp8ZLtz/WFSD3mguxP2cDnTbQabM/EyD3mgtJsz+X4ME8Uf+2P8l2vp8aL70/V7pJDAIrtz83iUFg5dC6P4ts5/up8bI/UrgehetRsD+AB/NE/RuxPxzME/VvhLI/f3mi/o1Qtj9I8GCeqH+7P9WHz7ArQLY/oBov3SQGuT9VgNxrLiS1P9K/EcrobbE/DBERERERsT92ME/UvxGyP6wcWmQ737c/yhP1b4Qyuj/+415zIWm6P6JUnH34DLs/8Las1THBsz/FL5b8YsmvP4aIiIiIiLA/gaQpFWcftj/JhaQpFWe3PwGdNtBpA7U/8Las1THBsz8+pw102kC3P1pzIWlKxbE/+FPjpZvEsD8UrkfhehSuPyUVZx8+w64/5d8IZfS2tD/9Riijt2W1Pwt02kCnDbQ/JRVnHz7Dtj+4LWt1TPCwP31OG+i0ga4/BFYOLbKdrz8ZEzyYJ+qvP10s+cWSX7Q/MqXi7MNnuD9wvp8aL920P3Wi/o1QRrc/sqzVMcGDsT+uVscED+apP9WHz7ArQK4/iLMPn2FXsD8HLbKd76e2P6R/I5TR27o/d82FpCkVtz8zQhm9LWu1Pw/K6G1Zq7M/vIN5ov6NsD/Vh8+wK0CuPy5P1L8RyrA/Di2yne+ntj8tsp3vp8a7P7gta3VM8Lg/jjSl4uzDtz/omODBPFG3Pwctsp3vp7Y/KWt1TPBgtj8+pw102kC3Pwi7AuRec7k/pH8jlNHbuj8q+cWSXyy5Px1pSsXZh7c/ucqhRbbztT+yrNUxwYOxP8UgsHJoka0/ZDvfT42Xrj8AD+aJ+jeyP2OtjgkezLM/UscED+aJsj85w64Aude0P5huEoPAyrE/FveaC0lTqj8ZBFYOLbKtP0u4HoXrUbA/5wqQe82FtD+oxks3iUG4PyUGgZVDi7Q/OlH/Riijtz9nEoPAyqG1PwisHFpkO68/YPS2rNUxsT9WHRM8mCeyP3Wi/o1QRrc/TnH24TPsuj+j4uzDZ9i1P51hV4Dca7Y/VYDcay4ktT9Xq2OCB/O0P/7jXnMhabI/LcGDeaL+tT9ooNMGOm24P7vmQtKUirs/UI2XbhKDuD/9Riijt2W1P+3u7u7u7rY/2msuJE2puD+gKRVnHz67P1CcffgMu7o/gAfzRP0buT98seQXS365Pw48mCfq37g/o/HSTWIQuD/mbVmrY4K3P2Xn+6nx0rU/j9HbslbHtD+iY4IH80StPy2yne+nxrM/5nw/NV66uT84JngwT9S3P6wcWmQ737c/mH34DLsCtD+YffgMuwK0P5qofyOU0bM/Tw4tsp3vtz9y2kCnDXS6P3WTGARWDr0/bFmrY4IHuz9iHz7DrgC5Px+U0duyVrc/LcGDeaL+tT/58Bl2Bci1P5Mn6t8IZbQ/17JWxwQPtj9QjZduEoO4PxKSplScfbg/WDm0yHa+tz/4U+Olm8S4PzMzMzMzM7s/PqcNdNpAvz/2KFyPwvXAP+Ez7AqQe8E/Gy/dJAaBwT/tNReSplTAP+IXS36x5MM/RLbz/dR40T/4mgtJUyrYP3yGXQFyr9U/QGDl0CLb1T/8qfHSTWLSP1eA3GsuJNU/qX8jlNHb4D/p3whl9LbYP1Fx9uEz7NA/FyD3mgtJyz9TnH34DLvGP/GLJb9Y8sM/Zh8+w64AxT+DwMqhRbbDP6mqqqqqqsI/jN6WtTom0D/dJAaBlUPVP0NERERERNY/BoGVQ4tsyz8fhetRuB7JP5MYBFYOLcY/arx0kxgExj956SYxCKzEP+QXS36x5NE/rkfhehSu0T84JngwT9THP9nO91PjpcM/N4lBYOXQwj+TGARWDi3KP4RdAXKvucg/ObTIdr6fxj/KWh0TPJjHP2XYFSD3msM/dZMYBFYOvT97FK5H4Xq8PydA7jUXkr4/0NuyVscEwz93vp8aL93EP8uhRbbz/cA/w/UoXI/CwT+im8QgsHLAP+8ZdgXIvb4/BfNE/RuhvD/Vh8+wK0C+PxAREREREcE/M+wKkHvNwT93vp8aL93AP3D24TPsCsA/IbByaJHtvD9OcfbhM+y6Pylcj8L1KLQ/ZwOdNtBpsz8iXI/C9Si8PyAiIiIiIro/TEZvy1oduz+R/GLJL5a8P5fgwTxR/7Y/hQkezBP1rz9pLiRNqTizP5+M3pa1OrY/vC1rdUzwwD8/NV66SQzCPyG/WPKLJb8/5m1Zq2OCwz9g5dAi2/nKP3Noke18P8k/pHA9CtejxD9qvHSTGATCP30/NV66ScQ/vljyiyW/xD/p3whl9LbEP1Qqzj58hsE/hoiIiIiIyD8YvS1rdUzQP6RwPQrXo9I/1OqY4ME8zT+CMnpb1urIP00b6LSBTsc/q44JHswTxT+411xImlLNP55hV4Dca9A/w/UoXI/CyT/58Bl2BcjFP2YfPsOuAMU/i2zn+6nxxj9dLPnFkl/IP7M6JngwT8Q/vcqhRbbzxT+SQ4ts5/vJPwisHFpkO8s/slbHBA/myT8/7jUXkqbIPwhl9Las1c0/HaGM3pa1yj/88Bl2BcjFP7PkF0t+scg/mLU6Jngwyz8neDBP1L/JP+iY4ME8Ucc/QIts5/upxT9NG+i0gU7HP3CvuZA0pcY/I9v5fmq8xD9PN4lBYOXMPx2wcmiR7cw/Q0REREREyD/VeOkmMQjIPzdCGb0ta8k/x5JfLPnF0j8WkqZUnH3WP/YoXI/C9dA/LWt1TPBgzj/QaQOdNtDbP6VUnH34DOQ/8Bl2Bci93D/LoUW28/3WP5XR27JWx9Y/mgtJUyrO1D8nMQisHFrSP0Vvy1odE9I/nmFXgNxr1j9I4XoUrkfVP5A0peLsw9E/Lmt1TPBg0D+xK0DuNRfUPzVeukkMAtM/jZduEoPA1D/Ag3mi/o3YPwfIveZC0tg/R5pScfbh1T/5DLsC5F7TPzLBg3mi/tE/Tak4+/AZ0j+PwvUoXI/SPzm0yHa+n9I/8Bl2Bci90j+6AuRecyHXP7HkF0t+sdI/dGiR7Xw/0T/G2YfPsCvQPxBYObTIdtA/YOXQItv5zj9NG+i0gU7PP9v5fmq8dM8/+JoLSVMqyj9aHRM8mCfKP85pA5020M0/2/l+arx00T9sdUzwYJ7eP/PSTWIQWN8/Gy/dJAaB1z+QNKXi7MPTP7wta3VM8NY/D59hV4Dc2T/2U+Olm8TWP3kwT9S/EdQ/NOwKkHvN0T/w0k1iEFjRP7MPn2FXgNQ/YJ6ofyOU0T/tNReSplTMP7oC5F5zIck/7tJNYhBYyT9sWatjggfLP34jlNHbsso/ZmZmZmZmyj9mHz7DrgDFP0nF2YfPsMc/U1VVVVVVzT/KWh0TPJjPP0T9G6GM3tA/u7u7u7u74j+s1THBg3nlPzbQaQOdNto/hetRuB6F0z8hsHJoke3SP8HKoUW289E/dnd3d3d3zz/14TPsCpDPP8/3U+Olm9A/4XoUrkfh0j9HmlJx9uHTP4WkKRVnH9I/W9bqmODB7T/AWPKLJf8YQI0lv1jyCxNA9ihcj8L1AkCcNtBpA534P/nFkl8s+fU/TxvotIFO8j8CK4cW2c7vPyzOPnyGXe0/pZvEILBy6T97W9bqmODlP/7UeOkmMeM/hHmi/o1Q4z8MAiuHFtnjP6tjggfzROM/ldHbslbH4T9cj8L1KFzhP7gehetRuN4/c2iR7Xw/3z8o6t8IZfTePyJpSsXZh90/sp3vp8ZL3T8ZdgXIvebeP+e0gU4b6Nw/sw+fYVeA2j9JmlJx9uHZP9QGOm2g09g/+/AZdgXI1z93vp8aL93WP+m0gU4b6NY/DuaJ+jdC1z8j2/l+arzWPy4kTak4+9Q/of6NUEZv0z/MhaQpFWfTPxX1b4QyetE/bxKDwMqhzT8AVg4tsp3PP9jqmODBPM0/5dAi2/l+yj9XVVVVVVXNP4AH80T9G8U/6nw/NV66wT9w9uEz7ArEP2hKxdmHz8Q/NReSplScxT+R7Xw/NV7KP+xRuB6F680/V2Q730+Nxz/wp8ZLN4nFP02pOPvwGdA/pSkVZx8+0T9E4XoUrkfNP3z4DLsC5Mo/XEiaUnH2zT9jggfzRP3TP3Foke18P9c/PzVeukkMzj9bq2OCB/PIP+p8PzVeusk/McGDeaL+yT9hggfzRP3LP0oMAiuHFs0/qMZLN4lBzD/5DLsC5F7TP5ZuEoPAytU/gcDKoUW20z8iTak4+/DNP0a28/3UeM0/Q0RERERE0D/VeOkmMQjIP30/NV66Scg/JqO3Za2OwT99PzVeuknAP3yx5BdLfrk/WDm0yHa+tz/LsCtA7jW3P/WaC0lTKr4/j9HbslbHvD/0/dR46Sa5P4PAyqFFtrs/EpKmVJx9uD9MRm/LWh2zPxSuR+F6FLY/VPKLJb9Yuj+xD59hV4DEP5BfLPnFkr8/P0REREREvD97W9bqmODBP9NNYhBYObw/hoiIiIiIsD9uhDJ6W9ayPwPXo3A9Crc/U1VVVVVVwT+/PFH/Rii7P0diEFg5tLg/j9HbslbHvD9LqTj78Bm2P4AH80T9G7k//VUOLbKdtz9HYhBYObS4P2k9CtejcL0/UscED+aJuj+jKRVnHz7HP37cay4kTc0/3SQGgZVDxz+yne+nxku/PwcezBP1b7w/TEZvy1oduz+j4uzDZ9i9PxqhjN6Wtbo/Tw4tsp3vtz86Uf9GKKO3P8xNYhBYObQ/Dkt+seQXqz9ooNMGOm2wP/y411xImrI/ZxKDwMqhvT9ooNMGOm24PwAP5on6N7I/lVJx9uEztD8JSVMqzj60P7TIdr6fGrc/Gz7DrgC5tz9cnqh/I5S5P9NcSJpScb4/bFmrY4IHuz/sUbgehevBP8M8Uf9GKMM/iyW/WPKLwT/MPnyGXQHCP9uyVscED8I/NReSplScwT9kO99PjZfCP7TIdr6fGr8/Ik2pOPvwsT9vEoPAyqG9P2xZq2OCB7M/hF0Bcq+5sD/l0CLb+X6yP1LHBA/mibI/N4lBYOXQuj9t5/up8dK9P/yp8dJNYsA/bxKDwMqhwT/HSzeJQWC9P5tFtvP91LA/djBP1L8Rsj+4HoXrUbi+PwuDwMqhRbY/I+rfCGX0tj9t9uEz7Aq4PwcezBP1b7Q/j8L1KFyPsj8LdNpApw20P+O0gU4b6LQ/j9HbslbHtD/bCGX0tqy1P0Uoo7dlrbY/QNKUirMPtz85w64Aude8P5SmVJx9+Lw/eekmMQisvD/+1HjpJjHAPw4tsp3vp8I/7TUXkqZUxD/KWh0TPJjHP0P9G6GM3sI/IzEIrBxaxD8CK4cW2c6/P6oPn2FXgKw/d9xrLiRNqT/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz93zYWkKRWnPxKSplScfag/kfxiyS+WrD9WLPnFkl+sP37rUbgehbM/dZMYBFYOrT+e/o1QRm+rP6RwPQrXo7A/CvVvhDJ6qz+gKRVnHz6jP/zWo3A9Cqc/3TPsCpB7rT/vKFyPwvWwP1pzIWlKxbE/xJJfLPnFsj/YQKcNdNqwP7TIdr6fGq8/DjyYJ+rfsD+RC0lTKs6uP90z7AqQe60/0s73U+Olsz8xCKwcWmSzPxfotIFOG7A/UrgehetRsD++veZC0pSqP1pzIWlKxak/vq4AuddcqD9vME/UvxGqPx1aZDvfT60/VOOlm8QgsD95+Ay7AuSuP+Xu7u7u7q4/BpB7zYWkqT+P76fGSzepPwI6baDTBqo/OwwCK4cWqT8rlvxiyS+2P1H/Riijt+M/5/up8dJN5T+8dJMYBFbSP8NLN4lBYMU/U5x9+Ay7wj97FK5H4XrAP1sBcq+5kMA/6sNn2BUgvz+iRbbz/dTEP+DBPFH/RtI/S6k4+/AZ2D/dJAaBlUPTP98IZfS2rME/i2zn+6nxuj/SvxHK6G25P1TjpZvEIMA/lMQgsHJouT95+Ay7AuS2P88GOm2g07Y/62CeqH8jtD9fV4Dcay60P39qvHSTGLQ/FpKmVJx9yD99PzVeukniPzsmeDBP1OM/oYzelrU63D8wT9S/EcrQPymjt2WtjsU/5m1Zq2OCwz9soNMGOm3AP8V2vp8aL8E/BA/mifo3wj8j6t8IZfS+P2Z1TPBgnrg/5FG4HoXruT8BnTbQaQO9P8/3U+Olm8Q/7TUXkqZUyD9dLPnFkl/AP+IXS36x5L8/EfVvhDJ6uz+gGi/dJAa5PxMg95oLSbs/wSCwcmiRwT+DwMqhRba7P0dTKs4+fLY/xKFFtvP9tD9xTPBgnqi3P/NvhDJ6W7Y/o+Lsw2fYtT9JfrHkF0u2P0SaUnH24bM/QmDl0CLbqT81XrpJDAKrPzTQaQOdNrA/0r8RyuhtuT8AAAAAAACwP6JjggfzRK0/XtgVIPeaqz97QWDl0CKrP5tFtvP91LA/Ll66SQwCsz+wgU4b6LSxPyAxCKwcWrw/0s73U+Oluz8IZfS2rNXFPxh2Bci95sI/VOOlm8QgwD/uiyW/WPKzPzB6W9bqmLA/8KfGSzeJsT/58Bl2Bci1PxqwcmiR7bQ/9ZoLSVMqtj//gJVDi2y3P+ZtWatjgrc/w/UoXI/CtT+Isw+fYVewP9prLiRNqbA/QwwCK4cWsT8q+cWSXyyxP4GVQ4ts57M/qWOCB/NEtT9Ei2zn+6mxPxfotIFOG6g/rmWtjgkerD/clrU6JniwP3sUrkfherw/Dkt+seQXqz9acyFpSsWpP1Eqzj58hrU/BpB7zYWksT9xTPBgnqivP1pzIWlKxbE/SPBgnqh/sz+6WPKLJb+4P2CeqH8jlME/CtejcD0Kyz9fV4Dcay7EP7uQNKXi7Mc/72CeqH8j0j/wp8ZLN4nNPyPb+X5qvMQ/ukkMAiuHvj8ZEzyYJ+q3P5+M3pa1OrY/U1VVVVVVtT+gGi/dJAaxPwwCK4cW2a4/djBP1L8Rsj82+/AZdgWwPx73mgtJU7I/sqzVMcGDsT8/NV66SQyyP4relrU6JrA/4XoUrkfhqj/A91PjpZukPydP1L8Ryqg/vHSTGARWrj+f76fGSzfhP+7u7u7u7vo/z7ArQO415D//uNdcSJrOP7vmQtKUisM/c3d3d3d3tz//gJVDi2y3P3Wi/o1QRrc/1hUg95oLwT/I6G1Zq2O6P7YC5F5zIbk/P0REREREvD+R7Xw/NV66P/NvhDJ6W7Y/wXa+nxovtT+Dz7ArQO61P6G3Za2OCb4/q44JHswTvT8X6LSBThu4P8DZh8+wK7g/6TUXkqZUtD/hifo3QhmtP3n4DLsC5K4/ZwOdNtBpsz93zYWkKRW3P/N+arx0k7g/FK5H4XoUtj/KItv5fmq0PxMREREREbk/3TPsCpB7vT/bCGX0tqy9Pzb78Bl2Bbg/j9HbslbHvD9t5/up8dK9PyuHFtnO97s/x1odEzyYvz9EmlJx9uG7P0dTKs4+fLY/RJpScfbhsz9fV4Dcay60P+Dsw2fYFbg/H5TR27JWtz/qw2fYFSC3PyUVZx8+w7Y/46WbxCCwsj8SoYzelrWqPzEXkqZUnK0/vRHK6G1Zsz+5u7u7u7uzP0jwYJ6of7s/sp3vp8ZLzz/14TPsCpDVPwlJUyrOPsw/VOOlm8QgwD+iVJx9+Ay7P28haUrF2bc/Y62OCR7Muz9+3GsuJE25P/fUeOkmMbg/7xl2Bci9tj8qCKwcWmSzPznSlIqzD68/4OzDZ9gVsD/+1HjpJjGwPz9ERERERLQ/WwFyr7mQtD/5N0IZvS3RP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP8vobVmrY9I/Pd9PjZdu0j8930+Nl27SP8nobVmrY9I/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI//Knx0k1i0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j80peLsw2fSP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/LWt1TPBg0j8930+Nl27SP9Mi2/l+atI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j+R7Xw/NV7SP+9gnqh/I9I/m1Jx9uEz0j+EeaL+jVDSP5HtfD81XtI/ke18PzVe0j/QlIqzD5/NP6RwPQrXo7A/0r8RyuhtsT/vGXYFyL2+PywkTak4+9Y/M8GDeaJ+9D8jIiIiIiL1P+DBPFH/Rtg/PQrXo3A9yj9KYhBYObTEPwXzRP0bocA/D8robVmruz+2AuRecyG5Pzx8hl0Bcrc/DAIrhxbZtj99ThvotIG2P79LN4lBYLU/sQ+fYVeAvD81XrpJDALhP3E9CtejcPw/EeaJ+jfC9j/D9Shcj8LVPxzotIFOG9A/89JNYhBY3T/4U+Olm8TmP1iA3GsuJOA/v8qhRbbz1z8JZfS2rNXRP8uhRbbz/cw/Yh8+w64AyT8m6t8IZfTGPw7mifo3QsU/16NwPQrXwz89CtejcD3CP3Noke18P8E/tWWtjgkewD/t7u7u7u6+P51hV4Dca74/fU4b6LSBvj9YObTIdr6/P3FM8GCeqL8/K5b8Yskvvj83iUFg5dC6P4AH80T9G7k/1hUg95oLuT8q+cWSXyy5P5KZmZmZmbk/tgLkXnMhuT+0gU4b6LTBP7SBThvotNE/Yskvlvxi0T+5u7u7u7vHPyUGgZVDi8A/mQtJUyrOvj9RcfbhM+zKPxKDwMqhRc4/i2zn+6nxyj+Hz7ArQO7BP6UNdNpAp70/z/dT46WbvD9zaJHtfD/JP5cn6t8IZd4/D+aJ+jdC4D9fcyFpSsXXP21Zq2OCB9M/x0s3iUFg0T+R7Xw/NV7QPzal4uzDZ8w//iqHFtnOxz92d3d3d3fHPyGwcmiR7cg/5Yn6N0IZyT9IUyrOPnzeP1ScffgMu+Y/kAkezBP12T8+fIZdAXLRP9QxwYN5otA/46WbxCCw1j+v5BdLfrHaP1YOLbKd79k/EzyYJ+rf4z9Hb8taHRPqP9qHz7ArQOM/x73mQtKU2j/yRP0boYzUPxl2Bci95tI/LiRNqTj70D/kQtKUirPPP3OvuZA0pc4/YOXQItv5zj8nXI/C9SjSP8l2vp8aL9M/1uqY4ME80T8Nn2FXgNzPPwisHFpkO88/y+htWatjzj8YvS1rdUzMP0SLbOf7qck/ctpApw10xj8uT9S/EcrEPz3DrgC518Q/q44JHswTxT8q+cWSXyzFPwGdNtBpA8U/qMZLN4lBxD81XrpJDALDPxUEVg4tssE/IbByaJHtwD+T0duyVsfAP8uhRbbz/cA/y6FFtvP9wD+v5BdLfrHAP6jGSzeJQcA/vHSTGARWvj+75kLSlIq7PwAP5on6N7o/nMQgsHJouT+sK0DuNRe6P6jVMcGDebo//LjXXEiauj/LoUW28/28P/7jXnMhaco/HbByaJHtxD/1mgtJUyq+PwXzRP0bobw/EyD3mgtJuz/hehSuR+G6P/y411xImro/EyD3mgtJuz8IuwLkXnO5P+iY4ME8Ubc/7xl2Bci9tj+fjN6WtTq2P51hV4Dca7Y/Q/0boYzetj/vGXYFyL22PylrdUzwYLY/EQRWDi2ytT9dLPnFkl+0P2cDnTbQabM/ShvotIFOsz/Qo3A9CtezPyAxCKwcWrQ/X1eA3GsutD+75kLSlIqzP8SSXyz5xbI/Prbz/dR4sT8q+cWSXyyxP57vp8ZLN7E/JqO3Za2OsT/KE/VvhDKyP8w+fIZdAbI/PzVeukkMsj+AB/NE/RuxPwAAAAAAALA/4ZjgwTxRrz/l7u7u7u6uPwisHFpkO68/TmIQWDm0sD+GiIiIiIiwP4izD59hV7A/iV8s+cWSrz8UrkfhehSuPznDrgC516w/eekmMQisrD/Jdr6fGi+tPz0oo7dlra4/zduyVscErz89KKO3Za2uP83MzMzMzKw/1XjpJjEIrD9e2BUg95qrP/LhM+wKkKs/rmWtjgkerD8ZBFYOLbKtPxSuR+F6FK4/mrdlrY4Jrj+JUEZvy1qtP421OiZ4MK8/5/up8dJNsj+/PFH/RiizP/Y3Qhm9LbM/wmfYFSD3sj+v1THBg3myP/1GKKO3ZbU/1XjpJjEItD9KDAIrhxaxP8Uvlvxiya8/zduyVscErz9xTPBgnqivP54cWmQ7368/jbU6Jngwrz8QWDm0yHauP90z7AqQe60/gZVDi2znqz+2EcrobVmrP90kBoGVQ6s/lVJx9uEzrD+NplScffisP6a5kDSl4qw//vJE/RuhrD9aggfzRP2rP7YRyuhtWas/vr3mQtKUqj+qALnXXEiqPwI6baDTBqo/4XoUrkfhqj/y4TPsCpCrP0bF2YfPsKs/dZMYBFYOrT/FILByaJGtP5VhV4Dca64/PRm9LWt1rD/RItv5fmqsP4GkKRVnH64/iVBGb8tarT+NplScffisPxSuR+F6FK4/umfYFSD3qj+YffgMuwK0P4lQRm/LWq0/fT81XrpJrD9KKs4+fIatP83MzMzMzKw/fT81XrpJrD8Gn2FXgNyrP2aEMnpb1qo/mpmZmZmZqT8j6t8IZfSmP+cZdgXIvaY/uljyiyW/qD9iLiRNqTirP17YFSD3mqs/thHK6G1Zqz+Le82FpCm1P+Z8PzVeurk/qMZLN4lBsD99ThvotIGuP/LwGXYFyK0/eekmMQisrD9Cb8taHROsP6oPn2FXgKw/NV66SQwCqz/dJAaBlUOrP+F6FK5H4ao/UscED+aJqj+JQWDl0CKrPzEIrBxaZKs/sru7u7u7qz+iVJx9+AyrPxb3mgtJU6o/nv6NUEZvqz+qALnXXEiqP3fcay4kTak/lkOLbOf7qT9OcfbhM+yqP05x9uEz7Ko/RsXZh8+wqz9mhDJ6W9aqP4X6N0IZva0/l5vEILByqD9/eaL+jVCmP2rLWh0TPKg/EqGM3pa1qj/hehSuR+GqP/ZGKKO3Za0/l5vEILByqD+HNKXi7MOnP99tWatjgqc//NajcD0Kpz8SkqZUnH2oP+58PzVeuqk/6SYxCKwcqj89CtejcD2qPz0K16NwPao/5dAi2/l+qj/pJjEIrByqP7695kLSlKo/ShvotIFOqz/2N0IZvS2rP8MT9W+EMqo/Yh8+w64AqT9/iIiIiIioP/QqhxbZzqc/j+DBPFH/pj9/eaL+jVCmPzv9G6GM3qY/c3d3d3d3pz/fbVmrY4KnPzenDXTaQKc/zwY6baDTpj9EqTj78BmmP2ASg8DKoaU/CNnO91PjpT8Eg8DKoUWmP4/gwTxR/6Y//NajcD0Kpz8j6t8IZfSmP1hmZmZmZqY/8MWSXyz5pT9I/0Yoo7elP9sIZfS2rKU/K5b8Yskvpj+sSQwCK4emP6xJDAIrh6Y/P1Mqzj58pj9cvHSTGASmP/QboYzelqU/vKFFtvP9pD+8oUW28/2kPwwv3SQGgaU/SP9GKKO3pT9cvHSTGASmP9NcSJpScaY/tPUoXI/CpT/0G6GM3palP4t7zYWkKaU/kyfq3whlpD+HJb9Y8oulPz9TKs4+fKY/01xImlJxpj93zYWkKRWnP5zi7MNn2KU/UKtjggfzpD8ML90kBoGlPwwv3SQGgaU/XLx0kxgEpj/wxZJfLPmlP9sIZfS2rKU/L+wKkHvNpT9kaJHtfD+lP5Mn6t8IZaQ/sJA0peLsoz91wMqhRbajP1hXgNxrLqQ/bBSuR+F6pD9UAXKvuZCkP1hXgNxrLqQ/62CeqH8jpD9crY4JHsyjP835fmq8dKM/oCkVZx8+oz91wMqhRbajP2wUrkfheqQ/kyfq3whlpD+YffgMuwKkP/QMuwLkXqM/qNUxwYN5oj+8kl8s+cWiP/y411xImqI//LjXXEiaoj95FtnO91OjP0xGb8taHaM/xU1iEFg5pD+gKRVnHz6jPxkiIiIiIqI/VPKLJb9Yoj8IyuhtWaujP4ts5/up8aI/i2zn+6nxoj+LbOf7qfGiP0xGb8taHaM/EHYFyL3moj+8kl8s+cWiPzvfT42XbqI/qNUxwYN5oj+LbOf7qfGiP4ts5/up8aI/DCD3mgtJoz/N+X5qvHSjP835fmq8dKM/TEZvy1odoz/4YskvlvyiP4ts5/up8aI/ZFmrY4IHoz8h3SQGgZWjPx2HFtnO96M/HYcW2c73oz8dhxbZzvejP6ApFWcfPqM/qNUxwYN5oj/n+6nx0k2iP7ySXyz5xaI/zfl+arx0oz8MIPeaC0mjPwSDwMqhRaY/47SBThvopD9QnH34DLuiP6ApFWcfPqM/j8L1KFyPoj8ZIiIiIiKiP5MYBFYOLaI/TEZvy1odoz8MIPeaC0mjP7CQNKXi7KM/uEs3iUFgpT9I8GCeqH+jP4ts5/up8aI/zfl+arx0oz9EmlJx9uGjPx2HFtnO96M/9BuhjN6WpT8QhetRuB6lP2Roke18P6U/2/l+arx0oz+PwvUoXI+iP1CcffgMu6I/HYcW2c73oz+8oUW28/2kP6jkF0t+saQ/GTEIrBxapD91wMqhRbajP835fmq8dKM/yaNwPQrXoz91wMqhRbajPz9TKs4+fKY//vJE/RuhrD81baDTBjqtP2IuJE2pOKs/K6Xi7MNnqD8j6t8IZfSmP9eyVscED6Y/315zIWlKpT8/RERERESkPx2HFtnO96M/+HGvuZA0pT+wkDSl4uyjPzvfT42XbqI/9Ay7AuReoz9or7mQNKWiPzvfT42XbqI/bAXIveZCoj/4YskvlvyiPzMzMzMzM6M/eRbZzvdToz/wxZJfLPmlP1CrY4IH86Q//LjXXEiaoj8AD+aJ+jeiP+xRuB6F66E/FMwT9W+Eoj8QhetRuB6lPwR02kCnDaQ/GSIiIiIioj+kfyOU0duiPzvfT42XbqI/WEiaUnH2oT/sUbgeheuhP6jVMcGDeaI/yaNwPQrXoz/0G6GM3palP1hXgNxrLqQ/CMrobVmroz8h3SQGgZWjP05x9uEz7LI/5d8IZfS2tD8xF5KmVJy1P+Dsw2fYFbA/bzBP1L8Rqj+Dz7ArQO6lP5h9+Ay7AqQ/HYcW2c73oz8dhxbZzvejP835fmq8dKM/XK2OCR7Moz9EqTj78BmmP+O0gU4b6KQ//LjXXEiaoj8/NV66SQyiP8U+fIZdAaI/O99PjZduoj8UzBP1b4SiP6R/I5TR26I/i2zn+6nxoj+LbOf7qfGiP4ts5/up8aI/N4lBYOXQoj8730+Nl26iPzvfT42XbqI/aK+5kDSloj+LbOf7qfGiP4ts5/up8aI/ZFmrY4IHoz9kWatjggejP99PjZduEqM/i2zn+6nxoj8UzBP1b4SiP6R/I5TR26I/i2zn+6nxoj+LbOf7qfGiP0xGb8taHaM/i2zn+6nxoj9QnH34DLuiPzvfT42XbqI/O99PjZduoj8730+Nl26iP1CcffgMu6I/i2zn+6nxoj9or7mQNKWiP1TyiyW/WKI/aK+5kDSloj8730+Nl26iP1TyiyW/WKI/7FG4HoXroT/A6G1Zq2OiPzeJQWDl0KI/VPKLJb9Yoj/FPnyGXQGiPzvfT42XbqI/O99PjZduoj8730+Nl26iPzvfT42XbqI/O99PjZduoj8730+Nl26iP6jVMcGDeaI/O99PjZduoj8730+Nl26iP8DobVmrY6I/WEiaUnH2oT/sUbgeheuhP8U+fIZdAaI/O99PjZduoj8730+Nl26iPzvfT42XbqI/AA/mifo3oj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/VPKLJb9Yoj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/c2iR7Xw/pT/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/6UT9G6GMrj/fXnMhaUq1PwtJUyrOPtI/2ECnDXTa1j+uVscED+bJP9NcSJpScb4/OCZ4ME/Utz/fXnMhaUq1P6aqqqqqqrI/zD58hl0Bsj+TGARWDi2yP+XfCGX0trQ/EQRWDi2ytT9VgNxrLiS1P1CcffgMu7I/5FG4HoXrsT8xF5KmVJytPxSuR+F6FK4//gErhxbZrj+Isw+fYVewP+xRuB6F67E/8Las1THBsz+BlUOLbOezP00b6LSBTsc/JL9Y8osl1T8WkqZUnH3MPxcv3SQGgcE/f2q8dJMYvD/4U+Olm8S4P+rDZ9gVILc/5m1Zq2OCtz/+415zIWm6P+81F5KmVOo/XI/C9Shc8D92d3d3d3fXP6d/I5TR28o/y/dT46WbxD8dWmQ730/BP5kLSVMqzr4/CUlTKs4+vD+R7Xw/NV66P/T91HjpJrk/MHpb1uqYuD+EXQFyr7m4P+Dsw2fYFbg/QNKUirMPtz+zSQwCK4e2PyuHFtnO97M/GHYFyL3msj+xD59hV4C0PyJcj8L1KLQ/JIcW2c73sz9hggfzRP2zP+6LJb9Y8rM/Y62OCR7Msz9I8GCeqH+zP4lBYOXQIrM/qNUxwYN5sj9WHRM8mCeyP5KZmZmZmbE/9P3UeOkmsT/YQKcNdNqwP5+bxCCwcrA/bfbhM+wKsD/2VQ4tsp2vP3FM8GCeqK8/+qscWmQ7rz89KKO3Za2uP9ExwYN5oq4/FK5H4XoUrj+F+jdCGb2tP3npJjEIrKw/7poLSVMqrj9G1L8RyuitP0bUvxHK6K0/gaQpFWcfrj9BfrHkF0uuP2Dl0CLb+a4/SirOPnyGrT8QWDm0yHauPxkEVg4tsq0/2d3d3d3drT/FILByaJGtPxkEVg4tsq0/1YfPsCtArj8UrkfhehSuP0F+seQXS64/qvHSTWIQsD8MAiuHFtm2P6MpFWcfPsM/3SQGgZVDxz97W9bqmODBP1NVVVVVVcE//iqHFtnOxz9cj8L1KFzHP26EMnpb1sI/ZdgVIPeauz8D16NwPQq3PwPXo3A9Crc/A9ejcD0Ktz8pa3VM8GC2P2cSg8DKobU/cL6fGi/dtD92PzVeukm0P7vmQtKUirM/UJx9+Ay7sj+qALnXXEiyP6wrQO41F7I/AjptoNMGsj/KE/VvhDKyP/7jXnMhabI/yhP1b4Qysj/n+6nx0k2yPwRl9Las1bE/0JSKsw+fsT+PwvUoXI+yPxMv3SQGgbU/EGcfPsOuuD+v8/3UeOm+P625kDSl4sg/M+wKkHvNzT8zMzMzMzPLP90kBoGVQ88/oYzelrU60D/YQKcNdNrIP0NERERERMQ/+fAZdgXIwT9fV4Dcay7AP4GkKRVnH74/6TUXkqZUvD8TIPeaC0m7P/7jXnMhabo/sqzVMcGDuT+yrNUxwYO5PywkTak4+7g/hF0Bcq+5uD+Isw+fYVe4Px1pSsXZh7c/WeXQItv5tj+j8dJNYhC4Pyajt2Wtjrk/MzMzMzMzuz+QbhKDwMq5P+391HjpJrk/P0REREREvD8HHswT9W/AP51hV4Dca8I/AuRecyFpwj+T0duyVsfIP3yx5BdLfsU/EBERERERyT/i7MNn2BXQPyGwcmiR7cg/4hdLfrHkwz/7G6GM3pbBP4relrU6JsQ/aQOdNtBp1T/NzMzMzMzcP42XbhKDwNQ/lpmZmZmZzT956SYxCKzIPyJNqTj78MU/9n5qvHSTxD/kQtKUirPDPwwCK4cW2cY//iqHFtnOzz9l2BUg95rPPw7mifo3Qsk/c2iR7Xw/xT8xCKwcWmTDPx73mgtJU8I/iyW/WPKLwT93vp8aL93AP+e0gU4b6MA/dekmMQiswD9WDi2yne+/P4GkKRVnH74/i3vNhaQpvT+zOiZ4ME+8P/QMuwLkXrs/ICIiIiIiuj+qALnXXEi6PyjOPnyGXbk/TnH24TPsuj8xCKwcWmS7P4GVQ4ts57s/yiLb+X5qvD+zOiZ4ME+8P9v5fmq8dLs/jZduEoPAuj8730+Nl266P3qGXQFyr7k/9P3UeOkmuT8sJE2pOPu4P7Ks1THBg7k/zD58hl0Buj8GkHvNhaS5Pzpg5dAi27k/hoiIiIiIuD/zfmq8dJO4Pzb78Bl2Bbg/wwQP5on6tz/7KocW2c63P28haUrF2bc//VUOLbKdtz+QXyz5xZK3P+iY4ME8Ubc/4XoUrkfhuj/4U+Olm8S4P9yWtTomeLg/YPS2rNUxuT8iTak4+/C5P9ejcD0K17s/GQRWDi2yvT8fhetRuB69P9nd3d3d3b0/FVpkO99PvT8BnTbQaQO9P+f7qfHSTbo/835qvHSTuD84JngwT9S3P8mFpCkVZ7c/7e7u7u7utj9D/RuhjN62P/FE/RuhjLY/2d3d3d3dtT/bCGX0tqy1P/1GKKO3ZbU/hfo3Qhm9tT8VWmQ730+1P8xNYhBYObQ/daL+jVBGtz+DwMqhRbazP4GkKRVnH7Y/rkfhehSuvz+GiIiIiIjAP3sUrkfherw/DBERERERuT9zd3d3d3e3P03jpZvEILg/mQtJUyrOtj9A0pSKsw+3P0Uoo7dlrbY/zwY6baDTtj+1dJMYBFa2P0DSlIqzD7c/01xImlJxtj8welvW6pi4PzNCGb0ta7U/9ZoLSVMqtj9fZmZmZma2P2GR7Xw/NbY/98WSXyz5tT8Lg8DKoUW2P/NvhDJ6W7Y/17JWxwQPtj/XslbHBA+2P2Xn+6nx0rU/L+wKkHvNtT+j4uzDZ9i1P9sIZfS2rLU/1YfPsCtAtj+9ILByaJG1P4GkKRVnH7Y/KWt1TPBgtj9LqTj78Bm2P9nd3d3d3bU/ZxKDwMqhtT+79Shcj8K1P19mZmZmZrY/J0DuNReStj9kO99PjZe2P3sjlNHbsrY/c3d3d3d3tz83mCfq3wi9P6c4+/AZdsE/XrpJDAIrwz+dYVeA3GvCP55FtvP91MA/H4XrUbgevT/GveZC0pS6P+8oXI/C9bg/ocZLN4lBuD9N46WbxCC4P4aIiIiIiLg/gAfzRP0buT/g7MNn2BW4P+Dsw2fYFbg/o/HSTWIQuD9vIWlKxdm3PzgmeDBP1Lc/HWlKxdmHtz+v8/3UeOm2P3FM8GCeqLc/zduyVscEtz8daUrF2Ye3P1sQWDm0yLY/JRVnHz7Dtj+4HoXrUbi2P6/z/dR46bY//4CVQ4tstz+EXQFyr7m4P+Z8PzVeurk/kG4Sg8DKuT+tyHa+nxq3P+3u7u7u7rY/f3mi/o1Qtj/3xZJfLPm1P6Pi7MNn2LU/7xl2Bci9tj9N1L8Ryui1PydA7jUXkrY/uB6F61G4tj8pa3VM8GC2PylrdUzwYLY/0JSKsw+fuT/GveZC0pTCPzKl4uzDZ8Q/dAXIveZCwj/HWh0TPJi/P2XYFSD3mrs/BpB7zYWkuT+CMnpb1uq4PzB6W9bqmLg/DjyYJ+rfuD9SxwQP5om6Px/b+X5qvMA/DZ9hV4Dcwz+75kLSlIrDP9yWtTomeMA/TdS/EcrovT9hggfzRP27P2xZq2OCB7s/i2zn+6nxuj8AD+aJ+je6P3hb1uqY4Lk/nMQgsHJouT+2AuRecyG5P2D0tqzVMbk/JqO3Za2OuT/l0CLb+X66PzvfT42Xbro/qgC511xIuj94W9bqmOC5P7TXXEiaUrk/7yhcj8L1uD8QZx8+w664P2ig0wY6bbg/+yqHFtnOtz/31HjpJjG4P0P9G6GM3rY/CKwcWmQ7tz8j6t8IZfS2P1sQWDm0yLY/WxBYObTItj+bNtBpA522P9WHz7ArQLY/nWFXgNxrtj8pa3VM8GC2P3n4DLsC5LY/t58aL90ktj+wcmiR7Xy3P6ud76fGS7c/I+rfCGX0tj+rne+nxku3P2ig0wY6bbg/lLU6Jngwtz8hv1jyiyW3P19mZmZmZrY/ucqhRbbztT+/SzeJQWC1P4t7zYWkKbU/GIXrUbgetT/Vh8+wK0C2Pxzb+X5qvLQ/nNMGOm2gsz+/SzeJQWC1PzeYJ+rfCLU/j9HbslbHtD8c2/l+ary0PxqwcmiR7bQ/M0IZvS1rtT8P2c73U+O1P5BfLPnFkrc/PIts5/upuT/b+X5qvHS7P1NVVVVVVb0/NW2g0wY6vT8COm2g0wa6P6wrQO41F7o/kxgEVg4tuj+2AuRecyG5P1TjpZvEILg/rch2vp8atz95+Ay7AuS2P+XQItv5fsI/Z9gVIPea1z+GpCkVZx/iP/1iyS+W/Ow/ILByaJHt6z+hRbbz/dThP7SBThvotNk/A5020GkD1T+x5BdLfrHSPwaBlUOLbNE/OPvwGXYF0D+Hz7ArQO7dP6vx0k1iEOs/0NuyVscE7T/ptIFOG+j4P0VERERERPY/ACuHFtnO6D+X/GLJL5bhPxFYObTIduA/eekmMQis4D9nHz7DrgDlPylcj8L1KOk/WDm0yHa+5T9x9uEz7ArhP/GLJb9Y8t0/Wx0TPJgn2j8XS36x5BfZP9hcSJpScdg/6G1Zq2OC1z90Bci95kLWP8SuALnXXNY/UuOlm8Qg3D+DeaL+jVDgP8cED+aJ+us/MzMzMzMz9T/cQKcNdNr0PzjQaQOdNuw/v+ZC0pSK5T9pke18PzXhPw+fYVeA3N8/FSD3mgtJ3T/8///////ZP7pJDAIrh9g/bz0K16Nw1z+UQ4ts5/vVP3PaQKcNdNQ/PnyGXQFy0z8MAiuHFtnSP3sUrkfhetI/rwC511xI0j8730+Nl27SP0Yoo7dlrdI/fT81XrpJ0j92d3d3d3fRP1vW6pjgwdA/mSfq3whl0D9QjZduEoPSP6tjggfzRNc/XI/C9Shc1T9g5dAi2/nSP/cMuwLkXtE/x73mQtKU0D/Xo3A9CtfPPz0K16NwPc4/vC1rdUzwzD+ZUnH24TPMP3IhaUrF2cs/rkfhehSuyz+HFtnO91PLP2Dl0CLb+co/fiOU0duyyj90Bci95kLKP15zIWlKxck/VYDcay4kyT8j2/l+arzIP3GTGARWDsk/tWWtjgkeyD9nrY4JHszHP00b6LSBTsc/4XoUrkfhxj/l0CLb+X7GP85pA5020MU/4TPsCpB7xT/SvxHK6G3FP8l2vp8aL8U/j3vNhaQpxT9VgNxrLiTFP+WJ+jdCGcU/OW2g0wY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48/G2t1TPBgjj/8qfHSTWKQPwwg95oLSZM/9mT0tqzVkT+m11xImlKRPxzSlIqzD48/rFjyiyW/iD/L3d3d3d2NP3tQRm/LWo0/fV0Bcq+5kD8OhxbZzveTP5MYBFYOLZI/O99PjZdukj8rw64AudeMPy0qzj58ho0/CKwcWmQ7jz+ug3mi/o2QP0w3iUFg5ZA/5Qy7AuRekz9sBci95kKSPzvfT42XbpI/ChM8mCfqjz8IrBxaZDuPP1TjpZvEIJA/VOOlm8QgkD/N6pjgwTyRP+2411xImpI/9mT0tqzVkT8730+Nl26SP0w3iUFg5ZA/GQRWDi2yjT/rjVBGb8uKP/5MqTj78Ik/GQRWDi2yjT+eK0DuNReSP3Wx5BdLfpE/GQRWDi2yjT+LbOf7qfGiPzEmeDBP1J8//i7dJAaBlT+VfyOU0duSP0w3iUFg5ZA/TDeJQWDlkD8tKs4+fIaNP9nO91PjpYs/OxvotIFOiz+sWPKLJb+IP0xzIWlKxYk/641QRm/Lij+LqH8jlNGLPwoTPJgn6o8/K8OuALnXjD+dZ9gVIPeKP+Eu3SQGgYU/DD7DrgC5hz+cALnXXEiKPzm0yHa+n4o/yXa+nxovjT+kcD0K16OQPz2CB/NE/Ys/OxvotIFOiz+LbOf7qfGCP5GhRbbz/YQ/boqzD59hhz+uvxHK6G2JP9nO91PjpYs/VOOlm8QgkD/pJjEIrByKP7gehetRuI4/XMtaHRM8iD/R1qNwPQqHPx/9G6GM3oY/bCOU0duyhj+wJjEIrByKP5zEILByaJE/GQRWDi2yjT/rjVBGb8uKP4lBYOXQIos/vhdLfrHkhz+BSQwCK4eGP1pkO99PjYc/7fRvhDJ6iz+m11xImlKRPxtrdUzwYI4/6SYxCKwcij/R1qNwPQqHP6xY8oslv4g/YJmZmZmZiT9O2kCnDXSKP40Pn2FXgIw/dbHkF0t+kT+LqH8jlNGLPzsb6LSBTos/rFjyiyW/iD8MPsOuALmHP14yelvW6og/THMhaUrFiT8tKs4+fIaNPwisHFpkO48/i6h/I5TRiz8rw64AudeMPz2CB/NE/Ys/eekmMQisjD956SYxCKyMPzsb6LSBTos/2zUXkqZUjD99t2WtjgmOP9s1F5KmVIw/TtpApw10ij9uirMPn2GHP1zLWh0TPIg/IGQ730+Nhz+q8dJNYhCIP4lBYOXQIos/jQ+fYVeAjD+amZmZmZmJP0xzIWlKxYk/CtejcD0Khz9/4uzDZ9iFPx/9G6GM3oY/vhdLfrHkhz+wJjEIrByKP40Pn2FXgIw/rFjyiyW/iD9eMnpb1uqIP4ts5/up8YI/Le41F5KmhD9eMnpb1uqIPyvDrgC514w/K8OuALnXjD956SYxCKyMPyvDrgC514w/iUFg5dAiiz+TGARWDi2SP7ySXyz5xZI/zUT9G6GMjj97UEZvy1qNP+kmMQisHJo/8tJNYhBYmT9YObTIdr6PP/yp8dJNYpA/G2t1TPBgjj+ND59hV4CMP9s1F5KmVIw/G2t1TPBgjj97UEZvy1qNP323Za2OCY4/avgMuwLkjj+LqH8jlNGLP+30b4Qyeos/eekmMQisjD/t9G+EMnqLP3npJjEIrIw/avgMuwLkjj/8qfHSTWKQP81E/RuhjI4/jQ+fYVeAjD9eMnpb1uqIPzm0yHa+n4o/zeqY4ME8kT+4HoXrUbiOP+30b4Qyeos/2c73U+Oliz+JQWDl0CKLP2CZmZmZmYk//OWJ+jdCiT/Afmq8dJOIP07aQKcNdIo/EAwCK4cWiT+amZmZmZmJP07aQKcNdIo/DqXi7MNniD/85Yn6N0KJP4FJDAIrh4Y/L1VVVVVVhT8QDAIrhxaJP+30b4Qyeos/yXa+nxovjT/pJjEIrByKP14yelvW6og/nWfYFSD3ij/fqfHSTWKQP9WWtTomeJA/OxvotIFOiz/+TKk4+/CJP4lBYOXQIos//OWJ+jdCiT++F0t+seSHPyBkO99PjYc/38e95kLShD+amZmZmZmJP66/EcrobYk/arx0kxgEhj/pJjEIrByKP6xY8oslv4g//OWJ+jdCiT9KDAIrhxaJPy9VVVVVVYU/z2+EMnpbhj8t7jUXkqaEPx2W/GLJL4Y/DD7DrgC5hz/85Yn6N0KJP66/EcrobYk/HZb8Yskvhj9uirMPn2GHP9/HveZC0oQ/8YYW2c73gz9BFK5H4XqEPww+w64AuYc//OWJ+jdCiT8MPsOuALmHP4FJDAIrh4Y/7FG4HoXrgT+w6pjgwTyBP486JngwT4Q/kaFFtvP9hD/85Yn6N0KJP14yelvW6og/Mbx0kxgEhj8dlvxiyS+GP4GFpCkVZ38/gYWkKRVnfz+LbOf7qfGCP317zYWkKYU/EAwCK4cWiT8gZDvfT42HP74XS36x5Ic/qvHSTWIQiD8730+Nl26CP3/i7MNn2IU/zQhl9LashT8dlvxiyS+GPw6l4uzDZ4g/nWfYFSD3ij8QDAIrhxaJPw6l4uzDZ4g/2/l+arx0gz9YObTIdr5/P5zEILByaIE/ofl+arx0gz9KDAIrhxaJP+uNUEZvy4o/y6FFtvP9hD8MPsOuALmHPzG8dJMYBIY/2/l+arx0gz/Pb4QyeluGP2wjlNHbsoY/0dajcD0Khz/hLt0kBoGFPwrXo3A9Coc/rFjyiyW/iD+POiZ4ME+EP9v5fmq8dIM/O99PjZdugj97FK5H4XqEP89vhDJ6W4Y/bCOU0duyhj9BFK5H4XqEPz1Gb8taHYM/TDeJQWDlgD+BhaQpFWd/P1pkO99PjYc/oJJfLPnFgj/Pb4QyeluGP26Ksw+fYYc/PUZvy1odgz8730+Nl26CPzvfT42XboI//Knx0k1igD+RoUW28/2EP3sUrkfheoQ/Le41F5KmhD+sWPKLJb+IPy9VVVVVVYU/jzomeDBPhD+gkl8s+cWCP7gehetRuH4/YF0Bcq+5gD/tuNdcSJqCPww+w64AuYc/SgwCK4cWiT/6fmq8dJOIPx/9G6GM3oY/+n5qvHSTeD8mmZmZmZl5P/4QEREREYE/PUZvy1odgz/85Yn6N0KJP4uofyOU0Ys/vLArQO41hz9qvHSTGASGP4OwK0DuNXc/vhdLfrHkdz8ZBFYOLbJ9P/yp8dJNYoA/THMhaUrFiT/rjVBGb8uKPww+w64AuYc/3WCeqH8jhD97FK5H4Xp0Pxsv3SQGgXU/4Wp1TPBgfj+LbOf7qfGCP26Ksw+fYYc/TtpApw10ij8vVVVVVVWFPxsv3SQGgYU/IstaHRM8eD/dnDbQaQN9P+8f95oLSYM/jzomeDBPhD+sWPKLJb+IP6xY8oslv4g/fXvNhaQphT/tuNdcSJqCP0w3iUFg5YA/PYIH80T9ez9MN4lBYOWAPzvfT42XboI/boqzD59hhz9uirMPn2GHP3sUrkfheoQ/oJJfLPnFgj9gXQFyr7mAP/4QEREREYE/PUZvy1odgz8730+Nl26CPwrXo3A9Coc/rr8RyuhtiT+POiZ4ME+EP+xRuB6F64E/8YYW2c73gz+eK0DuNReCP/yp8dJNYoA/Tp6ofyOUgT8MPsOuALmHP6xY8oslv4g/38e95kLShD8730+Nl26CP+8f95oLSYM/7bjXXEiagj+ug3mi/o2AP06eqH8jlIE/XMtaHRM8iD9O2kCnDXSKP3/i7MNn2IU/arx0kxgEhj9/4uzDZ9iFP7pJDAIrh4Y/f+Lsw2fYhT8dlvxiyS+GPww+w64AuYc/DD7DrgC5hz/hLt0kBoGFP2wjlNHbsoY/DD7DrgC5hz9uirMPn2GHP6rx0k1iEIg/wH5qvHSTiD9O2kCnDXSKP9s1F5KmVIw/001iEFg5lD92ME/UvxGyP5M20GkDnZY/641QRm/Lij9O2kCnDXSKP0xzIWlKxYk/EAwCK4cWiT85tMh2vp+KP9s1F5KmVIw/mpmZmZmZiT+6SQwCK4eGP6rx0k1iEIg/qvHSTWIQiD8OpeLsw2eIP5wAuddcSIo/EAwCK4cWiT8f/RuhjN6GP4FJDAIrh4Y/Mbx0kxgEhj+BSQwCK4eGPzG8dJMYBIY/gUkMAiuHhj9aZDvfT42HP26Ksw+fYYc/HZb8Yskvhj9BFK5H4XqEP+8f95oLSYM/QRSuR+F6hD+RoUW28/2EP9/HveZC0oQ/boqzD59hhz+BSQwCK4eGPy9VVVVVVYU/O99PjZdugj8730+Nl26CP/GGFtnO94M/38e95kLShD+RoUW28/2EP4FJDAIrh4Y/zQhl9LashT9QBci95kKCP91gnqh/I4Q/XvbhM+wKgD8AeDBP1L+BPxDQaQOdNoA/eekmMQisfD8dlvxiyS+GP43TBjptoIM/AHgwT9S/gT+POiZ4ME+EPxI3iUFg5YA/PYIH80T9ez8730+Nl26CP06eqH8jlIE/H/0boYzehj+q8dJNYhCIPwB4ME/Uv4E/sOqY4ME8gT+hNReSplR8P9nO91PjpXs/AHgwT9S/gT+h+X5qvHSDPw6l4uzDZ4g/0dajcD0Khz8/rY4JHsyDP+xRuB6F64E/Q3vNhaQpdT99t2Wtjgl+P0w3iUFg5YA/P62OCR7Mgz8QDAIrhxaJP/zlifo3Qok/H/0boYzehj8vVVVVVVWFP7DqmODBPIE/YF0Bcq+5gD/Pb4QyeluGP7ywK0DuNYc/cPHSTWIQiD+sWPKLJb+IP317zYWkKYU/oJJfLPnFgj/xhhbZzveDPz+tjgkezIM/nitA7jUXgj/tuNdcSJqCPw6l4uzDZ4g/cPHSTWIQiD+N0wY6baCDP0FQRm/LWn0/fbdlrY4Jfj8AeDBP1L+BP9v5fmq8dIM/L1VVVVVVhT+D/GLJL5acP2wFyL3mQpI/rFjyiyW/iD8bL90kBoGFPy9VVVVVVYU/K4cW2c73gz9gXQFyr7mAP2BdAXKvuYA/zQhl9LashT99e82FpCmFP54rQO41F4I/K4cW2c73gz/b+X5qvHSDP0w3iUFg5YA//Knx0k1igD+POiZ4ME+EP5GhRbbz/YQ/arx0kxgEhj/b+X5qvHSDPwB4ME/Uv4E/7bjXXEiagj/+EBERERGBP6CSXyz5xYI/jdMGOm2ggz99e82FpCmFPxsv3SQGgYU/7bjXXEiagj/+EBERERGBPz2CB/NE/Xs/uB6F61G4fj9gXQFyr7mAP1AFyL3mQoI/bCOU0duyhj+8sCtA7jWHP3sUrkfheoQ/i2zn+6nxgj+gkl8s+cWCPz1Gb8taHYM/z2+EMnpbhj9BFK5H4XqEP2wjlNHbsoY/WmQ730+Nhz/fx73mQtKEPz1Gb8taHYM/7bjXXEiagj+LbOf7qfGCP486JngwT4Q/QRSuR+F6hD/NCGX0tqyFP4FJDAIrh4Y/AHgwT9S/gT9ixCCwcmiBP92cNtBpA30/oTUXkqZUfD+w6pjgwTyBP+2411xImoI/XvbhM+wKgD8c0pSKsw9/P3npJjEIrHw/YgC511xIej/C5Yn6N0J5P/p+arx0k3g/AhvotIFOez+ug3mi/o2AP/4QEREREYE/Tp6ofyOUgT8CG+i0gU57P1g5tMh2vn8/PYIH80T9ez/EEBERERFxP3npJjEIrHw/wuWJ+jdCeT+w6pjgwTyBPzvfT42XboI/eekmMQisfD/vH/eaC0mDPxzSlIqzD38//Knx0k1icD/ZzvdT46V7P4GFpCkVZ38/UAXIveZCgj/ZzvdT46V7P3npJjEIrHw/f+Lsw2fYdT9mzvdT46V7P2QrQO41F3I/o2CeqH8jdD9mzvdT46V7P1AFyL3mQoI/YF0Bcq+5gD+dZ9gVIPd6P+OV/GLJL3Y/YF0Bcq+5cD/EEBERERFxP323Za2OCX4/ObTIdr6fej9MN4lBYOWAP1724TPsCoA/YgC511xIej++F0t+seR3P+OV/GLJL3Y/WmQ730+Ndz+Hfmq8dJN4PwIb6LSBTns/GQRWDi2yfT8c0pSKsw9/P8Llifo3Qnk/wuWJ+jdCeT/+TKk4+/B5P+OV/GLJL3Y/IstaHRM8eD+BhaQpFWd/P+FqdUzwYH4/IstaHRM8eD8iy1odEzx4P3/i7MNn2HU/ZCtA7jUXcj8k9uEz7ApwP+djO99PjXc/o2CeqH8jdD9MN4lBYOWAP323Za2OCX4/g7ArQO41dz956SYxCKx8PwRGb8taHXM/+n5qvHSTaD8iy1odEzx4P4d+arx0k3g//kypOPvweT+hNReSplR8P4d+arx0k3g/oTUXkqZUfD9BUEZvy1p9P323Za2OCX4/nMQgsHJogT+dZ9gVIPd6P6E1F5KmVHw/gYWkKRVnfz/b+X5qvHSDPxzSlIqzD38/eekmMQisfD8bL90kBoF1P2bO91PjpXs//kypOPvweT+BhaQpFWd/P9nO91PjpXs/52M730+Ndz++F0t+seR3P+djO99PjXc/YgC511xIej956SYxCKx8P3npJjEIrHw/ENBpA502gD9e9uEz7AqAPzm0yHa+n3o/vhdLfrHkdz8IFK5H4Xp0PzvfT42XbnI/nMQgsHJocT8730+Nl25yP/yp8dJNYoA//hARERERgT9BUEZvy1p9P5qZmZmZmXk/nWfYFSD3ej/ZzvdT46V7P14yelvW6ng/IstaHRM8eD+dZ9gVIPd6P+xRuB6F64E//Knx0k1igD8c0pSKsw9/P3sUrkfhenQ/Q3vNhaQpdT8Tfmq8dJNoP0FQRm/LWm0/2c73U+Olez9BUEZvy1p9P74XS36x5Hc/H/0boYzedj97FK5H4Xp0P7gehetRuG4/eekmMQisbD/EEBERERFxP1724TPsCoA/wuWJ+jdCeT8IFK5H4Xp0PzvfT42XbnI/P62OCR7Mcz8f/RuhjN52P3/i7MNn2HU/2/l+arx0cz99t2Wtjgl+P2bO91PjpXs/52M730+Ndz/fx73mQtJ0P6CSXyz5xXI/38e95kLSdD+gkl8s+cVyPwB4ME/Uv3E/fbdlrY4Jfj9mzvdT46V7P0dJDAIrh3Y/CBSuR+F6dD8AeDBP1L9xP1pkO99PjXc/h35qvHSTeD8iy1odEzx4PyaZmZmZmXk/TDeJQWDlgD89ggfzRP17PyLLWh0TPHg/WmQ730+Ndz/jlfxiyS92P0N7zYWkKXU/IstaHRM8eD/Gs8h2vp96P7DqmODBPIE/3WCeqH8jlD9aggfzRP2bP1AFyL3mQoI/JpmZmZmZeT+hNReSplR8P51n2BUg93o/mpmZmZmZeT/+TKk4+/B5Px/9G6GM3nY/YgC511xIej/N6pjgwTyRP/zlifo3Qok//Knx0k1igD8730+Nl25yPzm0yHa+n3o/nWfYFSD3ej+6SQwCK4d2P+OV/GLJL3Y/o2CeqH8jdD9BUEZvy1ptP3/i7MNn2HU/xBARERERcT+dZ9gVIPd6P/5MqTj78Hk/2/l+arx0cz8f/RuhjN52PyjEILByaHE/C+Lsw2fYZT/fx73mQtJ0P/yp8dJNYnA/45X8Yskvdj+hNReSplR8P51n2BUg93o/QVBGb8tafT9eMnpb1up4P3npJjEIrGw/WmQ730+Ndz8AeDBP1L9xP7DqmODBPIE/HNKUirMPfz/nYzvfT413P9v5fmq8dHM/gYWkKRVnbz9BUEZvy1ptPwm3Za2OCW4/nMQgsHJocT/hanVM8GB+P3/i7MNn2HU/aPl+arx0cz9HSQwCK4d2P0N7zYWkKXU/Gy/dJAaBdT+Hfmq8dJN4P4d+arx0k3g/Zs73U+Olez8ZBFYOLbJ9P51n2BUg93o/fbdlrY4Jfj9eMnpb1up4PwgUrkfhenQ/IstaHRM8eD/b+X5qvHRzP1pkO99PjXc/Gy/dJAaBdT+gkl8s+cVyP74XS36x5Hc/CbdlrY4Jbj/KgQfzRP1rP6CSXyz5xXI/ZCtA7jUXcj+amZmZmZl5P2IAuddcSHo/YF0Bcq+5cD/6fmq8dJN4P3/i7MNn2HU/QVBGb8tabT8iy1odEzx4Pz+tjgkezIM/+n5qvHSTqD+D/GLJL5acPz1Gb8taHYM/HZb8Yskvhj/+TKk4+/B5PwB4ME/Uv3E/vhdLfrHkdz8AeDBP1L9xP3npJjEIrHw/PYIH80T9ez++F0t+seR3P92cNtBpA30/uB6F61G4fj+dZ9gVIPd6P5zEILByaIE/3Zw20GkDfT956SYxCKx8P6E1F5KmVHw/g7ArQO41dz/+TKk4+/B5PwgUrkfhenQ/vhdLfrHkdz+Hfmq8dJN4P91gnqh/I4Q/kxgEVg4tkj+cxCCwcmiBPwIb6LSBTns/45X8Yskvdj9kK0DuNRdyP2BdAXKvuXA/O99PjZducj8iy1odEzx4P6E1F5KmVHw/YF0Bcq+5gD89ggfzRP17P66DeaL+jYA/YgC511xIej+Hfmq8dJN4P0FQRm/LWn0/h35qvHSTeD+Hfmq8dJN4P0FQRm/LWn0/JpmZmZmZeT9eMnpb1up4Px/9G6GM3nY/exSuR+F6dD97FK5H4Xp0P3/i7MNn2HU/R0kMAiuHdj++F0t+seR3P0FQRm/LWn0/sOqY4ME8gT8bL90kBoF1P7pJDAIrh3Y/nWfYFSD3ej8IFK5H4Xp0Px/9G6GM3nY/AhvotIFOez9e9uEz7AqAP2BdAXKvuYA/BEZvy1odcz+DsCtA7jV3P/yp8dJNYnA/nMQgsHJocT8bL90kBoF1P74XS36x5Hc/xBARERERcT8f/RuhjN52P6Ngnqh/I3Q//Knx0k1icD8/rY4JHsxzP4OwK0DuNXc/roN5ov6NgD85tMh2vp+KP+xRuB6F64E/HNKUirMPfz+hNReSplR8Pz2CB/NE/Xs/JpmZmZmZeT+dZ9gVIPd6P6E1F5KmVHw/XvbhM+wKgD/+TKk4+/B5P9/HveZC0nQ/py7dJAaBdT8oxCCwcmhxP6CSXyz5xXI/IstaHRM8eD9MN4lBYOWAP6CSXyz5xYI/3Zw20GkDfT9kK0DuNRdyP6Ngnqh/I3Q/AHgwT9S/cT97FK5H4Xp0P8Llifo3Qnk/ENBpA502gD/Gs8h2vp96P3sUrkfhenQ/o2CeqH8jdD+m11xImlKRP3sUrkfheoQ/1Za1OiZ4kD/dnDbQaQN9PxkEVg4tsn0//Knx0k1igD/jlfxiyS92P+OV/GLJL3Y/f+Lsw2fYdT9BUEZvy1ptP9v5fmq8dHM/O99PjZducj85tMh2vp96P5qZmZmZmXk/2/l+arx0gz/8qfHSTWKAPwB4ME/Uv3E/O99PjZducj8f/RuhjN52P/yp8dJNYnA/WmQ730+Ndz/hanVM8GB+P1g5tMh2vn8/38e95kLSdD+6SQwCK4d2P3npJjEIrGw/eekmMQisbD9gXQFyr7lwP1724TPsCoA/XvbhM+wKgD85tMh2vp96P14yelvW6ng/g7ArQO41dz956SYxCKxsPyT24TPsCnA/YF0Bcq+5cD+BhaQpFWd/PxzSlIqzD38/nWfYFSD3ej85tMh2vp96Pz+tjgkezHM/eekmMQisbD9BUEZvy1ptP8QQEREREXE/uB6F61G4fj+4HoXrUbh+P323Za2OCX4/3Zw20GkDfT8730+Nl25yP7gehetRuG4/YF0Bcq+5cD+4HoXrUbhuPzm0yHa+n3o/H/0boYzedj8iy1odEzx4P3sUrkfhenQ/WmQ730+Ndz+jYJ6ofyN0P5zEILByaHE/2c73U+Olez89ggfzRP17P+FqdUzwYH4/uB6F61G4fj+Hfmq8dJN4P9/HveZC0nQ/38e95kLSdD+DsCtA7jV3P4d+arx0k3g/wuWJ+jdCeT/nYzvfT413PwIb6LSBTns/3Zw20GkDfT/fx73mQtJ0P91gnqh/I4Q/oJJfLPnFgj/Gs8h2vp96P92cNtBpA30/AhvotIFOez+dZ9gVIPd6P/5MqTj78Hk/O99PjZducj8c0pSKsw9/P8azyHa+n3o/XvbhM+wKgD9qvHSTGASGP07aQKcNdIo/YF0Bcq+5gD+DsCtA7jV3PwRGb8taHXM/uB6F61G4bj/EEBERERFxP+OV/GLJL3Y/YF0Bcq+5gD9gXQFyr7mAP/5MqTj78Hk/ObTIdr6fej9kK0DuNRdyPwB4ME/Uv3E//Knx0k1icD8/rY4JHsxzP1g5tMh2vn8/wuWJ+jdCeT8bL90kBoF1P1pkO99PjXc/ObTIdr6fej8f/RuhjN52P2QrQO41F3I/g7ArQO41dz+ug3mi/o2APwB4ME/Uv4E/BukmMQisfD+TNtBpA52WP9prLiRNqcA/DCD3mgtJkz85tMh2vp+KP92cNtBpA40/jzomeDBPhD8bL90kBoGFP9/HveZC0oQ/7x/3mgtJgz+LbOf7qfGCP323Za2OCX4/roN5ov6NgD8ZBFYOLbJ9P1724TPsCoA/HZb8Yskvhj+LbOf7qfGSP9s1F5KmVIw/y6FFtvP9hD/fx73mQtKEP6E1F5KmVHw/sOqY4ME8gT+BhaQpFWd/P/4QEREREYE/uB6F61G4fj89ggfzRP17Pxsv3SQGgXU/f+Lsw2fYdT/+TKk4+/B5PxkEVg4tsn0/ENBpA502gD+gkl8s+cWCP66DeaL+jYA/QRSuR+F6hD+MCR7ME/XDPwwCK4cW2a4/2xdLfrHklz/rjVBGb8uKP8B+arx0k4g/z2+EMnpbhj9qvHSTGASGP+Eu3SQGgYU/fXvNhaQphT/fx73mQtKEP0EUrkfheoQ/gUkMAiuHhj/R1qNwPQqHP89vhDJ6W4Y/K4cW2c73gz8730+Nl26CPzvfT42XboI/AHgwT9S/gT8AeDBP1L+BP+FqdUzwYH4/8YYW2c73gz8730+Nl26CP1g5tMh2vn8/WDm0yHa+fz9QBci95kKCP/yp8dJNYoA/XvbhM+wKgD8c0pSKsw9/P+8f95oLSYM/2/l+arx0gz/RItv5fmq8P5q3Za2OCZ4/yXa+nxovjT/hLt0kBoGFP0EUrkfheoQ/2/l+arx0gz8vVVVVVVWFPw6l4uzDZ4g/arx0kxgEhj/+EBERERGBPwB4ME/Uv4E/O99PjZdugj/tuNdcSJqCPzvfT42XboI/g96WtTommD+cxCCwcmiRPy3QaQOdNpA/rFjyiyW/iD9Onqh/I5SBP/5MqTj78Hk/XvbhM+wKgD/LoUW28/2EP2ig0wY6bbA/Tp6ofyOUkT/D9Shcj8KVP3npJjEIrIw/PUZvy1odgz+w6pjgwTyBP+8f95oLSYM/7bjXXEiagj+POiZ4ME+EP+Eu3SQGgYU/P62OCR7Mgz/sUbgeheuBP92cNtBpA30/XjJ6W9bqeD+w6pjgwTyBPz+tjgkezIM/Le41F5KmhD/sUbgeheuBPz+tjgkezIM/y6FFtvP9hD8bL90kBoGFPxsv3SQGgYU/i2zn+6nxgj/8qfHSTWKAPzvfT42XboI/38e95kLShD89Rm/LWh2DPy9VVVVVVYU/PUZvy1odgz/b+X5qvHSDP4ts5/up8YI/HNKUirMPfz+w6pjgwTyBP91gnqh/I4Q/K4cW2c73gz97FK5H4XqEP/4QEREREYE/nMQgsHJogT9QBci95kKCP/4QEREREYE/bCOU0duyhj8QDAIrhxaJPx/9G6GM3oY/HZb8Yskvhj9Onqh/I5SBPy3uNReSpoQ/jdMGOm2ggz9Onqh/I5SBPz+tjgkezIM/arx0kxgEhj8K16NwPQqHP+xRuB6F64E/nitA7jUXgj+N0wY6baCDPzvfT42XboI/7bjXXEiagj+POiZ4ME+EPy3uNReSpoQ/oJJfLPnFgj9QBci95kKCP54rQO41F4I/nMQgsHJogT9e9uEz7AqAP1724TPsCoA/ofl+arx0gz89Rm/LWh2DP1724TPsCoA/eekmMQisfD8f/RuhjN52PwRGb8taHXM//kypOPvweT/dnDbQaQN9P5GhRbbz/YQ/AHgwT9S/gT8AeDBP1L+BPzvfT42XboI/AHgwT9S/cT/b+X5qvHRzP3npJjEIrHw/XvbhM+wKgD/vH/eaC0mDP0w3iUFg5YA/TDeJQWDlgD+hNReSplR8P7gehetRuH4/oTUXkqZUfD+hNReSplR8P43TBjptoIM/AHgwT9S/gT/b+X5qvHSDP3sUrkfheoQ/UAXIveZCgj9/4uzDZ9h1Px/9G6GM3nY/oJJfLPnFgj9Onqh/I5SBP317zYWkKYU/PUZvy1odgz+eK0DuNReCP6CSXyz5xYI/TDeJQWDlkD/vW4/C9SiMPy3uNReSpoQ/gUkMAiuHhj8bL90kBoGFPxsv3SQGgYU/7x/3mgtJgz956SYxCKx8Pz2CB/NE/Xs/gYWkKRVnfz9MN4lBYOWAP06eqH8jlIE/f+Lsw2fYhT8xvHSTGASGPz1Gb8taHYM/i2zn+6nxgj+TGARWDi2SPxzSlIqzD48/z2+EMnpbhj8vVVVVVVWFP4FJDAIrh4Y/Mbx0kxgEhj8rhxbZzveDPwB4ME/Uv4E/eekmMQisfD/8qfHSTWKAP7pJDAIrh5Y/bCOU0duylj8tKs4+fIaNPxTq3whl9JY/Br0ta3VMkD8f/RuhjN6GP7pJDAIrh4Y/zQhl9LashT8730+Nl26CP+8f95oLSYM/38e95kLShD8dlvxiyS+GPz+tjgkezIM/AHgwT9S/gT9gXQFyr7mAP4GFpCkVZ38/roN5ov6NgD/sUbgeheuBP317zYWkKYU/7bjXXEiagj9QBci95kKCPz1Gb8taHYM/UAXIveZCgj8730+Nl26CPwB4ME/Uv4E/Tp6ofyOUgT8xvHSTGASGP80IZfS2rIU/O99PjZdugj+yUbgeheuBP91gnqh/I4Q/nitA7jUXgj9sI5TR27KGP0EUrkfheoQ/HZb8Yskvhj9aZDvfT42HPy3uNReSpoQ/38e95kLShD/+EBERERGBPwB4ME/Uv4E/QRSuR+F6hD/Pb4QyeluGP89vhDJ6W4Y//OWJ+jdCiT8t7jUXkqaUP9nO91PjpYs/DFyPwvUonD81mlJx9uGTPwwg95oLSaM/MzMzMzMzuz9OcfbhM+yyPyP5xZJfLJk/i6h/I5TRiz/Pb4QyeluGP+xRuB6F64E/WDm0yHa+fz+cxCCwcmiBP/yp8dJNYoA/Le41F5KmhD+w6pjgwTyBPz2CB/NE/Xs/JpmZmZmZeT+gkl8s+cVyP+OV/GLJL3Y//kypOPvweT8CG+i0gU57P1724TPsCoA/pQNWDi2yfT/+TKk4+/B5P+FqdUzwYH4/P62OCR7Mcz/jlfxiyS92P2QrQO41F3I//Knx0k1igD+eK0DuNReCPwIb6LSBTns/H/0boYzedj8iy1odEzx4PwgUrkfhenQ/4Wp1TPBgfj8c0pSKsw9/P4GFpCkVZ38/PUZvy1odgz9gXQFyr7mAP51n2BUg93o/uB6F61G4nj8MPsOuALmHP1724TPsCoA/O99PjZdugj9gXQFyr7mAP0w3iUFg5YA/sOqY4ME8gT/hanVM8GB+P/p+arx0k3g/SxdLfrHkZz/fx73mQtJ0Px/9G6GM3nY/oTUXkqZUfD+w6pjgwTyBP1724TPsCoA/nWfYFSD3ej8/rY4JHsxzP0FQRm/LWm0/f+Lsw2fYdT8G6SYxCKx8P66DeaL+jYA/PUZvy1odgz+eK0DuNReCP2IAuddcSHo//kypOPvweT/fx73mQtJ0P74XS36x5Hc/H/0boYzedj/dnDbQaQN9PxDQaQOdNoA/nMQgsHJogT8dlvxiyS+GP06eqH8jlIE/vLArQO41hz8730+Nl26CP5zEILByaJE/pKzVMcGDmT/oQtKUirPfP5I0peLsw8s/f3mi/o1Qpj8rpeLsw2eYP/yp8dJNYpA/Yi4kTak4mz8GvS1rdUyQP5qZmZmZmYk/GRM8mCfqrz9mZmZmZmamP6rx0k1iEJg/62+EMnpblj8tKs4+fIaNPx/9G6GM3oY/XMtaHRM8iD8f/RuhjN6GP51n2BUg94o/2c73U+Oliz8f/RuhjN6GP9v5fmq8dIM/3Zw20GkDfT89ggfzRP17PyuHFtnO94M/jzomeDBPhD/fCGX0tqzRP6ApFWcfPrs/y6FFtvP9pD/j4TPsCpCbP2wjlNHbspY/g8DKoUW2kz+kcD0K16OQP81E/RuhjI4/zUT9G6GMjj+LqH8jlNGLP0byiyW/WJI/eekmMQisjD8xvHSTGASGP3/i7MNn2IU/Mbx0kxgEhj/R1qNwPQqHPx/9G6GM3oY/vhdLfrHkhz+dZ9gVIPeKP9TqmODBPLE/lX8jlNHbkj/bNReSplSMP40Pn2FXgIw/ObTIdr6fij9O2kCnDXSKP2wjlNHbsoY/HZb8Yskvhj/NCGX0tqyFP+xRuB6F64E/PUZvy1odgz/sUbgeheuBPzvfT42XboI/jzomeDBPhD/fx73mQtKEPz+tjgkezIM/Le41F5KmhD+BhaQpFWd/P/5MqTj78Hk/YgC511xIej+dZ9gVIPd6P7JRuB6F64E/7bjXXEiagj8Q0GkDnTaAP4ts5/up8YI/XvbhM+wKgD/+TKk4+/B5P+OV/GLJL3Y/h35qvHSTeD8Q0GkDnTaAP3sUrkfheoQ/O99PjZdugj+ug3mi/o2AP5qZmZmZmXk/AhvotIFOez85tMh2vp96P/5MqTj78Hk/i2zn+6nxgj/LoUW28/2EPxzSlIqzD38/h35qvHSTeD/+TKk4+/B5P4OwK0DuNXc/PYIH80T9ez9MN4lBYOWAP6CSXyz5xYI/P62OCR7Mgz/+EBERERGBP6E1F5KmVHw/P62OCR7Mcz/dYJ6ofyOEP4Un6t8IZZQ/4+Ez7AqQmz9EqTj78BmWPzsb6LSBTos/bCOU0duyhj+RoUW28/2EP4ts5/up8YI/0dajcD0Khz8dlvxiyS+GP89vhDJ6W4Y/fXvNhaQphT9qvHSTGASGP92cNtBpA40/qvHSTWIQiD9gXQFyr7mAP43TBjptoIM/2/l+arx0gz+eK0DuNReCP9/HveZC0oQ/oJJfLPnFgj99e82FpCmFP3/i7MNn2IU/dbHkF0t+kT8IyuhtWaujP88GOm2g06Y/e1BGb8tajT/t9G+EMnqLP0xzIWlKxYk/bCOU0duyhj+8sCtA7jWHP4FJDAIrh4Y/z2+EMnpbhj9qvHSTGASGPylcj8L1KIw/ObTIdr6fij9KDAIrhxaJPx/9G6GM3oY/THMhaUrFiT85tMh2vp+KP/p+arx0k4g/L1VVVVVVhT9aZDvfT42HP74XS36x5Ic/nWfYFSD3ij9sI5TR27KGP80IZfS2rIU/Tp6ofyOUgT+eK0DuNReCP0EUrkfheoQ/WmQ730+Nhz/Afmq8dJOIP6xY8oslv4g/bCOU0duyhj8rhxbZzveDPz1Gb8taHYM/i2zn+6nxgj+N0wY6baCDP317zYWkKYU/gUkMAiuHhj+8sCtA7jWHP9HWo3A9Coc/OxvotIFOiz89ggfzRP2LP4FJDAIrh4Y/gUkMAiuHhj+BSQwCK4eGP4FJDAIrh4Y/ukkMAiuHhj8vVVVVVVWFP2q8dJMYBIY/P62OCR7Mgz/fx73mQtKEP0EUrkfheoQ/QRSuR+F6hD/fx73mQtKEP3/i7MNn2IU/O99PjZdugj+ug3mi/o2AP/4QEREREYE/O99PjZdugj9QBci95kKCP0w3iUFg5YA/i2zn+6nxgj9e9uEz7AqAP5zEILByaIE/roN5ov6NgD+4HoXrUbh+P/4QEREREYE/nWfYFSD3ej/+TKk4+/B5P1AFyL3mQoI/O99PjZdugj8CG+i0gU57PxzSlIqzD38/45X8Yskvdj99t2Wtjgl+P6E1F5KmVHw//Knx0k1igD+h+X5qvHSDP0EUrkfheoQ/QRSuR+F6hD+LbOf7qfGCP0w3iUFg5YA//hARERERgT8730+Nl26CPz+tjgkezIM/QRSuR+F6hD9BFK5H4XqEP6CSXyz5xYI/i2zn+6nxgj+gkl8s+cWCP7vmQtKUirM/2/l+arx0kz/85Yn6N0KJP+Eu3SQGgYU/8YYW2c73gz+eK0DuNReCPx2W/GLJL4Y/38e95kLShD9YObTIdr5/P51n2BUg93o/7FG4HoXrgT9w8dJNYhCIPyuHFtnO94M/slG4HoXrgT/dnDbQaQN9P7pJDAIrh3Y/sOqY4ME8gT+LbOf7qfGCPzvfT42XboI/nitA7jUXgj+4HoXrUbh+P2BdAXKvuYA/sOqY4ME8gT/tuNdcSJqCPxDQaQOdNoA/oTUXkqZUfD956SYxCKx8P1724TPsCoA/7bjXXEiagj/+EBERERGBP+8f95oLSYM/UAXIveZCgj9Onqh/I5SBP1g5tMh2vn8/ObTIdr6fej89ggfzRP17P92cNtBpA30/gYWkKRVnfz+4HoXrUbh+P9/HveZC0nQ/nWfYFSD3ej85tMh2vp96P/yp8dJNYoA/Tp6ofyOUgT9BFK5H4XqEP1724TPsCoA/vhdLfrHkdz/8qfHSTWJwPwgUrkfhenQ/h35qvHSTeD+Hfmq8dJN4P7gehetRuH4/YF0Bcq+5gD+Hfmq8dJN4P6CSXyz5xXI/yoEH80T9az8/rY4JHsxzPyLLWh0TPHg/JpmZmZmZeT8Q0GkDnTaAP0w3iUFg5YA/XvbhM+wKgD/C5Yn6N0J5P9v5fmq8dHM/Gy/dJAaBdT+hNReSplR8P4GFpCkVZ38/TDeJQWDlgD+yUbgeheuBP/4QEREREYE/WDm0yHa+fz8iy1odEzx4P4OwK0DuNXc/PYIH80T9ez8f/RuhjN52PxzSlIqzD38/nitA7jUXgj/+TKk4+/B5P1pkO99PjXc/38e95kLSdD8f/RuhjN52P51n2BUg93o/nWfYFSD3ej8Q0GkDnTaAP0w3iUFg5YA/TDeJQWDlgD8ZBFYOLbJ9PzvfT42XbnI/g7ArQO41dz8f/RuhjN52PyaZmZmZmXk/roN5ov6NgD8Q0GkDnTaAP0w3iUFg5YA/2c73U+Olez+jYJ6ofyN0P4OwK0DuNXc/52M730+Ndz8iy1odEzx4P1724TPsCoA/nitA7jUXgj9mzvdT46V7P74XS36x5Hc/ZCtA7jUXcj8CG+i0gU57PyaZmZmZmXk/AhvotIFOez+w6pjgwTyBP9v5fmq8dIM/fbdlrY4Jfj/EEBERERFxP0FQRm/LWm0/38e95kLSdD+Hfmq8dJN4P14yelvW6ng/gYWkKRVnfz89Rm/LWh2DP4d+arx0k3g/uB6F61G4bj956SYxCKxsPyLLWh0TPHg/xrPIdr6fej956SYxCKx8P4ts5/up8YI/GQRWDi2yfT8ZBFYOLbJ9P51n2BUg93o/Q3vNhaQpdT/8qfHSTWKAP+FqdUzwYH4/gYWkKRVnfz9gXQFyr7mAP/yp8dJNYoA/roN5ov6NgD+LbOf7qfGCP486JngwT4Q/gYWkKRVnfz9Onqh/I5SBPz1Gb8taHYM/2/l+arx0gz9e9uEz7AqAP6CSXyz5xYI/L1VVVVVVhT+eK0DuNReCPy3uNReSpoQ/YF0Bcq+5gD8rhxbZzveDP2BdAXKvuYA/ChM8mCfqjz8MPsOuALmHP91gnqh/I4Q/QVBGb8tafT+N0wY6baCDP323Za2OCX4/jzomeDBPhD+gkl8s+cWCPy3uNReSpoQ/oJJfLPnFgj/8qfHSTWKAPxzSlIqzD38/gYWkKRVnfz/8qfHSTWKAP+2411xImoI/7bjXXEiagj8rhxbZzveDP+2411xImoI/AHgwT9S/gT+N0wY6baCDPz+tjgkezIM/rFjyiyW/iD8f/RuhjN6GP4FJDAIrh4Y/PWQ730+Nlz/DE/VvhDKaP2iR7Xw/NY4/boqzD59hhz8xvHSTGASGP9/HveZC0oQ/zQhl9LashT/Pb4QyeluGP80IZfS2rIU/O99PjZdugj/b+X5qvHSDP89vhDJ6W4Y/Gy/dJAaBhT+POiZ4ME+EP/4QEREREYE/i2zn+6nxgj8rhxbZzveDP9v5fmq8dIM/K4cW2c73gz8bL90kBoGFP7DqmODBPIE/jzomeDBPhD+N0wY6baCDPy3uNReSpoQ/nitA7jUXgj+N0wY6baCDP4ts5/up8YI/XvbhM+wKgD/dYJ6ofyOEP4ts5/up8YI/ENBpA502gD/fx73mQtKEP1724TPsCoA/TDeJQWDlgD8mmZmZmZl5P7gehetRuH4/Q3vNhaQpdT+dZ9gVIPd6Pz2CB/NE/Xs/HNKUirMPfz+w6pjgwTyBP/4QEREREYE/nitA7jUXgj8730+Nl25yP+2411xImoI/h35qvHSTeD9iALnXXEh6P1724TPsCoA/AHgwT9S/gT+w6pjgwTyBP3npJjEIrHw/AHgwT9S/cT/+TKk4+/B5P3npJjEIrHw/eekmMQisfD+4HoXrUbh+P43TBjptoIM/TDeJQWDlgD85tMh2vp96P2QrQO41F3I//kypOPvweT9BUEZvy1p9PzvfT42XboI/P62OCR7Mgz8bL90kBoGFPyuHFtnO94M/7x/3mgtJgz/dYJ6ofyOEPzvfT42XboI/Le41F5KmhD/sUbgeheuBP9v5fmq8dIM/K4cW2c73oz9Ei2zn+6mRPxsv3SQGgYU/2/l+arx0gz9ixCCwcmiBP4GFpCkVZ38/Tp6ofyOUgT9Onqh/I5SBP/yp8dJNYoA/7FG4HoXrgT9gXQFyr7mAPxkEVg4tsn0/sOqY4ME8gT+hNReSplR8P4GFpCkVZ38//hARERERgT9YObTIdr5/PxDQaQOdNoA/roN5ov6NgD8CG+i0gU57P92cNtBpA30/4Wp1TPBgfj9eMnpb1up4PxzSlIqzD38//hARERERgT+BhaQpFWd/P1g5tMh2vn8/Gy/dJAaBdT8iy1odEzx4PxzSlIqzD38/roN5ov6NgD9QBci95kKCP6CSXyz5xYI/7FG4HoXrgT/8qfHSTWKAP06eqH8jlIE/y6FFtvP9hD/NCGX0tqyFP486JngwT4Q/jdMGOm2ggz9sI5TR27KGP486JngwT4Q/AHgwT9S/gT9QBci95kKCP+8f95oLSYM/i2zn+6nxgj/tuNdcSJqCP486JngwT4Q/O99PjZdugj8dlvxiyS+GP4FJDAIrh4Y/38e95kLShD97FK5H4XqEP80IZfS2rIU/f+Lsw2fYhT85tMh2vp+aP5MYBFYOLaI/qg+fYVeAnD+6haQpFWePP3Dx0k1iEIg/0dajcD0Khz9/4uzDZ9iFP4ts5/up8YI/7bjXXEiagj+N0wY6baCDPyuHFtnO94M/Gy/dJAaBhT+POiZ4ME+EPz+tjgkezIM/3WCeqH8jhD8Q0GkDnTaAP1g5tMh2vn8/38e95kLShD/vH/eaC0mDP4ts5/up8YI/AHgwT9S/gT8AeDBP1L+BP1AFyL3mQoI/eekmMQisfD+hNReSplR8P4ts5/up8YI/HNKUirMPfz85tMh2vp96Pzm0yHa+n3o/YF0Bcq+5gD+lA1YOLbJ9P7DqmODBPIE/PUZvy1odgz8rhxbZzveDP486JngwT4Q/O99PjZdugj/b+X5qvHSDP54rQO41F4I/O99PjZdugj+gkl8s+cWCPz+tjgkezIM/fXvNhaQphT9BFK5H4XqEP+8f95oLSYM/QRSuR+F6hD8t7jUXkqaEP5GhRbbz/YQ/QRSuR+F6hD9BFK5H4XqEP317zYWkKYU/7bjXXEiagj+cxCCwcmiBP7gehetRuH4/Le41F5KmhD/dYJ6ofyOEPy9VVVVVVYU/Mbx0kxgEhj+q8dJNYhCIPxsv3SQGgYU/YF0Bcq+5gD+eK0DuNReCP06eqH8jlIE/Tp6ofyOUgT+POiZ4ME+EP0EUrkfheoQ/CtejcD0Khz9/4uzDZ9iFP26Ksw+fYYc/H/0boYzehj+8sCtA7jWHP7ywK0DuNYc/kaFFtvP9hD+POiZ4ME+EP3/i7MNn2IU/H/0boYzehj+8sCtA7jWHPww+w64AuYc/DD7DrgC5hz8K16NwPQqHP6CSXyz5xYI/PUZvy1odgz97FK5H4XqEPy9VVVVVVYU/K4cW2c73gz8Q0GkDnTaAPyuHFtnO94M/y6FFtvP9hD+LbOf7qfGCP317zYWkKYU/z2+EMnpbhj/dYJ6ofyOEPxDQaQOdNoA/GQRWDi2yfT+w6pjgwTyBPz+tjgkezIM/fXvNhaQphT9BFK5H4XqEP9/HveZC0oQ/0dajcD0Khz9sI5TR27KGPzG8dJMYBIY/Le41F5KmhD9BFK5H4XqEP0EUrkfheoQ/38e95kLShD9aZDvfT42HP+30b4Qyeos/fXvNhaQphT8t7jUXkqaEP3sUrkfheoQ/O99PjZdugj+LbOf7qfGCP+xRuB6F64E/nitA7jUXgj/fx73mQtKEPy3uNReSpoQ/jzomeDBPhD/NCGX0tqyFPz1Gb8taHYM/y6FFtvP9hD8xvHSTGASGP80IZfS2rIU/HZb8Yskvhj+LbOf7qfGCPwB4ME/Uv4E//hARERERgT8c0pSKsw9/P06eqH8jlIE/fbdlrY4Jfj89Rm/LWh2DP4ts5/up8YI/YgC511xIej/vH/eaC0mDP5zEILByaIE/L1VVVVVVhT+POiZ4ME+EP6CSXyz5xYI/CtejcD0Khz/NCGX0tqyFPz1Gb8taHYM/UAXIveZCgj8/rY4JHsyDPz1Gb8taHYM/P62OCR7Mgz/tuNdcSJqCP0EUrkfheoQ/i2zn+6nxgj8Q0GkDnTaAP92cNtBpA30/uB6F61G4fj/8qfHSTWKAP/yp8dJNYoA//Knx0k1igD9BFK5H4XqEP0EUrkfheoQ/2/l+arx0gz9QBci95kKCPzvfT42XboI/ofl+arx0gz9BFK5H4XqEP0EUrkfheoQ/CtejcD0Khz/fx73mQtKEP7gehetRuH4/QVBGb8tafT+cxCCwcmiBP54rQO41F4I/UAXIveZCgj/fx73mQtKEPz1Gb8taHYM/0dajcD0Khz8vVVVVVVWFP486JngwT4Q//hARERERgT+BhaQpFWd/PxDQaQOdNoA/O99PjZdugj97FK5H4XqEP3sUrkfheoQ/P62OCR7Mgz8730+Nl26CP3sUrkfheoQ/Le41F5KmhD8730+Nl26CP06eqH8jlIE/K4cW2c73gz/dYJ6ofyOEPz+tjgkezIM/gUkMAiuHhj8bL90kBoGFP3sUrkfheoQ/YF0Bcq+5gD/vH/eaC0mDP6uthQ6OG4Q/exSuR+F6hD+w6pjgwTyBPzvfT42XboI/P62OCR7Mgz+BhaQpFWd/P/4QEREREYE/3Zw20GkDfT+POiZ4ME+EPzvfT42XboI/ObTIdr6fej9iALnXXEh6P7gehetRuH4/roN5ov6NgD/8qfHSTWKAP/yp8dJNYoA/P62OCR7Mgz+N0wY6baCDP4OwK0DuNXc/wuWJ+jdCeT99t2Wtjgl+P/yp8dJNYoA/TDeJQWDlgD+eK0DuNReCPy9VVVVVVYU/3WCeqH8jhD/Gs8h2vp96PxDQaQOdNoA/O99PjZdugj/b+X5qvHSDP0FQRm/LWn0/Zs73U+Olez89Rm/LWh2DP91gnqh/I4Q/oTUXkqZUfD8G6SYxCKx8PwB4ME/Uv4E/i2zn+6nxgj8t7jUXkqaEP/4QEREREYE/nMQgsHJogT/b+X5qvHSDP2BdAXKvuYA/YsQgsHJogT+gkl8s+cWCPxzSlIqzD38/UAXIveZCgj+cxCCwcmiBP+2411xImoI/f+Lsw2fYhT/LoUW28/2EP2q8dJMYBIY/38e95kLShD+N0wY6baCDPy3uNReSpoQ/O99PjZdugj/tuNdcSJqCP486JngwT4Q/K4cW2c73gz8ZBFYOLbJ9P0w3iUFg5YA//Knx0k1igD8c0pSKsw9/Pz1Gb8taHYM/fXvNhaQphT+N0wY6baCDP43TBjptoIM/QRSuR+F6hD9BFK5H4XqEP+Eu3SQGgYU/QRSuR+F6hD8dlvxiyS+GP4FJDAIrh4Y/gUkMAiuHhj+N0wY6baCDP/yp8dJNYoA/GQRWDi2yfT8Q0GkDnTaAP/yp8dJNYoA//Knx0k1igD+6SQwCK4eGP43TBjptoIM/nitA7jUXgj+BSQwCK4eGPx2W/GLJL4Y/L1VVVVVVhT89Rm/LWh2DP4FJDAIrh4Y/jdMGOm2ggz9sI5TR27KGPxsv3SQGgYU/WmQ730+Nhz8dlvxiyS+GP7DqmODBPIE/nMQgsHJogT/8qfHSTWKAPzvfT42XboI/2/l+arx0gz/+EBERERGBP9/HveZC0oQ/Gy/dJAaBhT8t7jUXkqaEP9HWo3A9Coc/ObTIdr6fij9aZDvfT42HP66/EcrobYk/WmQ730+Nhz/2ZPS2rNWRPxsv3SQGgZU/i4qzD59hlz8deDBP1L+hP+Olm8QgsJI/IGQ730+Nhz89Rm/LWh2DP+djO99PjXc/sOqY4ME8gT8/rY4JHsyDP/GGFtnO94M/QRSuR+F6hD/6nDbQaQOdPze28/3UeKk/g/xiyS+WnD9oke18PzWOPww+w64AuYc/DqXi7MNniD8gZDvfT42HP4FJDAIrh4Y/gUkMAiuHhj+BSQwCK4eGP2q8dJMYBIY/Mbx0kxgEhj+8sCtA7jWHP/5MqTj78Ik/nAC511xIij9uirMPn2GHPx2W/GLJL4Y/jdMGOm2ggz8/rY4JHsyDP+8f95oLSYM/jdMGOm2ggz/vH/eaC0mDP5zEILByaIE//Knx0k1igD9MN4lBYOWAP91gnqh/I4Q/oJJfLPnFgj9QBci95kKCPz+tjgkezIM/gUkMAiuHhj8dlvxiyS+GPz+tjgkezIM/PYIH80T9iz9oke18PzWOP9HWo3A9Coc/y6FFtvP9hD+BSQwCK4eGP3sUrkfheoQ/UAXIveZCgj8c0pSKsw9/P0w3iUFg5YA/PUZvy1odgz/R1qNwPQqHPx2W/GLJL4Y/ukkMAiuHhj8MPsOuALmHP0gOLbKd76c/YPS2rNUxoT89ggfzRP2LP74XS36x5Ic/exSuR+F6hD+eK0DuNReCPy9VVVVVVYU/fXvNhaQphT/xhhbZzveDP0EUrkfheoQ/7x/3mgtJgz/dYJ6ofyOEP54rQO41F4I/eekmMQisfD+4HoXrUbh+P66DeaL+jYA/UAXIveZCgj+POiZ4ME+EP0EUrkfheoQ/38e95kLShD99e82FpCmFP9v5fmq8dIM/QRSuR+F6hD/NCGX0tqyFP4Un6t8IZZQ/7fRvhDJ6iz/ZzvdT46WLP7AmMQisHIo/K4cW2c73gz/LoUW28/2EPww+w64AuYc/WmQ730+Nhz81mlJx9uGTP9CUirMPn7E/4XoUrkfhqj+6AuRecyHBP57+jVBGb6s/LdBpA502oD8UvS1rdUywPxzME/VvhLo/K5b8Yskvpj9Qq2OCB/OkP+RC0pSKs9c/ZnVM8GCeuD+J+jdCGb3FP4XrUbgehdU/jAkezBP1xz+QbhKDwMq5P5qZmZmZmbE/jaZUnH34rD+P76fGSzepP1C6SQwCK6c/O/0boYzepj83iUFg5dCiPxkiIiIiIqI/XJ6ofyOUoT9zaJHtfD+1P3MhaUrF2eU/o/6NUEZv2z/PPnyGXQHCPyUGgZVDi7w/9+Ez7AqQ0T8Pn2FXgNzXP2t1TPBgnuI/L90kBoGV4T+tjgkezBPVP6G3Za2OCcY/PHyGXQFyvz+ZGi/dJAa5P3LpJjEIrLQ/EfVvhDJ6sz+xD59hV4DAP29oke18P8k/uNdcSJpSzT/B9Shcj8LVPzVeukkMAtU/nah/I5TRwz/Xo3A9Cte7P3n4DLsC5L4/7TUXkqZUwD89CtejcD26P1e6SQwCK7c/znjpJjEItD+wgU4b6LSxP0MMAiuHFrE/rbmQNKXitD9oSsXZh8/EP7as1THBg8k/+2LJL5b8wj/kQtKUirO/P+9gnqh/I8A/11xImlJxwj+SmZmZmZm5PxqwcmiR7bQ/Vh0TPJgnsj8ZEzyYJ+qvPwwCK4cW2a4/3ULSlIqzrz/dM+wKkHu1P8NLN4lBYME/C4PAyqFFtj/+415zIWmyP6RwPQrXo7A/yYWkKRVnrz8AAAAAAACwP1LW6pjgwaw/umfYFSD3qj+amZmZmZmpPw48mCfq36g/Gz7DrgC5pz+sSQwCK4emP6SOCR7ME6U/i3vNhaQppT/A91PjpZukP835fmq8dKM/+GLJL5b8oj9gA5020GmjP0xGb8taHaM/i2zn+6nxoj/rYJ6ofyO8PxqhjN6Wtbo/tWWtjgketD91kxgEVg6tPwaQe82FpKk/oEfhehSupz+09Shcj8KlP4clv1jyi6U//Me95kLSpD/FTWIQWDmkP2ADnTbQaaM/i2zn+6nxoj+PwvUoXI+iP3Fb1uqY4KE/9P3UeOkmoT+Bsw+fYVegP7qFpCkVZ58/wjHBg3minj8ZBFYOLbKdPxkEVg4tsp0/G2t1TPBgnj/ByqFFtvOdP0oqzj58hp0/qg+fYVeAnD/ZzvdT46WbP+F6FK5H4Zo/ke18PzVemj/LvxHK6G2ZP32ZmZmZmZk/fZmZmZmZmT99mZmZmZmZP9XSTWIQWJk/pKzVMcGDmT+FRbbz/dSYP/zlifo3Qpk/y78RyuhtmT/Tay4kTamYP9NrLiRNqZg/3X5qvHSTmD/Tay4kTamYP/aCwMqhRZY/9BuhjN6WlT/+Lt0kBoGVPyVCGb0ta5U/9BuhjN6WlT/2N0IZvS2rP/yp8dJNYqA/WoIH80T9mz9aggfzRP2bP+uNUEZvy5o//OWJ+jdCmT81uB6F61GYPz1kO99PjZc/M1H/Riijlz/2gsDKoUWWP/aCwMqhRZY/4ZjgwTxRnz/bF0t+seSnP99PjZduEqM/62CeqH8jpD95B/NE/RuhP+GY4ME8UZ8/wcqhRbbznT+iY4IH80SdP3npJjEIrJw/eekmMQisnD/hmODBPFGfP2JM8GCeqJ8/EFg5tMh2nj+oxks3iUGgP9nsw2fYFaA/SPBgnqh/oz/l3whl9La0P/7jXnMhabI/ICIiIiIisj+yne+nxkvDP2XYFSD3mrM/rBxaZDvfrz9mhDJ6W9aqPyul4uzDZ6g/d82FpCkVpz9cvHSTGASmPzNCGb0ta6U/2whl9LaspT8rlvxiyS+mP395ov6NUKY/p38jlNHbyj+rjgkezBO9P1hImlJx9rE/QX6x5BdLrj+NplScffisP7YC5F5zIak/J0DuNReSpj+09Shcj8KlP6SOCR7ME6U/EIXrUbgepT/n+6nx0k3GP5MYBFYOLdQ/05SKsw+fwT/MPnyGXQG6P5zEILByaLk/NW2g0wY6tT86YOXQItuxP4relrU6JrA/yXa+nxovrT8COm2g0waqP9NrLiRNqag/rEkMAiuHpj+09Shcj8KlPzeYJ+rfCKU/UJx9+Ay7oj9cnqh/I5ShP7ySXyz5xaI/EHYFyL3moj8QdgXIveaiP65lrY4JHqw/M1H/Riijpz+YffgMuwKkP6wrQO41F6I/SOF6FK5HoT/VlrU6JnigP8DZh8+wK6A/WDm0yHa+nz850pSKsw+fP+lE/RuhjJ4/c6QpFWcfnj9S1uqY4MGcP7K7u7u7u5s/iUFg5dAimz+yu7u7u7ubP7K7u7u7u5s/i6h/I5TRmz8rw64AudecP4GVQ4ts55s/k1ScffgMmz9DxwQP5omaP8MT9W+EMpo/1dJNYhBYmT9kd3d3d3eXPzv9G6GM3pY/K6Xi7MNnmD99mZmZmZmZPwSSplScfZg/hUW28/3UmD+sWPKLJb+YP5Wd76fGS5c/XMtaHRM8mD8dlvxiyS+WP55JDAIrh5Y/sp3vp8ZLlz8U6t8IZfSWP5M20GkDnZY/RKk4+/AZlj/lKocW2c6XPx2W/GLJL5Y/HZb8Yskvlj/jw2fYFSCXP1zLWh0TPJg/7dajcD0Klz/FXEiaUnGWP7ZNYhBYOZQ/BHTaQKcNlD8OhxbZzveTP6SOCR7ME5U/pI4JHswTlT/0G6GM3paVP9NNYhBYOZQ/9P3UeOkmkT+05kLSlIqTP2RZq2OCB5M/O99PjZdukj/sUbgeheuRP2RZq2OCB5M/tOZC0pSKkz89Rm/LWh2TP/T91HjpJpE/1Za1OiZ4kD/8qfHSTWKQP31dAXKvuZA/pHA9CtejkD+8kl8s+cWSPxTME/VvhJI/7FG4HoXrkT/N6pjgwTyRP6bXXEiaUpE/fV0Bcq+5kD+4HoXrUbiOPxzSlIqzD48/ptdcSJpSkT8t0GkDnTaQP8vd3d3d3Y0/GQRWDi2yjT97UEZvy1qNP7qFpCkVZ48/n873U+Oliz/t9G+EMnqLP2xfLPnFko8/VOOlm8QgkD/dnDbQaQONP1TjpZvEIJA/VOOlm8QgkD99XQFyr7mQP323Za2OCY4/uB6F61G4jj9YObTIdr6PP54rQO41F5I/5Qy7AuRekz+LbOf7qfGSP8VcSJpScZY/Trx0kxgElj91z7ArQO6VP6Ss1THBg5k/VYDcay4ktT8TIPeaC0m7P7EPn2FXgLQ/OwwCK4cWqT/wxZJfLPmlP2Roke18P6U/CNnO91PjpT+PwvUoXI+iP1hImlJx9qE/001iEFg5tD+fm8QgsHK4PyAiIiIiIrI/5wqQe82FtD8IuwLkXnOxP0SaUnH24bM/fLHkF0t+sT+Isw+fYVewPxSuR+F6FK4/rmWtjgkerD/+1HjpJjGwP7695kLSlKo/wwQP5on6pz8Eg8DKoUWmP4PPsCtA7qU/K5b8Yskvpj/0G6GM3palP5h9+Ay7AqQ/vJJfLPnFoj+011xImlKhPzEmeDBP1J8/wNmHz7AroD9iTPBgnqifP1TjpZvEIKA/aJHtfD81nj9zpCkVZx+eP1zpJjEIrJw/g/xiyS+WnD/ByqFFtvOdP/Q5baDTBpo/ObTIdr6fmj+LqH8jlNGbP5NUnH34DJs/fV0Bcq+5oD/wtqzVMcGjPyl6W9bqmKA/EFg5tMh2nj9YObTIdr6fP1TjpZvEIKA/qMZLN4lBoD+Bsw+fYVegPxS9LWt1TKA/qMZLN4lBoD8pelvW6pigPzEmeDBP1J8/WDm0yHa+nz9vEoPAyqGlP/qNUEZvy6o/AklTKs4+rD+amZmZmZm5P7YC5F5zIbE/1XjpJjEIrD8j+cWSXyypP88GOm2g06Y/47SBThvopD8QhetRuB6lP6w6JngwT6Q/+GLJL5b8oj+TGARWDi2iP/y411xImqI/PzVeukkMoj91seQXS36hP1CNl24Sg6A/f2q8dJMYtD+HQ4ts5/upP4t7zYWkKaU/MzMzMzMzoz9QnH34DLuiP2ivuZA0paI/wOhtWatjoj/FPnyGXQGiP5huEoPAyqE/XJ6ofyOUoT9MN4lBYOWgPxS9LWt1TKA/bfbhM+wKoD9iTPBgnqifP2Dl0CLb+Z4/c6QpFWcfnj+qD59hV4CcP8HKoUW2850/IxeSplScnT8hsHJoke2cP4GVQ4ts55s/Q8cED+aJmj9q2kCnDXSaPzm0yHa+n5o/wxP1b4Qymj9DxwQP5omaPzW4HoXrUZg/DD7DrgC5lz/bF0t+seSXP0UQWDm0yJY/kzbQaQOdlj8G2/l+aryUP14UrkfhepQ/JUIZvS1rlT99e82FpCmVP317zYWkKZU/XK2OCR7Mkz/b+X5qvHSTP/Zk9Las1ZE/Tp6ofyOUkT+cxCCwcmiRPzvfT42XbpI/z1G4HoXrkT91seQXS36RP1TjpZvEIJA/LSrOPnyGjT99t2WtjgmOPyvDrgC514w/eekmMQisjD9YObTIdr6PP9WWtTomeJA//hARERERkT+cALnXXEiKP40Pn2FXgIw/boqzD59hhz/85Yn6N0KJP3tQRm/LWo0//kypOPvwiT8MPsOuALmHPww+w64AuYc/LSrOPnyGjT8KEzyYJ+qPP06eqH8jlJE/VOOlm8QgkD+6haQpFWePP7gehetRuI4//kypOPvwiT9sI5TR27KGPylcj8L1KIw/i6h/I5TRiz956SYxCKyMPz2CB/NE/Ys//kypOPvwiT+cALnXXEiKP14yelvW6og/H/0boYzehj8MPsOuALmHP5GhRbbz/YQ/zQhl9LashT9aZDvfT42HP74XS36x5Ic/DqXi7MNniD++F0t+seSHP07aQKcNdIo/641QRm/Lij9eMnpb1uqIP74XS36x5Ic/vhdLfrHkhz9aZDvfT42HP14yelvW6og/XMtaHRM8iD8MPsOuALmHP9HWo3A9Coc/oJJfLPnFgj9QBci95kKCP+2411xImoI/bCOU0duyhj+sWPKLJb+IP8B+arx0k4g/mpmZmZmZiT/fx73mQtKEPz1Gb8taHYM/roN5ov6NgD/sUbgeheuBP+Eu3SQGgYU/Mbx0kxgEhj9qvHSTGASGPy9VVVVVVYU/O99PjZdugj/sUbgeheuBP1AFyL3mQoI/O99PjZdugj+BSQwCK4eGP3/i7MNn2IU/Le41F5KmhD/sUbgeheuBP06eqH8jlIE/i2zn+6nxgj+h+X5qvHSDP4ts5/up8YI/wH5qvHSTiD9cy1odEzyIP9/HveZC0oQ/4S7dJAaBhT9BFK5H4XqEP0EUrkfheoQ/QRSuR+F6hD8t7jUXkqaEP9s1F5KmVIw/jQ+fYVeAjD9eMnpb1uqIP+30b4Qyeos/EqGM3pa1mj9kWatjggejP32ZmZmZmZk/DocW2c73kz+m9Shcj8KVP66hRbbz/ZQ/NZpScfbhkz9mwMqhRbaTP/Zk9Las1ZE/7bjXXEiakj8730+Nl26SPzvfT42XbpI/g8DKoUW2kz89Rm/LWh2TP43TBjptoJM/bfbhM+wKoD/y8Bl2BcidP/qcNtBpA50/cWq8dJMYpD8j2/l+arykP/LwGXYFyJ0/umfYFSD3mj9zhl0Bcq+ZPzv9G6GM3pY/7dajcD0Klz/+Lt0kBoGVP9W0gU4b6JQ/Btv5fmq8lD85tMh2vp+aP7K7u7u7u5s/y78RyuhtmT/LvxHK6G2ZP6xY8oslv5g/ke18PzVemj/j4TPsCpCbPxtNqTj78Jk/nAC511xImj9q2kCnDXSaP+F6FK5H4Zo/k1ScffgMmz9g5dAi2/m2PzVtoNMGOq0/nOLsw2fYpT9or7mQNKWiPwAP5on6N6I/uC1rdUzwoD/pRP0boYyeP4uofyOU0Zs/THMhaUrFmT+LirMPn2GXP55JDAIrh5Y/xVxImlJxlj/lKocW2c6XP+3Wo3A9Cpc/lZ3vp8ZLlz/dfmq8dJOYP4VFtvP91Jg/2xdLfrHklz+TNtBpA52WP55JDAIrh5Y/nOLsw2fYlT/t1qNwPQqXP5M20GkDnZY/xVxImlJxlj/VtIFOG+iUP4Un6t8IZZQ/MzMzMzMzkz8WMzMzMzOTPxsv3SQGgZU/XhSuR+F6lD8G2/l+aryUP/QboYzelpU/JUIZvS1rlT/NCGX0tqyVP8P1KFyPwpU/RKk4+/AZlj/VtIFOG+iUP1Zoke18P5U/Le41F5KmlD/8x73mQtKUP5V/I5TR25I/K4cW2c73kz8730+Nl26SP43TBjptoJM/46WbxCCwkj+VfyOU0duSP06eqH8jlJE/bAXIveZCkj8UzBP1b4SSP5zEILByaJE/JSRNqTj7kD8GvS1rdUyQPzvfT42XbpI/HXgwT9S/kT/N6pjgwTyRP31dAXKvuZA/Br0ta3VMkD/Jdr6fGi+NP3tQRm/LWo0/GQRWDi2yjT/FPnyGXQGSP66DeaL+jZA/1Za1OiZ4kD/t9G+EMnqLP0xzIWlKxYk/i6h/I5TRiz99t2WtjgmOP2xfLPnFko8/pHA9CtejkD9U46WbxCCQP66DeaL+jZA/roN5ov6NkD9sXyz5xZKPPyUkTak4+5A/uB6F61G4jj+4HoXrUbiOPwa9LWt1TJA/CKwcWmQ7jz8KE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eZCgj9BUEZvy1p9P6E1F5KmVHw/QVBGb8tafT+DsCtA7jV3PyLLWh0TPHg/3Zw20GkDfT9ixCCwcmiBPxDQaQOdNoA/4Wp1TPBgfj+hNReSplR8PyLLWh0TPHg/JpmZmZmZeT8c0pSKsw9/P/yp8dJNYoA/Tp6ofyOUgT8730+Nl26CP6E1F5KmVHw/PYIH80T9ez8730+Nl26CPwB4ME/Uv4E/PUZvy1odgz+gkl8s+cWCPz1Gb8taHYM/i2zn+6nxgj9Onqh/I5SBP4GFpCkVZ38/3Zw20GkDfT+cxCCwcmiBP43TBjptoIM/jzomeDBPhD+LbOf7qfGCP9HWo3A9Coc/DD7DrgC5hz/LoUW28/2EP9nO91PjpXs/vhdLfrHkdz+hNReSplR8P2bO91PjpXs/7bjXXEiagj9MN4lBYOWAP+xRuB6F64E/uB6F61G4fj+6SQwCK4d2P2BdAXKvuYA/JpmZmZmZeT/LoUW28/2EP6CSXyz5xYI/sOqY4ME8gT/hanVM8GB+PxDQaQOdNoA/JPbhM+wKcD9/4uzDZ9h1Pz2CB/NE/Xs/eekmMQisfD+gkl8s+cWCP+xRuB6F64E/oTUXkqZUfD/ZzvdT46V7P/p+arx0k3g/BukmMQisfD+BhaQpFWd/P0FQRm/LWn0/oJJfLPnFgj/+EBERERGBP4GFpCkVZ38/rr8RyuhtiT99e82FpCmFP6CSXyz5xYI/7bjXXEiagj8CK4cW2c6XPxTME/VvhKI/HZb8Yskvhj+eK0DuNReCPyaZmZmZmXk//Knx0k1igD/+TKk4+/B5P0N7zYWkKXU/o2CeqH8jdD/dnDbQaQN9P9nO91PjpXs/BEZvy1odcz/8qfHSTWJwP4pMqTj78Gk/xBARERERcT8bL90kBoF1PxzSlIqzD38/4Wp1TPBgfj+4HoXrUbh+P4OwK0DuNXc/P62OCR7Mcz9/4uzDZ9h1P4d+arx0k3g/g7ArQO41dz+Hfmq8dJN4P51n2BUg93o/2c73U+Olez89ggfzRP17P14yelvW6ng/oJJfLPnFcj8iy1odEzx4PzvfT42XbnI//kypOPvweT/dnDbQaQN9P9nO91PjpXs/WmQ730+Ndz8/rY4JHsxzPz+tjgkezHM/Gy/dJAaBdT9De82FpCl1PxkEVg4tsn0/XvbhM+wKgD/ZzvdT46V7PxkEVg4tsn0/vhdLfrHkdz8iy1odEzx4P3/i7MNn2HU/ZCtA7jUXcj9De82FpCl1P2BdAXKvuYA/uB6F61G4fj/jlfxiyS92PzvfT42XbnI/ObTIdr6faj8k9uEz7ApwPz+tjgkezHM/38e95kLSdD+BhaQpFWd/P6E1F5KmVHw/R0kMAiuHdj8ERm/LWh1zPwvi7MNn2GU/CbdlrY4Jbj/EEBERERFxP2j5fmq8dHM/AhvotIFOez/nYzvfT413P/yp8dJNYnA/JPbhM+wKcD/EEBERERFhPwIb6LSBTms//Knx0k1icD8AeDBP1L9xP5qZmZmZmXk/Zs73U+Olez/jlfxiyS92PyT24TPsCnA/jXcwT9S/YT8k9uEz7ApwPwRGb8taHXM/JpmZmZmZeT8CG+i0gU57P92cNtBpA30/H/0boYzedj8730+Nl25yPwB4ME/Uv3E/ZCtA7jUXcj+cxCCwcmhxP9nO91PjpXs/ObTIdr6fej9MN4lBYOWAP1724TPsCoA/wuWJ+jdCeT+DsCtA7jV3PwRGb8taHXM/P62OCR7Mcz8ERm/LWh1zP74XS36x5Hc/P62OCR7Mcz9De82FpCl1P6Ngnqh/I3Q/g7ArQO41dz/6fmq8dJN4P4lBYOXQIps/fbdlrY4Jjj9gXQFyr7mAP2BdAXKvuYA/2c73U+Olez8f/RuhjN52P5zEILByaHE/P62OCR7Mcz97FK5H4Xp0P0dJDAIrh3Y/ObTIdr6fej9BUEZvy1p9P3npJjEIrHw/g7ArQO41dz/C5Yn6N0J5P3npJjEIrHw/nMQgsHJocT9kK0DuNRdyP+OV/GLJL3Y/wuWJ+jdCeT/b+X5qvHRzP/yp8dJNYnA/ikypOPvwaT8CG+i0gU5rP/yp8dJNYnA/ZCtA7jUXcj8bL90kBoF1P6E1F5KmVHw/YgC511xIej/b+X5qvHRzP0FQRm/LWm0/JPbhM+wKcD/fx73mQtJ0P74XS36x5Hc/JpmZmZmZeT9/4uzDZ9h1P0dJDAIrh3Y/ukkMAiuHdj8iy1odEzx4P1pkO99PjXc/H/0boYzedj/ZzvdT46V7P6E1F5KmVHw/45X8Yskvdj+BhaQpFWdvP/yp8dJNYnA/YF0Bcq+5cD8730+Nl25yP/yp8dJNYnA/BEZvy1odcz++F0t+seR3P9v5fmq8dHM/vhdLfrHkdz/6fmq8dJN4P0FQRm/LWm0//Knx0k1icD/b+X5qvHRzP+OV/GLJL3Y//kypOPvweT99t2Wtjgl+P9v5fmq8dHM/ZCtA7jUXcj8k9uEz7ApwP4mp8dJNYnA//Knx0k1icD/8qfHSTWJwP7pJDAIrh3Y/YgC511xIej+jYJ6ofyN0P5zEILByaHE/AHgwT9S/cT+BhaQpFWdvPzvfT42XbnI//kypOPvweT9/4uzDZ9h1P8Llifo3Qnk/38e95kLSdD8ERm/LWh1zP3npJjEIrGw/gYWkKRVnbz8AeDBP1L9xP2QrQO41F3I/PYIH80T9ez+hNReSplR8P7pJDAIrh3Y/PYIH80T9ez+Hfmq8dJN4P6E1F5KmVHw/I/nFkl8sqT/8qfHSTWKQP4FJDAIrh4Y/nitA7jUXgj+6SQwCK4eWP/yp8dJNYpA/2/l+arx0gz/sUbgeheuBP/5MqTj78Ik/K4cW2c73gz8Q0GkDnTaAP3npJjEIrHw/TtpApw10ij9MN4lBYOWQPy9VVVVVVYU/y6FFtvP9hD/vH/eaC0mDPxDQaQOdNoA/ENBpA502gD/dnDbQaQN9P92cNtBpA30/2c73U+Olez8CG+i0gU57P6E1F5KmVHw/ObTIdr6fij/b+X5qvHSDP4luEoPAyqE/O99PjZdukj+LbOf7qfGCP7gehetRuH4/XjJ6W9bqeD9kK0DuNRdyP3npJjEIrHw/nWfYFSD3ej956SYxCKx8P/5MqTj78Hk/+n5qvHSTeD+6SQwCK4d2P4OwK0DuNXc/g7ArQO41dz/C5Yn6N0J5P2IAuddcSHo/vhdLfrHkdz+DsCtA7jV3P6cu3SQGgXU/P62OCR7Mcz8CG+i0gU5rP/yp8dJNYnA/ZCtA7jUXcj/8qfHSTWJwP+OV/GLJL3Y/nWfYFSD3ej97FK5H4Xp0PzvfT42XbnI/wuWJ+jdCaT+4HoXrUbhuPyLLWh0TPHg/nWfYFSD3ej/+TKk4+/B5P+djO99PjXc/XjJ6W9bqeD8f/RuhjN52P5qZmZmZmXk/nWfYFSD3ej89ggfzRP17P0dJDAIrh3Y/2c73U+Olez/C5Yn6N0J5P51n2BUg93o/ukkMAiuHdj/C5Yn6N0J5P9nO91PjpXs/Q3vNhaQpdT/+TKk4+/B5P3npJjEIrHw//hARERERgT/8qfHSTWKAP4lfLPnFkp8/uoWkKRVnnz8U6t8IZfSWPyuHFtnO95M/wNmHz7ArsD81baDTBjq1P2wFyL3mQqI/aJHtfD81jj8vVVVVVVWFPzvfT42XboI/AHgwT9S/gT+BSQwCK4eGP317zYWkKYU/Mbx0kxgEhj+N0wY6baCDPyeLbOf7qZE/rDomeDBPlD+BSQwCK4eGPwrXo3A9Coc/QRSuR+F6hD+LbOf7qfGCP+2411xImoI/Er9Y8oslnz9q2kCnDXSaPz2CB/NE/Ys/UAXIveZCgj+gkl8s+cWCPz2CB/NE/Xs/eekmMQisfD+4HoXrUbh+P/4QEREREYE/uB6F61G4fj9/4uzDZ9h1P2BdAXKvuXA/38e95kLSdD+nLt0kBoF1P14yelvW6ng/gYWkKRVnfz/b+X5qvHSDP8Kp8dJNYoA/QVBGb8tafT9Onqh/I5SBP7DqmODBPIE//hARERERgT+cxCCwcmiBP92cNtBpA30/JpmZmZmZeT8CG+i0gU57P/5MqTj78Hk/38e95kLSdD8730+Nl25yP2IAuddcSHo/BEZvy1odcz8f/RuhjN52P8Llifo3Qnk//kypOPvweT8bL90kBoF1P4mp8dJNYnA/nMQgsHJocT9/4uzDZ9h1P4GFpCkVZ38/XvbhM+wKgD9BUEZvy1p9P7gehetRuH4/QVBGb8tafT+w6pjgwTyBP7DqmODBPIE/uB6F61G4jj8bL90kBoGFP66DeaL+jYA/2c73U+Olez956SYxCKx8P6E1F5KmVHw/vhdLfrHkdz85tMh2vp96P6E1F5KmVHw//Knx0k1igD9Onqh/I5SBP/zlifo3Qok/1XjpJjEIrD+q8dJNYhCoPyUkTak4+5A/rFjyiyW/iD8f/RuhjN6GP0EUrkfheoQ/8YYW2c73gz8/rY4JHsyDP7JRuB6F64E/TDeJQWDlgD/C5Yn6N0J5P7DqmODBPIE/PUZvy1odgz8OWmQ730+tP5wAuddcSJo/YJmZmZmZiT8gZDvfT42HP2wjlNHbsoY/H/0boYzehj/fx73mQtKEP0EUrkfheoQ/QRSuR+F6hD8vN4lBYOWQP/T91HjpJpE/HZb8Yskvhj9Onqh/I5SBP4ts5/up8YI/ENBpA502gD+w6pjgwTyBPz+tjgkezIM/DqXi7MNniD+uvxHK6G2JP9/HveZC0oQ/3WCeqH8jhD9BjZduEoOgP8u/EcrobZk/e1BGb8tajT9O2kCnDXSKP66/EcrobYk//kypOPvwiT9eMnpb1uqIP4FJDAIrh4Y/WDm0yHa+jz89CtejcD26P3e+nxov3bw/AB7ME/VvpD/j4TPsCpCbP0UQWDm0yJY/g8DKoUW2kz/N6pjgwTyRP1TjpZvEIJA/XvbhM+wKkD87G+i0gU6LPxtrdUzwYI4/7fRvhDJ6iz/pJjEIrByKP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP7ywK0DuNYc/wH5qvHSTiD9cy1odEzyIP89vhDJ6W4Y/2/l+arx0gz/b+X5qvHSDP54rQO41F4I/O99PjZdugj+POiZ4ME+EP8uhRbbz/YQ/i2zn+6nxgj/+EBERERGBP6E1F5KmVHw/XvbhM+wKgD8730+Nl26CP/yp8dJNYoA/Tp6ofyOUgT99e82FpCmFPwB4ME/Uv4E/TDeJQWDlgD+hNReSplR8P+FqdUzwYH4/uB6F61G4fj9YObTIdr5/PxzSlIqzD38/exSuR+F6hD+LbOf7qfGCPxDQaQOdNoA/4Wp1TPBgfj+ug3mi/o2AP06eqH8jlIE/sOqY4ME8gT/vH/eaC0mDPyuHFtnO94M/2/l+arx0gz9QBci95kKCP1AFyL3mQoI/2/l+arx0gz8v7AqQe82lPzNR/0Yoo5c/nAC511xIij+kcD0K16OQP+GY4ME8UZ8/y78RyuhtmT9Onqh/I5SRP4lBYOXQIos/IGQ730+Nhz+BSQwCK4eGP4FJDAIrh4Y/H/0boYzehj99e82FpCmFP486JngwT4Q/uB6F61G4fj9e9uEz7AqAP/yp8dJNYoA//Knx0k1igD8AeDBP1L+BP9v5fmq8dIM/nMQgsHJogT8CG+i0gU57P7DqmODBPIE/7x/3mgtJgz8730+Nl26CP+8f95oLSYM/zQhl9LashT8gZDvfT42HP31dAXKvuZA/9P3UeOkmkT/LoUW28/2kPxS9LWt1TKA/dc+wK0DulT+qD59hV4CcP4GVQ4ts55s/7bjXXEiakj9WSsXZh8+QP40Pn2FXgIw/DqXi7MNniD/85Yn6N0KJP4uofyOU0Ys/G2t1TPBgjj87G+i0gU6LPylcj8L1KIw//kypOPvwiT9uirMPn2GHP8B+arx0k4g//OWJ+jdCiT+sWPKLJb+IP5wAuddcSIo/ObTIdr6fij/FPnyGXQGSPy0qzj58ho0/gUkMAiuHhj9uirMPn2GHP4FJDAIrh4Y/ObTIdr6fmj9U46WbxCCQP8vd3d3d3Y0/YPS2rNUxoT8GvS1rdUyQP92cNtBpA40/umfYFSD3qj/rb4QyeluWP+xRuB6F65E/fV0Bcq+5kD9WSsXZh8+QP8u/Ecrobak/FL0ta3VMsD+8g3mi/o2gP1zLWh0TPJg/VmiR7Xw/lT+2TWIQWDmUP2bAyqFFtpM/5Qy7AuRekz+FJ+rfCGWUP2ZmZmZmZqY/K8OuALnXnD8G2/l+aryUP2RZq2OCB5M/xT58hl0Bkj9e9uEz7AqQPwoTPJgn6o8/uB6F61G4jj8c0pSKsw+PP40Pn2FXgIw/THMhaUrFiT9aZDvfT42HP8B+arx0k4g/mpmZmZmZiT9w8dJNYhCIP5qZmZmZmYk/DD7DrgC5hz+8sCtA7jWHP07aQKcNdIo/2c73U+Oliz85tMh2vp+KP9nO91PjpYs/6SYxCKwcij/Afmq8dJOIP/zlifo3Qok/boqzD59hhz9McyFpSsWJP0xzIWlKxYk/vLArQO41hz8OpeLsw2eIP8B+arx0k4g//OWJ+jdCiT++F0t+seSHPww+w64AuYc/rr8RyuhtiT8OpeLsw2eIPww+w64AuYc/gUkMAiuHhj8OpeLsw2eIP8B+arx0k4g/rFjyiyW/iD+8sCtA7jWHP8B+arx0k4g/rr8RyuhtiT85tMh2vp+KP07aQKcNdIo/ObTIdr6fij89ggfzRP2LP+kmMQisHIo/ObTIdr6fij8lJE2pOPuQP43TBjptoJM/nWfYFSD3ij9uirMPn2GHP80IZfS2rIU/bCOU0duyhj/hLt0kBoGFP3/i7MNn2IU/4S7dJAaBhT89Rm/LWh2DP/GGFtnO94M/kaFFtvP9hD8bL90kBoGFP89vhDJ6W4Y/vLArQO41hz/Pb4QyeluGP4FJDAIrh4Y/gUkMAiuHhj9O2kCnDXSKP7TmQtKUipM/nWfYFSD3ij/85Yn6N0KJP3Dx0k1iEIg/Le41F5KmhD9KDAIrhxaJPx/9G6GM3oY/qvHSTWIQiD/hLt0kBoGFP1AFyL3mQoI/kaFFtvP9hD8vVVVVVVWFPzvfT42XboI/nitA7jUXgj/sUbgeheuBPz1Gb8taHYM/gUkMAiuHhj/NCGX0tqyFP486JngwT4Q/gUkMAiuHhj9/4uzDZ9iFPx/9G6GM3oY/HZb8Yskvhj97FK5H4XqEP43TBjptoIM/gUkMAiuHhj8f/RuhjN6GP+Eu3SQGgYU/HZb8Yskvhj9/4uzDZ9iFP2wjlNHbsoY/L1VVVVVVhT+BSQwCK4eGP4FJDAIrh4Y/boqzD59hhz9uirMPn2GHPx/9G6GM3oY/gUkMAiuHhj9sI5TR27KGP2wjlNHbsoY/RvKLJb9Ykj+N0wY6baCTP3Wx5BdLfpE/k1ScffgMmz/+TKk4+/CJPxsv3SQGgYU/fXvNhaQphT9eMnpb1uqIP/5MqTj78Ik/wH5qvHSTiD8QDAIrhxaJPylcj8L1KIw/nAC511xIij9O2kCnDXSKP+uNUEZvy4o/+n5qvHSTiD/Afmq8dJOIP8B+arx0k4g/XMtaHRM8iD+amZmZmZmJP6xY8oslv4g/SgwCK4cWiT+q8dJNYhCIP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP74XS36x5Ic/nWfYFSD3ij8KEzyYJ+qPP3npJjEIrIw/XMtaHRM8iD8gZDvfT42HPx2W/GLJL4Y/gUkMAiuHhj/Pb4QyeluGP1pkO99PjYc/HZb8Yskvhj/pJjEIrByKP14yelvW6og/vhdLfrHkhz+BSQwCK4eGPxAMAiuHFok/K6Xi7MNnmD+FRbbz/dSYP2iR7Xw/NY4//kypOPvwiT+JQWDl0CKLP8B+arx0k4g/wH5qvHSTiD/Afmq8dJOIP66/EcrobYk/ObTIdr6fij+05kLSlIqTP3tQRm/LWp0/dc+wK0DulT9mwMqhRbaTPzvfT42XbpI/VOOlm8QgkD8rw64AudeMP8l2vp8aL40/71uPwvUojD+JQWDl0CKLP9s1F5KmVIw/3Zw20GkDjT9sXyz5xZKPP2r4DLsC5I4/XvbhM+wKkD8730+Nl26SPy0qzj58ho0/OxvotIFOiz+dZ9gVIPeKP8B+arx0k4g/TtpApw10ij+cALnXXEiKP66/EcrobYk/boqzD59hhz8f/RuhjN6GP7pJDAIrh4Y/3WCeqH8jhD9uirMPn2GHP317zYWkKYU/8YYW2c73gz8f/RuhjN6GP6rx0k1iEIg/z2+EMnpbhj8MPsOuALmHPw6l4uzDZ4g/boqzD59hhz/Afmq8dJOIPyBkO99PjYc/wH5qvHSTiD9eMnpb1uqIPx2W/GLJL4Y/QRSuR+F6hD8vVVVVVVWFP486JngwT4Q/3WCeqH8jhD/vH/eaC0mDP8uhRbbz/YQ/arx0kxgEhj+RoUW28/2EPwrXo3A9Coc/38e95kLShD+N0wY6baCDP0EUrkfheoQ/QRSuR+F6hD99e82FpCmFP3/i7MNn2IU/f+Lsw2fYhT8f/RuhjN6GPyBkO99PjYc/z2+EMnpbhj8xvHSTGASGP9/HveZC0oQ/H/0boYzehj8dlvxiyS+GP4FJDAIrh4Y/jzomeDBPhD+POiZ4ME+EP91gnqh/I4Q/gUkMAiuHhj8MPsOuALmHP0xGb8taHbM/47SBThvotD9jvHSTGAS+P9ejcD0K18M/K4cW2c73sz/FILByaJGtPw48mCfq36g/P1Mqzj58pj83mCfq3wilP6w6JngwT6Q//tR46SYxsD/XXEiaUnHCP8mFpCkVZ7c/TmIQWDm0yD+PwvUoXI/CP5KKsw+fYbc/9Ay7AuResz/YQKcNdNqwP99PjZduErM/yXa+nxovtT/Jdr6fGi+9P2IfPsOuALk/Y62OCR7Msz8sJE2pOPuwP7TIdr6fGq8/JRVnHz7Drj85w64AudesP6a5kDSl4qw/1XjpJjEIrD+aqH8jlNGrPyajt2WtjrE/pqqqqqqqsj+EXQFyr7m4PzMzMzMzM8c/EBERERERxT/JhaQpFWe/P7Ks1THBg7k/aJHtfD81tj+aqH8jlNGzP5ZDi2zn+7E/vIN5ov6NsD8hv1jyiyWvP6aqqqqqqqo/Dkt+seQXqz956SYxCKysP65lrY4JHqw/CvVvhDJ6qz+JQWDl0CKrP2IuJE2pOKs/jZduEoPAqj/pJjEIrByqP4/vp8ZLN6k/vq4AuddcqD9IDi2yne+nP6Sd76fGS6c/I+rfCGX0pj8lFWcfPsOuPw5LfrHkF6s/02suJE2pqD9QukkMAiunPzNCGb0ta6U/+HGvuZA0pT9sFK5H4XqkPxkxCKwcWqQ/9Ay7AuReoz/b+X5qvHSjP6AaL90kBqE/cVvW6pjgoT8/NV66SQyiP0jwYJ6of6M/nNMGOm2goz+LbOf7qfGiP8U+fIZdAaI/cVvW6pjgoT91seQXS36hP/Cnxks3iaE/8KfGSzeJoT/jpZvEILCiPz81XrpJDKI/dbHkF0t+oT9Ei2zn+6mhP3Fb1uqY4KE/8KfGSzeJoT8AD+aJ+jeiP5MYBFYOLaI/fV0Bcq+5oD8730+Nl26iPz81XrpJDKI/GSIiIiIioj91ov6NUEavPzuYJ+rfCMU/n4zelrU6wj8jIiIiIiLGPyPb+X5qvLw/vSCwcmiRtT+R7Xw/NV6yP9prLiRNqbA/gaQpFWcfrj+e/o1QRm+rP8MT9W+EMqo/BpB7zYWkqT/XwTxR/0aoP1LW6pjgwaw/Rrbz/dR4qT+HNKXi7MOnPz9TKs4+fKY/hyW/WPKLpT+Le82FpCmlP7yhRbbz/aQ/EIXrUbgepT/jtIFOG+ikP1hXgNxrLqQ/bzBP1L8Rqj89CtejcD2qP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b78Bl2Bcw/oGFXgNxrzj+cC0lTKs7OP96WtTomeNA/nkW28/3UxD/eehSuR+HOP1mrY4IH89I/EFg5tMh20D/tNReSplTMP1jyiyW/WM4/EjyYJ+rfzD9IKKO3Za3KPxcg95oLSdE/9G+EMnpb0D81F5KmVJzNP4IyelvW6sg/FpKmVJx9yD9N1L8RyujJP5JDi2zn+80/LbKd76fGxz+z5BdLfrHQP1XHBA/mic4/fLHkF0t+zT9pvHSTGATWP7as1THBg80/IGlKxdmHyz/CZ9gVIPfGP3ii/o1QRsM/eekmMQiszD8z7AqQe83JP4fPsCtA7sk/OlH/Riijwz9IN4lBYOXEP5cn6t8IZcA/n4zelrU6yj/NE/VvhDLKP5GmVJx9+Mw/4TPsCpB7zT+DwMqhRbbHP3ii/o1QRss/K4cW2c73xz/8qfHSTWLMP/yp8dJNYsw/0JSKsw+fyT/oQtKUirPPP2suJE2pONE/jN6WtTom0D/ufD81XrrNP9DbslbHBM8/oykVZx8+yz87mCfq3wjJPxPK6G1Zq8c/6wqQe82FzD/Q27JWxwTLPxsv3SQGgck/T/9GKKO3yT9oSsXZh8/IP4n6N0IZvck/kaZUnH34yD9oke18PzXGP6c4+/AZdsU/L5b8Yskvwj+f0wY6baDHP8M8Uf9GKMM/62CeqH8jvD+kcD0K16PEP9ejcD0K18M/HveaC0lTwj8aoYzelrXCPzPsCpB7zck/iUFg5dAiwz81XrpJDALDP8CDeaL+jcg/mpmZmZmZyT8AAAAAAAD4f4/C9Shcj8o/Y2ZmZmZmzj/cay4kTanQP519+Ay7AtA/XnMhaUrFxT/hehSuR+HKP0jhehSuR80/VA4tsp3v2T9I4XoUrkfdPxfZzvdT49s/nDbQaQOd3j+PUEZvy1rdP8gED+aJ+tc/2/l+arx01T/9YskvlvzUP4zelrU6JtY/3whl9Las3T+JiIiIiIjwP04b6LSBzgBAJL9Y8osl8z/AEcrobdnxP/+NUEZvy+U/D+aJ+jdC4T/3DLsC5F7dPyMiIiIiItw/QRm9LWt12D+eqH8jlNHgPxP1b4Qyets/wq4Auddc1j8vCKwcWmTXP/Cnxks3idk/jML1KFyP2D840GkDnTbYPwFyr7mQNNk/Watjggfz2D+l4uzDZ9jXP10Bcq+5kNY/nDbQaQOd1j+/EcrobVnVP8CDeaL+jdI/4TPsCpB70T9wr7mQNKXKP2OCB/NE/dM/1AY6baDT0j/D9Shcj8LNP0hTKs4+fNA/NtBpA5020j8Sg8DKoUXQP75Y8oslv9I/r7mQNKXi1D9Z8oslv1jSP/L91HjpJtM/t2Wtjgke0j+T0duyVsfQP/2NUEZvy84/lLU6Jngwzz8oFWcfPsPOP1g5tMh2vs8/aErF2YfPzD/P91PjpZvIP0TSlIqzD9M/pVScffgMxz8q+cWSXyzBP/1GKKO3ZcE/N4lBYOXQwj9TnH34DLvKP4IyelvW6sQ/USrOPnyGxT+xD59hV4DEPy+W/GLJL8Y/ObTIdr6fxj8MAiuHFtnGP8vobVmrY8Y/BoGVQ4tszz+ZUnH24TPMP4lBYOXQIss/Vh0TPJgnxj94ov6NUEbHP0P9G6GM3sY/SX6x5BdLxj/smODBPFHHP0eaUnH24cc/ftxrLiRNyT84JngwT9TDP/hT46WbxMA/zmkDnTbQwT8QERERERHFP/+411xImsY/9wy7AuRewz/lifo3QhnNPzb78Bl2Bcg/C3TaQKcNyD/TTWIQWDnEP4izD59hV8Q/RgwCK4cWwT/0/dR46SbBP2GCB/NE/cM/pHA9CtejxD9HUyrOPny2PwfIveZC0sA/KM4+fIZdwT90FK5H4Xq8P8uhRbbz/cA/BfNE/RuhwD8gaUrF2YfDPxI8mCfq38g/001iEFg5vD+gGi/dJAbBP7bz/dR46b4/i3vNhaQpvT/3xZJfLPnBP1Eqzj58hsk/jjSl4uzDxz/GBA/mifrHPzTQaQOdNsQ/dekmMQisxD+CB/NE/RvRPzHBg3mi/sU/Qrbz/dR4xT9zd3d3d3e/P5kLSVMqzsY/obdlrY4Jyj+yVscED+bBP0EZvS1rdcg/SgwCK4cWzT/l0CLb+X7SP5JfLPnFktM/mVJx9uEz0D+jKRVnHz7PP02pOPvwGdA/+JoLSVMqzj/D9Shcj8LJPwsezBP1b8Q/tIFOG+i0xT8Sg8DKoUXKPwFyr7mQNNE/e1vW6pjg7T99seQXS37/P+F6FK5H4QNAgU4b6LSB+D8DnTbQaQMCQHE9Ctej8PA/u5A0peLs6D/v7u7u7u7kPzLBg3mi/uI/9ZoLSVMq4j9xr7mQNKXiPxUg95oLyfg/uR6F61G4AEAI16NwPQr5P+F6FK5H4fQ/G+i0gU4b+T9PG+i0gU7vP1zW6pjgweo/oNMGOm2g5z+sHFpkO9/kPyRNqTj78OE/o/6NUEZv4T8HrBxaZDvhP+AIZfS2rOc/wIN5ov4N9z+kcD0K16P2PxwTPJgn6u4/a0rF2YfP6z8BRyijt2XtP3d3d3d3d+Y/KaO3Za2O5D/pJjEIrBzkP8Rn2BUg9+M/UI2XbhKD5D86tMh2vp/iP+zDZ9gVIOA/S/Bgnqh/2z9n2BUg95rXPyz5xZJfLNk/rEfhehSu2T90TPBgnqjZP7Tz/dR46do/eqL+jVBG1z807AqQe83XP3D24TPsCtQ/arx0kxgE0j+8dJMYBFbSP2IQWDm0yNI/C0lTKs4+1D8klNHbslbVPxdLfrHkF9U/hl0Bcq+51D8xCKwcWmTRPy5rdUzwYNA/TxvotIFO0T9hggfzRP3PPzTsCpB7zdE/ME/UvxHK1D9soNMGOm3SPwXIveZC0tI/FGcfPsOu0D+pqqqqqqrOPzltoNMGOs0/t5A0peLszz/0RP0boYzOPz/uNReSptI/8Bl2Bci90D8fzBP1b4TOPypA7jUXksY/RSijt2Wtxj9I4XoUrkfJP5MYBFYOLco/+FPjpZvEyD/vYJ6ofyPAPzHBg3mi/s0/DAIrhxbZzj8Sg8DKoUXKPyuHFtnO98c/IGlKxdmHyz9/arx0kxjMP7dJDAIrh8o//Knx0k1izD9VxwQP5onOPxBYObTIdsY/JL9Y8oslxz/YQKcNdNrEP+nfCGX0tsQ/CUlTKs4+xD+h/o1QRm/HP+ZtWatjgss/GqGM3pa1yj9GtvP91HjNPxMg95oLSc8/30+Nl24Sxz/61HjpJjHEP8Jn2BUg98Y/WmQ730+Nyz9uhDJ6W9bOP+8ZdgXIvc4/g8+wK0DuzT8lFWcfPsO+P/cMuwLkXsM/mpmZmZmZxT8nMQisHFrMP7VlrY4JHsg/w/UoXI/CzT9VxwQP5onOPwrXo3A9Css/6nw/NV66xT/0RP0boYzGPzTQaQOdNsg/BjptoNMGwj/KE/VvhDLKPwOBlUOLbMs/oozelrU6yj+YbhKDwMrNP1WA3GsuJM0/qvHSTWIQzD8MAiuHFtnKP0P9G6GM3so/zSLb+X5qyD+wcmiR7XzHP2yg0wY6bcw/w0s3iUFgxT/mbVmrY4K/P27LWh0TPMQ/k9HbslbHyD/61HjpJjHIP6gcWmQ738c/vHSTGARWvj9iEFg5tMjCPx/ME/VvhMo/BoGVQ4tsxz+cGi/dJAbFPxqhjN6WtcI/GQRWDi2yxT+yrNUxwYPJPwGdNtBpA80/TrgehetRzD8ta3VM8GDGP+8ZdgXIvcY/opvEILByxD+ONKXi7MPHP/T91HjpJsE/pQ102kCnyT8vlvxiyS/KP3sUrkfhesg/n4zelrU6wj/I6G1Zq2PGPwwCK4cW2cI/wSCwcmiRxT8O5on6N0LFP4RdAXKvucQ/K4cW2c73xz81F5KmVJzBP+kmMQisHMY/XnMhaUrFzT+lVJx9+AzDPwcezBP1b8A/2msuJE2pwD/ByqFFtvPBP9YVIPeaC8k/NReSplScxT9g5dAi2/nGP45Di2zn+7k/rbmQNKXiwD/l0CLb+X7CP/nwGXYFyME/dnd3d3d3wz/bslbHBA/KP8gvlvxiycc/q44JHswTxT+rjgkezBPBPywkTak4+8A/WmQ730+Nvz8JSVMqzj7AP5S1OiZ4MMM/7e7u7u7uwj9nA5020GnDPz/uNReSpsQ/+yqHFtnOtz/ZzvdT46W7P9dcSJpSccI/uB6F61G4vj9qdUzwYJ7IPw4tsp3vp9I/lrU6Jngw2z+oxks3iUHYPwnzRP0bodQ/x73mQtKU0D8Sg8DKoUXKP0x+seQXS8I/XI/C9Shcxz+4HoXrUbjGPzKl4uzDZ8g/AFYOLbKdxz/HWh0TPJi/PxS9LWt1TLA/FpKmVJx9xD8bL90kBoHBP70RyuhtWcM/iyW/WPKLxT94W9bqmODBP+iY4ME8UcM/jZduEoPAyj+VUnH24TO8P26EMnpb1ro/xJJfLPnFsj9aHRM8mCfCP7as1THBg8E/L5b8Yskvwj/L6G1Zq2PCP+WJ+jdCGcE/FpKmVJx9wD+HJb9Y8ou9Px/ME/VvhMI/exSuR+F6wD+DwMqhRbbDP/2NUEZvy8I/EyD3mgtJwz8bPsOuALm/P8mFpCkVZ7c/835qvHSTuD/GveZC0pS6P9dcSJpSccI/mQtJUyrOvj8K5on6N0K5Pwy7AuRec8E/ZmZmZmZmvj/hifo3Qhm1P3n4DLsC5LY/SOF6FK5HuT97W9bqmODBP5fgwTxR/74/o+Lsw2fYvT/0/dR46SbBP4lBYOXQIrs/V6tjggfztD9GxdmHz7C7PywkTak4+7A/8UT9G6GMwj+ZC0lTKs6+P5s20GkDncI/Q/0boYzewj8tsp3vp8a7P2cSg8DKobU/DBERERERuT/pJjEIrBy6Pyr5xZJfLME/4hdLfrHkwz8sJE2pOPu4Pwi7AuRec7k/FVpkO99PvT+LbOf7qfG6P/y411xImro/CUlTKs4+vD9pLiRNqTi7P6/kF0t+scA/WwFyr7mQwD/1mgtJUyq+Pz9ERERERLw/JQaBlUOLvD+411xImlLBP9dcSJpSccY/szomeDBPyD9Z1uqY4MHEP/WaC0lTKsY/HBM8mCfqwz8QERERERHBP5lScfbhM8A/mQtJUyrOvj/Zh8+wK0DCP95rLiRNqcA/BfNE/RuhvD+bNtBpA53CPyVcj8L1KMA/2/l+arx0uz8twYN5ov61P1TjpZvEILg/7yhcj8L1uD956SYxCKzAP4n6N0IZvcE/XI/C9Shcvz8daUrF2Ye/P2OtjgkezLM/vSCwcmiRtT+kfyOU0duyP9nO91Pjpas/Q/0boYzevj/RaQOdNtDBP4GkKRVnH74/315zIWlKtT+DsCtA7jV3v7Kd76fGS6c/kfxiyS+WtD85w64Aude0P0P9G6GM3rY/sbmQNKXiwD9uy1odEzzAP8CDeaL+jcA/RIts5/upuT/ZzvdT46WzP3hb1uqY4LE/QmDl0CLbuT/Vh8+wK0C+P+3u7u7u7r4/mzbQaQOdvj+uVscED+a5P5VScfbhM7w/SX6x5BdLtj9LuB6F61GwP6aqqqqqqrI/EQRWDi2ytT//gJVDi2y/P9TqmODBPLk/yiLb+X5qvD8GOm2g0wbKP+f7qfHSTbI/umfYFSD3qj/bCGX0tqylP7Ks1THBg7k/USrOPnyGvT+W76fGSze5PxMREREREbE/lVJx9uEzrD/MPnyGXQGyP6JUnH34DLs/FUt+seQXsz9bAXKvuZDAP0jhehSuR7k/YJ6ofyOUwT8vlvxiyS/CP6G3Za2OCbY/9ZoLSVMqvj9FKKO3Za2+P5fgwTxR/74/wIN5ov6NwD81F5KmVJzBP9mHz7ArQMI/kxgEVg4twj81baDTBjq9P8oi2/l+arw//3GvuZA0vT/KE/VvhDK6Px+U0duyVr8/ToDcay4krT/6jVBGb8uqPzjQaQOdNsw/iUFg5dAisz+9EcrobVmzP0//Riijt7U/eyOU0duytj/Bdr6fGi+9P7SBThvotME/zczMzMzMtD+3kDSl4uyzP0u4HoXrUbg/olScffgMqz+GiIiIiIiwP6JUnH34DLM/NNBpA502uD/Xo3A9CtezP7yDeaL+jbg/7xl2Bci9tj8rhxbZzvezP6oAuddcSLI/AC2yne+npj8Gn2FXgNyrP6AaL90kBrk/anVM8GCewD9U8oslv1i6P6JUnH34DLs/5m1Zq2OCtz86Uf9GKKO3P+rDZ9gVILc/RtS/EcrorT8bPsOuALm3P2GCB/NE/bM/7oslv1jyuz/Xo3A9Cte7P0MMAiuHFrk/cukmMQistD+c0wY6baCzP0jwYJ6of7M/DjyYJ+rfuD/P91PjpZu8P3qGXQFyr7k/TEZvy1odsz/2fmq8dJPAP2LJL5b8YsE/oBov3SQGwT8WkqZUnH3AP17JL5b8Yrk/SPBgnqh/uz8v7AqQe829P7EPn2FXgLQ/kyfq3whltD/hifo3Qhm1Pyr5xZJfLLk/6JjgwTxRtz+6WPKLJb+4P28Sg8DKob0/RsXZh8+wuz9wr7mQNKW6P5H8Yskvlrw/SZpScfbh1T8Bcq+5kDThP02pOPvwGdQ/0r8RyuhtyT9+I5TR27LGP788Uf9GKLs/rwC511xI0D83Qhm9LWvXP+f7qfHSTc4/puLsw2fYzT/CrgC511zIP4cW2c73U8c/LWt1TPBgxj9TnH34DLvGPzgmeDBP1L8/1hUg95oLuT/LsCtA7jW/P9eyVscED74/qWOCB/NEvT+F+jdCGb29P19mZmZmZrY/rbmQNKXiwD9Fb8taHRPAP7ByaJHtfL8/vzxR/0Youz8iTak4+/C5P+tgnqh/I7w/Vg4tsp3vtz+JUEZvy1q9P8uhRbbz/bw/7e7u7u7uvj/7KocW2c63P+GJ+jdCGbU/9Ay7AuResz/7G6GM3pa1PwXzRP0bobw/sHJoke18vz//ca+5kDS9P/C2rNUxwbs/vSCwcmiRtT/ffD81XrqpP4RdAXKvubA/xS+W/GLJrz/kQtKUirO3P/Y3Qhm9Lbs/n4zelrU6tj/2Riijt2WtP2ig0wY6bbA/wiLb+X5qrD+bRbbz/dSwP+XfCGX0trQ/JQaBlUOLvD92ME/UvxG6P83bslbHBLc/ZErF2YfPuD8dWmQ730+tPxTME/VvhJI/G2t1TPBgnj8MIPeaC0mjP5ELSVMqzq4/O+41F5KmpD9oke18PzW+P0upOPvwGbY/RJpScfbhsz/8uNdcSJqiPyHdJAaBlaM/x0s3iUFgpT/aehSuR+GyPyr5xZJfLLk/VYDcay4ktT8MuwLkXnPFP8CDeaL+jcA/olScffgMsz/OaQOdNtCxPz628/3UeLE/ZdgVIPeasz9MRm/LWh27Pw/ZzvdT47U/Y7x0kxgEtj+TGARWDi2yP5MYBFYOLaI/fXvNhaQplT9cnqh/I5ShP6JyaJHtfK8/bxKDwMqhwT+q8dJNYhDAP3QFyL3mQro/iVBGb8tarT+kcD0K16OwP/NE/RuhjOU/NdBpA532F0C/WPKLJX8VQHd3d3d39wFAagOdNtBp9D+N3pa1OqbwPx+F61G4HuE/pw102kCn1T9KN4lBYOXSP/+NUEZvy9A/4TPsCpB70T+Isw+fYVfEPwGdNtBpA8U/iF0Bcq+51D8GgZVDi2zLP/4qhxbZzss/awOdNtBpyz+pqqqqqqrKPzHBg3mi/sk/Gy/dJAaBxT8aoYzelrXCPzPsCpB7zcU/sQ+fYVeAwD+DsCtA7jV3P8w+fIZdAcI/0SLb+X5qwD8WkqZUnH3EP1NVVVVVVcE/JurfCGX0wj8hsHJoke28P3qGXQFyr7k/GHYFyL3msj+kcD0K16O4PyPq3whl9LY/h8+wK0DuwT8hv1jyiyW/P2q8dJMYBL4/PqcNdNpAvz/LoUW28/20P6AaL90kBrE/V6tjggfztD9iEFg5tMi2P8oT9W+EMro/X0iaUnH2uT+HFtnO91O7P6oAuddcSLo/E9nO91PjzT800GkDnTa4P1pzIWlKxbE/O99PjZdusj91ov6NUEa/P/1VDi2ynbc/olScffgMuz8QZx8+w664P5H8Yskvlrw/DZ9hV4Dcsz92ME/UvxGyP7eQNKXi7LM/CLsC5F5zuT9dLPnFkl+0P85pA5020LE/tNdcSJpSuT8F80T9G6G0P7pY8oslv7A/it6WtTomsD/4U+Olm8SwP6JFtvP91Lg/CuaJ+jdCuT/HWh0TPJi3P/sboYzelrU/9Ay7AuResz8gIiIiIiKyP9CUirMPn7E/+n5qvHSTsD8v7AqQe821P6UcWmQ737c/17JWxwQPtj/wtqzVMcGzP99PjZduErM/PRm9LWt1rD++rgC511yoP05x9uEz7LI//4CVQ4tstz8HLbKd76e2P/NvhDJ6W7Y/4OzDZ9gVuD8xCKwcWmSzP7ByaJHtfK8/4ZjgwTxRrz/JhaQpFWevP1e6SQwCK7c/nu+nxks3sT+F+jdCGb2tP2xZq2OCB7M/c3d3d3d3pz9I4XoUrkexP/ZGKKO3Za0/MSZ4ME/Urz+JUEZvy1q1P2Xn+6nx0rU/szomeDBPvD/HSzeJQWDBPyJNqTj78Lk/boQyelvWsj/nCpB7zYW0PzB6W9bqmLA/FVpkO99PtT/vGXYFyL22P+GJ+jdCGbU/I/nFkl8sqT850pSKsw+vP8oT9W+EMrI/WDm0yHa+tz+Isw+fYVfAP9uyVscED8I/OW2g0wY6wT8030+Nl266P9v5fmq8dLs/6SYxCKwc7j/MWh0TPJj4P4slv1jyi90/+JoLSVMqzj+MCR7ME/XHP3tb1uqY4M0/UI2XbhKDwD+Isw+fYVfAP9OUirMPn8E/A8i95kLSxD807AqQe83hPwisHFpkO+I/Q0RERERE1j+95kLSlIrVP/+411xImtA/xgQP5on6xz/IL5b8YsnHPzdCGb0ta8E/XI/C9Shcvz9OcfbhM+y6Py1rdUzwYMI/+sWSXyz5wT/RMcGDeaK+P9eyVscED7Y/8KfGSzeJuT8AAAAAAACwP/LSTWIQWLE/AAAAAAAAuD9N1L8Ryui9P7TIdr6fGr8/8Las1THBuz9oke18PzW2P8DobVmrY6I/Lk/UvxHKuD9RKs4+fIa9P0xGb8taHbM/boQyelvWuj+gGi/dJAbBP3yx5BdLfsk/c9pApw100D9A0pSKsw/HP6UNdNpAp70/7f3UeOkmuT9sWatjgge7P6ud76fGS78/vp8aL90kvj9JfrHkF0u+PyBpSsXZh8c/HveaC0lTwj9gnqh/I5TBPyjOPnyGXbk/mG4Sg8DKuT9raJHtfD+9PxEEVg4tsrU/mQtJUyrOvj+kfyOU0du6PylrdUzwYLY/3ULSlIqzrz800GkDnTawP+Olm8QgsLI/c3d3d3d3vz84JngwT9S3P6G3Za2OCb4/uB6F61G4vj8xF5KmVJy1P37cay4kTbE/jZduEoPAsj+9EcrobVmzP5+M3pa1OrY/S6k4+/AZtj/hehSuR+GqP7EPn2FXgLQ/MHpb1uqYsD/y8Bl2BcitPzpg5dAi27E/IDEIrBxatD/g7MNn2BW4P0diEFg5tLg/KVyPwvUorD+BhaQpFWdvP4pMqTj78Gm/1XjpJjEIrD9SuB6F61GwP5VhV4Dca64/Ll66SQwCsz8PyuhtWauzP9v5fmq8dLM/LcGDeaL+rT/bCGX0tqylP7YRyuhtWas/LCRNqTj7sD9Ei2zn+6mxP9LO91PjpbM/IlyPwvUotD9OcfbhM+yqPwPIveZC0rQ/FK5H4XoUwj8nMQisHFrAP7ySXyz5xaI/cVvW6pjgoT/l0CLb+X6yP6jVMcGDebI/pI4JHswTpT8zb8taHROcP3OkKRVnH54/vRHK6G1Zsz9KDAIrhxapP91RuB6F66E/kfxiyS+WtD/hifo3Qhm1P+rSTWIQWLE/BFYOLbKdrz8R9W+EMnqzP0ob6LSBTqs/9CqHFtnOpz/81qNwPQqnP7Ks1THBg7E/5/up8dJNuj8JWDm0yHa2P7efGi/dJLY/SOF6FK5HsT9KKs4+fIatPzVeukkMAqs/x1odEzyYpz8o3SQGgZWzP+xRuB6F67k/iVBGb8tarT/y0k1iEFixP7g8Uf9GKKM/sJ8aL90kpj/4U+Olm8SgPyl6W9bqmKA/gjJ6W9bqsD8K16NwPQq3P9V46SYxCLQ/boQyelvWsj9t9uEz7AqwP/LSTWIQWLE/9kYoo7dlrT82+/AZdgWwP99PjZduEsc/lyfq3whl2D/IL5b8YsnPP2XYFSD3msM/WxBYObTItj9S1uqY4MGsP4aIiIiIiLA/PSijt2Wtrj94W9bqmOC5P2rLWh0TPLg/cUzwYJ6otz9eukkMAiu3P3QFyL3mQrI/hyW/WPKLpT97I5TR27KmP7p2vp8aL60/0THBg3mitj/31HjpJjG4P/1GKKO3ZbU/7FG4HoXruT/uiyW/WPKrP3OGXQFyr6k/4ZjgwTxRnz8pelvW6pigPzb78Bl2BbA/aKDTBjptuD/hmODBPFGvP83bslbHBK8/WoIH80T9qz8QWDm0yHa2P5iM3pa1OqY/sIFOG+i0oT+2AuRecyGxP+IXS36x5Lc/kG4Sg8DKuT8sJE2pOPuwPx73mgtJU7I/YBKDwMqhpT+TRbbz/dSoP2D0tqzVMaE/vIN5ov6NsD9JfrHkF0u2P26EMnpb1rI/vr3mQtKUqj/fXnMhaUqlPxBnHz7DrqA/VOOlm8Qg3j9kggfzRP3kP8TZh8+wK94/pzj78Bl2xT8QZx8+w664P7CBThvotLk/ZwOdNtBpsz89KKO3Za2uPydP1L8Ryqg/8Las1THBoz+3kDSl4uyzPzb78Bl2Bbg/gAfzRP0bsT+0yHa+nxq3P4GkKRVnH7Y/+FPjpZvEoD/A6G1Zq2OiPxKDwMqhRaY/O99PjZdusj/jpZvEILC6PwAAAAAAALg/dZMYBFYOtT8R9W+EMnqzP28haUrF2ac/xT58hl0Boj+Bsw+fYVegP+lE/RuhjK4/TmIQWDm0sD9G1L8RyuitPw5LfrHkF6s/rgC511xIwj/Q27JWxwTLP6BhV4Dca8I/jAkezBP1tz+CMnpb1uq4P/p+arx0k7g/ubu7u7u7sz97I5TR27K2PwI6baDTBro/8KfGSzeJwT9mdUzwYJ64P03UvxHK6LU/dBSuR+F6tD88i2zn+6m5P65WxwQP5rk/c3d3d3d3tz9HUyrOPnzCP9ejcD0K18c/GL0ta3VMxD9Ei2zn+6nBPwIrhxbZzr8/ubu7u7u7uz+uR+F6FK63P+cKkHvNhbQ/QmDl0CLbsT/LsCtA7jWnP17JL5b8Yqk/ke18PzVeqj9iHz7DrgCxP9s1F5KmVJw/CbdlrY4Jbr8VqfHSTWJgP1yPwvUoXK8/PRm9LWt1rD+W76fGSzexP3sUrkfheqQ/hxbZzvdTsz/qw2fYFSC3P8MED+aJ+rc/boQyelvWuj/dJAaBlUPLP3LaQKcNdLI/BfNE/RuhtD/N27JWxwS3P3qGXQFyr7k/j9HbslbHvD/fT42XbhK7Pyr5xZJfLLk/EfVvhDJ6sz+o1THBg3miP0j/Riijt6U//Me95kLSpD/mfD81XrqxP90kBoGVQ7M/ObTIdr6fsj81fIZdAXKvP1LHBA/miao/iV8s+cWSnz+kfyOU0duiP/DFkl8s+aU/jZduEoPAqj+TGARWDi2yPx73mgtJU7I/DjyYJ+rfsD9q2kCnDXSqP5zEILByaKE/FL0ta3VMoD9g9Las1TGhP+k1F5KmVKw/pH8jlNHbsj96hl0Bcq+xP7yDeaL+jbA/y78RyuhtqT8K16NwPQqXP8uhRbbz/ZQ//Me95kLSlD/rfmq8dJOoP/yp8dJNYrA/gaQpFWcfrj/clrU6JniwP/LSTWIQWKk/byFpSsXZpz8zYOXQItupP7yDeaL+jaA/x0s3iUFgpT99PzVeukmsP0mNl24Sg7A/MSZ4ME/Urz8nT9S/EcqoP6SOCR7ME6U/zxUg95oLqT8q+cWSXyy5P9YVIPeaC7k/CKwcWmQ7tz/jpZvEILCyP2ig0wY6bbA/CNnO91PjpT+wgU4b6LShP6ApFWcfPqM/i4qzD59hpz/clrU6JniwP+Olm8QgsLo/JHgwT9S/uT/hifo3Qhm1P5ELSVMqzq4//NajcD0Kpz9mhDJ6W9aqP5zx0k1iEKg/RtS/EcrorT/0/dR46SaxPxKSplScfbA/KWt1TPBgrj9OgNxrLiStP6oPn2FXgJw/2c73U+Olmz+sK0DuNReiP/LhM+wKkKs/9jdCGb0tsz9bAXKvuZC0PxkTPJgn6q8/TdS/EcrowT8pa3VM8GC+P5KZmZmZmbk/qWOCB/NEtT+75kLSlIqzP7VlrY4JHrQ/RsXZh8+wsz/A2YfPsCuwP17JL5b8Yqk/72CeqH8jyD9NYhBYObTiPxm9LWt1TOI/+H5qvHST0D/t7u7u7u7GPwisHFpkO88/YYIH80T9yz+QbhKDwMq5P7Ks1THBg7E/IlyPwvUotD877jUXkqa0P2k9CtejcL0/EfVvhDJ6wz+Dz7ArQO69P7CBThvotLk/FfVvhDJ6xz91kxgEVg7BPwctsp3vp7Y/X1eA3GsutD/3xZJfLPm1P/QboYzelqU/jXcwT9S/UT8bGui0gU5bv5zEILByaKE/VB8+w64AmT+HFtnO91OjP/DFkl8s+aU/kxgEVg4tsj/dM+wKkHu1P/zHveZC0qQ/Yh8+w64AsT9tLiRNqTjLP9v5fmq8dKM/wNmHz7AroD9sBci95kKiPyr5xZJfLLE/aJHtfD81tj/l7u7u7u6uP4GkKRVnH64/NvvwGXYFsD+2AuRecyGpP6SOCR7ME6U/RJpScfbhoz9BfrHkF0uuP2cDnTbQabM/UtbqmODBrD/PFSD3mgupP5h9+Ay7AqQ/tNdcSJpSoT+yu7u7u7ubP31dAXKvuaA/YOXQItv5rj+aqH8jlNGzP/LSTWIQWLE/SOF6FK5HsT9mZmZmZmamPxK/WPKLJZ8/FMwT9W+Eoj9YZmZmZmamPxtcj8L1KKw/+FPjpZvEsD8daUrF2YevP1Ys+cWSX6w/L+wKkHvNpT/TTWIQWDmUPx2W/GLJL5Y/e1BGb8tanT/4ca+5kDSlPxkEVg4tsq0/umfYFSD3qj9mdUzwYJ6oP7qFpCkVZ58/lX8jlNHbkj9zpCkVZx+eP6wrQO41F6I/atpApw10qj/WFSD3mguxPzb78Bl2BbA/4Yn6N0IZrT8IyuhtWaujP9OJ+jdCGZ0/dc+wK0DulT8nMQisHFqkP1hImlJx9rE/AA/mifo3uj86Uf9GKKO/P26EMnpb1ro/sHJoke18rz+RC0lTKs6eP4P8Yskvlpw/WoIH80T9mz+VUnH24TOsP7gehetRuK4/CbdlrY4JXj/8qfHSTWJwv3sUrkfheoS/bCOU0duyhr9BUEZvy1ptP4uofyOU0Ys/9BuhjN6WpT8ozj58hl2xP421OiZ4MK8/2c73U+Olqz+gKRVnHz6jP2ig0wY6baA/YgC511xIej9YSJpScfahP/LwGXYFyJ0/uC1rdUzwsD+gGi/dJAahP0jwYJ6of6M/bAXIveZCoj/wtqzVMcGjPxDQaQOdNoA/N4lBYOXQoj8AAAAAAACgP7nKoUW287U/DCD3mgtJoz+RC0lTKs6uPxaSplScfcQ/bxKDwMqhtT97Mnpb1uqYP/zlifo3Qpk/8MWSXyz5pT/pNReSplSsPylrdUzwYK4/H4XrUbgepT+011xImlKhPznhehSuR6E/4+Ez7AqQmz+05kLSlIqTP99PjZduEqM/02suJE2pqD+HJb9Y8oulP/QboYzelqU/uC1rdUzwoD/bNReSplSMP66/EcrobYk/7fRvhDJ6iz8QdgXIveaiP65H4XoUrqc/46WbxCCwoj8bPsOuALmnP4cW2c73U6M/641QRm/Lmj8EdNpApw2UP91gnqh/I4Q/j8L1KFyPoj/2N0IZvS2zP8UgsHJoka0/tgLkXnMhqT+yne+nxkunP9FApw102qA/dbHkF0t+oT/nCpB7zYWkP7K7u7u7u6s/A8i95kLStD98wMqhRbazP8HKoUW2860/17JWxwQPpj99e82FpCmVP9nO91PjpZs/9oLAyqFFlj91seQXS36hPylrdUzwYK4//LjXXEiasj/OeOkmMQi0P90kBoGVQ6s/62CeqH8jpD+uVscED+apP0F+seQXS54/qNUxwYN5oj+q8dJNYhDWP8m95kLSlPE/kDSl4uzD9j8Sg8DKoUXSP5TEILByaLk/l+DBPFH/tj8/RERERES0P1pzIWlKxbk/ctpApw10sj85tMh2vp96PyjEILByaHE/LbKd76fGqz933GsuJE2pP88GOm2g06Y/DBERERERoT/jpZvEILCyPzEIrBxaZLM/GHYFyL3msj+lDXTaQKe1P6oPn2FXgKw/Gy/dJAaBlT8QWDm0yHaeP/zHveZC0qQ/ppvEILBysD+YjN6WtTqmP4GVQ4ts56s/uC1rdUzwsD9RKs4+fIa1P4uKsw+fYZc/PUZvy1odkz+kjgkezBOlPxfotIFOG6g/fLHkF0t+sT+AB/NE/RuxPy/dJAaBlbM/dc+wK0DulT9sI5TR27KWPxkEVg4tsn0/04n6N0IZnT9c6SYxCKycP+XQItv5frI/KWt1TPBgrj8JSVMqzj60P99ecyFpSqU/JSRNqTj7kD+8sCtA7jWHP/T91HjpJpE/XJ6ofyOUoT9t5/up8dK1P6SOCR7ME6U/UrgehetRsD/mbVmrY4LDP2Z1TPBgnrg/6UT9G6GMrj9Ei2zn+6mhP5kaL90kBrE/mH34DLsCtD82+/AZdgW4P9Ei2/l+aqw/CKwcWmQ7nz/A2YfPsCugP0SLbOf7qaE/THMhaUrFmT9YSJpScfahPz+tjgkezHM//Knx0k1iQD8+4OzDZ9hFP0N7zYWkKXW/WDm0yHa+f7/6fmq8dJNov8vd3d3d3Z0/VkrF2YfPkD9BfrHkF0ueP5iM3pa1OqY/L90kBoGVoz8j+cWSXyyZP4Un6t8IZZQ/exSuR+F6lD+0BA/mifqXP0xVVVVVVaU/sqzVMcGDsT/l0CLb+X6qP5NFtvP91Kg//OWJ+jdCmT87G+i0gU6LP0byiyW/WJI/XMtaHRM8mD83iUFg5dCiP4izD59hV7A/kpmZmZmZuT/fCGX0tqzJP8u/Ecrobak/UtbqmODBnD9DxwQP5omaP5HtfD81Xpo/62CeqH8jpD/w1HjpJjGoP+F6FK5H4ao/6SYxCKwcsj8/NV66SQyiP/5MqTj78Ik/FOrfCGX0lj/pRP0boYyeP5M20GkDnaY/eekmMQisrD/Tay4kTamoPznSlIqzD68/qMZLN4lBoD/rb4QyeluWP7TXXEiaUqE/gZVDi2znmz8730+Nl26iP2Z1TPBgnqg//vJE/RuhrD8pa3VM8GCuP8mUirMPn6E/TDeJQWDlgD9De82FpCl1v2IAuddcSHq/nK8rQO41V7/8qfHSTWJgP/yp8dJNYjA/GxrotIFOS78KEzyYJ+qfPzEIrBxaZJs/gYWkKRVnfz8CSVMqzj6cPylcj8L1KJw/TnH24TPsqj/fT42XbhKjP+F6FK5H4ao/xrPIdr6fej9Onqh/I5SRP43TBjptoJM/ptdcSJpSkT99t2Wtjgl+P3kH80T9G6E/L90kBoGVoz8AD+aJ+jeiP7Ks1THBg6k/PYIH80T9iz8OpeLsw2eIPz1Gb8taHZM/30+Nl24Soz9WLPnFkl+sP9NrLiRNqag/sQ+fYVeAxD9LuB6F61G4PzNR/0Yoo5c/0UCnDXTaoD8UvS1rdUygPzm0yHa+n5o/6UT9G6GMnj9g5dAi2/meP6ApFWcfPrM/L/vwGXYFqD/6fmq8dJOoP9Ei2/l+aqw/TGQ730+Npz/hehSuR+GqP0bUvxHK6K0/Bp9hV4Dcqz9OcfbhM+yqPyPq3whl9KY/qOQXS36xpD9Cb8taHROsPy2yne+nxqs/J0DuNReSpj/uiyW/WPKrP/N+arx0k7A/GHYFyL3msj/4gJVDi2ynPyl6W9bqmKA/O99PjZduoj9I4XoUrkehP5ELSVMqzp4/hQkezBP1rz+dYVeA3Gu2P19XgNxrLsA/p0fhehSutz+F61G4HoWzP9nO91Pjpas/l5vEILByqD8SkqZUnH2oPzsb6LSBTps/CbdlrY4JXr++F0t+seR3v8l2vp8aL42/4Wp1TPBgfr/EEBERERFhv+xRuB6F64E/K8OuALnXnD8EdNpApw2kP/hiyS+W/KI/BHTaQKcNpD8UzBP1b4SiP9nsw2fYFaA/K4cW2c73gz/wtqzVMcGjP5MYBFYOLZI/aJHtfD81rj8OS36x5BerP2aEMnpb1qo/sCYxCKwcij/pJjEIrByKP323Za2OCX4/WmQ730+Nlz956SYxCKyMPx+yne+nxqs/xJJfLPnFsj/6nDbQaQOdPxK/WPKLJZ8/Zs73U+Olez97FK5H4XqEP26Ksw+fYYc/xT58hl0Bkj+8g3mi/o2gP8/3U+Olm6Q/i3vNhaQppT/Jdr6fGi+NPxtNqTj78Kk/jdMGOm2gkz8v3SQGgZWjP81E/RuhjI4/02suJE2pqD9I4XoUrkehP323Za2OCY4/8vAZdgXInT8mmZmZmZl5P1724TPsCpA/LdBpA502kD/N6pjgwTyRP2xfLPnFko8/EFg5tMh2nj8MERERERGhPz9iEFg5tKg/4ZjgwTxRnz/VlrU6JniQP4ts5/up8ZI/02suJE2pmD9sBci95kKiP+FqdUzwYH4/CvVvhDJ6mz8ML90kBoGlP9WWtTomeJA/exSuR+F6dL/6fmq8dJNoPx+U0duyVqc/i2zn+6nxkj+eK0DuNReSP6ljggfzRME/p0fhehSuvz87G+i0gU6LP1724TPsCoA/3Zw20GkDfT+0Itv5fmqcP5iM3pa1OqY/sJA0peLsoz/4U+Olm8SgP0oMAiuHFok/tAQP5on6lz8QWDm0yHaeP8HKoUW2850/sru7u7u7mz9sBci95kKiP4/C9Shcj6I/mH34DLsCpD+iRbbz/dSYP+30b4Qyeos/FL0ta3VMoD/Jdr6fGi+dP32ZmZmZmZk/G02pOPvwmT95B/NE/RuhPydP1L8Ryqg/RJpScfbhoz+yne+nxkuXP54rQO41F5I/LSrOPnyGjT9EqTj78BmWP/QMuwLkXqM/6UT9G6GMnj8EkqZUnH2YP0xzIWlKxYm/xT58hl0Bkr9Onqh/I5SRvwisHFpkO4+/eekmMQisjL85tMh2vp9qvx1Fb8taHUM/AiuHFtnOpz85tMh2vp+aPwm3Za2OCW4/g96WtTommD8f/RuhjN52v/qcNtBpA50/nOLsw2fYlT/jw2fYFSCXP0w3iUFg5ZA/fV0Bcq+5kD9eMnpb1uqIP2q8dJMYBJY/uB6F61G4jj+oxks3iUGgP6xY8oslv5g//hARERERkT+iY4IH80SdP31OG+i0gbY/PUZvy1odkz+Bsw+fYVegP4EW6LSBTju/c2iR7Xw/lT+6haQpFWefP0F+seQXS54/YOXQItv5nj/8qfHSTWJwv7ySXyz5xZI/ukkMAiuHZr+4LWt1TPCgP8MT9W+EMpo/WoIH80T9qz+udJMYBFauPxkiIiIiIqI/kyfq3whlpD+sWPKLJb+IP395ov6NUKY/z2+EMnpbhj/NCGX0tqyVPzvuNReSpqQ/38e95kLSdD+2AuRecyGpPxB2Bci95qI/4Wp1TPBgfj9g9Las1TGhP4EW6LSBTjs/EHYFyL3moj8bTak4+/CZP/Cnxks3iaE/pI4JHswTpT8G6SYxCKx8PzvfT42XbpI/YF0Bcq+5gL+yUbgeheuBP9v5fmq8dIM//Me95kLSpD9eMnpb1up4P0SLbOf7qZE/zKyOCR7MYz8K2ezDZ9glP4pMqTj78Gk/38e95kLSdD/fx73mQtKEPyP5xZJfLKk/SPBgnqh/oz8K16NwPQqXP3npJjEIrGw/eekmMQisfD8iy1odEzx4P0N7zYWkKXU/XjJ6W9bqiD87DAIrhxapP99ecyFpSqU/0SLb+X5qnD+iY4IH80SdPz7g7MNn2EW/fbdlrY4Jjj8bGui0gU5Lv5ELSVMqzp4/aJHtfD81nj+gKRVnHz6jPwoTPJgn6p8/f+Lsw2fYhT95B/NE/RuhP5yvK0DuNVc/EGcfPsOuoD/pRP0boYyePwisHFpkO48/17JWxwQPpj/VtIFOG+iUPy83iUFg5ZA/CbdlrY4Jbj+R7Xw/NV6aP2iR7Xw/NY4/AHgwT9S/gT8AeDBP1L9xvydA7jUXkqY/roN5ov6NgD+ND59hV4CMP4pMqTj78Fm/FMwT9W+Ekj/NRP0boYyOP+2411xImpI/MQisHFpkmz/sUbgeheuRP/C2rNUxwaM//Knx0k1iML/vW4/C9SiMPx1Fb8taHUO/avgMuwLkjj8KEzyYJ+qfP06eqH8jlIE/uB6F61G4jj9eMnpb1uqIP3Noke18P5U/nitA7jUXkj/jpZvEILCSP7Ks1THBg6k/bAXIveZCoj/sUbgeheuhP+F6FK5H4Zo/CvVvhDJ6mz99PzVeukm0P6w6JngwT5Q/i2zn+6nxkj+dZ9gVIPeKP1TjpZvEIJA/FMwT9W+Ekj88tWWtjglOP3Noke18P5U/Fy/dJAaByT8nQO41F5KmP2JM8GCeqJ8/kQtJUyrOnj8ZBFYOLbKdPxTq3whl9JY/WoIH80T9mz9I8GCeqH+jP4ts5/up8bI/yXa+nxovwT8rhxbZzvfDP5X8YskvlsA/M0IZvS1rtT/clrU6JniwPywkTak4+7A/MqXi7MNnuD9mdUzwYJ64P4PPsCtA7r0/1hUg95oLuT/dJAaBlUOzPxkTPJgn6q8/WDm0yHa+rz+mqqqqqqqqP2rLWh0TPKg/bFmrY4IHzz+PwvUoXI/YPz0K16NwPdQ/gU4b6LSBxj9kO99PjZe+PyuHFtnO97s/qXJoke18tz8v3SQGgZWzP99tWatjgqc/ZFmrY4IHoz8AAAAAAACgP8IxwYN5op4/WDm0yHa+nz+6dr6fGi+tP06A3GsuJK0/ezJ6W9bqqD933GsuJE2pP/vwGXYFyNE/KKO3Za2O1z+SNKXi7MPRP47elrU6JsQ/0THBg3mivj/HWh0TPJi3P57+jVBGb7M/CvVvhDJ6qz+JUEZvy1qtP8uwK0DuNac/UscED+aJqj/dQtKUirOvPyJNqTj78LE/atpApw10qj/LvxHK6G2pPxb3mgtJU6o/48Nn2BUgpz/y4TPsCpCrPyUVZx8+w64/vq4AuddcsD9l2BUg95qzP0w3iUFg5bA/KVyPwvUorD+4HoXrUbieP4uKsw+fYZc/nOLsw2fYlT+2TWIQWDmUP1LW6pjgwZw/okW28/3UqD+011xImlKhP4lBYOXQIqs/nNMGOm2goz+8sCtA7jWXPx2W/GLJL5Y/Trx0kxgElj91z7ArQO6VP1QBcq+5kKQ/VPKLJb9Yoj8KEzyYJ+qfPxkEVg4tso0/uB6F61G4fj8dlvxiyS+GPw6l4uzDZ4g/bF8s+cWSjz9Cb8taHROsP7Kd76fGS6c/2/l+arx0oz9sXyz5xZKPP6oPn2FXgJw/K8OuALnXnD8ZBFYOLbKdPxCF61G4HqU/bef7qfHSrT+qALnXXEiqP4relrU6JrA/nPHSTWIQqD9ooNMGOm2gP+tvhDJ6W6Y/+pw20GkDnT9KDAIrhxaZPwauR+F6FK4/wwQP5on6pz+DsCtA7jVnP7ySXyz5xZK/nAC511xIir/8qfHSTWKAvzv9G6GM3pY/eekmMQisnD/y8Bl2BcidP3FqvHSTGKQ/ZwOdNtBpuz+0yHa+nxq/P3tQRm/LWp0/wjHBg3minj9xW9bqmOChP2Dl0CLb+Z4/nNMGOm2goz9gEoPAyqGlPzvfT42XbqI/dbHkF0t+kT+m9Shcj8KVP6rx0k1iEJg/atpApw10mj9UPQrXo3CdP4/vp8ZLN6k/c4ZdAXKvqT/rYJ6ofyOkP+f7qfHSTaI/uoWkKRVnnz/sUbgeheuhP2324TPsCqA/FL0ta3VMoD9I/0Yoo7elP99ecyFpSqU/XLx0kxgEpj8lJE2pOPugP/QboYzelqU/pHA9CtejsD9kSsXZh8+wP3hb1uqY4LE/R2IQWDm0sD+R/GLJL5asPx+U0duyVqc/48Nn2BUglz/pJjEIrByaP8l2vp8aL50/g8+wK0DupT+c4uzDZ9ilP998PzVeuqk/QmDl0CLbqT/TTWIQWDmkP9WWtTomeKA/PTeJQWDloD8Eg8DKoUWmPwwv3SQGgaU/CNnO91PjpT8SsHJoke2sPwAAAAAAALA/dAXIveZCsj9TVVVVVVW1P7VlrY4JHrQ/vRHK6G1Zsz+F61G4HoWzP8Jn2BUg97I/RJpScfbhsz90Bci95kKyP4lBYOXQIqs/+o1QRm/Lqj+mqqqqqqqqP57+jVBGb6s/PQrXo3A9qj+JQWDl0CKrP/ZVDi2yna8/6SYxCKwcqj8bPsOuALmnP/QboYzelqU/O99PjZduoj/FPnyGXQGiP4ts5/up8ZI/PzVeukkMoj/nKFyPwvWoP0bF2YfPsKs/oDj78Bl2pT/ZzvdT46WbP4uKsw+fYZc/AAAAAAAAoD/wp8ZLN4mhPyHOPnyGXaE/Yi4kTak4qz/j0k1iEFipPxTME/VvhKI/jfHSTWIQmD+Le82FpCmlP31OG+i0ga4/sJA0peLsoz8AAAAAAACgP9ejcD0K16M/J0/UvxHKqD+YbhKDwMqhP/4QEREREYG/roN5ov6NkL8UzBP1b4SSv3tQRm/LWo2/IxeSplScnT8AAAAAAACgP1pkO99Pjac/9P3UeOkmoT85tMh2vp+qP7TmQtKUipM/IxeSplScnT8/UyrOPnymP1TyiyW/WKI/GQRWDi2yjT8OPJgn6t+oP/qNUEZvy6o/KWt1TPBgyj8pa3VM8GCuPx+jt2Wtjqk/aKDTBjptoD9I4XoUrkehP+PSTWIQWKk/fU4b6LSBrj89Gb0ta3W0P6RwPQrXo8w/ay4kTak41T+YtTomeDDPPzEIrBxaZMM/UscED+aJuj/JhaQpFWe3P8daHRM8mLc/r+QXS36xtD81baDTBjqtP+58PzVeuqk/ng102kCnrT9GxdmHz7CrP3WTGARWDq0/aKDTBjptsD/2N0IZvS2zP7NJDAIrh7Y/UXH24TPswj/RItv5fmrmP/VvhDJ6W+Y/iM+wK0Du0z/JzMzMzMzIPwstsp3vp8Y/FK5H4XoUwj/Vh8+wK0C+PxMg95oLSbs/DjyYJ+rfuD9QnH34DLu6P5t9+Ay7AsA/9ZoLSVMqwj/Jdr6fGi/FP3RM8GCeqMc/27JWxwQPwj9JfrHkF0u+PwPIveZC0rw/CUlTKs4+wD956SYxCKy8P3yx5BdLfrk/j8L1KFyPuj8+tvP91Hi5P9nd3d3d3bU/VYDcay4ktT+79Shcj8K1P9yWtTomeLg/A3KvuZA0wT+e76fGSzfFP6KbxCCwcsQ/PQrXo3A9wj/dJAaBlUO7P/Y3Qhm9LbM/pzj78Bl2tT/MTWIQWDm0PyAiIiIiIrI/XJ6ofyOUsT8HLbKd76e2P+cKkHvNhbQ/bef7qfHSrT9YV4Dcay6kP+coXI/C9ag/okW28/3UsD+kcD0K16OwP3FM8GCeqK8/XJ6ofyOUsT9wr7mQNKWyP421OiZ4MK8/vq4AuddcqD/dM+wKkHutP3tBYOXQIqs/xSCwcmiRrT+NtTomeDCvP26EMnpb1rI/futRuB6Fsz+amZmZmZmxP/hxr7mQNKU/EpKmVJx9sD+mm8QgsHKwP6wcWmQ7368/5e7u7u7urj8sJE2pOPuwP8w+fIZdAbI/RsXZh8+wsz+VYVeA3GuuP4/gwTxR/6Y/daL+jVBGrz+uVscED+axP7YC5F5zIbk/Gz7DrgC5vz/bslbHBA/CPyAiIiIiIro/fU4b6LSBtj9l5/up8dK1P1nl0CLb+bY/TdS/EcrotT/g7MNn2BW4P7EPn2FXgMA/YskvlvxixT9jrY4JHszDP9WHz7ArQL4/Vh0TPJgnuj9ooNMGOm24PxkTPJgn6rc/82+EMnpbtj/DBA/mifq/PwY6baDTBso/Q/0boYzeyj8ePsOuALnDP+IXS36x5L8/XI/C9Shcvz+Dz7ArQO69PwcezBP1b7w/EfVvhDJ6wz+1Za2OCR7IP+01F5KmVMQ/tvP91Hjpvj+R/GLJL5a8P0bF2YfPsLs/yOhtWatjuj9dLPnFkl+8P28haUrF2b8/6JjgwTxRvz8Lg8DKoUW+PxfotIFOG7g/rBxaZDvftz+nR+F6FK63Pw/ZzvdT47U/pzj78Bl2tT+v8/3UeOm2P2Xn+6nx0rU/IDEIrBxatD91ov6NUEa3P0u4HoXrUbg/7yhcj8L1uD8uT9S/Ecq4P4relrU6Jrg/cUzwYJ6otz+tyHa+nxq3Pzb78Bl2Bbg/WdbqmODBtD/7G6GM3pa1P7m7u7u7u7M/ShvotIFOsz/OaQOdNtCxPwXzRP0bobQ/EQRWDi2ytT92ME/UvxGyPwAP5on6N7I/jZduEoPAsj/y4TPsCpCzPxzME/VvhLI/6SYxCKwcsj+Le82FpCm1PyJNqTj78Lk/LCRNqTj7uD9ooNMGOm24P1yPwvUoXLc/2msuJE2puD+QXyz5xZK3P3n4DLsC5LY/EGcfPsOuuD8welvW6pi4P/Y3Qhm9LbM/futRuB6Fsz8xF5KmVJy1P8bMzMzMzLQ/2c73U+Oluz99PzVeuknSPxjZzvdT49k/nah/I5TRzz+CMnpb1urEP9yWtTomeMg/6yYxCKwc0D8X2c73U+PJP5JDi2zn+8U/Q0REREREyD9XxwQP5onSPycxCKwcWuE/NV66SQwC8j9SuB6F61ECQJx9+Ay7Avc/0SLb+X5q4z9EtvP91HjbPwOdNtBpA9c/FGcfPsOu2D8lBoGVQ4vcP7dlrY4JHt4/z8zMzMzM2j9bHRM8mCfWP1H/Riijt9M/Rrbz/dR40T+oxks3iUHQP/FE/RuhjM4/HBM8mCfqyz8QERERERHJP8CDeaL+jcg/5ELSlIqzxz/9jVBGb8vGPy2yne+nxsc/S/Bgnqh/xz8Sg8DKoUXGPz5g5dAi28U/vRHK6G1Zwz83Qhm9LWvJP5iZmZmZmdE/b1mrY4IH0T+fjN6WtTrOP/iaC0lTKso/XEiaUnH2yT9KfrHkF0vSPw8tsp3vp+U/VVVVVVVV9z+wcmiR7Xz2P3E9CtejcOQ/p1ScffgM4D+EeaL+jVDcPxfZzvdT498/7zUXkqZU5j+pfyOU0dviP0jhehSuR90/g8DKoUW23z/hwTxR/0bnP7Od76fGS+U/NHpb1uqY3j/PItv5fmraPwAAAAAAANo/A+RecyFp2D/pJjEIrBzWPx4+w64AudM/dEzwYJ6o0T+t1THBg3nQP4cW2c73U88/OPvwGXYF0D+j4uzDZ9jNP1Eqzj58hsk/OlH/Riijxz+tuZA0peLIP86wK0DuNcs/t2Wtjgke0D9Z8oslv1jQP3OvuZA0pc4/szomeDBPzD8+pw102kDHPzJeukkMAsM/JQaBlUOLxD/CZ9gVIPfGP3YwT9S/EcY/tvP91Hjpxj9E0pSKsw/HP+p8PzVeusk/4hdLfrHkyz84JngwT9TLP86wK0DuNcs/gZVDi2zn0T8lBoGVQ4vWPwPkXnMhadQ/nX34DLsC0j8dzBP1b4TQPwOdNtBpA9E/LbKd76fG1T96zYWkKRXVPwisHFpkO9U/gcDKoUW22T8Rg8DKoUXYP4Dcay4kTdU/d+kmMQis2D/w0k1iEFjbP5X8YskvltY/TGIQWDm01D//Riijt2XTP4/C9Shcj9I//PAZdgXI2T//1HjpJjHnP/OLJb9Y8uU/9uEz7AqQ4T90IWlKxdndP0REREREROM/EZ9hV4Dc7T8YBFYOLbLmP+ltWatjguE/ov6NUEZv4D+95kLSlIrgPxwTPJgn6uQ/Qxm9LWt15D+pOPvwGXbgP2fYFSD3mts/fPgMuwLk2D8/NV66SQzYP3IhaUrF2dc/1jHBg3mi1j/xiyW/WPLTP2+EMnpb1tQ/tPP91Hjp1j8bL90kBoHgP/EZdgXIveU/NKXi7MNn4T9Db8taHRPeP6BFtvP91No/uNdcSJpS1T+T7Xw/NV7UP3Z3d3d3d9M/exSuR+F61D+hjN6WtTrUP86wK0DuNdM/B8i95kLS1D97W9bqmODVPzomeDBP1NM/3whl9Las0z9NG+i0gU7VP0NERERERNg/kHvNhaQp6j+tjgkezBPxP+uY4ME8UeY/A5020GkD4T+MCR7ME/XdP/0boYzeltk/BFYOLbKd2T+rjgkezBPZP/nFkl8s+dU/zczMzMzM0j9dSJpScfbVP+nfCGX0ttQ/CKwcWmQ70z/dJAaBlUPRP/nwGXYFyM0/+TdCGb0tzz/RItv5fmrQPxI8mCfq38w/+TdCGb0tzz8IrBxaZDvPPxlLfrHkF88/3sE8Uf9GzD/Ag3mi/o3IP1nW6pjgwcw/LbKd76fGyz98seQXS37JP0TSlIqzD8s/xr3mQtKUyj/GBA/mifrHP9nO91Pjpcc/fT81XrpJyD/hM+wKkHvFP+7STWIQWMU/it6WtTomxD+411xImlLFP9dcSJpSccY/+Knx0k1ixD8dWmQ730/BP4IyelvW6sA/aErF2YfPwD9/arx0kxjAPwisHFpkO78/zrArQO41wz/MPnyGXQHGP/2NUEZvy8I/Q0REREREwD9VgNxrLiS9PyuHFtnO97s/qNUxwYN5uj9DRERERETAP/fFkl8s+cE/pVScffgMwz81F5KmVJzBP/7UeOkmMcA/ZDvfT42Xwj8FrBxaZDvDPwwCK4cW2cI/QNKUirMPwz9g5dAi2/nCP6+d76fGS8M/0NuyVscEwz++nxov3STCPxsv3SQGgcE/N0IZvS1rwT/RItv5fmrAP0P9G6GM3r4/qWOCB/NEvT8K16NwPQq/P3E9CtejcL0/Ib9Y8osltz9GxdmHz7CzP9eyVscED7Y/Y62OCR7Muz/vGXYFyL22PzNCGb0ta7U/m0W28/3UuD9YObTIdr63P5qofyOU0bs/sHJoke18vz91ov6NUEa/P8KuALnXXMA/mVJx9uEzwD9jvHSTGAS+P8oT9W+EMsI/LWt1TPBgwj9mZmZmZmbCPxkTPJgn6r8/obdlrY4Jwj8j6t8IZfS+P9v5fmq8dLs/mVJx9uEzwD9iyS+W/GLBP1CNl24Sg8A/C3TaQKcNwD9xTPBgnqi/P4aIiIiIiMA/bstaHRM8wD85baDTBjrBP/k3Qhm9LcM/m334DLsCxD/P91PjpZvEP1DjpZvEIMQ/9ihcj8L1xD9w9uEz7ArEP6MpFWcfPsM/mLU6Jngwwz+/PFH/RijDP5KKsw+fYcM/wRHK6G1Zwz9vEoPAyqHBP3LaQKcNdMI/82+EMnpbwj+V/GLJL5bAPxKDwMqhRcI/B9ejcD0Kwz+28/3UeOnCP6MpFWcfPsM/Cy2yne+nxj+WmZmZmZnJPxeSplScfeA/yC+W/GLJ/j9XVVVVVVUAQDttoNMGOv8/A5020GkDA0CF61G4HoUDQFnyiyW/WP4/c9pApw108z96zYWkKRXtP7x0kxgEVug/Q4ts5/up5D9Zq2OCB/PiP9NNYhBYOeI/35a1OiZ44T/7qfHSTWLiP5020GkDneE/yuhtWatj4D8MAiuHFtneP0//Riijt90/89JNYhBY3T9vEoPAyqHdP3sUrkfhet4/j3vNhaQp3z8fzBP1b4TcP+81F5KmVNo/ldHbslbH2D/jM+wKkHvXP76fGi/dJNY/PzVeukkM1j+PwvUoXI/SP6AaL90kBtE/Y4IH80T90T91kxgEVg7TP1QOLbKd79E/JQaBlUOL0j9QjZduEoPSPyKU0duyVtM/vp8aL90k2j/QsCtA7jXkPyR4ME/Uv+8/c6+5kDSl8D8zelvW6pjrP4UW2c73U+Y/G+i0gU4b9z9z2kCnDXQBQOF6FK5H4fU/1uqY4ME88D9/arx0kxjxP3E9CtejcPM/bRKDwMqh7j+yne+nxkvtP1urY4IH8+s/YZ6ofyOU6D8TyuhtWavlP9KUirMPn+M/DElTKs4+4j+FpCkVZx/hP1pkO99Pjd8/ivo3Qhm93T8UZx8+w67cP7mQNKXi7Ns/U5x9+Ay72D8uJE2pOPvUP7as1THBg9M/RP0boYze0j8YvS1rdUzSP6dUnH34DNM/001iEFg51D+Pe82FpCnTP6abxCCwctI//tR46SYx0j+gRbbz/dTSPzJ6W9bqmNI/DXTaQKcN0j98+Ay7AuTQP7m7u7u7u88/mVJx9uEz0D9cSJpScfbNP7x0kxgEVso/CUlTKs4+yD+sHFpkO9/HP3ii/o1QRsc/3whl9LasyT9w9uEz7ArMP4AH80T9G80/Bx7ME/VvzD8LHswT9W/MP9TqmODBPM0/aef7qfHSyT8T2c73U+PFPwaBlUOLbMc/pLdlrY4Jyj/iF0t+seTLP3D24TPsCsg/g8DKoUW2xz+X4ME8Uf/GP73KoUW288U/jAkezBP1wz/5N0IZvS3DP52ofyOU0cc/IpTR27JWxz+rjgkezBPFP0EZvS1rdcQ/3Ja1OiZ4xD/xiyW/WPLDPz81XrpJDMI/pHA9CtejwD/oUbgehevBP+ZtWatjgsM/Bx7ME/VvwD/rYJ6ofyO8Pz0K16NwPbo/nv6NUEZvuz9y2kCnDXTCPy+W/GLJL8o/exSuR+F6zD+EXQFyr7nEP5RuEoPAysE/5/up8dJNwj8IZfS2rNXBP7gehetRuMI/yb3mQtKUwj+2rNUxwYPBP34jlNHbssI/vzxR/0Yowz8JSVMqzj7EP2XYFSD3msM/qaqqqqqqwj8YdgXIvebCPxKDwMqhRcI/sCtA7jUXwj95ME/UvxHCPyd4ME/Uv8E/VYDcay4kwT9Xq2OCB/PAPwPIveZC0sA/UI2XbhKDwD8YvS1rdUzAP97BPFH/RsA/gjJ6W9bqwD+v5BdLfrHAP0YMAiuHFsE/ftxrLiRNwT93vp8aL93AP8/3U+Olm8A/vljyiyW/wD8YvS1rdUzAPx+F61G4HsE/pzj78Bl2wT+FpCkVZx/CP1XHBA/micI/wmfYFSD3wj8vlvxiyS/CPyJNqTj78ME/l+DBPFH/wj9G/RuhjN7CP00b6LSBTsM/GHYFyL3mwj9A0pSKsw/DP/tiyS+W/MI/djBP1L8Rwj9TVVVVVVXBP5+M3pa1OsI/ScXZh8+wwz96zYWkKRXHP7ByaJHtfMc/YYIH80T9xz++WPKLJb/EP52ofyOU0cM/XSz5xZJfxD8YvS1rdUzEP0yNl24Sg8Q/6wqQe82FxD/5N0IZvS3DP5KKsw+fYcM/f2q8dJMYxD9dLPnFkl/EPwcezBP1b8Q/kkOLbOf7xT+TGARWDi3GP+8ZdgXIvcY/9ihcj8L1zD/P91PjpZvgP1G4HoXrUeg/xwQP5on64T9OYhBYObTcP6ebxCCwcuA/46WbxCCw6T/tw2fYFSDoP7tJDAIrh+I/X0iaUnH23T8LHswT9W/aPySU0duyVtk/54n6N0IZ2T8pXI/C9SjYP/iaC0lTKtg/1873U+Ol1z/D9Shcj8LVP28Sg8DKodU/fT81XrpJ1D8IrBxaZDvTP97d3d3d3dE/OW2g0wY60T8GgZVDi2zRP2yg0wY6bcw/qX8jlNHb1D9aZDvfT43PPyr5xZJfLM0/xr3mQtKUyj83Qhm9LWvNPxrotIFOG8w/l+DBPFH/zj8zMzMzMzPPP/7UeOkmMcw/X0iaUnH2yT+411xImlLJP/IoXI/C9cg/r53vp8ZLxz9KDAIrhxbFP1nW6pjgwcg/rkfhehSuxz+TGARWDi3GP7M6JngwT8Q/jAkezBP1wz89CtejcD3CP/+411xImsI/vzxR/0Yowz+Hz7ArQO7FPwlJUyrOPsg/pvHSTWIQxD/ZzvdT46XDP13l0CLb+cI/T0Zvy1odwz8xwYN5ov7BP5s20GkDncI/OCZ4ME/Uwz/D9Shcj8LFP0SLbOf7qcU/7xl2Bci9yj9wy1odEzzaP04b6LSBTuM/EjyYJ+rf3D9cj8L1KFzXPx3ME/VvhNY/ukkMAiuH1j/KWh0TPJjVP6cNdNpAp9M/3GsuJE2p0j+5kDSl4uzRPwisHFpkO9E/ZvS2rNUx0T9DRERERETQP0B8hl0Bcs8/o+Lsw2fYzT+iRbbz/dTMPxH1b4Qyess/5/up8dJNyj8DyL3mQtLIPwOBlUOLbMc/zIWkKRVnxz+QUEZvy1rJP4LrUbgehcc/EBERERERxT+f0wY6baDDPyJNqTj78ME/6JjgwTxRvz/Jdr6fGi/BP41QRm/LWsU/sHJoke18xz+bffgMuwLIPwQP5on6N8o/q44JHswTzT9EtvP91HjRP0bhehSuR9M/vHSTGARW0j89mCfq3wjTP1VVVVVVVdE/VOOlm8Qg0D/BEcrobVnPP06pOPvwGc4/oykVZx8+0T+uR+F6FK7RP68AuddcSNY/Hz7DrgC55D+nDXTaQKf5PyIiIiIiogFAIyIiIiIi+j8s+cWSXyzyP6uqqqqqquw/LWt1TPBg5z/K6G1Zq2PkP/dT46WbxOE/rwC511xI4D+tjgkezBPfP2LJL5b8Yt0/TfBgnqh/3T8/7jUXkqbaP3E9CtejcNc/uUkMAiuH1j9lrY4JHszXPzomeDBP1Nc/K4cW2c731T9TcfbhM+zUPxAREREREdU/3GsuJE2p1D/obVmrY4LTP1WcffgMu9I/0pSKsw+f0z8s+cWSXyzTP/JE/RuhjNI/slbHBA/m0T/VeOkmMQjQP98IZfS2rM0/ukkMAiuH0D+pOPvwGXbRP2IQWDm0yNI/MJb8Yskv2D94ov6NUEbfP4ddAXKvueU/Uf9GKKM38T9iV4Dca67wP7SBThvotO8/T9S/Ecro7T8wT9S/EcrnP/VvhDJ6W+U//o1QRm/L4j9jEFg5tMjgP1nyiyW/WOE/bxKDwMqh4T9gnqh/I5TgP4HAyqFFtt8/eKL+jVBG3z83F5KmVJzdP6jx0k1iENo/mODBPFH/1D8Pn2FXgNzXP9Ei2/l+atg/j8L1KFyP2D9Y8oslv1jYP2t1TPBgnuE/1E1iEFg57D9x9uEz7ArpP7XIdr6fGuA/SAwCK4cW3T+uR+F6FK7dPwAAAAAAANw/9eEz7AqQ2z9TcfbhM+zcP/RvhDJ6W9g/I9v5fmq81j/cslbHBA/WPxSuR+F6FNY/Z62OCR7M1T8FD+aJ+jfUP78RyuhtWdM/4TPsCpB70z/DILByaJHTP4ts5/up8dI/NKXi7MNn0j8lTak4+/DTP86wK0DuNdM/d76fGi/d0j8Pn2FXgNzTP5tScfbhM9g/ukkMAiuH3j936SYxCKzcP8w+fIZdAdg/ME/UvxHK1j8tsp3vp8bVP2VmZmZmZtQ//RuhjN6W0z93vp8aL93SP5X8YskvltI/1XjpJjEI0j85baDTBjrRPx73mgtJU84/1OqY4ME8zT8hBoGVQ4vMP1K4HoXrUcw/DZ9hV4Dcyz/jXnMhaUrNP2etjgkezMs/sp3vp8ZLyz9AfIZdAXLLP/1GKKO3Zck/CpB7zYWkyT/zb4QyelvKP2IQWDm0yMo/arx0kxgEyj9ecyFpSsXJP+nfCGX0tsg/JL9Y8oslxz8iTak4+/DFPwisHFpkO8M/uB6F61G4vj+cGi/dJAbFP2nn+6nx0sU/es2FpCkVxz8+YOXQItvBPxfZzvdT48U/iLMPn2FXxD84JngwT9TDP6+d76fGS8M/87as1THBwz/3DLsC5F7DP5KKsw+fYcM/XxBYObTIwj9k9Las1THBP0bF2YfPsLs/ObTIdr6fuj+ht2Wtjgm+P7wta3VM8MQ/415zIWlKxT8CK4cW2c7DP2kuJE2pOMM/8UT9G6GMwj8bL90kBoHBP/hT46WbxMA/+FPjpZvEwD9ecyFpSsXBP7dJDAIrh8I/gZVDi2znwz+3kDSl4uzDP/+411xImsI/szomeDBPxD8HHswT9W/EP/yp8dJNYsQ/4TPsCpB7xT+8dJMYBFbGPwt02kCnDcQ/CUlTKs4+wD8IZfS2rNXBP3E9CtejcME/OW2g0wY6wT97FK5H4XrAP/IoXI/C9cQ/v+ZC0pSKwz/pJjEIrBzCP2nn+6nx0sE/koqzD59hwz/GBA/mifrDP4IyelvW6sQ/MHpb1uqYxD/HSzeJQWDFP2XYFSD3msc/HveaC0lTxj8dWmQ730/JP6zVMcGDeco/b1mrY4IHyz8ED+aJ+jfKP6ljggfzRMk/P+41F5KmyD8LdNpApw3IP26EMnpb1sY//UYoo7dlwT+QXyz5xZLDP/+411xImsI/iyW/WPKLwT9cSJpScfbBP6/kF0t+scQ/m334DLsCxD9A0pSKsw/DP27LWh0TPMA/aErF2YfPwD93vp8aL93AP5GmVJx9+MA/OW2g0wY6wT8R9W+EMnrDPxrotIFOG8Q/7TUXkqZUxD/mbVmrY4LDP/FE/RuhjMI/c2iR7Xw/wT+SirMPn2HDPwwCK4cW2cI/82+EMnpbyj8+pw102kDLPxP1b4QyetM/J79Y8osl7D8nMQisHFrxP6h/I5TR2+Y/wRHK6G1Z4T+K+jdCGb3fP1cOLbKd7+c/6ELSlIqz7T85tMh2vp/mP6scWmQ73+M/wvUoXI/C4j9rvHSTGAThPwaBlUOLbOE/ay4kTak44D9aZDvfT43fP3z4DLsC5N4/jlBGb8ta4D/MhaQpFWfdP30/NV66SeA/CKwcWmQ75j8UrkfhehT2P6cNdNpAp/U/9v3UeOkm8T8cWmQ730/rPxM8mCfq3+Y/0NuyVseE8j/ntIFOG+j8P+F6FK5H4fM/AQAAAAAA8T+411xImlLtP6BhV4Dca+o/qA102kCn5z8Sg8DKoUXlP+98PzVeuuI/d76fGi/d4D/Ag3mi/o3eP1TjpZvEIN4/TRvotIFO3T8VZx8+w67jPyA+w64Aueg/v58aL90k4z9w9uEz7AreP/+NUEZvy9w//Knx0k1i3j+WbhKDwMrfPzomeDBP1P4//GLJL5Z8D0AFOm2g04YKQFVVVVVV1RBAddpApw20FEAHOm2g00YRQON6FK5HYQxA6LSBThtoCkBTuB6F69EDQAGdNtBpA/8/HOi0gU4b+D+uR+F6FK7zPzlCGb0ta+0/uwLkXnMh6j840GkDnTboP4MH80T9G+Y/Z5HtfD815D8fzBP1b4TmP5HtfD81XuQ/R2/LWh0T4z/ntIFOG+jeP9gVIPeaC90/PcOuALnX3D99PzVeuknaP1dVVVVVVds/TxvotIFO3z+Pl24Sg8DcP7jXXEiaUts/001iEFg52j/glrU6JnjaP3QhaUrF2dk/eDBP1L8R2D/dJAaBlUPXP5GmVJx9+Ng/o7dlrY4J1j+95kLSlIrTP65H4XoUrtE/5dAi2/l+0D9SuB6F61HMPzm0yHa+n84/Qrbz/dR4zT/yRP0boYzSP4/C9Shcj9A/ke18PzVe0D8klNHbslbRP0dTKs4+fNI/nO+nxks31T8K16NwPQrVP9bqmODBPNU/Di2yne+n1D/6fmq8dJPSP0CnDXTaQNE/jVBGb8tazT8fhetRuB7NP4relrU6Jsw/FyD3mgtJyz9cSJpScfbJP3hb1uqY4M0/2msuJE2pzD+kt2WtjgnOP5fgwTxR/8o/7JjgwTxRyz9I4XoUrkfJP2Dl0CLb+cY/+2LJL5b8xj+8dJMYBFbKP9ejcD0K18c/ONBpA502yD+im8QgsHLIP9YVIPeaC8k/+2LJL5b8xj8GOm2g0wbGP5huEoPAysU/s+QXS36xyD9nA5020GnHP8paHRM8mMc/0XjpJjEIxD/tNReSplTEPymyne+nxsM/PqcNdNpAwz8/7jUXkqbEP2p1TPBgnsg/Q/0boYzexj/6fmq8dJPIP32GXQFyr8U/HVpkO99PxT/OaQOdNtDFPz5g5dAi28U/CGX0tqzVxT/Zh8+wK0DGP7m7u7u7u8c/FyD3mgtJxz+8dJMYBFbGPyajt2WtjsU/MHpb1uqYwD+AB/NE/RvBP7VlrY4JHsQ/gZVDi2znxz8jIiIiIiLGP7SBThvotMU/anVM8GCexD916SYxCKzEPxaSplScfcQ/Hj7DrgC5wz9l2BUg95rDP7SBThvotMU/zD58hl0Bxj+RplScffjEPxi9LWt1TMQ/KvnFkl8sxT/9Riijt2XFP29oke18P8U/aErF2YfPxD/qw2fYFSDHP7gehetRuMY/Lk/UvxHKxD8ypeLsw2fAP3fNhaQpFb8/m334DLsCwD8rhxbZzve7PwrXo3A9Cr8/6FG4HoXrwT9hggfzRP3DP2NXgNxrLsQ/7FG4HoXrwT8dWmQ730/BP497zYWkKcE/tWWtjgkewD+8LWt1TPDAP/hT46WbxMA/m334DLsCwD/FL5b8Ysm/PwGsHFpkO7c/cUzwYJ6otz8K5on6N0K5P3sUrkfhesA/z/dT46WbwD9VxwQP5onCP7Kd76fGS8M/7KfGSzeJwT91kxgEVg69P/C2rNUxwbs/+o1QRm/Luj9jO99PjZfeP28Sg8DKodE/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/KVyPwvUozD8pXI/C9SjMPylcj8L1KMw/30+Nl24Syz9mZmZmZmbCP4XrUbgehcM/Uv9GKKO3yT/ufD81XrrJP1odEzyYJ8Y/7TUXkqZUxD+6AuRecyHFPy+W/GLJL8Y/wmfYFSD3wj+Pe82FpCnBP5X8YskvlsA/KM4+fIZdwT8SPJgn6t/APy5P1L8RysA/72CeqH8jwD+v5BdLfrHAPyG/WPKLJb8/uB6F61G4vj9g5dAi2/m+P+ZtWatjgr8/5m1Zq2OCvz88fIZdAXK/P9hApw102sA/NvvwGXYFwD84JngwT9S/P+O0gU4b6Lw/wcqhRbbzvT//Riijt2XRP5kn6t8IZeI/VscED+aJ5D8FD+aJ+jfgP6H+jVBGb9c/oYzelrU60j8NdNpApw3QP0dTKs4+fM4/+xuhjN6W1z/vNReSplTgPxAREREREds/P8OuALnX1j/5xZJfLPnVP+F6FK5H4dI/F9nO91Pj1z8ywYN5ov7gP/Cnxks3id0/3GsuJE2p2D9R/0Yoo7fXPyGwcmiR7dY/6bSBThvo1D8MuwLkXnPVPxHK6G1Zq9U/dgXIveZC1D9Ei2zn+6nfPyUGgZVDi+E/LPnFkl8s3T+dqH8jlNHZPy2yne+nxtc/bKDTBjpt1j+M3pa1OibSP8jobVmrY84/zBP1b4Qy0D/hehSuR+HSPxdLfrHkF9M/ULgehetR0j+jKRVnHz7PP5zEILByaM0/Vg4tsp3v0z/XzvdT46XVP+iY4ME8UdM/zrArQO410z92Bci95kLUP7EPn2FXgNY/w/UoXI/C2z+vR+F6FK7kP0vF2YfPsN0/iYiIiIiI4z9BYOXQItvpP+EIZfS2rPA/68Nn2BUg7D+bxCCwcmjrP8ERyuhtWeU/W9bqmODB4T9QjZduEoPePydcj8L1KNo/1L8Ryuht1z+tjgkezBPVP9V46SYxCNg/1873U+Ol1z9vhDJ6W9bQPxBYObTIdtY/3LJWxwQP2D9R/0Yoo7fTP2Q730+Nl9A/s1bHBA/m0T/obVmrY4LTP8uhRbbz/cw/8kT9G6GM0D/MPnyGXQHSP+9gnqh/I8g/dEzwYJ6oxz82+/AZdgXMP/hT46WbxMg/YVeA3Gsu0D/7G6GM3pbNP+7STWIQWMk/7FG4HoXryT/5xZJfLPnVPzHBg3mi/sk/pHA9CtejzD/3DLsC5F7RP2DJL5b8YtM/YOXQItv50D+SirMPn2HPP4IyelvW6sw/NvvwGXYFyD/wp8ZLN4nBP3WTGARWDsE/ciFpSsXZwz/P91PjpZvIP+f7qfHSTco/szomeDBPxD9/seQXS37FP3sUrkfhesQ/3SQGgZVDwz9k9Las1THFPzeJQWDl0MI/XrpJDAIrxz/4qfHSTWLEPzMzMzMzM8M/Gy/dJAaBxT97arx0kxjEP1XHBA/micI/eekmMQiswD9uy1odEzzAP788Uf9GKMM/D3TaQKcNxD8ED+aJ+jfCPzMzMzMzM8M/xNmHz7ArxD/JveZC0pTCP28Sg8DKocE/fT81XrpJwD8WkqZUnH3EP+ynxks3icU/Gui0gU4bxD+uR+F6FK7DP+F6FK5H4cI/M+wKkHvNwT8IZfS2rNXBP1WA3GsuJME/of6NUEZvwz8IrBxaZDvDP0upOPvwGcI/XEiaUnH2wT8OLbKd76e+P2Q730+Nl74/wq4AuddcwD8uT9S/EcrAP8HKoUW288E/vp8aL90kwj8v7AqQe829P6rx0k1iEMA/2whl9LasvT/QlIqzD5+5P3FM8GCeqLc/X2ZmZmZmtj9cj8L1KFy/PyUGgZVDi8A/5d8IZfS2vD8lBoGVQ4vAP/7jXnMhabo/AjptoNMGuj+OQ4ts5/u5P26EMnpb1ro/Qm/LWh0TvD/jtIFOG+i8P0upOPvwGb4/ZwOdNtBpuz+wgU4b6LS5P7efGi/dJLY/kfxiyS+WtD8aoYzelrWyP26EMnpb1ro/ocZLN4lBuD+yrNUxwYOpP/NvhDJ6W74/5/up8dJNuj+TJ+rfCGW0Pz0K16NwPbI/eoZdAXKvsT9TZDvfT423P/sboYzelr0/wwQP5on6tz/31HjpJjG4P1erY4IH87Q/qMZLN4lBsD++rgC511ywP10s+cWSX7Q/TEZvy1oduz+ZC0lTKs7OP90z7AqQe7U/H5TR27JWtz+9EcrobVmzP5VhV4Dca64/A8i95kLStD9vEoPAyqG1P65WxwQP5rk/jZduEoPAuj+lDXTaQKe1Pzx8hl0Bcrc/hetRuB6Fsz9q2kCnDXSqPwwREREREbE/u+ZC0pSKsz9cj8L1KFy3P7TIdr6fGrc/IlyPwvUotD8F80T9G6G0P4cW2c73U7M/6UT9G6GMrj9OcfbhM+yqP7LKoUW2860/q44JHswTtT/uiyW/WPKzP1yeqH8jlLE/SX6x5BdLtj9sWatjggezP/N+arx0k7A/LcGDeaL+rT/Jdr6fGi+tP5+M3pa1OrY//3GvuZA0tT+R7Xw/NV6yP5s20GkDnbY/kxgEVg4tsj8zYOXQItupP4uZmZmZmak/CvVvhDJ6qz8lFWcfPsO2P9K/Ecrobbk/CNnO91PjpT/op8ZLN4mxP06A3GsuJK0/I/nFkl8sqT+Nl24Sg8CqP90z7AqQe60/47SBThvotD/aay4kTam4P5bvp8ZLN7k/Y62OCR7Muz9I4XoUrkfJP8uhRbbz/bQ/kG4Sg8DKsT+6WPKLJb+wP0//Riijt7U/i3vNhaQptT8BnTbQaQO1P0xGb8taHbM/GHYFyL3msj9IDi2yne+nPw48mCfq36g/kfxiyS+WrD/Z3d3d3d21Pz0ZvS1rdaw/y78RyuhtqT/b+X5qvHSzP0F+seQXS64/8MWSXyz5pT9qy1odEzyoP0Jvy1odE6w/4hdLfrHktz/HWh0TPJi3Py2yne+nxrM/AjptoNMGsj85tMh2vp+qPxYGgZVDi6w/MqXi7MNnsD+EXQFyr7mwPwwCK4cW2bY/aT0K16NwtT/YQKcNdNqwPxs+w64Aubc/xWfYFSD3yj9VgNxrLiS1PxH1b4QyerM/BfNE/RuhtD+v8/3UeOm2PzNCGb0ta7U/wmfYFSD3sj/jpZvEILCyP/yp8dJNYrA/8NR46SYxqD+iVJx9+AyrP8DZh8+wK7A/cL6fGi/dtD/y4TPsCpCzP4AH80T9G7E/QwwCK4cWsT/2Riijt2WtP0bF2YfPsKs/Yj0K16NwrT9YObTIdr6vP+Dsw2fYFbg/PcOuALnXwD9wr7mQNKW6P9CUirMPn7E/qMZLN4lBsD8lFWcfPsOuPxSuR+F6FK4/LcGDeaL+rT81fIZdAXKvP7pY8oslv7A/xJJfLPnFsj8LdNpApw20P4lBYOXQIrM/DBERERERsT9G1L8RyuitP6oAuddcSKo/F+i0gU4bsD+RC0lTKs6uP5VhV4Dca64/ToDcay4krT8CSVMqzj6sP5zx0k1iEKg/oDj78Bl2pT9kaJHtfD+lPyG/WPKLJa8/FK5H4XoUrj+8dJMYBFauP2Q730+Nl64/SirOPnyGrT/6jVBGb8uqP+kmMQisHKo/5yhcj8L1qD+NtTomeDCvP97BPFH/RrA/GQRWDi2yrT/Vh8+wK0CuP4XrUbgehas/Vh0TPJgnqj+qALnXXEiqP88VIPeaC6k/4Yn6N0IZrT+iY4IH80StP6rx0k1iELA/1YfPsCtArj9SxwQP5omqP17JL5b8Yqk/pI4JHswTpT/DBA/mifqnP65lrY4JHqw/fU4b6LSBrj9WLPnFkl+sP0ob6LSBTqs/1YfPsCtArj9OcfbhM+yqP1CrY4IH86Q/KVyPwvUorD8iTak4+/CxPy5P1L8RyrA/2msuJE2psD8hv1jyiyWvP6a5kDSl4qw/321Zq2OCpz9aggfzRP2rP/7yRP0boaw/tMh2vp8arz/umgtJUyquPxtNqTj78Kk/rlbHBA/mqT8v+/AZdgWoP/hxr7mQNKU/O+41F5KmpD+Xm8QgsHKoP1YdEzyYJ6o/ZoQyelvWqj8W95oLSVOqPx+jt2Wtjqk/vHSTGARWrj8zMzMzMzOzP6ud76fGS7c/ZDvfT42Xtj/mfD81XrqxP4/R27JWx6Q/Vh0TPJgnsj9UEFg5tMimPw48mCfq37g/NXyGXQFyrz/RMcGDeaKuP/LhM+wKkKs/psh2vp8arz/DE/VvhDKqPwwREREREbE/vHSTGARWvj9iLiRNqTirP7gehetRuK4/Vg4tsp3vpz8bPsOuALmnP8Ii2/l+aqw/DjyYJ+rfqD9ovp8aL92kP9prLiRNqbA/CKwcWmQ7rz8IyuhtWaujP5h9+Ay7AqQ/JzEIrBxapD/U6pjgwTyxP+k1F5KmVKw/xU1iEFg5pD9S1uqY4MGsP8/3U+Olm7Q/VAFyr7mQpD8Sg8DKoUWmP0ob6LSBTqs/Yh8+w64AsT+iVJx9+AyrP4lQRm/LWq0/LcGDeaL+rT8nMQisHFq0P5zx0k1iEKg/Yi4kTak4qz8ZBFYOLbKtP0Jvy1odE6w/7poLSVMqrj/+8kT9G6GsP6oAuddcSKo/L/vwGXYFqD/rYJ6ofyOkP9NNYhBYOaQ/XrpJDAIrpz/fbVmrY4KnP0Jg5dAi26k/DCD3mgtJoz8X6LSBThuoPznSlIqzD68/f4iIiIiIqD/wtqzVMcGjP6jkF0t+saQ/L/vwGXYFqD+NplScffisPwAezBP1b6Q/x2kDnTbQqT91ov6NUEavP+PDZ9gVIKc/qOQXS36xpD9crY4JHsyjP3fcay4kTak/ppvEILByqD9YZmZmZmamP7pn2BUg96o/pqqqqqqqsj/fT42XbhKjPycxCKwcWqQ/VAFyr7mQpD/bF0t+seSnP7CfGi/dJKY/x2kDnTbQqT+JUEZvy1qtPy5P1L8RyrA/62+EMnpbpj9EqTj78BmmP395ov6NUKY/J0DuNReSpj/6fmq8dJOoP/DUeOkmMag/+pw20GkDrT+kne+nxkunP1g5tMh2vq8/tgLkXnMhqT8CSVMqzj6sP91C0pSKs68/qOQXS36xpD9MZDvfT42nP/7jXnMhaao/CuaJ+jdCqT9YSJpScfahPwAP5on6N6I/pH8jlNHboj9mdUzwYJ6wPxkEVg4tsq0/i3vNhaQppT/dM+wKkHutP/iAlUOLbKc/JQaBlUOLrD/A6G1Zq2OiP+O0gU4b6KQ/WmQ730+Npz8nQO41F5KmPxsv3SQGgaU/CtejcD0Kpz8czBP1b4TCP9v5fmq8dKM/WEiaUnH2oT+sK0DuNReiP0j/Riijt6U/C2X0tqzVyT9jyS+W/GLsPzzfT42Xbuo/TGIQWDm00D9TVVVVVVW9PzvuNReSprQ/1hUg95oLsT8ozj58hl2xP7695kLSlKo/Vh0TPJgnqj91ov6NUEavP+6aC0lTKq4/KVyPwvUorD+F61G4HoWrP0xkO99Pjac/pHA9CtejsD/hifo3QhmtPy/78Bl2Bag/ObTIdr6fqj9qvHSTGASmP1hImlJx9qE/P0REREREpD/rb4QyelumP0F+seQXS64/BFYOLbKdrz8W95oLSVOqP/Y3Qhm9Las/ng102kCnrT+iRbbz/dSwP+8ZdgXIvbY/jAkezBP1tz/Qo3A9CtezP19ImlJx9rE/Ib9Y8oslrz9kO99PjZeuP8a95kLSlLI/CtejcD0Ktz+GiIiIiIi4P9v5fmq8dLM/astaHRM8sD+K3pa1OiawP8Uvlvxiya8/NW2g0wY6rT9KG+i0gU6rPz9TKs4+fKY/P1Mqzj58pj/HaQOdNtCpPxb3mgtJU6o/bzBP1L8Rqj9CYOXQItupPz9iEFg5tKg/H5TR27JWpz+kne+nxkunP+coXI/C9ag/DC/dJAaBpT+qD59hV4CsPw5LfrHkF6s/d9xrLiRNqT8dWmQ730+tP1YdEzyYJ6o/16NwPQrXoz8UzBP1b4SiP2ivuZA0paI/6UT9G6GMrj8zUf9GKKOnPxTME/VvhKI/XK2OCR7Moz9kWatjggejP5MYBFYOLaI/GSIiIiIioj/sUbgeheuhP1pkO99Pjac/bzBP1L8Rqj+pcmiR7Xy3P7TXXEiaUrE/K4cW2c73oz9MVVVVVVWlP6w6JngwT6Q/exSuR+F6pD83iUFg5dCiP1CcffgMu6I/xT58hl0Boj9or7mQNKWiPzNCGb0ta6U/arx0kxgEpj+Dz7ArQO6lP4t7zYWkKaU/uB6F61G4rj+pY4IH80TBP7M6JngwT8w/5DPsCpB72T/pJjEIrBzGP70RyuhtWbM/3TPsCpB7rT+Xm8QgsHKoP0Jg5dAi26k/6SYxCKwcqj+sSQwCK4emP4PPsCtA7qU/L90kBoGVoz/sUbgeheuhP6R/I5TR26I/oDj78Bl2pT/clrU6JniwP3Noke18P7U/+pw20GkDrT8OS36x5BerP5zi7MNn2KU/NXyGXQFyrz+MCR7ME/W3P+Z8PzVeurE/zduyVscErz89Gb0ta3WsP17JL5b8Yqk/yhP1b4Qysj+fjN6WtTq+Pz9ERERERLw/7nw/NV66sT8IrBxaZDuvPyGwcmiR7aw/cT0K16NwrT+q8dJNYhCwP05x9uEz7Lo/vp8aL90kwj9l2BUg95q7P6JUnH34DLM/6JjgwTxRtz9/arx0kxi0P6R/I5TR27I/5/up8dJNsj9YSJpScfaxP4X6N0IZva0/z/dT46WbpD8QhetRuB6lPxTb+X5qvKQ/ZGiR7Xw/pT+kjgkezBOlP1LW6pjgwaw/NW2g0wY6rT8v7AqQe82lP30/NV66Saw/c3d3d3d3tz/Z3d3d3d21P6oAuddcSKo/vJJfLPnFoj/8uNdcSJqiP2RZq2OCB6M/mqh/I5TRqz/jpZvEILCiPydA7jUXkqY/Dkt+seQXqz8CWDm0yHauPznDrgC516w/Yh8+w64AqT+2AuRecyGpPxfotIFOG6g/ShvotIFOqz+uVscED+apP76uALnXXKg/AiuHFtnOpz8nT9S/EcqoPzv9G6GM3qY/CUlTKs4+tD+nR+F6FK63P2ADnTbQaaM/cWq8dJMYpD+sOiZ4ME+kP+f7qfHSTaI/315zIWlKpT9iEFg5tMimP3N3d3d3d6c/CMrobVmroz+gOPvwGXalP4ts5/up8aI//Me95kLSpD/rb4QyelumP5iM3pa1OqY/47SBThvopD87/RuhjN6mP3sjlNHbsqY/+HGvuZA0pT+kjgkezBOlPyPb+X5qvKQ/w/UoXI/CpT9YSJpScfahPxB2Bci95qI/x0s3iUFgpT+75kLSlIrHP6w6JngwT6Q/TEZvy1odoz+gKRVnHz6jPy/dJAaBlaM/HYcW2c73oz/nCpB7zYWkP3Noke18P6U/bAXIveZCoj/0DLsC5F6jP7TmQtKUiqM/RKk4+/AZpj9vME/UvxGqP6oAuddcSKo/sqzVMcGDqT8ALbKd76emP2i+nxov3aQ/uDxR/0Yooz+TGARWDi2iPzMzMzMzM6M/M0IZvS1rpT8AHswT9W+kP7T1KFyPwqU//Me95kLSpD9I8GCeqH+jP1hImlJx9qE/VPKLJb9Yoj/FPnyGXQGiP+O0gU4b6KQ/pH8jlNHboj+PwvUoXI+iP6SOCR7ME6U/aK+5kDSloj9or7mQNKWiP2wFyL3mQqI/7FG4HoXroT++nxov3SSmP/p+arx0k7A/hxbZzvdToz/FPnyGXQGiP5MYBFYOLaI/tPUoXI/CpT9sFK5H4XqkP6R/I5TR26I/uDxR/0Yooz/n+6nx0k2iPz81XrpJDKI/GSIiIiIioj9qy1odEzywPy2yne+nxrs/3SQGgZVDuz91ov6NUEa3P+6LJb9Y8qs/zfl+arx0oz9I8GCeqH+jP+xRuB6F66E/qNUxwYN5oj9MRm/LWh2jP6jVMcGDeaI/qNUxwYN5oj+kfyOU0duiP1CcffgMu6I/g8DKoUW2oz9sBci95kKiP6R/I5TR26I/cWq8dJMYpD8ML90kBoGlP+tgnqh/I6Q/+GLJL5b8oj+LbOf7qfGiP/C2rNUxwaM/7FG4HoXroT/fT42XbhKjP5iM3pa1OqY/9BuhjN6WpT8EdNpApw2kP4/C9Shcj6I/62CeqH8jpD+8kl8s+cWiPzvfT42XbqI//LjXXEiaoj+TRbbz/dSoP4/gwTxR/6Y/UKtjggfzpD+sK0DuNReiPzvfT42XbqI/SPBgnqh/oz/FPnyGXQGiP5MYBFYOLaI/K4cW2c73oz+c0wY6baCjP7g8Uf9GKKM/O99PjZduoj/FPnyGXQGiPwAP5on6N6I/kxgEVg4toj9kWatjggejP88VIPeaC6k/vKFFtvP9pD+sOiZ4ME+kP6jVMcGDeaI/AA/mifo3oj8ZIiIiIiKiP6wrQO41F6I/i2zn+6nxoj8v3SQGgZWjPz81XrpJDKI/AA/mifo3oj9YSJpScfahP+xRuB6F66E/WEiaUnH2oT9JxdmHz7DDPxsv3SQGgaU/j9HbslbHpD9YV4Dcay6kP6ApFWcfPqM/WFeA3GsupD9QnH34DLuiPwAP5on6N6I/9kYoo7dlrT89KKO3Za2uP8uwK0DuNac/+GLJL5b8oj8ZIiIiIiKiP7g8Uf9GKKM/bAXIveZCoj/jpZvEILCiP+xRuB6F66E/rCtA7jUXoj9crY4JHsyjP4/C9Shcj6I/WEiaUnH2oT/sUbgeheuhP+xRuB6F66E/5/up8dJNoj9U8oslv1iiPz81XrpJDKI/pH8jlNHboj/fT42XbhKjP1hXgNxrLqQ/O99PjZduoj+05kLSlIqjP/hiyS+W/KI/GSIiIiIioj+LbOf7qfGiP57vp8ZLN6k/hyW/WPKLpT9I/0Yoo7elPzeJQWDl0KI/UJx9+Ay7oj+LbOf7qfGiP+xRuB6F66E/i2zn+6nxoj8v+/AZdgWoP3sjlNHbsqY/tPUoXI/CpT+kfyOU0duiP7ySXyz5xaI/pH8jlNHboj/sUbgeheuhPzeJQWDl0KI/0JSKsw+fsT9JjZduEoO4P+XQItv5frI/KWt1TPBgrj9MN4lBYOWwP4ts5/up8bI/KM4+fIZdsT8rpeLsw2eoP8MT9W+EMqo/XrpJDAIrpz+eDXTaQKetP1QBcq+5kKQ/KVyPwvUorD8W95oLSVOqP/QMuwLkXqM/9wy7AuRewz/n+6nx0k2iPwwg95oLSaM/7FG4HoXroT+sOiZ4ME+kPzeJQWDl0KI/aK+5kDSloj+o1THBg3miP+Olm8QgsKI/i3vNhaQppT+8oUW28/2kPxTb+X5qvKQ/FMwT9W+Eoj9OYhBYObTAP3H24TPsCug/wMqhRbbz5D/ntIFOG+jaP4/R27JWx7w/8vAZdgXIrT/PBjptoNOmP6BH4XoUrqc/JzEIrBxapD9or7mQNKWiP/hiyS+W/KI/rCtA7jUXoj+LbOf7qfGiP5zTBjptoKM/7FG4HoXroT+8kl8s+cWiP1TyiyW/WKI/i2zn+6nxoj/LsCtA7jW3P/p+arx0k8w/DuaJ+jdCzT/QlIqzD5/BP3yx5BdLfrk/vzxR/0Youz+gGi/dJAaxPx+jt2Wtjqk/FNv5fmq8pD/jpZvEILCiP6wrQO41F6I/7FG4HoXroT8ZIiIiIiKiPzvfT42XbqI/O99PjZduoj9YSJpScfahP5MYBFYOLaI/AA/mifo3oj+05kLSlIqjPz81XrpJDKI/UJx9+Ay7oj/sUbgeheuhP+xRuB6F66E/AA/mifo3oj/sUbgeheuhP5MYBFYOLaI/01xImlJxpj8/RERERESkP/hiyS+W/KI/AA/mifo3oj9kWatjggejP2wUrkfheqQ/rCtA7jUXoj/rYJ6ofyOkPxKDwMqhRaY/f3mi/o1Qpj+09Shcj8KlP7ySXyz5xaI/j+DBPFH/pj8v+/AZdgWoPwwg95oLSaM/62+EMnpbpj8OS36x5BerP9eyVscED6Y/BHTaQKcNpD/n+6nx0k2iP/hiyS+W/KI/WFeA3GsupD/wtqzVMcGjPxKSplScfag/CvVvhDJ6qz9/eaL+jVCmP1CrY4IH86Q/oCkVZx8+oz8MIPeaC0mjP/hiyS+W/KI/5/up8dJNoj8v3SQGgZWjPxCF61G4HqU/zwY6baDTpj9MVVVVVVWlPwAP5on6N6I/GSIiIiIioj/0DLsC5F6jP4/C9Shcj6I/zfl+arx0oz8GkHvNhaSpP99ecyFpSqU/TFVVVVVVpT+LbOf7qfGiP6wrQO41F6I/rCtA7jUXoj/A6G1Zq2OiP8U+fIZdAaI/bAXIveZCoj83mCfq3wilP5Mn6t8IZaQ/i2zn+6nxoj/4YskvlvyiP+O0gU4b6KQ/MzMzMzMzoz8ML90kBoGlP6BH4XoUrqc/pJ3vp8ZLpz9UAXKvuZCkP8U+fIZdAaI/rCtA7jUXoj+4PFH/RiijP/y411xImqI/JTMzMzMzoz/TXEiaUnGmPxB2Bci95qI//LjXXEiaoj/sUbgeheuhP1hImlJx9qE/O99PjZduoj8ZIiIiIiKiP0xGb8taHaM/I/nFkl8sqT9YV4Dcay6kP6ApFWcfPqM/O99PjZduoj8ZIiIiIiKiP+xRuB6F66E/wOhtWatjoj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/8uNdcSJqiP8U+fIZdAaI/pH8jlNHboj/sUbgeheuhP1TyiyW/WKI/Id0kBoGVoz+HFtnO91OjP1hXgNxrLqQ/F9nO91PjpT9Cb8taHROsP/zHveZC0qQ/nNMGOm2goz+PwvUoXI+iPwAP5on6N6I/j8L1KFyPoj+8kl8s+cWiP6R/I5TR26I/AA/mifo3oj+gKRVnHz6jP/ZGKKO3Za0/ICIiIiIisj+YbhKDwMqxP31OG+i0ga4/mqh/I5TRqz8xCKwcWmSrPwaQe82FpKk/rkfhehSupz9/arx0kxikP7yhRbbz/aQ/YBKDwMqhpT83iUFg5dCiP4uKsw+fYac/k0W28/3UqD8730+Nl26iPyHdJAaBlaM/AC2yne+npj+wkDSl4uyjP2ADnTbQaaM/5/up8dJNoj++nxov3SSmPxb3mgtJU6o/rlbHBA/mqT9eukkMAiu3Pzb78Bl2BbA/wxP1b4Qyqj+kjgkezBOlP6SOCR7ME6U/tOZC0pSKoz8zUf9GKKOnP+cKkHvNhaQ/UKtjggfzpD/DBA/mifqnP1hXgNxrLqQ/+HGvuZA0pT+P4ME8Uf+mP3YwT9S/EcY/7FG4HoXroT9YSJpScfahP5MYBFYOLaI/szomeDBPtD+e/o1QRm+7P/y411xImrI/JQaBlUOLrD+o5BdLfrGkP8DobVmrY6I/xT58hl0Boj9MRm/LWh2jP1hmZmZmZqY/XK2OCR7Moz9U8oslv1iiP8DobVmrY6I/wOhtWatjoj/FPnyGXQGiPxkiIiIiIqI/j8L1KFyPoj/b+X5qvHSjPz81XrpJDKI/7FG4HoXroT/sUbgeheuhP8DobVmrY6I/j8L1KFyPoj9sBci95kKiP/p+arx0k6g/AC2yne+npj8UzBP1b4SiP6jVMcGDeaI/bAXIveZCoj8QdgXIveaiP6jVMcGDeaI/qNUxwYN5oj8AD+aJ+jeiP3XAyqFFtqM/qOQXS36xpD9ovp8aL92kP6R/I5TR26I/YAOdNtBpoz+TGARWDi2iP1TyiyW/WKI/PzVeukkMoj91wMqhRbajP2wUrkfheqQ/wOhtWatjoj8730+Nl26iP+Olm8QgsKI/TEZvy1odoz+kfyOU0duiP9eyVscED6Y//uNecyFpqj/l7u7u7u6uP5kLSVMqzrY/pH8jlNHbsj8dWmQ730+tP5ZDi2zn+6k/nOLsw2fYpT9I8GCeqH+jP5h9+Ay7AqQ/j9HbslbHpD9sFK5H4XqkP1TyiyW/WKI/AA/mifo3oj/jpZvEILCiP4/C9Shcj6I/eRbZzvdToz/wtqzVMcGjP8DobVmrY6I/j8L1KFyPoj+o1THBg3miPwAP5on6N6I/tOZC0pSKoz+PwvUoXI+iPzvuNReSpqQ/oCkVZx8+oz9gA5020GmjP2Roke18P6U/UJx9+Ay7oj9MRm/LWh2jP5M20GkDnaY/L90kBoGVoz/4YskvlvyiP8DobVmrY6I/xT58hl0Boj8/NV66SQyiP+xRuB6F66E/7FG4HoXroT+sK0DuNReiP+xRuB6F66E/7FG4HoXroT/sUbgeheuhPw/K6G1Zq7s/7nw/NV469z9OG+i0gQ4SQJb8YskvFhJALfnFkl8sC0AUrkfhepQAQFnyiyW/WP4/6LSBThvoAkDXo3A9CtcIQIiIiIiIiAdACtejcD0K/T9Di2zn+6nhPzxR/0Yoo9M/tWWtjgkezD9D/RuhjN7GP4ts5/up8cI/RIts5/upwT/clrU6JnjAPyPq3whl9L4/nv6NUEZvuz/9VQ4tsp23Py/sCpB7zbU/boQyelvWsj8lFWcfPsOuP+58PzVeurE/ke18PzVesj+9EcrobVmzP4AH80T9G7E/Lk/UvxHKsD877jUXkqa0P30/NV66Saw/8uEz7AqQqz89Gb0ta3WsP05x9uEz7Ko/AklTKs4+rD+JQWDl0CKrP3fcay4kTak/pH8jlNHbsj/A6G1Zq2OiP+xRuB6F66E/7FG4HoXroT9YSJpScfahPy/sCpB7zaU/N5gn6t8IpT/Jo3A9CtejP7hLN4lBYKU/j8L1KFyPoj8/NV66SQyiP+xRuB6F66E/wOhtWatjoj/jtIFOG+ikP5iM3pa1OqY/L90kBoGVoz8IyuhtWaujP1CrY4IH86Q/qNUxwYN5oj8ZMQisHFqkP3sjlNHbsrY/wq4AuddcxD/l0CLb+X7QPz6nDXTaQM8/7FG4HoXrxT/3xZJfLPm1PzNg5dAi26k/O/0boYzepj+c0wY6baCjP0xVVVVVVaU/sJA0peLsoz+c4uzDZ9ilPz9TKs4+fKY/hyW/WPKLpT/fT42XbhKjP8U+fIZdAaI/PzVeukkMoj9QnH34DLuiP4cW2c73U6M/rCtA7jUXoj99bOf7qfGiP+Olm8QgsKI/daL+jVBGvz+1OiZ4ME/SPw7mifo3QtE/3SQGgZVDwz/4U+Olm8S4P0u4HoXrUbg/ZxKDwMqhtT8uT9S/EcqwP9TqmODBPLE/QOF6FK5HsT9JfrHkF0u2PyPb+X5qvLw/h8+wK0DuwT+mqqqqqqq6Pw2fYVeA3LM/YOXQItv5rj9WHRM8mCeqP76uALnXXKg/pJ3vp8ZLpz8K9W+EMnqrPwJJUyrOPqw/qPP91Hjppj/PBjptoNOmP99PjZduEqM/RJpScfbhoz8dhxbZzvejP5h9+Ay7AqQ/w/UoXI/CpT/nCpB7zYWkP99PjZduEqM/eyOU0duypj81fIZdAXKvP9NNYhBYObw/mVJx9uEzxD8BnTbQaQPFP7SBThvotNU/dEzwYJ6o7T8HOm2g0wbsP+nfCGX0ttw/Bx7ME/VvyD/aay4kTam4P2XYFSD3mrM/Y56ofyOUsT/8uNdcSJqyP5zi7MNn2KU/ukkMAiuHpj+AB/NE/RuxP7gta3VM8Lg/hfo3Qhm9rT8jCKwcWmSrP1Ys+cWSX6w/6TUXkqZUrD/jw2fYFSCnP8u/Ecrobak/CKwcWmQ7rz9/iIiIiIioPxKDwMqhRaY/O/0boYzepj/6fmq8dJOoPwafYVeA3Ks/rEkMAiuHpj+PwvUoXI+iP6R/I5TR26I/8Las1THBoz/fT42XbhKjPzeJQWDl0KI/fWzn+6nxoj8K16NwPQqnP/LSTWIQWKk/P1Mqzj58pj+TNtBpA52mPxTME/VvhKI/AA/mifo3oj/sUbgeheuhPw4tsp3vp6Y/+HGvuZA0pT8SoYzelrWqP9eyVscED6Y/aL6fGi/dpD/A6G1Zq2OiP8U+fIZdAaI/DCD3mgtJoz8zMzMzMzOjPwAtsp3vp6Y/g96WtTomqD+05kLSlIqjP/QMuwLkXqM/PQrXo3A9wj+LirMPn2GnP+xRuB6F66E/PzVeukkMoj9QnH34DLuiP2ADnTbQaaM//LjXXEiaoj8nMQisHFqkPyR4ME/Uv7E/f2q8dJMYpD9vEoPAyqGlP5ebxCCwcqg/CLsC5F5zsT82+/AZdgWwP99ecyFpSqU/tOZC0pSKoz8AD+aJ+jeiP+xRuB6F66E/aK+5kDSloj8UzBP1b4SiP2Roke18P6U/oEW28/3U0D+2rNUxwYPbP06Nl24Sg9I/ZmZmZmbm8T/yiyW/WDITQJ020GkDXR5AR+F6FK4HGECkcD0K12MQQBERERERkQRA7FG4HoXr/j9VVVVVVVX6P/8boYzeluk/WYDcay4k3T+jKRVnHz7ZPzCW/GLJL9Y/uKzVMcGD1T8meDBP1L/TP6Xi7MNn2NE/HcwT9W+E0D+J+jdCGb3JP+Dsw2fYFcg/KVyPwvUoxD+oHFpkO9/DP/WaC0lTKsY/gAfzRP0bxT9D/RuhjN7CPzKl4uzDZ8A/SPBgnqh/oz+iY4IH80StP6RwPQrXo7g/Y7x0kxgEtj+cxCCwcmi5P0bF2YfPsLM/vzxR/0Youz9ooNMGOm24P6JFtvP91Mg/62CeqH8jtD/l3whl9LasP5VhV4Dca64/6KfGSzeJsT89CtejcD2yP7YgsHJoka0/0r8RyuhtsT+icmiR7XyvPw48mCfq37A/RIts5/upsT/I6G1Zq2OyP+XQItv5frI/TnH24TPssj/I6G1Zq2OyP5huEoPAyrE/1iQGgZVDsz+1Za2OCR60P3QFyL3mQro/c2iR7Xw/xT+R7Xw/NV7KPzpR/0Yoo78//UYoo7dltT/KItv5fmq0P4JBYOXQIrM/pH8jlNHbsj98seQXS36xP0oqzj58hq0/yYWkKRVnrz85w64AudesPzVeukkMAqs/dZMYBFYOrT9q2kCnDXSqPy/dJAaBlcM/Gui0gU4bxD+ONKXi7MO3Pxzb+X5qvLQ/sqzVMcGDsT+NtTomeDCvP4GkKRVnH64/N5gn6t8IpT8AHswT9W+kP1CrY4IH86Q/ZnVM8GCeqD/ByqFFtvOtP+XfCGX0tqw/+ICVQ4tspz9acyFpSsWpP5Mn6t8IZaQ/uEs3iUFgpT8rlvxiyS+mP76uALnXXKg/thHK6G1Zqz+NplScffisP4aIiIiIiLA/efgMuwLkrj9I/0Yoo7elP1pkO99Pjac/DjyYJ+rfqD/6jVBGb8uqP7pn2BUg96o/d9xrLiRNqT9MZDvfT42nP8u/Ecrobak/f2q8dJMYpD9MRm/LWh2jP2ADnTbQaaM/cWq8dJMYpD9iHz7DrgCpP6JUnH34DKs/x1odEzyYpz9I/0Yoo7elP9CUirMPn7E/u+ZC0pSKsz/+415zIWmqP6wrQO41F6I/5wqQe82FpD+o5BdLfrGkP4clv1jyi6U/i3vNhaQppT9BGb0ta3XAP1yPwvUoXK8/UJx9+Ay7oj9YV4Dcay6kP76fGi/dJKY/17JWxwQPpj9xarx0kxikP28haUrF2ac/vKFFtvP9pD8ML90kBoGlPxfotIFOG6g/yYWkKRVnrz8xJngwT9SvP9nO91Pjpas/+ICVQ4tspz/0KocW2c6nPxkxCKwcWqQ/UKtjggfzpD+R/GLJL5asP90z7AqQe60/SPBgnqh/oz/jpZvEILCiP/zHveZC0qQ/VAFyr7mQpD+pY4IH80TFPycxCKwcWrw/1hUg95oLuT/ErgC511zjPzfQaQOdtgtAEHTaQKfNEkC5HoXrUbgQQAAAAAAAAAlA7+7u7u7uAUD1KFyPwvX5P7xJDAIrh+4/a3VM8GCe5D9fLPnFkl/gP7uQNKXi7N8/UI2XbhKD2j//jVBGb8vUP6uqqqqqqtI/uB6F61G40j8fzBP1b4TSP3npJjEIrNI/jZduEoPA0j83Qhm9LWvRP/tiyS+W/M4/x5JfLPnFyj/61HjpJjHIP440peLsw8c/5m1Zq2OCxz9jZmZmZmbGP4WkKRVnH8Y/82+EMnpbxj/E2YfPsCvEP64AuddcSMI/dZMYBFYOwT/d3d3d3d3BP6bi7MNn2ME/rNUxwYN5wj9Y8oslv1jCP9NNYhBYOcQ/bstaHRM8xD+DeaL+jVDCP3N3d3d3d7c/ZErF2YfPuD+6WPKLJb+4P+rSTWIQWLk/47SBThvovD93vp8aL928P3QFyL3mQro/tNdcSJpSuT9KG+i0gU67P5w20GkDndY/1QY6baDTBEDkF0t+seQLQHsUrkfh+gJA5RdLfrHk9D9ImlJx9uHrP6k4+/AZduU/IiIiIiIi4z+RNKXi7MPhP5gn6t8IZeA/q2OCB/NE3T9jV4Dcay7aP0NERERERNg/4XoUrkfh2D8uJE2pOPvUP4XrUbgehdE/72CeqH8jzD8AAAAAAADMP4relrU6Jsw/2msuJE2pzD+6SQwCK4fOPzltoNMGOs0/ZmZmZmZmxj/2KFyPwvXAP7M6JngwT8A/9ihcj8L1wD/14TPsCpDDP1pkO99PjcM/dEzwYJ6owz+AB/NE/RvBP6RwPQrXo8A/9P3UeOkmwT9bq2OCB/PAP05iEFg5tMA/dZMYBFYOwT9Z1uqY4MHAP9YVIPeaC8E/001iEFg5wD/TTWIQWDm8P3CvuZA0pbo/V7pJDAIrtz+JUEZvy1q1P8SSXyz5xbI/PqcNdNpAtz+YffgMuwK8PzeJQWDl0Lo/wwQP5on6tz+sHFpkO9+3P5+M3pa1OrY/epVDi2znsz+VUnH24TO0P0Uoo7dlrbY/nNMGOm2gsz8EZfS2rNWxP2Xn+6nx0rU/ICIiIiIisj/SzvdT46WzP37cay4kTbE/MHpb1uqYsD8/NV66SQyyPzMzMzMzM7M/j8L1KFyPsj8c2/l+ary0P0jhehSuR7E/hF0Bcq+5sD/umgtJUyquP0Jvy1odE6w/hfo3Qhm9rT9G1L8RyuitP/7yRP0boaw/5e7u7u7urj9WDi2yne+nP2IfPsOuAKk/vq4AuddcqD/ufD81XrqpP5HtfD81Xqo/jZduEoPAqj+F61G4HoWrP4GkKRVnH64/9BuhjN6WpT/4gJVDi2ynPz9TKs4+fKY/sJ8aL90kpj89Gb0ta3WsP4GVQ4ts56s/ObTIdr6fqj8CSVMqzj6sP+PDZ9gVIKc/XskvlvxiqT9vIWlKxdmnP1hmZmZmZqY/OcOuALnXrD82+/AZdgWwP2iR7Xw/Na4/2c73U+Olqz9iHz7DrgCpP+kmMQisHKo/WFeA3GsupD+TJ+rfCGWkP+coXI/C9ag/aKDTBjptsD9I4XoUrkexPwisHFpkO68/5dAi2/l+qj85tMh2vp+qP0Jvy1odE6w/iUFg5dAiqz/l3whl9LasPyG/WPKLJa8/sHJoke18rz+VYVeA3GuuP5VScfbhM6w/sqzVMcGDsT/Vh8+wK0C+P+YmMQisHMo/dnd3d3d3zz9P/0Yoo7fFPzpg5dAi27k/FVpkO99PtT8YdgXIveayP4RdAXKvubA/qg+fYVeArD/DE/VvhDKqP+GJ+jdCGa0/aKDTBjptsD/pJjEIrByqP4lQRm/LWq0/uEs3iUFgpT/TXEiaUnGmP4/gwTxR/6Y/hzSl4uzDpz+wcmiR7XyvPxVLfrHkF7M/9P3UeOkmsT9acyFpSsWxP6RwPQrXo7A/5dAi2/l+sj9U8oslv1iyP3YwT9S/EbI/OcOuALnXtD8Sg8DKoUXCP09Gb8taHcc/sHJoke18vz9l5/up8dK1P/nwGXYFyLU/C0lTKs4+0D820GkDnTbhP+wKkHvNheU/jSW/WPKL9D9J4XoUrkfyP7y7u7u7u/g/TxvotIFO+z+kcD0K16P7P36x5BdLfvM/FPVvhDJ66j+RplScffjhPyvOPnyGXeA/pSkVZx8+2z9+I5TR27LYP1XHBA/midQ/aJHtfD811D/9YskvlvzSP+iY4ME8Uc8/fPgMuwLkzj9+I5TR27LQP+Lsw2fYFdA/ZdgVIPeayz8ZWmQ730/JP+01F5KmVMg/46WbxCCwxj+3SQwCK4fGPxrotIFOG8g/N0IZvS1ryT/78Bl2BcjTP/vwGXYFyN0/bS4kTak47j9xPQrXo3D8PxAREREREe4//WLJL5b84D8IrBxaZDvbP3npJjEIrNg/2/l+arx04T+4HoXrUbj/Pylcj8L1qANAFK5H4XoU+z99arx0kxjsP6NFtvP91Oc/veZC0pSK4z+3HoXrUbjiP519+Ay7At4/n6h/I5TR2z9vEoPAyqHTP4AjlNHbstI/CR7ME/Vv0j8CK4cW2c7RP73mQtKUitM/XI/C9Shc1T+xK0DuNRfUP1jyiyW/WNI/AiuHFtnO0T+/5kLSlIrRP23n+6nx0uw/4XoUrkfhAkBz2kCnDXQCQB6F61G4nvQ/JE2pOPvw5z/MzMzMzMziPxi9LWt1TOE/ZfS2rNUx4j8Bcq+5kDTiP7sC5F5zIeE/PJgn6t8I4D+Nl24Sg8DeP7SBThvotN0/6SYxCKwc3j+gGi/dJAbbP8UgsHJokdk/PCZ4ME/U2T9z2kCnDXTYPy1rdUzwYNg/fYZdAXKv2T8AK4cW2c7XP2Q730+Nl9Y/3SQGgZVD1z8IZfS2rNXVP30/NV66SdQ/ugLkXnMh0z/b+X5qvHTTP3YFyL3mQtQ/rBxaZDvf0z9kyS+W/GLRP8KuALnXXMw/3d3d3d3dzT/P91PjpZvMP8a95kLSlM4/sHJoke18zz/fT42XbhLVP10Bcq+5kNo/SOF6FK5H1T8EVg4tsp3LP+WJ+jdCGck/zczMzMzMyD9mZmZmZmbKPxaSplScfcg/lyfq3whlyD8aoYzelrXGP+NecyFpSsU/TmIQWDm0xD8q+cWSXyzFP2xZq2OCB8M/gU4b6LSBxj+sHFpkO9/HP/9xr7mQNMk/5/up8dJNyj800GkDnTbIP1sBcq+5kMg/VOOlm8QgyD93vp8aL93IP3npJjEIrMg/sQ+fYVeAyD+NUEZvy1rJP1Eqzj58hsk/dEzwYJ6oxz90Bci95kLGP4QW2c73U8c/9wy7AuRexz/vGXYFyL3GP+8ZdgXIvcY/sp3vp8ZLxz/bslbHBA/GP0K28/3UeMU/it6WtTomxD/KWh0TPJjDP4FOG+i0gcI/NV66SQwCwz9pLiRNqTjDP4XrUbgehcM/z/dT46WbxD9RcfbhM+zGP98IZfS2rNM/e82FpCkV4j8JZfS2rNXgP4QyelvW6tQ/7AqQe82F5T8NdNpAp40BQE8b6LSBzgBAjZduEoPA6j8LHswT9W/eP+0KkHvNhdo/0SLb+X5q1j/lifo3QhnXP5HtfD81XtQ/xNmHz7Ar1D/HSzeJQWDTP06Nl24Sg9I/o7dlrY4J1j9soNMGOm3WPwwCK4cW2dQ/1DHBg3mi0j8o6t8IZfTSP9S/EcrobdM/5/up8dJN0j8neDBP1L/RP1pkO99Pjdk/FSD3mgtJ4j8OLbKd76fhP9v5fmq8dNs/LPnFkl8s1z+c76fGSzfVPxt2Bci95tI/001iEFg52j8ZvS1rdYwBQBdLfrHkFw9AodMGOm0gCkD2KFyPwnUDQH+x5BdL/gZAZmZmZmamEECx5BdLfjEJQIXrUbgehQFAQacNdNpA+D9+seQXS37zP0maUnH24fA/mW4Sg8DK6j/Fkl8s+cXnP4frUbgeheY/n6h/I5RR9D8b6LSBTtsSQBSuR+F6VBdAAQAAAAAAGkCdNtBpA90XQFhVVVVVVQxAXY/C9ShcBUD8YskvlnwDQLgehetRuP4/VVVVVVVV9j/QaQOdNtAKQASdNtBpwxdAVVVVVVVVF0CPwvUoXA8QQMSSXyz5RSRAzczMzMxMMEAjIiIiIuI3QDMzMzMzczlAiIiIiIioOUAhIiIiIgI5QLu7u7u7WzRAzczMzMzMKkBmZmZmZgYiQIiIiIiI6CJABzptoNMGIUDNzMzMzAwXQIFOG+i0gQ5A6LSBThtoCEBxPQrXo/AFQHE9CtejcAJAVVVVVVVV9j8BAAAAAAD0PxdLfrHkF/I/SgwCK4cW8D/ziyW/WPLrP9QGOm2g0+k/09uyVscE5z8o6t8IZfTkP58aL90kBuM/TxvotIFO4z+gGi/dJAbiP++nxks3ieA/NxeSplSc4D/9qfHSTWLgP1Y5tMh2vt8/OW2g0wY63z+PUEZvy1rdPxXZzvdT490/EmcfPsOu3D8/NV66SQzcP+zDZ9gVINs/A5020GkD2z/tNReSplTaPz/uNReSptg/qX8jlNHb1j9UDi2yne/XP9LbslbHBNc/3LJWxwQP1j9cukkMAivVP55hV4Dca9Q/xSCwcmiR0z/7N0IZvS3TP8/3U+Olm9I/es2FpCkV0z/2U+Olm8TSP2OCB/NE/dE/PFH/Riij0T9kO99PjZfQPzMzMzMzM88/R1Mqzj58zj9p5/up8dLNPxzME/VvhM4/Vg4tsp3v0T9VVVVVVVXRP7TIdr6fGtE/pLdlrY4J0D8C5F5zIWnOP2T0tqzVMdE/ggfzRP0b0T91kxgEVg7RP5/TBjptoNE/QKcNdNpA0T9FRERERETQP166SQwCK88/ukkMAiuH0D+DwMqhRbbPP/FE/RuhjM4/p38jlNHbzj8TIPeaC0nPP8EgsHJokc0/EoPAyqFFyj8m6t8IZfTGP6ljggfzRMk/JurfCGX0yj/xRP0boYzKP/Z+arx0k8w/W7pJDAIrzz+Ksw+fYVfQP+f7qfHSTdA/K4cW2c73zz8H80T9G6HSPxKDwMqhRdY/84slv1jy1z/UBjptoNPWP6WbxCCwcuE/0WkDnTbQ8D/4U+Olm8TlP1nyiyW/WNw/0LArQO412z8fsHJoke3WP/hT46WbxNo/6wqQe82F7j9kyS+W/GLpP23n+6nx0t8/XQFyr7mQ4D8Bcq+5kDTsP9S/Ecrobew/dwXIveZC4z/lifo3QhnfP6uqqqqqqtw/o7dlrY4J3D/W6pjgwTzbP5t9+Ay7Ato/7Xw/NV664z+ZUnH24TPsP6GM3pa1Oug/xK4Auddc4z/xYJ6ofyPeP0B8hl0Bcts/m1Jx9uEz2j/BPFH/RijXP3cFyL3mQtY/8Bl2Bci91D9g5dAi2/nSP+F6FK5H4dI/m334DLsC1D9hV4Dcay7SP8yFpCkVZ9E/BQ/mifo30j9tWatjggfRP9Ei2/l+atA/ZDvfT42Xzj/n+6nx0k3OP7gehetRuM4/k9HbslbHzD+4HoXrUbjKPwLkXnMhaco/gAfzRP0byT87mCfq3wjJP9NNYhBYOcg/sQ+fYVeAyD81F5KmVJzJP1NVVVVVVck/IyIiIiIiyj+kt2WtjgnKPx1aZDvfT8k/vljyiyW/yD+K3pa1OibIP/XhM+wKkMc/ukkMAiuHxj8qQO41F5LGP6Pi7MNn2MU/EjyYJ+rfxD8PyuhtWavDP5KKsw+fYcM/jZduEoPAwj/zb4QyelvCP64AuddcSMI/1hUg95oLwT+411xImlLBP3cFyL3mQsI/kkOLbOf7wT++WPKLJb/APx4GgZVDi7w/H5TR27JWtz/KE/VvhDK6PyuHFtnO97s/CuaJ+jdCuT//ca+5kDS9P6c4+/AZdsE/TdS/EcrowT9zaJHtfD/BP9IGOm2g08I/t5A0peLswz8R9W+EMnrDPwGdNtBpA8U/l+DBPFH/xj9IN4lBYOXMP6AaL90kBuQ/WPKLJb9YAECBThvotAEKQEjhehSuRw9AXyz5xZIfEEBY8oslv9gLQI/C9ShcDw1AKVyPwvUoBUASEREREZECQJFfLPnFEgFASgwCK4cW8j8RERERERHrPyFpSsXZh+Y/QacNdNpA5D9jO99PjZfiPz98hl0BcuA/nDbQaQOd3D+WtTomeDDbP1Nx9uEz7No/dkzwYJ6o2T+lKRVnHz7ZP3L24TPsCtg/8NJNYhBY1z+xK0DuNRfWP8uhRbbz/dQ/q6qqqqqq1D9lrY4JHszTPwIrhxbZztM/jVBGb8ta0z+ZUnH24TPSP7eQNKXi7M8/1hUg95oLzT8QWDm0yHbOP8vobVmrY84/pVScffgMzz+dYVeA3GvOP90kBoGVQ88/AiuHFtnOyz++nxov3STOPwqQe82FpM0/+fAZdgXIzT8ozj58hl3NP9TqmODBPM0/XI/C9Shc0T+EMnpb1urWP1OcffgMu9w/A5020GkD3z/XzvdT46XdP3D24TPsCtw/r+QXS36x2j9b1uqY4MHYP+htWatjgtc/u7u7u7u71z9yIWlKxdnVP4izD59hV9Q/1L8Ryuht0z9YObTIdr7RP9QxwYN5os4/yC+W/GLJyz8wT9S/EcrQP1eA3GsuJNE/gU4b6LSBzj/E2YfPsCvMPwisHFpkO8c/oykVZx8+xz8z7AqQe83FP8paHRM8mMM/Gy/dJAaBxT8BnTbQaQPFP7JWxwQP5sU/7xl2Bci9xj8cEzyYJ+rHP8yFpCkVZ8c/zz58hl0Bxj8welvW6pjEP/7UeOkmMcQ/p38jlNHbwj/ufD81XrrBP4lQRm/LWr0/exSuR+F6wD877jUXkqa8PxKDwMqhRb4/tvP91Hjpwj/rCpB7zYXEP/+411xImsY/IpTR27JWwz/CZ9gVIPfCP1jyiyW/WMI/BFYOLbKdwz9xPQrXo3DFP8Jn2BUg98Y/Q0REREREyD8NdNpApw3QP28Sg8DKofE/7FG4HoXrCUBdj8L1KNwIQKuqqqqqqvY/n4zelrU67j/w7u7u7u7mP0HuNReSpuE/peLsw2fY4D8Sg8DKoUXeP9bqmODBPNs/Qots5/up1z8DnTbQaQPZP6UpFWcfPtU/11xImlJx0j+UirMPn2HTPw4tsp3vp9Q/WmQ730+N0z/sfD81XrrTP2fYFSD3mtM/yb3mQtKU0j+Y4ME8Uf/QP3WTGARWDs0/QHyGXQFyzz+/PFH/RijPP9uyVscED9A/+/AZdgXI0T8QWDm0yHbQP93d3d3d3c0/xNmHz7AryD/xiyW/WPLHPwwCK4cW2cY/V6tjggfzxD+4HoXrUbi+P6Pi7MNn2MU/aErF2YfPzD/DPFH/RijLP7bz/dR46co/kkOLbOf7yT+9yqFFtvPJP0K28/3UeMk/27JWxwQPyj89CtejcD3QP7HkF0t+sdA/PcOuALnX0D/8qfHSTWLQP+Olm8QgsNA/ImlKxdmH0T+DwMqhRbbRP3ii/o1QRtM/q2OCB/NE1T+eGi/dJAbVP2L0tqzVMdU/g3mi/o1Q1D+J+jdCGb3TPyd4ME/Uv9M/hxbZzvdT0z+IiIiIiIjSP0/UvxHK6NE/kl8s+cWS0T+cxCCwcmjRP1vW6pjgwdA/p38jlNHb0D9GKKO3Za3QP8m95kLSlNA/4hdLfrHkzz9mZmZmZmbQP4FOG+i0gc4/gjJ6W9bqzD/Hkl8s+cXKP5GmVJx9+MQ/9wy7AuRewz9+I5TR27LGP2Dl0CLb+cI/nah/I5TRxz/t7u7u7u7KP+p8PzVeusk/KVyPwvUoyD/0/dR46SbJP5GmVJx9+Mg/wq4AuddcyD9SuB6F61HIP1odEzyYJ8o/DLsC5F5zyT+LbOf7qfHKP4N5ov6NUMo/BfNE/RuhyD95ME/UvxHKP/IoXI/C9cg/QNKUirMPxz83iUFg5dDKP8EgsHJokck/FGcfPsOuyD+MCR7ME/XHPzb78Bl2Bcg/1XjpJjEIyD+1Za2OCR7IP6MpFWcfPsc/kaZUnH34yD8ozj58hl3JP7as1THBg8k/dwXIveZCyj8ePsOuALnLPypA7jUXks4/2kCnDXTa0j+j/o1QRm/dP8SuALnXXOc/nxov3SQG6z/BPFH/RijrPxFYObTIdus/sHJoke187D+/WPKLJb/sPxzotIFOG+0/TmIQWDm07j91kxgEVg7wPxP1b4Qyeuk/qDj78Bl24z8X2c73U+PgPwRWDi2ynd8/2ofPsCtA3j9LqTj78BnePyJNqTj78N0/lm4Sg8DK3T81F5KmVJzdP0vF2YfPsN0/CpB7zYWk3T9TcfbhM+zeP/fhM+wKkN8/jZduEoPA4D9bHRM8mCfhPy5rdUzwYOA/54n6N0IZ3T8s+cWSXyzbPzm0yHa+n9g/tIFOG+i01T+/yqFFtvPVP21Zq2OCB9c/hxbZzvdT1T8Sg8DKoUXSP03wYJ6of9M/S/Bgnqh/0z/qUbgehevTPy4kTak4+9Q/peLsw2fY1T8zMzMzMzPXPzvfT42XbtY/Z9gVIPea0z81XrpJDALTP+f7qfHSTdI/9G+EMnpb0j8WkqZUnH3SP4ts5/up8dI/+FPjpZvE0j8GgZVDi2zRPxBYObTIdtI/rkfhehSu0T88Uf9GKKPRP+7u7u7u7tA/gU4b6LSB0D8wlvxiyS/QPycxCKwcWtA/8Yslv1jyzz/9G6GM3pbRP76fGi/dJNI/3Ja1OiZ40j/tNReSplTeP5iZmZmZmec/l24Sg8DK6T+UXyz5xZLuP5b8YskvlgNAvljyiyW/D0ClcD0K16MEQFG4HoXrUfU/DAIrhxbZ7z9TKs4+fIbuP3XaQKcNdPQ/Sn6x5BdL9D/v7u7u7u4BQB+F61G4Hv8/TxvotIFO9D+x5BdLfrHzP6cNdNpAp/8/oNMGOm2g+D8UrkfhehTzPwvXo3A9CvE/yS+W/GLJ8z/ptIFOG+jzPyijt2WtDvA/2BUg95oL6j8klNHbslblPzn78Bl2BeQ/tvP91Hjp4z9n2BUg95riP1+6SQwCK+A/y6FFtvP92j/IL5b8YsnZP2q8dJMYBNw/H8wT9W+E2j8+fIZdAXLZP78RyuhtWds/F9nO91Pj2T8AK4cW2c7XP1TjpZvEINo/rBxaZDvf2T/PPnyGXQHaP5HtfD81Xto/IGlKxdmH2z+F61G4HoXiP6wcWmQ73+c/u0kMAiuH5j+DeaL+jVDpP2MQWDm0yOU/mwtJUyrO4T8v3SQGgZXdP1urY4IH89w/gwfzRP0b4j+EeaL+jVD5P0p+seQXSwJAN9BpA522B0CF61G4HsUVQDCW/GLJLxZApHA9CtcjGED3KFyPwvUgQHsUrkfhuiRAIyIiIiKiJEBoZmZmZmYeQNQGOm2gExVAw/UoXI+CGEAOdNpAp00UQK/kF0t+sQ5Ar0fhehQuCUCF61G4HgUHQOF6FK5H4QVAs+QXS36x/z8AAAAAAAAAQO/u7u7u7gNAH4XrUbge/z/hehSuR+H1PxhLfrHkF/M/MTMzMzMz8j+nDXTaQKfxP6DTBjptoPA/Xyz5xZJf7j+fqH8jlNHrP6Xi7MNn2Ok/1b8Ryuht5z/5xZJfLPnlP1BGb8taHeY/R7bz/dR45T/rCpB7zYXjP6DTBjptoOE/EcrobVmr4T/IBA/mifrgP9CwK0DuNeA/HcwT9W+E4D8XIPeaC0ngP4GVQ4ts598/TfBgnqh/3z9PG+i0gU7gP4slv1jyi98/2yQGgZVD3T+TGARWDi3eP4PAyqFFtt8/1uqY4ME83z+/yqFFtvPbP3sUrkfhetw/haQpFWcf2j9GKKO3Za3WP98IZfS2rNM/O99PjZdu1D/Ag3mi/o3UP0jhehSuR9U/sw+fYVeA1j9iyS+W/GLVPxUg95oLSdU/8Bl2Bci90j/VeOkmMQjSP5A0peLsw9E/hetRuB6F0z9Apw102kDVPx4+w64AudM/vOZC0pSK6z/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP/D91HjpJu0/8P3UeOkm7T/w/dR46SbtP+9gnqh/I+4/gU4b6LSB6z+j/o1QRm/mP/W2rNUxweI/KVyPwvUo4D8nMQisHFrePz81XrpJDN4/HOi0gU4b3j9KfrHkF0vePzMzMzMzM9s/7QqQe82F2D+NUEZvy1rXP8/3U+Olm9Y/DXTaQKcN1j/UvxHK6G3VP0bhehSuR9U/nX34DLsC1D+cxCCwcmjTPzEIrBxaZNM/7u7u7u7u0j/jpZvEILDQP9j5fmq8dM8/5dAi2/l+zj/WMcGDeaLQPyGwcmiR7dA/dgXIveZC0D+UtTomeDDPPyVNqTj78M0/6nw/NV66zT+3kDSl4uzLP+rDZ9gVIMs/dwXIveZCyj+V/GLJL5bMP/O2rNUxwcs/OlH/Riijyz9VxwQP5onKPzuYJ+rfCMk/2c73U+Olxz9uy1odEzzIP8TZh8+wK8g/ubu7u7u7xz95PzVeuknIPwLkXnMhacY/kxgEVg4txj9zr7mQNKXGP+3u7u7u7sY/UXH24TPsxj+1Za2OCR7IP41QRm/LWsk/Y62OCR7Mxz+XJ+rfCGXIP8CDeaL+jcg/rBxaZDvfxz9yIWlKxdnHPzKl4uzDZ8g/tIFOG+i0yT8730+Nl27KP9IGOm2g08o/6wqQe82FzD+8LWt1TPDMP3tb1uqY4M0/SlMqzj58zj9uhDJ6W9bOPyajt2Wtjs0/c2iR7Xw/zT8LdNpApw3MPzltoNMGOsk/4OzDZ9gVzD8neDBP1L/NP6Pi7MNn2M0/ftxrLiRNzT9P/0Yoo7fNP2Q730+Nl84/T0Zvy1odzz9D/RuhjN7OPwQP5on6N84/Fy/dJAaBzT/4U+Olm8TMP7uQNKXi7Ms/m334DLsCzD+q8dJNYhDMPylcj8L1KMw/rbmQNKXizD8hsHJoke3MPzgmeDBP1Ms/Q/0boYzeyj9b8oslv1jKP2LJL5b8Ysk/j3vNhaQpyT800GkDnTbIP30/NV66Scg/NvvwGXYFyD9nA5020GnHPyH3mgtJU8Y/xJJfLPnFxj+h/o1QRm/HP2p1TPBgnsg/DuaJ+jdCyT85baDTBjrJP2rLWh0TPMg/HVpkO99PxT+411xImlLBP0xGb8taHbs/27JWxwQPxj/XXEiaUnHGP1NVVVVVVcU/O+41F5KmvD9y2kCnDXTCP0EZvS1rdcQ/vljyiyW/xD+GiIiIiIjMP90kBoGVQ8s/pVScffgMyz8LdNpApw3IPwPIveZC0sg/98WSXyz5yT9JfrHkF0vKPz81XrpJDMo/E9nO91PjyT+nfyOU0dvKP+XQItv5fso/M+wKkHvNzT+vuZA0peLQPx3ME/VvhNQ/O99PjZdu3j8fhetRuB7fPyOU0duyVuI/dEzwYJ6o7j9QjZduEoPqP9dcSJpSceM/c2iR7Xw/2z8jIiIiIiLYP9mHz7ArQNY/okW28/3U1D+EMnpb1urUP3IhaUrF2dU/dwXIveZC1D8vCKwcWmTXP0NERERERNY/uZA0peLs0T/hehSuR+HQP5MYBFYOLdA/FSD3mgtJ0T8730+Nl27SP2iR7Xw/NdI//WLJL5b80D8DnTbQaQPRP9gVIPeaC9E/eqL+jVBG0T+aC0lTKs7QP57vp8ZLN9E/r7mQNKXi1D9PRm/LWh3VP6k4+/AZdtE/anVM8GCezD9qvHSTGATKPxsv3SQGgc0/h8+wK0DuzT+lVJx9+AzPP3ii/o1QRtE/B/NE/Ruh0D8QWDm0yHbOP1Nx9uEz7NA/NOwKkHvN0z/n+6nx0k3WPxl2Bci95tI/JzEIrBxa0D9iEFg5tMjQPwqQe82FpNE/EZ9hV4Dczz9TRm/LWh3LP0x+seQXS8Y/5ELSlIqzxz8GgZVDi2zHP5lScfbhM8g/LbKd76fGyz/CveZC0pTOP+ZtWatjgs8/S6k4+/AZyj/xRP0boYzKP9v5fmq8dMs/y6FFtvP9zD8keDBP1L/NPx/ME/VvhM4/Wh0TPJgnzj95PzVeuknMPwlJUyrOPsw/1OqY4ME8zT/P91PjpZvMPzgmeDBP1Ms/EoPAyqFFzj8+pw102kDPP4qzD59hV9A/EFg5tMh20D+Y4ME8Uf/YP65H4XoUruA/B6wcWmQ74D9Ei2zn+6ngP4/C9Shcj9w/T0Zvy1od2T9DRERERETWP42XbhKDwNQ/6SYxCKwc1D9AYOXQItvTP/+411xImtI/Q0RERERE0j+V0duyVsfSP44JHswT9dM/w2fYFSD31D/hM+wKkHvTP3QhaUrF2dM/rwC511xI0j8OLbKd76fQPx/3mgtJU9A/FK5H4XoU0D+JQWDl0CLPP/hT46WbxMw/4uzDZ9gV0D+EXQFyr7nIP1ecffgMu8o//3GvuZA0zT/HveZC0pTQP9V46SYxCNA/SFMqzj580D/ah8+wK0DQPwkezBP1b9A/bxKDwMqh0z/p3whl9DbyP0RERERExApA5BdLfrFkCEDziyW/WPL6P+m0gU4b6PY/zczMzMzM9T9xPQrXo3DwP+f7qfHSTeg/rkfhehSu5D8MAiuHFtnjP9v5fmq8dOI/bqDTBjpt4T9aZDvfT43hP9gVIPeaC+E/ZvS2rNUx4D+8LWt1TPDePwhl9Las1d0/gjJ6W9bq3D8LSVMqzj7cPylcj8L1KNw/x73mQtKU3D9jggfzRP3sP5X8YskvlgNAPQrXo3A9+T+rqqqqqqr0P9ijcD0K1/U/FyD3mgtJ8T8cWmQ730/sP3vNhaQpFek/MXpb1uqY5T9KxdmHz7DjP39qvHSTGOI/hHmi/o1Q4T+3rNUxwYPgP8T1KFyPwt8/UyrOPnyG4D+dffgMuwLlP7MPn2FXgOE/YRBYObTI3j8O5on6N0LdPxwv3SQGgds/F9nO91Pj2T9eukkMAivZPxcg95oLSdk/SCijt2Wt2D9wEoPAyqHXP7ArQO41F9Y/3LJWxwQP1j+hjN6WtTrWP2vn+6nx0tU/j8L1KFyP1D9cj8L1KFzTP32GXQFyr9M/TfBgnqh/1T8f95oLSVPWP5JfLPnFktM/tzomeDBP0D86CtejcD3OPwhl9Las1c0/5ELSlIqzzz8fzBP1b4TOPybq3whl9M4/iIiIiIiI0D9qdUzwYJ7MP2Dl0CLb+co/iyW/WPKLyT/pJjEIrBzKP80T9W+EMso/J3gwT9S/yT/BILByaJHJP/GLJb9Y8ss/tMh2vp8axz9LqTj78BnGP99PjZduEsc//Knx0k1iyD9iyS+W/GLJP3rNhaQpFcs/HBM8mCfqyz+jKRVnHz7LP4n6N0IZvck/6nw/NV66yT+nOPvwGXbFPygVZx8+w8Y/U1VVVVVVxT8QWDm0yHbGP4XrUbgehcc/VOOlm8QgyD/VeOkmMQjEP00b6LSBTsM/jjSl4uzDwz+xD59hV4DEP7TIdr6fGsM/sCtA7jUXwj/KE/VvhDLCPyJNqTj78MU/JHgwT9S/wT8asHJoke28P7Kd76fGS78/byFpSsXZvz9uy1odEzzEP/4qhxbZzsM/q44JHswTxT9NG+i0gU7HPyUGgZVDi8A/+2LJL5b8xj9L8GCeqH/DPyKU0duyVsc/30+Nl24Sxz8UZx8+w67IP8KuALnXXMw/XwFyr7mQzD8GOm2g0wbKPz3DrgC518g/ciFpSsXZxz+v5BdLfrHIP4FOG+i0gco/qMZLN4lBzD+v5BdLfrHMP/yp8dJNYsw/Y62OCR7Myz9bukkMAivLPwhl9Las1ck/ScXZh8+wxz+T0duyVsfIPzpR/0Yoo8c/GHYFyL3mxj/jpZvEILDGP5RuEoPAysE/1OqY4ME8wT8YdgXIvebCP1WA3GsuJMU/AZ020GkDxT+75kLSlIrHPwsezBP1b8g/uNdcSJpSyT+dqH8jlNHHP4XrUbgehcc/hoiIiIiIyD9oSsXZh8/IP10s+cWSX8g/+FPjpZvEyD+pqqqqqqrGP/1GKKO3ZcU/BoGVQ4tswz/b+X5qvHTDP4QW2c73U8M/eTBP1L8Rwj8Sg8DKoUXCP9K/EcrobcU/c76fGi/dxD8R9W+EMnrDP7ArQO41F8I/rBxaZDvfvz9HmlJx9uHDP1K4HoXrUcA/Ik2pOPvwwT9kO99PjZfGPzPsCpB7zcU/0NuyVscExz/fT42XbhLDP8a95kLSlMI/bef7qfHSwT9vIWlKxdm/P6mqqqqqqsI/Vg4tsp3vwz+lVJx9+AzDP6mqqqqqqsI/BfNE/RuhwD+ht2WtjgnCP3cFyL3mQsI/cT0K16NwwT9oke18PzXCP8Jn2BUg98I/XxBYObTIwj8qQO41F5LCPwQP5on6N8I/wcqhRbbzwT8WkqZUnH3AP/NvhDJ6W74/U1VVVVVVwT/b+X5qvHTDPw2fYVeA3MM/EBERERERwT/FILByaJHFP68AuddcSNI/jVBGb8ta1T//uNdcSJrOP4ts5/up8cY/T0Zvy1odwz/Ag3mi/o3AP0vwYJ6of8M/XI/C9Shcvz/b+X5qvHS7P+Z8PzVeurk/d76fGi/dvD+UtTomeDC/P26EMnpb1sI/82+EMnpbvj/LoUW28/3APzx8hl0Bcrc/BFYOLbKdtz+Nl24Sg8C6P9NNYhBYObw/s0kMAiuHvj/lifo3QhnBP7VlrY4JHrw/vC1rdUzwwD/1mgtJUyq2P28Sg8DKobU/NNBpA502uD8keDBP1L+5P90z7AqQe70/6SYxCKwcwj9QnH34DLu6P42mVJx9+Lw/BGX0tqzVuT877jUXkqa8P7Ks1THBg7k/f3mi/o1Qtj8dWmQ730+9PyGwcmiR7cA/mqh/I5TRuz+411xImlLBPyUGgZVDi7w/vRHK6G1Zuz/vGXYFyL22P65WxwQP5rk/OcOuALnXvD/qfD81XrrBP7TIdr6fGsM/C3TaQKcNyD+QXyz5xZLDP1yPwvUoXL8/2msuJE2pwD9TZDvfT42/P4lBYOXQIsM/9P3UeOkmyT+dYVeA3Gu+Pz/uNReSpsA/g8DKoUW2uz/2N0IZvS2zP8MED+aJ+rc/99R46SYxuD916SYxCKzAP+iY4ME8Ub8/u/UoXI/CvT+VUnH24TO8P0SaUnH24bs/zwY6baDTvj/kQtKUirO/Py/dJAaBlbs/+fAZdgXIvT/Jdr6fGi/BP5zEILByaME/k9HbslbHwD/vKFyPwvW4P51hV4Dca7Y/RSijt2Wttj/zb4Qyelu2P3sUrkfherw/N5gn6t8IvT/NzMzMzMzAP8mFpCkVZ78/XTvfT42Xtj+R7Xw/NV6yP7M6JngwT7Q/USrOPnyGtT/2N0IZvS27P5BfLPnFkr8/KM4+fIZduT9kO99PjZe+P19XgNxrLrQ/kyfq3whltD/WFSD3mgu5Px1pSsXZh78/dekmMQiswD+j4uzDZ9jBP/T91HjpJsE/WmQ730+Nvz9A0pSKsw+/P6gcWmQ738M/oGFXgNxrxj/ewTxR/0bEP97BPFH/RsQ/wq4AuddczD+V/GLJL5bQP99PjZduEss/JHgwT9S/xT+MCR7ME/XDP2xZq2OCB8M/lLU6Jngwwz88fIZdAXLDP+iY4ME8UcM/0NuyVscEwz+s1THBg3nCPz3DrgC518A/w/UoXI/CvT/VeOkmMQi8P0DSlIqzD78/U5x9+Ay7wj9Y8oslv1jCP93d3d3d3cE/oHA9CtejxD9fZmZmZma+P1g5tMh2vr8/001iEFg5vD9aZDvfT42/P/sboYzelsE/uNdcSJpSwT9uy1odEzzAPxBYObTIdr4/xr3mQtKUuj85tMh2vp+6P9sIZfS2rL0/8uEz7AqQuz8HHswT9W+8PzgXkqZUnL0/GIXrUbgevT/aay4kTam4P+cKkHvNhbw/EGcfPsOuuD/0/dR46Sa5P5zTBjptoLs/QNKUirMPvz9zaJHtfD/BPyUGgZVDi7w/L+wKkHvNvT/7G6GM3pa9P7oC5F5zIcE/N0IZvS1rwT9SuB6F61HAPw2uR+F6FL4/dZMYBFYOvT+NplScffi8P0Uoo7dlrb4//3GvuZA0tT+sHFpkO9+3PwXzRP0bobw/QNKUirMPtz+cxCCwcmi5P2xZq2OCB7s/0THBg3mitj9t9uEz7Aq4P5VScfbhM7Q/EFg5tMh2tj9l5/up8dK1PxMg95oLSbM/H5TR27JWtz++rgC511y4Pxzb+X5qvLQ/S7gehetRuD+/SzeJQWC1PxzME/VvhLI/+n5qvHSTsD+AB/NE/RuxP7Kd76fGS7c/y7ArQO41tz8gMQisHFq0P5TEILByaLk/DZ9hV4Dcsz90Bci95kKyP2ig0wY6bbA/hxbZzvdTsz9vIWlKxdm3P2ig0wY6bbg/FVpkO99PtT+o1THBg3m6PyAiIiIiIrI/AklTKs4+rD/A2YfPsCuwPwRl9Las1bE/RTeJQWDluD+aqH8jlNG7P28haUrF2bc//uNecyFpuj95+Ay7AuS2P9sIZfS2rLU/vHSTGARWtj91ov6NUEa3P4aIiIiIiLg/hoiIiIiIuD8YhetRuB61PyuW/GLJL7Y/5/up8dJNsj8pa3VM8GCuP31OG+i0ga4/qgC511xIsj86Uf9GKKO3P8mFpCkVZ7c/BfNE/RuhtD92PzVeukm0P/QMuwLkXrM/oCkVZx8+sz+YffgMuwK0P+cKkHvNhbQ/WxBYObTItj+kcD0K16O4P9sIZfS2rLU/obdlrY4Jtj+tuZA0peK0P0bF2YfPsLM/GqGM3pa1sj9nA5020GmzPwwCK4cW2bY/daL+jVBGtz92ME/UvxGyP4JBYOXQIrM/7poLSVMqrj8zYOXQItupPzpg5dAi27E/WDm0yHa+rz95+Ay7AuS2P0P9G6GM3rY//Knx0k1isD+Xm8QgsHKoP7YRyuhtWas/bfbhM+wKsD9iHz7DrgC5P2324TPsCrg/bzBP1L8Rqj+qD59hV4CsP4IyelvW6rA/Ks4+fIZd0T9/eaL+jVC2P8u/Ecrobak/AC2yne+npj+TRbbz/dSoP19XgNxrLrQ/GIXrUbgetT/dQtKUirOvPxqhjN6WtbI/ZnVM8GCeqD+HJb9Y8oulP0Jg5dAi26k/prmQNKXirD/vGXYFyL22P3E9CtejcLU/dj81XrpJtD+sK0DuNReyPxKSplScfag/WGZmZmZmpj+Le82FpCmlP/QqhxbZzqc/ctpApw10sj+BlUOLbOezP5H8Yskvlqw/pHA9CtejsD8bPsOuALmnP1hXgNxrLqQ/hzSl4uzDpz9WHRM8mCeqPzEIrBxaZLM/pQ102kCntT9t5/up8dKtP2D0tqzVMbE/FveaC0lTqj+gR+F6FK6nP7K7u7u7u6s/WEiaUnH2sT+v5BdLfrG0P5s20GkDnbY/y7ArQO41tz+pcmiR7Xy3P2D0tqzVMbE/HYcW2c73oz9YZmZmZmamP+cZdgXIvaY/PzVeukkMsj89Gb0ta3W0P6RwPQrXo7A/EFg5tMh2rj/0KocW2c6nP5zi7MNn2KU/QmDl0CLbqT8zUf9GKKOnP1qR7Xw/Na4/aT0K16NwtT86YOXQItuxP/LSTWIQWLE/gaQpFWcfrj/PFSD3mgupPxKSplScfag/DjyYJ+rfqD+W76fGSzexP/C2rNUxwbM/prmQNKXirD8ypeLsw2ewP1LW6pjgwaw//NajcD0Kpz8AHswT9W+kP4/R27JWx6Q/YPS2rNUxsT+amZmZmZmxP+GJ+jdCGa0/RIts5/upsT/ZzvdT46WrP8Ii2/l+aqw/XskvlvxiqT8GkHvNhaSpP+Xu7u7u7q4/umfYFSD3qj+LmZmZmZmpPz0K16NwPao/c4ZdAXKvqT+uVscED+axP9V46SYxCLQ/5/up8dJNuj+xHoXrUbi2P7CBThvotLk/0SLb+X5qvD+R7Xw/NV7GPyjOPnyGXck/uC1rdUzwuD+3nxov3SS2P7vmQtKUirM/WdbqmODBtD83iUFg5dC6PwRWDi2ynbc/OCZ4ME/Utz8uT9S/EcqwP42mVJx9+LQ/2ECnDXTasD/op8ZLN4mxP70gsHJokbU/TnH24TPssj/t/dR46SaxP+6LJb9Y8rM/9ihcj8L1sD+8g3mi/o2wP5ELSVMqzq4/2d3d3d3drT+sK0DuNReyP/yp8dJNYrA/PSijt2Wtrj+5u7u7u7uzP+8oXI/C9bA/cUzwYJ6orz/RMcGDeaKuPyUGgZVDi6w/Yh8+w64AsT/pRP0boYyuP9nO91Pjpas/astaHRM8sD8OS36x5BerP+PSTWIQWKk/18E8Uf9GqD8nT9S/EcqoP5+bxCCwcrA/vr3mQtKUqj+P4ME8Uf+mPz0oo7dlra4/ZmZmZmZmpj83mCfq3wilPzvuNReSpqQ//Me95kLSpD9JjZduEoOwP/7yRP0boaw/zwY6baDTpj/RMcGDeaKuPzsMAiuHFqk/kzbQaQOdpj/LsCtA7jWnP5iM3pa1OqY/ObTIdr6fsj81fIZdAXKvP4/vp8ZLN6k/PSijt2Wtrj8nQO41F5KmPwwg95oLSaM/O+41F5KmpD/dJAaBlUOrPwcezBP1b7Q/XskvlvxisT+0yHa+nxqvP6rx0k1iELA/17JWxwQPpj/Jo3A9CtejP0xkO99Pjac/JQaBlUOLrD9RKs4+fIa1P7M6JngwT7Q/sqzVMcGDsT+R7Xw/NV6yP9V46SYxCKw/H5TR27JWpz8pa3VM8GCuPzb78Bl2BbA/hpduEoPAsj+iVJx9+AyzP5VhV4Dca64/SirOPnyGrT+R7Xw/NV6qP6oAuddcSKo/TGQ730+Npz+kne+nxkunPxBnHz7DrrA/eoZdAXKvsT/hifo3QhmtP9CjcD0K17M/0JSKsw+fsT/2N0IZvS2rPwI6baDTBqo/RtS/EcrorT8rhxbZzvezPzPsCpB7zcE/L5b8Yskvwj/aay4kTanAP7x0kxgEVrY/AklTKs4+rD8/UyrOPnymP395ov6NUKY/XskvlvxisT+muZA0peKsPxKwcmiR7aw/AjptoNMGsj/pRP0boYyuP3syelvW6qg/g8+wK0DupT++rgC511yoP8DZh8+wK7A/UrgehetRsD+6dr6fGi+tPwwREREREbE/fT81XrpJrD8v7AqQe82lP6jz/dR46aY/WnMhaUrFqT/n+6nx0k2yP8l2vp8aL60/3ULSlIqzrz8v3SQGgZWzP9NcSJpScaY/CMrobVmroz83mCfq3wilP3fNhaQpFac/NvvwGXYFsD+at2WtjgmuP7Ks1THBg6k/ToDcay4krT/l3whl9LasP3OGXQFyr6k/TnH24TPsqj/pJjEIrByqP+6aC0lTKq4/FK5H4XoUrj+qD59hV4CsP2iR7Xw/Na4/bz81XrpJrD+uZa2OCR6sP0bF2YfPsKs/TnH24TPsqj/A2YfPsCuwP5zEILByaLE/+o1QRm/Lsj/kUbgeheuxP9TqmODBPLE/BpB7zYWksT850pSKsw+vPy3Bg3mi/q0/mG4Sg8DKsT8gIiIiIiKyPy5P1L8RyrA/BpB7zYWksT+iY4IH80StP8MT9W+EMqo/XLx0kxgEpj8X6LSBThuoP6abxCCwcrA/Rrbz/dR4sT8IrBxaZDvHP9K/Ecrobck/EFg5tMh2rj/FTWIQWDmkP3OGXQFyr6k/LbKd76fGqz9BfrHkF0uuP/sboYzelrU/T/9GKKO3tT8nMQisHFq8P/Wp8dJNYrg/TmIQWDm0sD+4LWt1TPCwP2XYFSD3mrM/+xuhjN6WvT9HYhBYObS4P8daHRM8mLc/UscED+aJuj/n+6nx0k2yPzenDXTaQKc/2xdLfrHkpz9q2kCnDXSqP8uwK0DuNbc/9jdCGb0tsz/+ASuHFtmuP+6LJb9Y8rM/aJHtfD81rj9vIWlKxdmnP+Dsw2fYFbA/UtbqmODBrD/uiyW/WPKzP4GkKRVnH7Y/lVJx9uEztD8JSVMqzj60P0jhehSuR7E/nhxaZDvfrz/hehSuR+GqP8dpA5020Kk/5wqQe82FtD/pJjEIrByyPxh2Bci95rI/6sNn2BUgtz8xCKwcWmSzP+F6FK5H4ao/0JSKsw+fsT9SuB6F61GwP17JL5b8YrE/CuaJ+jdCsT89CtejcD2yP4t7zYWkKbU/7FG4HoXrsT/Tay4kTamoP4PelrU6Jqg/1XjpJjEIrD9Z1uqY4MG0P9CUirMPn7E/EGcfPsOusD9FN4lBYOW4PwlJUyrOPrQ/mH34DLsCpD+TRbbz/dSoP5bvp8ZLN7E/epVDi2znsz/hifo3Qhm1P/fFkl8s+bU/CVg5tMh2tj84JngwT9S3P0l+seQXS7Y/01xImlJxtj/WFSD3mgu5P+RC0pSKs8c/9eEz7AqQwz9k9Las1THBP00b6LSBTsM/q44JHswTvT/iF0t+seS3P1CNl24Sg7g/ZDvfT42Xtj8RBFYOLbK9P7TXXEiaUrk/N4lBYOXQoj83iUFg5dCiP9NcSJpScaY/JVyPwvUoxD8ozj58hl3FP5/TBjptoMM/KWt1TPBgtj/nKFyPwvWoP+xRuB6F66E/2c73U+Olqz/TTWIQWDnWPzVeukkMAqs/oCkVZx8+oz9I8GCeqH+jP7gehetRuK4/5dAi2/l+qj+gR+F6FK6nP4PPsCtA7qU/xU1iEFg5pD93zYWkKRWnPzNR/0Yoo6c/c3d3d3d3pz+c8dJNYhCoP2IuJE2pOKs/x2kDnTbQqT+yu7u7u7urPydA7jUXkqY/DCD3mgtJoz/FPnyGXQGiP6wrQO41F6I/nv6NUEZvqz+yne+nxkunPwAezBP1b6Q/i4qzD59hpz+kjgkezBOlP6jVMcGDeaI/xT58hl0Boj/sUbgeheuhP4lBYOXQIqs/UKtjggfzpD+05kLSlIqjPzNR/0Yoo6c/YBKDwMqhpT+gKRVnHz6jPwjK6G1Zq6M/SPBgnqh/oz9q2kCnDXSqP/QboYzelqU/j9HbslbHpD83tvP91HipP/hxr7mQNKU/UJx9+Ay7oj+05kLSlIqjPxkxCKwcWqQ/d9xrLiRNqT9EuB6F61GoP99ecyFpSqU/pqqqqqqqqj+4SzeJQWClP7YC5F5zIak/DC/dJAaBpT8nQO41F5KmP2wUrkfheqQ/ZnVM8GCeqD89Gb0ta3WsPxKSplScfag/F+i0gU4bqD/TXEiaUnGmP5M20GkDnaY/8NR46SYxqD+aqH8jlNGrPz81XrpJDLI/835qvHSTsD9gnqh/I5TTPzLBg3mi/t8/nu+nxks3yT+5yqFFtvO1PznSlIqzD68/KWt1TPBgrj/Z3d3d3d2tPwJJUyrOPqw//vJE/RuhrD9xTPBgnqivP8F2vp8aL7U/6JjgwTxRtz9KG+i0gU6zP1sBcq+5kLQ/EGcfPsOusD8GkHvNhaSxP7p2vp8aL60/qgC511xIqj+kjgkezBOlP0xGb8taHaM/cWq8dJMYpD+muZA0peKsP2Z1TPBgnqg/LcGDeaL+rT/zfmq8dJOwP6oAuddcSKo/UJx9+Ay7oj9EmlJx9uGjPz9ERERERKQ/ZnVM8GCeqD++veZC0pSqPxb3mgtJU6o/CgRWDi2yrT+kcD0K16OwP+XQItv5fqo/OwwCK4cWqT9WHRM8mCeqPyUVZx8+w64/iLMPn2FXsD8welvW6piwP2iR7Xw/Na4/Yi4kTak4qz9MVVVVVVWlP6jkF0t+saQ/H5TR27JWpz9ooNMGOm2wP+kmMQisHKo/47SBThvopD9zd3d3d3enPxfotIFOG6g/x1odEzyYpz/HWh0TPJinP28haUrF2ac/pqqqqqqqqj/Vh8+wK0CuPwoEVg4tsq0/DAIrhxbZrj8lFWcfPsOuP8uwK0DuNac/I/nFkl8sqT+4SzeJQWClP7695kLSlKo/AC2yne+npj/jtIFOG+ikPxtNqTj78Kk/F9nO91PjpT/sUbgeheuhP6ApFWcfPqM/ULpJDAIrpz/dM+wKkHutP9Ei2/l+aqw/l5vEILByqD+VUnH24TOsP3fcay4kTak/pH8jlNHboj9UEFg5tMimP05x9uEz7Ko/TnH24TPssj+0gU4b6LTTP9S/EcrobdM/aS4kTak4xz9VgNxrLiS9P42XbhKDwLI/1YfPsCtArj+LirMPn2GnPyGwcmiR7aw/i5mZmZmZqT+D3pa1OiaoP+F6FK5H4ao/3TPsCpB7rT/JhaQpFWevPxkEVg4tsq0/kQtJUyrOrj+PwvUoXI+yP5HtfD81XrI/ZnVM8GCesD/mfD81XrqxPxSuR+F6FK4/cT0K16NwrT+aqH8jlNGrPwr1b4Qyeqs/wmfYFSD3sj/PBjptoNO2P8546SYxCLQ/EyD3mgtJsz81XrpJDAKrPy/dJAaBlaM/zfl+arx0oz9vIWlKxdmnP8dpA5020Kk/9kYoo7dlrT9t9uEz7AqwP91C0pSKs68/wcqhRbbzrT9e2BUg95qrP9Ei2/l+aqw/PSijt2Wtrj8pa3VM8GCuP5H8Yskvlqw/OcOuALnXrD9CYOXQItuxP6oAuddcSKo/vKFFtvP9pD+Dz7ArQO6lPz9TKs4+fKY/18E8Uf9GqD/XwTxR/0aoPzb78Bl2BbA/wNmHz7ArsD/JhaQpFWevPzNg5dAi26k/olScffgMqz/rfmq8dJOoP05x9uEz7Ko/olScffgMqz+e/o1QRm+rP4lfLPnFkq8/4Yn6N0IZrT+P76fGSzepPzNR/0Yoo6c/tPUoXI/CpT+2AuRecyGpPx+U0duyVqc/l5vEILByqD/ewTxR/0awP/QqhxbZzqc/j8L1KFyPoj8MIPeaC0mjP6w6JngwT6Q/y7ArQO41pz9xTPBgnqivP8F2vp8aL7U/o+Lsw2fYtT9dLPnFkl+0PwwREREREbE/jbU6Jngwrz9Cb8taHROsP90z7AqQe60/cUzwYJ6orz8AAAAAAACwP5qZmZmZmbE/TnH24TPsqj8bL90kBoGlPzeYJ+rfCKU/J0DuNReSpj9acyFpSsWxPxaSplScfcA/qgC511xIqj91ov6NUEavP9fBPFH/Rqg/GTEIrBxapD97I5TR27KmPzeYJ+rfCKU/RtS/EcrorT8EZfS2rNWxPyMIrBxaZKs/j++nxks3qT8ALbKd76emP7VlrY4JHrQ/L90kBoGVuz877jUXkqa0P/9xr7mQNLU/ObTIdr6fsj+yrNUxwYOxP+Olm8QgsLI/ToDcay4krT+P0duyVsekP+xRuB6F66E/j8L1KFyPoj9mdUzwYJ6oP2Roke18P6U/XrpJDAIrpz+qD59hV4CsP6c4+/AZdrU/jZduEoPAqj+2AuRecyGpP7yhRbbz/aQ/iUFg5dAiqz+WQ4ts5/upP4PelrU6Jqg/jZduEoPAqj8zQhm9LWulP6R/I5TR26I/PzVeukkMoj/sUbgeheuhP8daHRM8mKc/N5gn6t8IpT/4YskvlvyiP7g8Uf9GKKM/g8+wK0DupT9MRm/LWh2jPzMzMzMzM6M/VPKLJb9Yoj8dhxbZzvejPwAP5on6N6I/SP9GKKO3pT83pw102kCnP7M6JngwT7w/HBM8mCfqwz/sUbgeheuhP+xRuB6F66E/Rrbz/dR4qT+Le82FpCmlP5iM3pa1OqY/j+DBPFH/pj+gOPvwGXalP6jVMcGDeaI/7FG4HoXroT9sBci95kKiP0oMAiuHFqk/N6cNdNpApz9/arx0kxikP9NrLiRNqag/qOQXS36xpD9YV4Dcay6kP5zTBjptoKM/yaNwPQrXoz9YZmZmZmamPwAtsp3vp6Y/K6Xi7MNnqD9LuB6F61GwP65lrY4JHqw/oCkVZx8+oz+P0duyVsekP/zHveZC0qQ/qPP91Hjppj87/RuhjN6mP4t7zYWkKaU//uNecyFpqj8OPJgn6t+oP/y411xImqI/+ICVQ4tspz/w1HjpJjGoP1Ys+cWSX6w/olScffgMqz+JQWDl0CKrP06A3GsuJK0/i4qzD59hpz+05kLSlIqjP/QboYzelqU/XLx0kxgEpj/nKFyPwvWoP97BPFH/RrA/+FPjpZvEsD+2AuRecyGxP17YFSD3mqs/wOhtWatjoj+PwvUoXI+iPwwg95oLSaM/k0W28/3UqD+WQ4ts5/upP5iM3pa1OqY/jZduEoPAqj/LsCtA7jWnP3FqvHSTGKQ/N4lBYOXQoj+PwvUoXI+iP7YC5F5zIak/H4XrUbgepT+TJ+rfCGWkP3syelvW6qg//uNecyFpqj/TXEiaUnGmP/y411xImqI/46WbxCCwoj/4gJVDi2ynP+PSTWIQWKk/62+EMnpbpj/w1HjpJjGoP3CEMnpb1uc/ZMkvlvxi/T/7YskvlvzYPwwCK4cW2b4/t5A0peLssz/ewTxR/0awP7gehetRuK4/AklTKs4+rD8nT9S/EcqoP4/gwTxR/6Y/DC/dJAaBpT/A91PjpZukP9sIZfS2rKU/g96WtTomqD8DyL3mQtK0P7Pz/dR46cY/kpmZmZmZuT9kSsXZh8+wPwrmifo3Qqk/kyfq3whlpD8CK4cW2c6nP1CrY4IH86Q/mH34DLsCpD/nCpB7zYWkP/y411xImqI/qNUxwYN5oj8AD+aJ+jeiP+xRuB6F66E/fWzn+6nxoj+wkDSl4uyjPxB2Bci95qI/HYcW2c73oz+SQ4ts5/vJPzhCGb0ta+c/3GsuJE2p5D+4HoXrUbjQPz3DrgC518A/9ZoLSVMqtj9qy1odEzywP8DZh8+wK7A/NW2g0wY6rT/dM+wKkHutP06A3GsuJK0/kfxiyS+WrD9WLPnFkl+sPxfotIFOG7A/efgMuwLkrj/Tay4kTamoPy/78Bl2Bag/hyW/WPKLpT9MVVVVVVWlP/QMuwLkXqM/qPP91Hjppj87/RuhjN6mP1hXgNxrLqQ/XK2OCR7Moz8ZMQisHFqkPwjK6G1Zq6M//LjXXEiaoj8730+Nl26iPzeYJ+rfCKU/62+EMnpbpj9vIWlKxdm/P6zVMcGDecY/ubu7u7u7sz/0G6GM3palP1QBcq+5kKQ/P0REREREpD9kaJHtfD+lPzeYJ+rfCKU/sJ8aL90kpj/4ca+5kDSlPxwTPJgn6sM/kaZUnH34wD+amZmZmZmxP23n+6nx0q0/q44JHswTtT83iUFg5dC6P9hApw102rg/27JWxwQPwj+SmZmZmZm5P99tWatjgqc/qOQXS36xpD8Eg8DKoUWmP1pkO99Pjbc/okW28/3UxD+ONKXi7MPDPzpR/0Yoo7c/ng102kCnrT8GgZVDi2ynP0Jg5dAi26k/OwwCK4cWqT8bPsOuALmnP3+IiIiIiKg/RLgehetRqD/4gJVDi2ynP8/3U+Olm6Q/WEiaUnH2oT8zMzMzMzOjP8VNYhBYOaQ/aL6fGi/dpD/P91PjpZukP5ebxCCwcqg//Knx0k1isD/dJAaBlUOrPxb3mgtJU6o/P2IQWDm0qD+P4ME8Uf+mP+cKkHvNhaQ/WmQ730+Npz8COm2g0waqP5zEILByaLk/CKwcWmQ7vz9crY4JHsyjP5zTBjptoKM/pH8jlNHboj8ZMQisHFqkP6SOCR7ME6U/j9HbslbHpD+TJ+rfCGWkPz9ERERERKQ/oCkVZx8+oz+kfyOU0duiP0jwYJ6of6M/g8+wK0DupT/hehSuR+GqPxS9LWt1TLA/5d8IZfS2rD/PBjptoNOmP99ecyFpSqU/HYcW2c73oz8AHswT9W+kPxCF61G4HqU/sJA0peLsoz+05kLSlIqjP+cZdgXIvaY/i3vNhaQppT/0G6GM3palP+tgnqh/I6Q/BHTaQKcNpD+8oUW28/2kP1y8dJMYBKY/K5b8Yskvpj8ML90kBoGlP8D3U+Olm6Q/9Ay7AuReoz9kWatjggejP6R/I5TR26I/oDj78Bl2pT/XslbHBA+mP1CrY4IH86Q/GTEIrBxapD+kfyOU0duiP+f7qfHSTaI/7FG4HoXroT/sUbgeheuhPxKDwMqhRaY/62CeqH8jpD/8uNdcSJqiP1QQWDm0yKY/5wqQe82FpD8nMQisHFqkP5MYBFYOLaI/7FG4HoXroT8ZMQisHFqkP+O0gU4b6KQ//LjXXEiaoj/FPnyGXQGiP+xRuB6F66E/bAXIveZCoj/FPnyGXQGiP4/C9Shcj6I/9Ay7AuReoz8U2/l+arykP/zWo3A9Cqc/BpB7zYWkqT8rhxbZzvejP+xRuB6F66E/j8L1KFyPoj9YSJpScfahP7yhRbbz/aQ/mH34DLsCpD9U8oslv1iiP2wFyL3mQqI/17JWxwQPpj+c8dJNYhCoP7CfGi/dJKY/j++nxks3qT9/iIiIiIioP/iAlUOLbKc/RJpScfbhoz+HFtnO91OjP1TyiyW/WKI/7FG4HoXroT/sUbgeheuhP8U+fIZdAaI/hyW/WPKLpT+c4uzDZ9ilP0xGb8taHaM/nNMGOm2goz83iUFg5dCiPwrmifo3Qqk/Yh8+w64AqT++rgC511yoP3syelvW6qg//NajcD0Kpz8rhxbZzvejP+O0gU4b6KQ/j8L1KFyPoj8/NV66SQyiP/hiyS+W/KI/ZnVM8GCeqD/pJjEIrByyP7M6JngwT8A/5Yn6N0IZxT+gGi/dJAa5P0jwYJ6of7M/7oslv1jyqz+LirMPn2GnP2ASg8DKoaU/TFVVVVVVpT83mCfq3wilP2ADnTbQaaM/HYcW2c73oz+kfyOU0duiPxTME/VvhKI/7FG4HoXroT9YSJpScfahP/C2rNUxwaM/uDxR/0Yooz+8kl8s+cWiP+cKkHvNhaQ/TEZvy1odoz/sUbgeheuhP+xRuB6F66E/xT58hl0Boj9MRm/LWh2jP5h9+Ay7AqQ/K5b8Yskvpj+yrNUxwYOpP7ySXyz5xaI/FMwT9W+Eoj8zMzMzMzOjP1ytjgkezKM/2/l+arx0oz9xarx0kxikP+PDZ9gVIKc/pJ3vp8ZLpz877jUXkqakP2RZq2OCB6M/oCkVZx8+oz9or7mQNKWiP395ov6NUKY/ZGiR7Xw/pT++veZC0pSqP+rSTWIQWLE/qgC511xIuj9WDi2yne+/PxSuR+F6FMI/j8L1KFyP1D/NE/VvhDLrP7MrQO41F+s/MJb8Yskv1D8bL90kBoHBP3C+nxov3bQ/byFpSsXZpz/81qNwPQqnPzNR/0Yoo6c/nv6NUEZvqz/HaQOdNtCpP2ASg8DKoaU/L/vwGXYFqD+kfyOU0duiPwAP5on6N6I/aK+5kDSloj83iUFg5dCiP+O0gU4b6KQ/c2iR7Xw/pT8zQhm9LWulP99tWatjgqc/aK+5kDSloj9U8oslv1iiP6R/I5TR26I/O99PjZduoj/FTWIQWDmkP99PjZduEqM/yaNwPQrXoz8K5on6N0KpPwwg95oLSaM/P0REREREpD/8uNdcSJqiP+xRuB6F66E/xU1iEFg5pD9UAXKvuZCkP5iM3pa1OqY/XskvlvxiqT9WHRM8mCeqP0ob6LSBTqs/0THBg3mirj/DE/VvhDKqP8D3U+Olm6Q/kyfq3whlpD+TNtBpA52mP1QQWDm0yKY/vJJfLPnFoj+sK0DuNReiPz81XrpJDKI/7FG4HoXroT8dhxbZzvejP0jwYJ6of6M/wPdT46WbpD9iEFg5tMimP/hiyS+W/KI/GSIiIiIioj/8uNdcSJqiP/C2rNUxwaM/UrgehetRqD+P76fGSzepPxKhjN6Wtao/MQisHFpkqz9EqTj78BmmP1hImlJx9qE/7FG4HoXroT/FPnyGXQGiP+Olm8QgsKI/BHTaQKcNpD8/UyrOPnymP2ASg8DKoaU/AC2yne+npj/nKFyPwvWoP2rLWh0TPLA/NW2g0wY6tT9uWatjggfxPye/WPKLpQlA7FG4HoVrA0ARERERERHhPwGdNtBpA8k/AZ020GkDwT9qvHSTGAS+PzVeukkMArs/tWWtjgkewD+SXyz5xZLTP88+fIZdAdY/ZPS2rNUxzT9P/0Yoo7e9PxqhjN6WtbI/YPS2rNUxsT/n+6nx0k2yP8P1KFyPwrU/znjpJjEItD91kxgEVg6tP1Ys+cWSX6w/i3vNhaQppT8zQhm9LWulP2rLWh0TPKg/AklTKs4+rD+sHFpkO9/nP69H4XoUrvc/4E+Nl24S6T8/NV66SQzWP8a95kLSlMY/4OzDZ9gVwD8gIiIiIiK6P0mNl24Sg7g/UI2XbhKDuD+wcmiR7Xy3P4PPsCtA7rU/CuaJ+jdCuT8YhetRuB61P7pY8oslv7A/lWFXgNxrrj/A2YfPsCuwPzb78Bl2BbA/RTeJQWDlsD+eDXTaQKetP+8ZdgXIvcI/27JWxwQPyj+SirMPn2G/PzNCGb0ta7U/CLsC5F5zsT+LbOf7qfGyP3yx5BdLfrE/4OzDZ9gVsD89Gb0ta3WsP3syelvW6qg/8NR46SYxqD8QhetRuB6lP0xkO99Pjac/i5mZmZmZqT+VUnH24TOsP4IyelvW6rA/3Ja1OiZ4sD/w1HjpJjGoP4/R27JWx6Q/RKk4+/AZpj8j6t8IZfSmP5VhV4Dca64/QX6x5BdLrj8ALbKd76emP4lBYOXQIqs/17JWxwQPpj+8oUW28/2kP5Mn6t8IZaQ/f3mi/o1Qpj9Cb8taHROsP90kBoGVQ6s/Gz7DrgC5pz9KKs4+fIatP+cZdgXIvaY/vq4AuddcqD/HaQOdNtCpP8daHRM8mKc/1YfPsCtArj800GkDnTawP2aEMnpb1qo/1hUg95oLsT9/eaL+jVCmP/y411xImqI/pI4JHswTpT9mdUzwYJ6oP4GkKRVnH64/qvHSTWIQsD9q2kCnDXSqP2rLWh0TPLA/oCkVZx8+oz+YffgMuwKkP1TjpZvEILA/z/dT46WbvD9NG+i0gU7DP2YfPsOuAMU/ZdgVIPeauz/58Bl2Bci1P+k1F5KmVKw/6TUXkqZUrD/A2YfPsCuwPzeYJ+rfCKU/h10Bcq+5AEBPG+i0gc72P2VmZmZmZhtA3pa1Oib49D/gwTxR/0bSPzeJQWDl0NI/N4lBYOXQ0j83iUFg5dDSPzeJQWDl0NI/0pSKsw+f0T+Nl24Sg8CqP9NrLiRNqag/QmDl0CLbqT+3kDSl4uyzPzuYJ+rfCMU/Ik2pOPvwyT/GveZC0pTCPzb78Bl2Bbg/uljyiyW/sD+AB/NE/RuxP83MzMzMzKw/jZduEoPAqj9SxwQP5omqP/7yRP0boaw/rnSTGARWrj/WFSD3mguxP4IyelvW6rA/hoiIiIiIsD+at2WtjgmuP+GY4ME8Ua8/HWlKxdmHrz85w64AudesP6JjggfzRK0/MSZ4ME/Urz+iRbbz/dSwP2Q730+Nl64/c3d3d3d3pz87/RuhjN6mPx+jt2Wtjqk/hetRuB6Fqz8pa3VM8GCuP5VScfbhM6w/sqzVMcGDsT8BrBxaZDu3P7x0kxgEVq4/LbKd76fGqz+NplScffisP42XbhKDwKo/Yj0K16NwrT89Gb0ta3WsP+t+arx0k6g/nPHSTWIQqD+c8dJNYhCoP+k1F5KmVKw/kfxiyS+WrD8lBoGVQ4usPzm0yHa+n6o/WoIH80T9qz+F61G4HoWrP42mVJx9+Kw/+ICVQ4tspz8nT9S/EcqoP/QMuwLkXqM/oCkVZx8+oz/0G6GM3palPwSDwMqhRaY/g8+wK0DupT+D3pa1OiaoP9ejcD0K16M/RJpScfbhoz+05kLSlIqjP+xRuB6F66E/9Ay7AuReoz+gKRVnHz6jPxB2Bci95qI/RJpScfbhoz83iUFg5dCiP5zTBjptoKM/WEiaUnH2oT8AD+aJ+jeiPwwg95oLSaM/+GLJL5b8oj+TNtBpA52mP0xVVVVVVaU/aK+5kDSloj8730+Nl26iP4ts5/up8aI/GTEIrBxapD/PFSD3mgupP4/gwTxR/6Y/AjptoNMGqj9KG+i0gU6rP7ySXyz5xaI/TEZvy1odoz9MRm/LWh2jP/QMuwLkXqM/VAFyr7mQpD/rYJ6ofyOkP1ytjgkezKM/tOZC0pSKoz/4YskvlvyiP+k1F5KmVLQ/17JWxwQPvj+TJ+rfCGW8P/7jXnMhabI/4XoUrkfhqj/wxZJfLPmlPz9ERERERKQ/RJpScfbhoz9QnH34DLuiPzeJQWDl0KI/O+41F5KmpD/PFSD3mgupP2rLWh0TPKg/XskvlvxiqT+6WPKLJb+oP6jVMcGDeaI/HYcW2c73oz/8x73mQtKkP8D3U+Olm6Q/i3vNhaQppT9I/0Yoo7elP2ADnTbQaaM/tOZC0pSKoz83iUFg5dCiP9v5fmq8dKM/0U+Nl24Soz9I8GCeqH+jP/C2rNUxwaM/M0IZvS1rpT9MVVVVVVWlP0SaUnH24aM/5wqQe82FpD8X6LSBThuoP7CQNKXi7KM/GSIiIiIioj9MVVVVVVWlP3fcay4kTak/TnH24TPsqj++rgC511yoP9eyVscED6Y/N5gn6t8IpT/4ca+5kDSlPydA7jUXkqY/vq4AuddcqD/dJAaBlUOrPyul4uzDZ6g/ezJ6W9bqqD8730+Nl26iP/QMuwLkXqM/tOZC0pSKoz9kWatjggejPxKDwMqhRaY/VBBYObTIpj9EmlJx9uGjPz9TKs4+fKY/KvnFkl8ssT81XrpJDAKzP6wcWmQ7368/3TPsCpB7rT83pw102kCnP7pY8oslv6g/PSijt2Wtrj91ov6NUEavP9DbslbHBMs/RJpScfbhoz/nCpB7zYWkP2ADnTbQaaM/MzMzMzMzoz9gA5020GmjP7TmQtKUiqM/SPBgnqh/oz+kfyOU0duiP6R/I5TR26I/YAOdNtBpoz/jpZvEILCiP8mjcD0K16M/rDomeDBPpD/HWh0TPJinP/iAlUOLbKc/AA/mifo3oj+sK0DuNReiP5MYBFYOLaI/7FG4HoXroT/4YskvlvyiP395ov6NUKY/XK2OCR7Moz8Eg8DKoUWmPxkiIiIiIqI/kxgEVg4toj8QdgXIveaiPz81XrpJDKI/rDomeDBPpD+gOPvwGXalPwAP5on6N6I/UJx9+Ay7oj/0DLsC5F6jP5MYBFYOLaI/7FG4HoXroT8/NV66SQyiP8DobVmrY6I//LjXXEiaoj8AD+aJ+jeiP8DobVmrY6I/uDxR/0Yooz9U8oslv1iiP+xRuB6F66E/GSIiIiIioj/A6G1Zq2OiP8DobVmrY6I/PzVeukkMoj8/NV66SQyiP+O0gU4b6KQ/zmkDnTbQsT+e/o1QRm+zPx73mgtJU7I/wNmHz7ArsD8CSVMqzj6sP1CrY4IH86Q/bzBP1L8Rqj/pJjEIrBzOPyuHFtnO96M/VPKLJb9Yoj83iUFg5dCiP8P1KFyPwqU/wwQP5on6pz+F61G4HoWrP+Xu7u7u7q4/9BuhjN6WpT+P76fGSzepP/zWo3A9Cqc/UscED+aJqj+uZa2OCR6sP23n+6nx0q0/SirOPnyGrT/y8Bl2BcitP+k1F5KmVKw/4XoUrkfhqj/FILByaJGtP6oPn2FXgKw/lVJx9uEzrD9t5/up8dKtP+lE/RuhjK4/MSZ4ME/Urz89KKO3Za2uP83bslbHBK8/3Ja1OiZ4sD8MAiuHFtmuP/L//////68/XI/C9Shcrz+TGARWDi2yP6dH4XoUrrc/F+i0gU4bsD+mqqqqqqqyP/LwGXYFyK0/wwQP5on6pz+qALnXXEiqPx+jt2Wtjqk//uNecyFpqj/HaQOdNtCpP0S4HoXrUag/M0IZvS1rpT/w1HjpJjGoP1pkO99Pjac/IwisHFpkqz8+tvP91HixP7gta3VM8LA/wcqhRbbzrT9WLPnFkl+sPyGwcmiR7aw/cT0K16NwrT8EVg4tsp2vP8oT9W+EMrI/K5b8Yskvtj9KDAIrhxbBPy+W/GLJL8Y/KM4+fIZdxT/aay4kTanAP3YwT9S/Ebo/82+EMnpbtj83mCfq3wi1P5Mn6t8IZbQ/hetRuB6Fsz+amZmZmZmxP9K/EcrobbE/jkOLbOf7sT/4U+Olm8SwPzKl4uzDZ7A/Ib9Y8oslrz94W9bqmOCxPwi7AuRec7E/nMQgsHJosT++rgC511ywP2ig0wY6bbA/EpKmVJx9sD8xJngwT9SvP4lfLPnFkq8/uljyiyW/sD9JjZduEoOwP2rLWh0TPLA/c4ZdAXKvqT9iPQrXo3CtP9ExwYN5oq4/WnMhaUrFqT8j+cWSXyypP6JUnH34DKs/N7bz/dR4qT/fbVmrY4KnP9NcSJpScaY/d9xrLiRNqT9gA5020GmjPxkiIiIiIqI/YAOdNtBpoz/81qNwPQqnP6xJDAIrh6Y/EpKmVJx9qD+HFtnO91OjPy2yne+nxqs/HveaC0lTsj8iTak4+/CxP2iR7Xw/Na4/gjJ6W9bqsD/n+6nx0k2iP/QMuwLkXqM/AiuHFtnOpz8Gn2FXgNyrP42mVJx9+Kw/lkOLbOf7qT/4gJVDi2ynP4PPsCtA7qU/G02pOPvwqT8nT9S/EcqoP8UgsHJokb0/PqcNdNpAtz/D9Shcj8KlPydP1L8Ryqg//uNecyFpqj8dWmQ730+tP0F+seQXS64/JQaBlUOLrD/j0k1iEFipP2raQKcNdKo/AklTKs4+rD9q2kCnDXSqP7pY8oslv6g/RsXZh8+wsz9oSsXZh8/AP7ByaJHtfMM/yYWkKRVntz8welvW6piwP42XbhKDwKo/5xl2Bci9pj/DBA/mifqnP57+jVBGb6s/uC1rdUzwsD96lUOLbOezPzB6W9bqmLA/Vh0TPJgnsj81XrpJDAKrPzenDXTaQKc/RLgehetRqD+qALnXXEiqP/DUeOkmMag/x2kDnTbQqT8QdgXIveaiP+tgnqh/I6Q/9BuhjN6WpT87/RuhjN6mP6Sd76fGS6c/+ICVQ4tspz/wxZJfLPmlP6jz/dR46aY/MzMzMzMzoz/jpZvEILCiP1QBcq+5kKQ/DC/dJAaBpT/fbVmrY4KnP9sXS36x5Kc/YBKDwMqhpT/HWh0TPJinP2wUrkfheqQ/ZoQyelvWqj/PFSD3mgupP5ebxCCwcqg/F+i0gU4bqD9q2kCnDXSqP4XrUbgehas/it6WtTomsD/0b4QyelvQP28wT9S/Eao/9CqHFtnOpz8flNHbslanP8dpA5020Kk/Dkt+seQXqz+R7Xw/NV6qP6JUnH34DKs/02suJE2pqD/VeOkmMQisP8HKoUW2860/PQrXo3A9qj9wr7mQNKWyP/tiyS+W/MY/bVmrY4IH1T8Q5on6N0LTP2OtjgkezMc/98WSXyz5vT/Bdr6fGi+1PySHFtnO97M/yhP1b4Qysj8sJE2pOPuwP97BPFH/RrA/AAAAAAAAsD9OgNxrLiStPzEXkqZUnK0/PSijt2Wtrj9G1L8RyuitPyUGgZVDi6w/2msuJE2psD+oxks3iUGwP4dDi2zn+6k/zxUg95oLqT81baDTBjqtPxkEVg4tsq0/lkOLbOf7qT9iHz7DrgCpP9ExwYN5oq4/rlbHBA/mqT+amZmZmZmpPydA7jUXkqY/lkOLbOf7qT/LvxHK6G2pPw5LfrHkF6s/JQaBlUOLrD91ov6NUEavP4relrU6JrA/CvVvhDJ6qz9OcfbhM+yqPz0K16NwPao/Yi4kTak4qz+R/GLJL5asPxSuR+F6FK4/2msuJE2psD/umgtJUyquPylrdUzwYK4/nhxaZDvfrz800GkDnTawP7TIdr6fGq8/YOXQItv5rj9aggfzRP2rP/ZGKKO3Za0/9jdCGb0tqz+qALnXXEiqP2ASg8DKoaU/0THBg3mirj+at2WtjgmuP4UJHswT9a8/Lk/UvxHKsD+6WPKLJb+wP+Xu7u7u7q4/lVJx9uEzrD9Oj8L1KFyvP7TIdr6fGq8/3ULSlIqzrz/n+6nx0k2yP7yDeaL+jbA/CuaJ+jdCsT+TGARWDi2yPy5P1L8RyrA/qNUxwYN5sj/SvxHK6G2xP79LN4lBYLU/oCkVZx8+sz9jrY4JHsyzP03UvxHK6LU/kyfq3whltD/rYJ6ofyO0PyAxCKwcWrQ/cL6fGi/dtD97I5TR27K2P1NVVVVVVbU/4Yn6N0IZtT8pa3VM8GC2P2k9CtejcLU/RJpScfbhsz8X6LSBThuwP8a95kLSlLI/GrByaJHttD9TVVVVVVW1P9eyVscED7Y/R2IQWDm0uD8hv1jyiyW3P1erY4IH87Q/MReSplSctT9jrY4JHsyzPxfZzvdT47U/i3vNhaQptT+0yHa+nxq3P8Uvlvxiybc/YOXQItv5tj8lFWcfPsO2P8uwK0DuNbc/XI/C9Shctz/vGXYFyL22P4X6N0IZvbU/i3vNhaQptT9RKs4+fIa1P8uwK0DuNbc/j8L1KFyPuj/MPnyGXQG6P8mFpCkVZ7c/H5TR27JWtz/wtqzVMcGzPznDrgC517Q/jAkezBP1tz9PDi2yne+3P2IfPsOuALk/n5vEILByuD9cj8L1KFy3Pz81XrpJDLo/pqqqqqqquj9pLiRNqTi7P0dTKs4+fL4/lLU6Jngwvz/QlIqzD5+5Pz9ERERERLQ/FVpkO99PtT/6jVBGb8uyP1hImlJx9rE/30+Nl24Ssz/jpZvEILC6Pz628/3UeLk/cukmMQistD8COm2g0wayP99ecyFpSrU/Q/0boYzetj8rlvxiyS+2P1sQWDm0yLY/y7ArQO41tz92ME/UvxG6PwRWDi2ynbc/xKFFtvP9tD9dO99PjZe2P/FE/RuhjLY/DjyYJ+rfuD+5yqFFtvO1P3qGXQFyr7k/vq4AuddcuD+R/GLJL5a0P2Z1TPBgnrA/PQrXo3A9sj8xCKwcWmSzP8a95kLSlLI/9P3UeOkmsT8j6t8IZfS2PydA7jUXkrY/98WSXyz5tT97I5TR27K2P0P9G6GM3rY/I+rfCGX0tj/Z3d3d3d21PwGdNtBpA7U/9ZoLSVMqtj+bNtBpA522P3WTGARWDrU/4OzDZ9gVsD8GkHvNhaSxP4izD59hV7A/WEiaUnH2sT8Lg8DKoUW2Pw/K6G1Zq7M/bxKDwMqhtT8nQO41F5K2P37cay4kTbE/FVpkO99PtT+6WPKLJb+wP0bUvxHK6K0/N4lBYOXQsj/dM+wKkHu1P6Pi7MNn2LU/bFmrY4IHsz9acyFpSsWxPylrdUzwYL4/iLMPn2FXuD+9EcrobVmzP1CcffgMu7I/d82FpCkVtz/7KocW2c63P3fNhaQpFbc/R2IQWDm0uD877jUXkqa8PxMg95oLSbs/aJHtfD81tj9uhDJ6W9ayP9eyVscED7Y/s0kMAiuHtj+Dz7ArQO61P3LaQKcNdLI/aS4kTak4sz/rYJ6ofyO0Pxh2Bci95rI/3Ja1OiZ4sD8flNHbsla3P/WaC0lTKrY/ucqhRbbztT+6Z9gVIPeqP2aTGARWDq0/oBov3SQGsT9+3GsuJE2xP5bvp8ZLN7E/WDm0yHa+tz/t/dR46Sa5PyJNqTj78LE/IbByaJHtrD+FCR7ME/WvP/yp8dJNYrA/JHgwT9S/sT94W9bqmOCxP1nW6pjgwbQ/6SYxCKwcuj+BpCkVZx+2P9LO91PjpbM//uNecyFpsj9l5/up8dK1P/qNUEZvy7I/SgwCK4cWsT+qALnXXEi6PxKSplScfbg/+GLJL5b8sj+FCR7ME/WvP625kDSl4rQ/1YfPsCtAtj800GkDnTa4P2Dl0CLb+bY/Lk/UvxHKuD9HYhBYObS4P/nwGXYFyLU/znjpJjEItD9jvHSTGAS2Pw/K6G1Zq7M/LDMzMzMzsz8asHJoke20P08OLbKd77c/uljyiyW/uD82+/AZdgW4P6Px0k1iELg/efgMuwLktj82+/AZdgW4PzTQaQOdNrg/wNmHz7AruD93zYWkKRW3PwI6baDTBro/o/HSTWIQuD9uhDJ6W9ayPwPIveZC0rQ/wmfYFSD3sj9y2kCnDXSyP7NJDAIrh7Y/2c73U+Oluz+PwvUoXI+6PxkTPJgn6rc/j8L1KFyPuj8gIiIiIiK6P70RyuhtWbs/yOhtWatjuj+3kDSl4uy7P8/3U+Olm7w/17JWxwQPvj84JngwT9S3PzV8hl0Bcq8/O99PjZdusj+o1THBg3myP2kuJE2pOLM/3SQGgZVDsz8czBP1b4S6P1TyiyW/WLo/u/UoXI/CtT8EZfS2rNW5P8a95kLSlLo/xr3mQtKUuj9GxdmHz7C7P7VlrY4JHrw/hetRuB6Fuz8X6LSBThu4P0jwYJ6of7s/A8i95kLSwD956SYxCKzAP8Uvlvxiybc/ZnVM8GCesD/6jVBGb8uyPyuHFtnO97s/hxbZzvdTuz+F+jdCGb21P10730+Nl7Y/TEZvy1oduz/kUbgeheu5P31OG+i0gb4/qWOCB/NEwT8gIiIiIiLCP0EZvS1rdcQ/CKwcWmQ7wz92ME/UvxHCP8V2vp8aL8k/L90kBoGVyz/bslbHBA/KP+01F5KmVMw/iUFg5dAixz8h95oLSVPCP6/z/dR46bY/Bx7ME/VvtD8c2/l+ary0P4t7zYWkKbU/kfxiyS+WtD97I5TR27K2P6GM3pa1OtA/V8cED+aJ3D8/NV66SQzYP93d3d3d3ck/CGX0tqzVwT8HHswT9W+8P0diEFg5tLg/mzbQaQOdtj+bNtBpA522P6UNdNpAp7U/WwFyr7mQtD+o1THBg3myP5qofyOU0bM/gaQpFWcftj9pPQrXo3C1P+k1F5KmVLQ/iVBGb8tatT8gMQisHFq0PzvfT42XbrI/99R46SYxsD8daUrF2YevP4izD59hV7A/6TUXkqZUrD8xF5KmVJytP3yx5BdLfrE/YPS2rNUxsT/y8Bl2BcitP+F6FK5H4ao/ng102kCnrT/vKFyPwvWwPyAiIiIiIrI/EfVvhDJ6sz9pLiRNqTi7P76fGi/dJL4/6sNn2BUgtz/0DLsC5F6zPwAP5on6N7I//vJE/RuhrD+yrNUxwYOpP1YdEzyYJ6o/1hUg95oLsT+qALnXXEiyP3YwT9S/EbI/aS4kTak4sz+1Za2OCR60P9hApw102rg/2c73U+Ol0T+SXyz5xZLVPzgmeDBP1Ms/aef7qfHSwT9U8oslv1i6P70gsHJokbU//uNecyFpsj+fm8QgsHKwP4relrU6JrA/QX6x5BdLrj8keDBP1L+xPy5eukkMArM/KWt1TPBgrj/XwTxR/0aoP+kmMQisHKo/+qscWmQ7rz9FN4lBYOWwP+8oXI/C9bA/FUt+seQXsz90Bci95kKyPz0oo7dlra4/5/up8dJNsj/2N0IZvS2zP28haUrF2bc/vq4AuddcuD9WDi2yne+3PxfotIFOG7g/WEiaUnH2uT97I5TR27K2PzNCGb0ta7U/a2iR7Xw/tT/3xZJfLPm1P1dkO99Pjcs//RuhjN6W4T/bQKcNdNrmPycxCKwc2vQ/tIFOG+i07j/GSzeJQWDgPyzOPnyGXe4/JngwT9S/8D/5DLsC5F7jP0fhehSux/o/hetRuB4FB0CamZmZmZn9P4FOG+i0gQRA3d3d3d1dDkCbmZmZmZkHQH2x5BdLfvo/s1bHBA9m8D9bZDvfT43oPxeSplScfeU/XbpJDAIr4z8DuddcSJreP4+mVJx9+Nw/z/dT46Wb2j8zMzMzMzPZP1VVVVVVlQJAw/UoXI/CGkC1gU4b6PQTQJX8YskvlgdAK1yPwvUo/z9mZmZmZuYRQLHkF0t+cRpAWfKLJb9YIEBgLPnFkr8gQKcNdNpAZxZAPQrXo3A9CEDziyW/WPL2P6RwPQrXo/U/gk4b6LSB8z+eNtBpA530P3h3d3d3d/0/16NwPQrXAkAvlvxiyS8IQJX8YskvVhFA5BdLfrFkC0CkcD0K16P9P6HTBjptoPQ/BzptoNMG9T/9Yskvlvz0Pylcj8L1KPM/lvxiyS+W8z9SuB6F61H0P0SLbOf7qew/aNgVIPea7D9kyS+W/GL1P5uZmZmZmf4/odMGOm2gAEAXS36x5Bf7P93d3d3d3fc/dnd3d3d3/z8EnTbQaYMAQJw20GkDnfc/hOtRuB6F8j93Bci95kLtP2lKxdmHz+k/zYWkKRVn5z+d76fGSzfoPzEIrBxa5PQ/pHA9Ctej+D87baDTBjrzP68AuddcSOw/tIFOG+i06D/x0k1iEFjoP9W/Ecrobec/sLmQNKXi5z+oDXTaQKfmP/fhM+wKkOQ/CawcWmQ74j956SYxCKzgPzltoNMGOuA/7Hw/NV663z/DZ9gVIPfeP2CeqH8jlN0/2FxImlJx3D8qQO41F5LaP6MpFWcfPtk/Watjggfz2j98+Ay7AuTePxIRERERkfE/SeF6FK5H9j8DnTbQaQPsPwUP5on6N+U/uddcSJpS4T+EXQFyr7nePyz5xZJfLN8/QRm9LWt13j9oke18PzXcPxsv3SQGgds/HaGM3pa12j8DnTbQaQPbP5HtfD81Xto/+cWSXyz52T/+///////XPx+F61G4Htc/w2fYFSD31D9zr7mQNKXUP4ZdAXKvudQ/7TUXkqZU1D/34TPsCpDTP/0boYzeltE/7MNn2BUg0z+QCR7ME/XRP/hT46WbxNA/irMPn2FX0D/tRP0boYzOPzeJQWDl0M4/sCtA7jUXzj+2rNUxwYPNP8paHRM8mMs/7TUXkqZUzD8a6LSBThvMP/O2rNUxwcs/ScXZh8+wyz+DwMqhRbbLP4XrUbgehcs/pVScffgMzz/aQKcNdNrQP4ts5/up8co/GVpkO99PyT/tNReSplTIPzgmeDBP1Mc/FpKmVJx9yD+BlUOLbOfPP2ZmZmZmZto/I9v5fmq82D/fT42XbhLTPwisHFpkO9E/H8wT9W+E0D/bslbHBA/OP3qGXQFyr80/hxbZzvdTyz9YObTIdr7HP2etjgkezMc/VccED+aJyj9jV4Dcay7SP1fHBA/mido/L90kBoGV2z89w64AudfaP+e0gU4b6Ng/Mnpb1uqY1j/IL5b8YsnVPzJ6W9bqmNQ/dkzwYJ6o0z9iyS+W/GLTP57vp8ZLN9U/XrpJDAIr1T/hehSuR+HSP+NecyFpStM/nDbQaQOd1D/AWPKLJb/WP4QH80T9G/E/Xyz5xZJf7D8ZBFYOLbLzP1yPwvUoXPo/LbKd76fG8T8LkHvNhaTnP4XrUbgeheQ/i7MPn2FX4T+Y4ME8Uf/eP3L24TPsCt4/bstaHRM83j9fLPnFkl/ePz58hl0Bct0/+Qy7AuRe6T8yMzMzMzMDQK9H4XoUrvw/YleA3Gsu8D9b1uqY4MHoP0TSlIqzD+Y/vp8aL90k4j8VZx8+w67gP5+M3pa1Ot4/UI2XbhKD3D9CGb0ta3XiP0GnDXTaQAdAUrgehesREEC7u7u7u7v9P/tiyS+W/PY/9Shcj8L19j+LJb9Y8ov0PzltoNMGOvU/A5020GkD9T9Ei2zn+6ntP2X0tqzVMeg/uR6F61G45D+XbhKDwMriP5HtfD81XuE/zIWkKRVn2z9cj8L1KFzZPzcXkqZUnNs/G6GM3pa12j/DZ9gVIPfaPzCW/GLJL94/NewKkHvN4z+bUnH24TPjP7is1THBg98/I9v5fmq82j+DeaL+jVDYP4zelrU6Jtg/6JjgwTxR1z/J6G1Zq2PWP7uQNKXi7NU/SOF6FK5H1T/sw2fYFSDTPwisHFpkO9E/hDJ6W9bq0D+NUEZvy1rRP497zYWkKdE/gU4b6LSB0D8XIPeaC0nRP2FXgNxrLtA/Tak4+/AZ0D+xK0DuNRfQP73KoUW2880/bstaHRM8zD/PPnyGXQHKP7dJDAIrh8Y/VccED+aJyj800GkDnTbMP9uyVscED8o/sCtA7jUXyj9p5/up8dLJP8uhRbbz/cg/s+QXS36xyD/hehSuR+HGP2yg0wY6bcg/AZ020GkDyT9NG+i0gU7HPwhl9Las1cU/YJ6ofyOUxT/SBjptoNPGP2LJL5b8YsU/DLsC5F5zxT97FK5H4XrIP6/kF0t+scg/zrArQO41xz/clrU6JnjEP7bz/dR46b4/6TUXkqZUvD+0yHa+nxq/PydA7jUXkr4/J3gwT9S/wT9MfrHkF0vCP1g5tMh2vr8/F+i0gU4buD8j6t8IZfS+P2iR7Xw/Nb4/GHYFyL3muj800GkDnTa4Pxsv3SQGgb0/O5gn6t8IwT8xF5KmVJy9PxqhjN6Wtbo/f3mi/o1Qtj9/eaL+jVC2PwisHFpkO7c/V7pJDAIrtz+TJ+rfCGW8P/NvhDJ6W74/bFmrY4IHuz/aay4kTam4P0SLbOf7qbk/QwwCK4cWuT9/eaL+jVC2P4PPsCtA7rU/DjyYJ+rfuD8VS36x5Be7Pxs+w64Aubc/FUt+seQXsz94arx0kxi0P9CjcD0K17M/3SQGgZVDsz/OeOkmMQi0P7Ks1THBg7k/VOOlm8QguD8pXI/C9Si0P90kBoGVQ7M/tXSTGARWtj+9ILByaJG1PxSuR+F6FLY/efgMuwLktj+TGARWDi26PyAiIiIiIro/FUt+seQXuz+JUEZvy1q9P5lScfbhM8A/vHSTGARWwj9oSsXZh8/EP41QRm/LWsU/U5x9+Ay7zj8oo7dlrY7pP0VERERERPU/DZB7zYWk7z9b1uqY4MHiP2IQWDm0yNw/DAIrhxbZ2j90TPBgnqjZP+Olm8QgsNg/bVmrY4IH2z+85kLSlIroP1WcffgMu+4/WDm0yHa+6D9toNMGOm3qPw8tsp3vp+o/BVYOLbKd6z9rA5020GnpP1ScffgMu+Y/L90kBoGV4z9Bpw102kDiP9dcSJpSceI/K4cW2c734D9mHz7DrgDbP4/C9Shcj9o/s1bHBA/m2z8rhxbZzvfbPzxR/0Yoo9k/oYzelrU62D8wT9S/EcrUP4XrUbgehdE/Yskvlvxi0T+A3GsuJE3RP3DLWh0TPNI/3SQGgZVD0T9DGb0ta3XQP8a95kLSlM4/1XjpJjEIzD8QERERERHJP1CNl24Sg8g//3GvuZA0yT/MhaQpFWfLP6MpFWcfPss/qWOCB/NEyT8pXI/C9SjQP68AuddcSNI/7Hw/NV660T+EeaL+jVDQP5RfLPnFks8/GXYFyL3m0D+PUEZvy1rRP1mrY4IH89A/9P3UeOkm0T9ZgNxrLiTRP1VVVVVVVdE/SOF6FK5H0T8NdNpApw3SP75Y8oslv9Y/jgkezBP12T9N8GCeqH/fP90kBoGVQ+k/MU/UvxHK5j/6N0IZvS3gP9hcSJpScdo/FdnO91Pj1T9NqTj78BnYP+81F5KmVNg/0SLb+X5q1j/b+X5qvHTTP/JE/RuhjNQ/+zdCGb0t1T94ov6NUEbTP7mQNKXi7NE/a+f7qfHS0z9vEoPAyqHiP3VM8GCeqOI/3pa1OiZ42D96zYWkKRXVPxwTPJgn6tM/8WCeqH8j1D/HSzeJQWDTP5jgwTxR/9I/N4lBYOXQ0j9zaJHtfD/RPwG511xImtA/Sn6x5BdL0D9eukkMAivPPz0K16NwPc4/4TPsCpB7zT+XJ+rfCGXMP05iEFg5tMw/ke18PzVeyj+lDXTaQKfJP3XpJjEIrMg/exSuR+F6yD/5N0IZvS3HPylcj8L1KMg/opvEILByyD92d3d3d3fHP4IyelvW6sQ/Gui0gU4bxD8WkqZUnH3EP+iY4ME8UcM/obdlrY4Jwj+EXQFyr7nAP41QRm/LWsE/d76fGi/dwD8QERERERHBP/FE/RuhjL4/byFpSsXZvz+F+jdCGb29PxH1b4Qyers/tvP91Hjpwj+2rNUxwYPNP7Kd76fGS78/cK+5kDSluj91ov6NUEa3P8uwK0DuNbc/NvvwGXYFuD9Xq2OCB/O8P0DSlIqzD78/c3d3d3d3vz8rlvxiyS+2P0dTKs4+fLY/0THBg3mitj/TTWIQWDm0P7vmQtKUirM/5dAi2/l+qj9cnqh/I5SxPzeJQWDl0Lo/3SQGgZVDuz9zaJHtfD+1P7695kLSlKo/U1VVVVVVtT/JhaQpFWe3P9yWtTomeLg/XI/C9Shctz8nQO41F5K2P+6LJb9Y8rM/4XoUrkfhsj8WBoGVQ4usP2k9CtejcLU/0KNwPQrXsz/jpZvEILCyP3QFyL3mQrI/CLsC5F5zsT89KKO3Za2uP+xRuB6F67E/OdKUirMPrz/ffD81XrqpP1pzIWlKxak/qNUxwYN5sj/y4TPsCpC7P93d3d3d3cU/mzbQaQOdtj+kfyOU0duyP/T91HjpJrE/Ll66SQwCsz+R7Xw/NV6yP5HtfD81XrI/bFmrY4IHsz8zMzMzMzOzP9prLiRNqbA/JqO3Za2OsT/NzMzMzMysP0bUvxHK6K0/ObTIdr6fqj8nQO41F5KmP/QboYzelqU/HMwT9W+Esj8zMzMzMzOzP/Cnxks3ibE/KM4+fIZdsT8twYN5ov6tPz9TKs4+fKY/mIzelrU6pj8Eg8DKoUWmP0xGb8taHbM/tMh2vp8arz+VYVeA3GuuP6a5kDSl4qw/Bp9hV4Dcqz/6jVBGb8uqPzv9G6GM3qY/c3d3d3d3pz9cj8L1KFyvPz0oo7dlra4/4Yn6N0IZrT8OPJgn6t+oP/zWo3A9Cqc/XLx0kxgEpj8ALbKd76emPzenDXTaQKc/KM4+fIZdsT8EZfS2rNWxP2ig0wY6bbA/cUzwYJ6orz/g7MNn2BWwP4relrU6JrA/NNBpA502sD+CMnpb1uqwP9nO91PjpbM/koqzD59htz+W76fGSze5P/FT46WbxLg/V6tjggfzvD+TGARWDi3QP5SKsw+fYd8/o+Lsw2fY1T9qvHSTGATQPwaBlUOLbMc/h8+wK0DuxT8TyuhtWavHPzdCGb0ta8k/d76fGi/dyD+h/o1QRm/HP9yWtTomeMg/1OqY4ME8yT+GiIiIiIjIP34jlNHbssY/V2Q730+Nyz/5N0IZvS3VP2LJL5b8Ytk/ID7DrgC52z+LbOf7qfHiPyGwcmiR7eM/5DPsCpB73T+BThvotIHWP2Dl0CLb+dA/KaO3Za2O0T8nMQisHFrQPxSuR+F6FM4/L90kBoGVyz83iUFg5dDOP+XQItv5ftQ/j8L1KFyP1D8OLbKd76fSP4AjlNHbstI/Sn6x5BdL0j/8qfHSTWLSP18s+cWSX9I/bstaHRM80j+hjN6WtTrSP9V46SYxCNI/EFg5tMh20j8QERERERHXP/hT46WbxO0/rBxaZDvf6T94d3d3d3fgPxwTPJgn6ts/IGlKxdmH1z+95kLSlIrVP8E8Uf9GKNE/1DHBg3mizj/7YskvlvzKP/9xr7mQNMk/opvEILByyD9fSJpScfbJP5KKsw+fYcc/iLMPn2FXyD+XJ+rfCGXIP9QxwYN5oso/iUFg5dAiyz9cSJpScfbJP/GLJb9Y8sc/k9HbslbHyD9QjZduEoPIPyMiIiIiIsY/AZ020GkDxT8PyuhtWavHP42XbhKDwMY/PHyGXQFywz+fjN6WtTrCP6d/I5TR28Y/+xuhjN6WxT97FK5H4XrEP+7STWIQWMU/slbHBA/mxT9CtvP91HjFP4FOG+i0gcY/YOXQItv5xj8rhxbZzvfHPw2fYVeA3Mc/ROF6FK5HxT9jrY4JHszDP7M6JngwT8Q/6d8IZfS2xD+uR+F6FK7DP00b6LSBTsM/UI2XbhKDxD+WmZmZmZnFP+yY4ME8UcM/nu+nxks3wT9ecyFpSsXBP57vp8ZLN8E/6JjgwTxRvz99PzVeukm8P/Z+arx0k8A/hfo3Qhm9vT+dYVeA3Gu+P39qvHSTGLw/boQyelvWuj+bNtBpA522P395ov6NULY/q53vp8ZLtz/E2YfPsCvAP2p1TPBgnsA/01xImlJxvj8HLbKd76e2P4ts5/up8bI/ZDvfT42Xtj+LbOf7qfG6Pwrmifo3Qrk/ukkMAiuHvj+zOiZ4ME+8Pw4tsp3vp74/TdS/EcrovT/qw2fYFSC/P3n4DLsC5L4/n4zelrU6vj+j4uzDZ9i9PwuDwMqhRb4/daL+jVBGvz8pXI/C9Si8P37cay4kTbk/nMQgsHJouT9PDi2yne+3P4IyelvW6rg/Lk/UvxHKuD9KG+i0gU67P8l2vp8aL70/MzMzMzMzuz/1qfHSTWK4PwIrhxbZzrc/daL+jVBGtz//gJVDi2y3P/fUeOkmMbg/4OzDZ9gVuD800GkDnTa4PwRWDi2ynbc/koqzD59htz/aay4kTam4P4izD59hV7g/+f//////tz+GiIiIiIi4P1yeqH8jlLk/O99PjZduuj9DDAIrhxa5Pyr5xZJfLLk/zD58hl0Buj/WFSD3mgu5P2rLWh0TPLg/JHgwT9S/uT+3kDSl4uy7P5MYBFYOLbo/835qvHSTuD8MERERERG5P5kLSVMqzrY/PRm9LWt1tD/7KocW2c63P6HGSzeJQbg/fLHkF0t+uT+W76fGSze5P+xRuB6F67k/47SBThvovD8UZx8+w67QP8KuALnXXNY//7jXXEia1D9I4XoUrkfjP7pJDAIrB/Q/gU4b6LSB/D+QwvUoXI8KQIiIiIiICAhAQacNdNpAAEA30GkDnTb2P93d3d3d3fU/yi+W/GLJ9D+vR+F6FK7yP0jhehSuR+o/wBHK6G1Z5z+N3pa1OiblP79Y8oslv+I/ZfS2rNUx4T8UrkfhehThP2jYFSD3muA/mpmZmZmZ4D9zaJHtfD/fP7x0kxgEVus/U7gehetRCkBdj8L1KNwIQBzotIFOG/0/toFOG+i09D97FK5H4XryPz6nDXTaQO4/ldHbslbH5z+Qe82FpCnnP+j7qfHSTeI/KaO3Za2O4T8J80T9G6HiP/L91HjpJt8/mODBPFH/3j+SXyz5xZLdP1sdEzyYJ9w/GJKmVJx93D9jggfzRP3ZP7eQNKXi7Nk/g8DKoUW22T8Sg8DKoUXYPwJWDi2yndc/Qxm9LWt12D/jXnMhaUrXPyxA7jUXktY/E/VvhDJ60z86JngwT9TRP8gvlvxiydE/PzVeukkM0j+nDXTaQKfRP1Nx9uEz7NA/xSCwcmiRzT+bUnH24TPQP8paHRM8mMs/XnMhaUrFxT/7YskvlvzGP7M6JngwT8g/DuaJ+jdCyT9soNMGOm3MP85pA5020Mk/tMh2vp8ayz/qfD81XrrFP9IGOm2g08Y/EjyYJ+rfyD/mbVmrY4LHP/cMuwLkXsc/6d8IZfS2yD/RItv5fmrIP/nwGXYFyMU/e1vW6pjgxT8ZWmQ730/FP4AH80T9G8U/VYDcay4kxT9oSsXZh8/EP8dLN4lBYMU/nkW28/3UxD/LoUW28/3EP6jGSzeJQcA/RsXZh8+wuz/3xZJfLPm9P+RC0pSKs78/kF8s+cWSvz/lifo3QhnFP9v5fmq8dMM/vC1rdUzwxD//gJVDi2y3P3qGXQFyr7k/3sE8Uf9GwD8/NV66SQzCPzgmeDBP1MM/tWWtjgkexD8O5on6N0LFP6AaL90kBsU/YYIH80T9uz/bslbHBA/CP9hApw102sA/olScffgMuz87mCfq3wjBP7HIdr6fGsM//3GvuZA0wT/Ag3mi/o3APxsv3SQGgcE/mzbQaQOdwj/9Riijt2XBP8l2vp8aL8E/MzMzMzMzwz8PyuhtWavDP/WaC0lTKsI/xNmHz7ArwD+F61G4HoW7P63Idr6fGrc/BfNE/RuhvD85w64Aude0Pwi7AuRec7k/9jdCGb0tuz/omODBPFG3P45Di2zn+7k/+GLJL5b8sj9MN4lBYOWwP3QUrkfherQ/gjJ6W9bquD/kUbgeheu5P+Dsw2fYFbg/OlH/Riijtz+wgU4b6LS5P6ApFWcfPrM/NV66SQwCsz+YffgMuwK0P7TXXEiaUrE/f2q8dJMYtD8e95oLSVO6Pxsv3SQGgbU/tNdcSJpSuT8BnTbQaQO1P9nO91PjpbM/BGX0tqzVsT+CMnpb1uqwP9WHz7ArQLY/g8DKoUW2uz+hxks3iUG4P10s+cWSX7w/q53vp8ZLtz/WFSD3mguxP2cDnTbQabM/EyD3mgtJsz+X4ME8Uf+2P8l2vp8aL70/V7pJDAIrtz83iUFg5dC6P4ts5/up8bI/UrgehetRsD+AB/NE/RuxPxzME/VvhLI/f3mi/o1Qtj9I8GCeqH+7P9WHz7ArQLY/oBov3SQGuT9VgNxrLiS1P9K/EcrobbE/DBERERERsT92ME/UvxGyP6wcWmQ737c/yhP1b4Qyuj/+415zIWm6P6JUnH34DLs/8Las1THBsz/FL5b8YsmvP4aIiIiIiLA/gaQpFWcftj/JhaQpFWe3PwGdNtBpA7U/8Las1THBsz8+pw102kC3P1pzIWlKxbE/+FPjpZvEsD8UrkfhehSuPyUVZx8+w64/5d8IZfS2tD/9Riijt2W1Pwt02kCnDbQ/JRVnHz7Dtj+4LWt1TPCwP31OG+i0ga4/BFYOLbKdrz8ZEzyYJ+qvP10s+cWSX7Q/MqXi7MNnuD9wvp8aL920P3Wi/o1QRrc/sqzVMcGDsT+uVscED+apP9WHz7ArQK4/iLMPn2FXsD8HLbKd76e2P6R/I5TR27o/d82FpCkVtz8zQhm9LWu1Pw/K6G1Zq7M/vIN5ov6NsD/Vh8+wK0CuPy5P1L8RyrA/Di2yne+ntj8tsp3vp8a7P7gta3VM8Lg/jjSl4uzDtz/omODBPFG3Pwctsp3vp7Y/KWt1TPBgtj8+pw102kC3Pwi7AuRec7k/pH8jlNHbuj8q+cWSXyy5Px1pSsXZh7c/ucqhRbbztT+yrNUxwYOxP8UgsHJoka0/ZDvfT42Xrj8AD+aJ+jeyP2OtjgkezLM/UscED+aJsj85w64Aude0P5huEoPAyrE/FveaC0lTqj8ZBFYOLbKtP0u4HoXrUbA/5wqQe82FtD+oxks3iUG4PyUGgZVDi7Q/OlH/Riijtz9nEoPAyqG1PwisHFpkO68/YPS2rNUxsT9WHRM8mCeyP3Wi/o1QRrc/TnH24TPsuj+j4uzDZ9i1P51hV4Dca7Y/VYDcay4ktT9Xq2OCB/O0P/7jXnMhabI/LcGDeaL+tT9ooNMGOm24P7vmQtKUirs/UI2XbhKDuD/9Riijt2W1P+3u7u7u7rY/2msuJE2puD+gKRVnHz67P1CcffgMu7o/gAfzRP0buT98seQXS365Pw48mCfq37g/o/HSTWIQuD/mbVmrY4K3P2Xn+6nx0rU/j9HbslbHtD+iY4IH80StPy2yne+nxrM/5nw/NV66uT84JngwT9S3P6wcWmQ737c/mH34DLsCtD+YffgMuwK0P5qofyOU0bM/Tw4tsp3vtz9y2kCnDXS6P3WTGARWDr0/bFmrY4IHuz9iHz7DrgC5Px+U0duyVrc/LcGDeaL+tT/58Bl2Bci1P5Mn6t8IZbQ/17JWxwQPtj9QjZduEoO4PxKSplScfbg/WDm0yHa+tz/4U+Olm8S4PzMzMzMzM7s/PqcNdNpAvz/2KFyPwvXAP+Ez7AqQe8E/Gy/dJAaBwT/tNReSplTAP+IXS36x5MM/RLbz/dR40T/4mgtJUyrYP3yGXQFyr9U/QGDl0CLb1T/8qfHSTWLSP1eA3GsuJNU/qX8jlNHb4D/p3whl9LbYP1Fx9uEz7NA/FyD3mgtJyz9TnH34DLvGP/GLJb9Y8sM/Zh8+w64AxT+DwMqhRbbDP6mqqqqqqsI/jN6WtTom0D/dJAaBlUPVP0NERERERNY/BoGVQ4tsyz8fhetRuB7JP5MYBFYOLcY/arx0kxgExj956SYxCKzEP+QXS36x5NE/rkfhehSu0T84JngwT9THP9nO91PjpcM/N4lBYOXQwj+TGARWDi3KP4RdAXKvucg/ObTIdr6fxj/KWh0TPJjHP2XYFSD3msM/dZMYBFYOvT97FK5H4Xq8PydA7jUXkr4/0NuyVscEwz93vp8aL93EP8uhRbbz/cA/w/UoXI/CwT+im8QgsHLAP+8ZdgXIvb4/BfNE/RuhvD/Vh8+wK0C+PxAREREREcE/M+wKkHvNwT93vp8aL93AP3D24TPsCsA/IbByaJHtvD9OcfbhM+y6Pylcj8L1KLQ/ZwOdNtBpsz8iXI/C9Si8PyAiIiIiIro/TEZvy1oduz+R/GLJL5a8P5fgwTxR/7Y/hQkezBP1rz9pLiRNqTizP5+M3pa1OrY/vC1rdUzwwD8/NV66SQzCPyG/WPKLJb8/5m1Zq2OCwz9g5dAi2/nKP3Noke18P8k/pHA9CtejxD9qvHSTGATCP30/NV66ScQ/vljyiyW/xD/p3whl9LbEP1Qqzj58hsE/hoiIiIiIyD8YvS1rdUzQP6RwPQrXo9I/1OqY4ME8zT+CMnpb1urIP00b6LSBTsc/q44JHswTxT+411xImlLNP55hV4Dca9A/w/UoXI/CyT/58Bl2BcjFP2YfPsOuAMU/i2zn+6nxxj9dLPnFkl/IP7M6JngwT8Q/vcqhRbbzxT+SQ4ts5/vJPwisHFpkO8s/slbHBA/myT8/7jUXkqbIPwhl9Las1c0/HaGM3pa1yj/88Bl2BcjFP7PkF0t+scg/mLU6Jngwyz8neDBP1L/JP+iY4ME8Ucc/QIts5/upxT9NG+i0gU7HP3CvuZA0pcY/I9v5fmq8xD9PN4lBYOXMPx2wcmiR7cw/Q0REREREyD/VeOkmMQjIPzdCGb0ta8k/x5JfLPnF0j8WkqZUnH3WP/YoXI/C9dA/LWt1TPBgzj/QaQOdNtDbP6VUnH34DOQ/8Bl2Bci93D/LoUW28/3WP5XR27JWx9Y/mgtJUyrO1D8nMQisHFrSP0Vvy1odE9I/nmFXgNxr1j9I4XoUrkfVP5A0peLsw9E/Lmt1TPBg0D+xK0DuNRfUPzVeukkMAtM/jZduEoPA1D/Ag3mi/o3YPwfIveZC0tg/R5pScfbh1T/5DLsC5F7TPzLBg3mi/tE/Tak4+/AZ0j+PwvUoXI/SPzm0yHa+n9I/8Bl2Bci90j+6AuRecyHXP7HkF0t+sdI/dGiR7Xw/0T/G2YfPsCvQPxBYObTIdtA/YOXQItv5zj9NG+i0gU7PP9v5fmq8dM8/+JoLSVMqyj9aHRM8mCfKP85pA5020M0/2/l+arx00T9sdUzwYJ7eP/PSTWIQWN8/Gy/dJAaB1z+QNKXi7MPTP7wta3VM8NY/D59hV4Dc2T/2U+Olm8TWP3kwT9S/EdQ/NOwKkHvN0T/w0k1iEFjRP7MPn2FXgNQ/YJ6ofyOU0T/tNReSplTMP7oC5F5zIck/7tJNYhBYyT9sWatjggfLP34jlNHbsso/ZmZmZmZmyj9mHz7DrgDFP0nF2YfPsMc/U1VVVVVVzT/KWh0TPJjPP0T9G6GM3tA/u7u7u7u74j+s1THBg3nlPzbQaQOdNto/hetRuB6F0z8hsHJoke3SP8HKoUW289E/dnd3d3d3zz/14TPsCpDPP8/3U+Olm9A/4XoUrkfh0j9HmlJx9uHTP4WkKRVnH9I/W9bqmODB7T/AWPKLJf8YQI0lv1jyCxNA9ihcj8L1AkCcNtBpA534P/nFkl8s+fU/TxvotIFO8j8CK4cW2c7vPyzOPnyGXe0/pZvEILBy6T97W9bqmODlP/7UeOkmMeM/hHmi/o1Q4z8MAiuHFtnjP6tjggfzROM/ldHbslbH4T9cj8L1KFzhP7gehetRuN4/c2iR7Xw/3z8o6t8IZfTePyJpSsXZh90/sp3vp8ZL3T8ZdgXIvebeP+e0gU4b6Nw/sw+fYVeA2j9JmlJx9uHZP9QGOm2g09g/+/AZdgXI1z93vp8aL93WP+m0gU4b6NY/DuaJ+jdC1z8j2/l+arzWPy4kTak4+9Q/of6NUEZv0z/MhaQpFWfTPxX1b4QyetE/bxKDwMqhzT8AVg4tsp3PP9jqmODBPM0/5dAi2/l+yj9XVVVVVVXNP4AH80T9G8U/6nw/NV66wT9w9uEz7ArEP2hKxdmHz8Q/NReSplScxT+R7Xw/NV7KP+xRuB6F680/V2Q730+Nxz/wp8ZLN4nFP02pOPvwGdA/pSkVZx8+0T9E4XoUrkfNP3z4DLsC5Mo/XEiaUnH2zT9jggfzRP3TP3Foke18P9c/PzVeukkMzj9bq2OCB/PIP+p8PzVeusk/McGDeaL+yT9hggfzRP3LP0oMAiuHFs0/qMZLN4lBzD/5DLsC5F7TP5ZuEoPAytU/gcDKoUW20z8iTak4+/DNP0a28/3UeM0/Q0RERERE0D/VeOkmMQjIP30/NV66Scg/JqO3Za2OwT99PzVeuknAP3yx5BdLfrk/WDm0yHa+tz/LsCtA7jW3P/WaC0lTKr4/j9HbslbHvD/0/dR46Sa5P4PAyqFFtrs/EpKmVJx9uD9MRm/LWh2zPxSuR+F6FLY/VPKLJb9Yuj+xD59hV4DEP5BfLPnFkr8/P0REREREvD97W9bqmODBP9NNYhBYObw/hoiIiIiIsD9uhDJ6W9ayPwPXo3A9Crc/U1VVVVVVwT+/PFH/Rii7P0diEFg5tLg/j9HbslbHvD9LqTj78Bm2P4AH80T9G7k//VUOLbKdtz9HYhBYObS4P2k9CtejcL0/UscED+aJuj+jKRVnHz7HP37cay4kTc0/3SQGgZVDxz+yne+nxku/PwcezBP1b7w/TEZvy1oduz+j4uzDZ9i9PxqhjN6Wtbo/Tw4tsp3vtz86Uf9GKKO3P8xNYhBYObQ/Dkt+seQXqz9ooNMGOm2wP/y411xImrI/ZxKDwMqhvT9ooNMGOm24PwAP5on6N7I/lVJx9uEztD8JSVMqzj60P7TIdr6fGrc/Gz7DrgC5tz9cnqh/I5S5P9NcSJpScb4/bFmrY4IHuz/sUbgehevBP8M8Uf9GKMM/iyW/WPKLwT/MPnyGXQHCP9uyVscED8I/NReSplScwT9kO99PjZfCP7TIdr6fGr8/Ik2pOPvwsT9vEoPAyqG9P2xZq2OCB7M/hF0Bcq+5sD/l0CLb+X6yP1LHBA/mibI/N4lBYOXQuj9t5/up8dK9P/yp8dJNYsA/bxKDwMqhwT/HSzeJQWC9P5tFtvP91LA/djBP1L8Rsj+4HoXrUbi+PwuDwMqhRbY/I+rfCGX0tj9t9uEz7Aq4PwcezBP1b7Q/j8L1KFyPsj8LdNpApw20P+O0gU4b6LQ/j9HbslbHtD/bCGX0tqy1P0Uoo7dlrbY/QNKUirMPtz85w64Aude8P5SmVJx9+Lw/eekmMQisvD/+1HjpJjHAPw4tsp3vp8I/7TUXkqZUxD/KWh0TPJjHP0P9G6GM3sI/IzEIrBxaxD8CK4cW2c6/P6oPn2FXgKw/d9xrLiRNqT/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz/81qNwPQqnP/zWo3A9Cqc//NajcD0Kpz93zYWkKRWnPxKSplScfag/kfxiyS+WrD9WLPnFkl+sP37rUbgehbM/dZMYBFYOrT+e/o1QRm+rP6RwPQrXo7A/CvVvhDJ6qz+gKRVnHz6jP/zWo3A9Cqc/3TPsCpB7rT/vKFyPwvWwP1pzIWlKxbE/xJJfLPnFsj/YQKcNdNqwP7TIdr6fGq8/DjyYJ+rfsD+RC0lTKs6uP90z7AqQe60/0s73U+Olsz8xCKwcWmSzPxfotIFOG7A/UrgehetRsD++veZC0pSqP1pzIWlKxak/vq4AuddcqD9vME/UvxGqPx1aZDvfT60/VOOlm8QgsD95+Ay7AuSuP+Xu7u7u7q4/BpB7zYWkqT+P76fGSzepPwI6baDTBqo/OwwCK4cWqT8rlvxiyS+2P1H/Riijt+M/5/up8dJN5T+8dJMYBFbSP8NLN4lBYMU/U5x9+Ay7wj97FK5H4XrAP1sBcq+5kMA/6sNn2BUgvz+iRbbz/dTEP+DBPFH/RtI/S6k4+/AZ2D/dJAaBlUPTP98IZfS2rME/i2zn+6nxuj/SvxHK6G25P1TjpZvEIMA/lMQgsHJouT95+Ay7AuS2P88GOm2g07Y/62CeqH8jtD9fV4Dcay60P39qvHSTGLQ/FpKmVJx9yD99PzVeukniPzsmeDBP1OM/oYzelrU63D8wT9S/EcrQPymjt2WtjsU/5m1Zq2OCwz9soNMGOm3AP8V2vp8aL8E/BA/mifo3wj8j6t8IZfS+P2Z1TPBgnrg/5FG4HoXruT8BnTbQaQO9P8/3U+Olm8Q/7TUXkqZUyD9dLPnFkl/AP+IXS36x5L8/EfVvhDJ6uz+gGi/dJAa5PxMg95oLSbs/wSCwcmiRwT+DwMqhRba7P0dTKs4+fLY/xKFFtvP9tD9xTPBgnqi3P/NvhDJ6W7Y/o+Lsw2fYtT9JfrHkF0u2P0SaUnH24bM/QmDl0CLbqT81XrpJDAKrPzTQaQOdNrA/0r8RyuhtuT8AAAAAAACwP6JjggfzRK0/XtgVIPeaqz97QWDl0CKrP5tFtvP91LA/Ll66SQwCsz+wgU4b6LSxPyAxCKwcWrw/0s73U+Oluz8IZfS2rNXFPxh2Bci95sI/VOOlm8QgwD/uiyW/WPKzPzB6W9bqmLA/8KfGSzeJsT/58Bl2Bci1PxqwcmiR7bQ/9ZoLSVMqtj//gJVDi2y3P+ZtWatjgrc/w/UoXI/CtT+Isw+fYVewP9prLiRNqbA/QwwCK4cWsT8q+cWSXyyxP4GVQ4ts57M/qWOCB/NEtT9Ei2zn+6mxPxfotIFOG6g/rmWtjgkerD/clrU6JniwP3sUrkfherw/Dkt+seQXqz9acyFpSsWpP1Eqzj58hrU/BpB7zYWksT9xTPBgnqivP1pzIWlKxbE/SPBgnqh/sz+6WPKLJb+4P2CeqH8jlME/CtejcD0Kyz9fV4Dcay7EP7uQNKXi7Mc/72CeqH8j0j/wp8ZLN4nNPyPb+X5qvMQ/ukkMAiuHvj8ZEzyYJ+q3P5+M3pa1OrY/U1VVVVVVtT+gGi/dJAaxPwwCK4cW2a4/djBP1L8Rsj82+/AZdgWwPx73mgtJU7I/sqzVMcGDsT8/NV66SQyyP4relrU6JrA/4XoUrkfhqj/A91PjpZukPydP1L8Ryqg/vHSTGARWrj+f76fGSzfhP+7u7u7u7vo/z7ArQO415D//uNdcSJrOP7vmQtKUisM/c3d3d3d3tz//gJVDi2y3P3Wi/o1QRrc/1hUg95oLwT/I6G1Zq2O6P7YC5F5zIbk/P0REREREvD+R7Xw/NV66P/NvhDJ6W7Y/wXa+nxovtT+Dz7ArQO61P6G3Za2OCb4/q44JHswTvT8X6LSBThu4P8DZh8+wK7g/6TUXkqZUtD/hifo3QhmtP3n4DLsC5K4/ZwOdNtBpsz93zYWkKRW3P/N+arx0k7g/FK5H4XoUtj/KItv5fmq0PxMREREREbk/3TPsCpB7vT/bCGX0tqy9Pzb78Bl2Bbg/j9HbslbHvD9t5/up8dK9PyuHFtnO97s/x1odEzyYvz9EmlJx9uG7P0dTKs4+fLY/RJpScfbhsz9fV4Dcay60P+Dsw2fYFbg/H5TR27JWtz/qw2fYFSC3PyUVZx8+w7Y/46WbxCCwsj8SoYzelrWqPzEXkqZUnK0/vRHK6G1Zsz+5u7u7u7uzP0jwYJ6of7s/sp3vp8ZLzz/14TPsCpDVPwlJUyrOPsw/VOOlm8QgwD+iVJx9+Ay7P28haUrF2bc/Y62OCR7Muz9+3GsuJE25P/fUeOkmMbg/7xl2Bci9tj8qCKwcWmSzPznSlIqzD68/4OzDZ9gVsD/+1HjpJjGwPz9ERERERLQ/WwFyr7mQtD/5N0IZvS3RP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP8vobVmrY9I/Pd9PjZdu0j8930+Nl27SP8nobVmrY9I/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI//Knx0k1i0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j80peLsw2fSP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/ke18PzVe0j+R7Xw/NV7SP5HtfD81XtI/LWt1TPBg0j8930+Nl27SP9Mi2/l+atI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j8930+Nl27SPz3fT42XbtI/Pd9PjZdu0j+R7Xw/NV7SP+9gnqh/I9I/m1Jx9uEz0j+EeaL+jVDSP5HtfD81XtI/ke18PzVe0j/QlIqzD5/NP6RwPQrXo7A/0r8RyuhtsT/vGXYFyL2+PywkTak4+9Y/M8GDeaJ+9D8jIiIiIiL1P+DBPFH/Rtg/PQrXo3A9yj9KYhBYObTEPwXzRP0bocA/D8robVmruz+2AuRecyG5Pzx8hl0Bcrc/DAIrhxbZtj99ThvotIG2P79LN4lBYLU/sQ+fYVeAvD81XrpJDALhP3E9CtejcPw/EeaJ+jfC9j/D9Shcj8LVPxzotIFOG9A/89JNYhBY3T/4U+Olm8TmP1iA3GsuJOA/v8qhRbbz1z8JZfS2rNXRP8uhRbbz/cw/Yh8+w64AyT8m6t8IZfTGPw7mifo3QsU/16NwPQrXwz89CtejcD3CP3Noke18P8E/tWWtjgkewD/t7u7u7u6+P51hV4Dca74/fU4b6LSBvj9YObTIdr6/P3FM8GCeqL8/K5b8Yskvvj83iUFg5dC6P4AH80T9G7k/1hUg95oLuT8q+cWSXyy5P5KZmZmZmbk/tgLkXnMhuT+0gU4b6LTBP7SBThvotNE/Yskvlvxi0T+5u7u7u7vHPyUGgZVDi8A/mQtJUyrOvj9RcfbhM+zKPxKDwMqhRc4/i2zn+6nxyj+Hz7ArQO7BP6UNdNpAp70/z/dT46WbvD9zaJHtfD/JP5cn6t8IZd4/D+aJ+jdC4D9fcyFpSsXXP21Zq2OCB9M/x0s3iUFg0T+R7Xw/NV7QPzal4uzDZ8w//iqHFtnOxz92d3d3d3fHPyGwcmiR7cg/5Yn6N0IZyT9IUyrOPnzeP1ScffgMu+Y/kAkezBP12T8+fIZdAXLRP9QxwYN5otA/46WbxCCw1j+v5BdLfrHaP1YOLbKd79k/EzyYJ+rf4z9Hb8taHRPqP9qHz7ArQOM/x73mQtKU2j/yRP0boYzUPxl2Bci95tI/LiRNqTj70D/kQtKUirPPP3OvuZA0pc4/YOXQItv5zj8nXI/C9SjSP8l2vp8aL9M/1uqY4ME80T8Nn2FXgNzPPwisHFpkO88/y+htWatjzj8YvS1rdUzMP0SLbOf7qck/ctpApw10xj8uT9S/EcrEPz3DrgC518Q/q44JHswTxT8q+cWSXyzFPwGdNtBpA8U/qMZLN4lBxD81XrpJDALDPxUEVg4tssE/IbByaJHtwD+T0duyVsfAP8uhRbbz/cA/y6FFtvP9wD+v5BdLfrHAP6jGSzeJQcA/vHSTGARWvj+75kLSlIq7PwAP5on6N7o/nMQgsHJouT+sK0DuNRe6P6jVMcGDebo//LjXXEiauj/LoUW28/28P/7jXnMhaco/HbByaJHtxD/1mgtJUyq+PwXzRP0bobw/EyD3mgtJuz/hehSuR+G6P/y411xImro/EyD3mgtJuz8IuwLkXnO5P+iY4ME8Ubc/7xl2Bci9tj+fjN6WtTq2P51hV4Dca7Y/Q/0boYzetj/vGXYFyL22PylrdUzwYLY/EQRWDi2ytT9dLPnFkl+0P2cDnTbQabM/ShvotIFOsz/Qo3A9CtezPyAxCKwcWrQ/X1eA3GsutD+75kLSlIqzP8SSXyz5xbI/Prbz/dR4sT8q+cWSXyyxP57vp8ZLN7E/JqO3Za2OsT/KE/VvhDKyP8w+fIZdAbI/PzVeukkMsj+AB/NE/RuxPwAAAAAAALA/4ZjgwTxRrz/l7u7u7u6uPwisHFpkO68/TmIQWDm0sD+GiIiIiIiwP4izD59hV7A/iV8s+cWSrz8UrkfhehSuPznDrgC516w/eekmMQisrD/Jdr6fGi+tPz0oo7dlra4/zduyVscErz89KKO3Za2uP83MzMzMzKw/1XjpJjEIrD9e2BUg95qrP/LhM+wKkKs/rmWtjgkerD8ZBFYOLbKtPxSuR+F6FK4/mrdlrY4Jrj+JUEZvy1qtP421OiZ4MK8/5/up8dJNsj+/PFH/RiizP/Y3Qhm9LbM/wmfYFSD3sj+v1THBg3myP/1GKKO3ZbU/1XjpJjEItD9KDAIrhxaxP8Uvlvxiya8/zduyVscErz9xTPBgnqivP54cWmQ7368/jbU6Jngwrz8QWDm0yHauP90z7AqQe60/gZVDi2znqz+2EcrobVmrP90kBoGVQ6s/lVJx9uEzrD+NplScffisP6a5kDSl4qw//vJE/RuhrD9aggfzRP2rP7YRyuhtWas/vr3mQtKUqj+qALnXXEiqPwI6baDTBqo/4XoUrkfhqj/y4TPsCpCrP0bF2YfPsKs/dZMYBFYOrT/FILByaJGtP5VhV4Dca64/PRm9LWt1rD/RItv5fmqsP4GkKRVnH64/iVBGb8tarT+NplScffisPxSuR+F6FK4/umfYFSD3qj+YffgMuwK0P4lQRm/LWq0/fT81XrpJrD9KKs4+fIatP83MzMzMzKw/fT81XrpJrD8Gn2FXgNyrP2aEMnpb1qo/mpmZmZmZqT8j6t8IZfSmP+cZdgXIvaY/uljyiyW/qD9iLiRNqTirP17YFSD3mqs/thHK6G1Zqz+Le82FpCm1P+Z8PzVeurk/qMZLN4lBsD99ThvotIGuP/LwGXYFyK0/eekmMQisrD9Cb8taHROsP6oPn2FXgKw/NV66SQwCqz/dJAaBlUOrP+F6FK5H4ao/UscED+aJqj+JQWDl0CKrPzEIrBxaZKs/sru7u7u7qz+iVJx9+AyrPxb3mgtJU6o/nv6NUEZvqz+qALnXXEiqP3fcay4kTak/lkOLbOf7qT9OcfbhM+yqP05x9uEz7Ko/RsXZh8+wqz9mhDJ6W9aqP4X6N0IZva0/l5vEILByqD9/eaL+jVCmP2rLWh0TPKg/EqGM3pa1qj/hehSuR+GqP/ZGKKO3Za0/l5vEILByqD+HNKXi7MOnP99tWatjgqc//NajcD0Kpz8SkqZUnH2oP+58PzVeuqk/6SYxCKwcqj89CtejcD2qPz0K16NwPao/5dAi2/l+qj/pJjEIrByqP7695kLSlKo/ShvotIFOqz/2N0IZvS2rP8MT9W+EMqo/Yh8+w64AqT9/iIiIiIioP/QqhxbZzqc/j+DBPFH/pj9/eaL+jVCmPzv9G6GM3qY/c3d3d3d3pz/fbVmrY4KnPzenDXTaQKc/zwY6baDTpj9EqTj78BmmP2ASg8DKoaU/CNnO91PjpT8Eg8DKoUWmP4/gwTxR/6Y//NajcD0Kpz8j6t8IZfSmP1hmZmZmZqY/8MWSXyz5pT9I/0Yoo7elP9sIZfS2rKU/K5b8Yskvpj+sSQwCK4emP6xJDAIrh6Y/P1Mqzj58pj9cvHSTGASmP/QboYzelqU/vKFFtvP9pD+8oUW28/2kPwwv3SQGgaU/SP9GKKO3pT9cvHSTGASmP9NcSJpScaY/tPUoXI/CpT/0G6GM3palP4t7zYWkKaU/kyfq3whlpD+HJb9Y8oulPz9TKs4+fKY/01xImlJxpj93zYWkKRWnP5zi7MNn2KU/UKtjggfzpD8ML90kBoGlPwwv3SQGgaU/XLx0kxgEpj/wxZJfLPmlP9sIZfS2rKU/L+wKkHvNpT9kaJHtfD+lP5Mn6t8IZaQ/sJA0peLsoz91wMqhRbajP1hXgNxrLqQ/bBSuR+F6pD9UAXKvuZCkP1hXgNxrLqQ/62CeqH8jpD9crY4JHsyjP835fmq8dKM/oCkVZx8+oz91wMqhRbajP2wUrkfheqQ/kyfq3whlpD+YffgMuwKkP/QMuwLkXqM/qNUxwYN5oj+8kl8s+cWiP/y411xImqI//LjXXEiaoj95FtnO91OjP0xGb8taHaM/xU1iEFg5pD+gKRVnHz6jPxkiIiIiIqI/VPKLJb9Yoj8IyuhtWaujP4ts5/up8aI/i2zn+6nxoj+LbOf7qfGiP0xGb8taHaM/EHYFyL3moj+8kl8s+cWiPzvfT42XbqI/qNUxwYN5oj+LbOf7qfGiP4ts5/up8aI/DCD3mgtJoz/N+X5qvHSjP835fmq8dKM/TEZvy1odoz/4YskvlvyiP4ts5/up8aI/ZFmrY4IHoz8h3SQGgZWjPx2HFtnO96M/HYcW2c73oz8dhxbZzvejP6ApFWcfPqM/qNUxwYN5oj/n+6nx0k2iP7ySXyz5xaI/zfl+arx0oz8MIPeaC0mjPwSDwMqhRaY/47SBThvopD9QnH34DLuiP6ApFWcfPqM/j8L1KFyPoj8ZIiIiIiKiP5MYBFYOLaI/TEZvy1odoz8MIPeaC0mjP7CQNKXi7KM/uEs3iUFgpT9I8GCeqH+jP4ts5/up8aI/zfl+arx0oz9EmlJx9uGjPx2HFtnO96M/9BuhjN6WpT8QhetRuB6lP2Roke18P6U/2/l+arx0oz+PwvUoXI+iP1CcffgMu6I/HYcW2c73oz+8oUW28/2kP6jkF0t+saQ/GTEIrBxapD91wMqhRbajP835fmq8dKM/yaNwPQrXoz91wMqhRbajPz9TKs4+fKY//vJE/RuhrD81baDTBjqtP2IuJE2pOKs/K6Xi7MNnqD8j6t8IZfSmP9eyVscED6Y/315zIWlKpT8/RERERESkPx2HFtnO96M/+HGvuZA0pT+wkDSl4uyjPzvfT42XbqI/9Ay7AuReoz9or7mQNKWiPzvfT42XbqI/bAXIveZCoj/4YskvlvyiPzMzMzMzM6M/eRbZzvdToz/wxZJfLPmlP1CrY4IH86Q//LjXXEiaoj8AD+aJ+jeiP+xRuB6F66E/FMwT9W+Eoj8QhetRuB6lPwR02kCnDaQ/GSIiIiIioj+kfyOU0duiPzvfT42XbqI/WEiaUnH2oT/sUbgeheuhP6jVMcGDeaI/yaNwPQrXoz/0G6GM3palP1hXgNxrLqQ/CMrobVmroz8h3SQGgZWjP05x9uEz7LI/5d8IZfS2tD8xF5KmVJy1P+Dsw2fYFbA/bzBP1L8Rqj+Dz7ArQO6lP5h9+Ay7AqQ/HYcW2c73oz8dhxbZzvejP835fmq8dKM/XK2OCR7Moz9EqTj78BmmP+O0gU4b6KQ//LjXXEiaoj8/NV66SQyiP8U+fIZdAaI/O99PjZduoj8UzBP1b4SiP6R/I5TR26I/i2zn+6nxoj+LbOf7qfGiP4ts5/up8aI/N4lBYOXQoj8730+Nl26iPzvfT42XbqI/aK+5kDSloj+LbOf7qfGiP4ts5/up8aI/ZFmrY4IHoz9kWatjggejP99PjZduEqM/i2zn+6nxoj8UzBP1b4SiP6R/I5TR26I/i2zn+6nxoj+LbOf7qfGiP0xGb8taHaM/i2zn+6nxoj9QnH34DLuiPzvfT42XbqI/O99PjZduoj8730+Nl26iP1CcffgMu6I/i2zn+6nxoj9or7mQNKWiP1TyiyW/WKI/aK+5kDSloj8730+Nl26iP1TyiyW/WKI/7FG4HoXroT/A6G1Zq2OiPzeJQWDl0KI/VPKLJb9Yoj/FPnyGXQGiPzvfT42XbqI/O99PjZduoj8730+Nl26iPzvfT42XbqI/O99PjZduoj8730+Nl26iP6jVMcGDeaI/O99PjZduoj8730+Nl26iP8DobVmrY6I/WEiaUnH2oT/sUbgeheuhP8U+fIZdAaI/O99PjZduoj8730+Nl26iPzvfT42XbqI/AA/mifo3oj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/VPKLJb9Yoj/sUbgeheuhP+xRuB6F66E/7FG4HoXroT/sUbgeheuhP+xRuB6F66E/c2iR7Xw/pT/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/+qscWmQ7rz/6qxxaZDuvP/qrHFpkO68/6UT9G6GMrj/fXnMhaUq1PwtJUyrOPtI/2ECnDXTa1j+uVscED+bJP9NcSJpScb4/OCZ4ME/Utz/fXnMhaUq1P6aqqqqqqrI/zD58hl0Bsj+TGARWDi2yP+XfCGX0trQ/EQRWDi2ytT9VgNxrLiS1P1CcffgMu7I/5FG4HoXrsT8xF5KmVJytPxSuR+F6FK4//gErhxbZrj+Isw+fYVewP+xRuB6F67E/8Las1THBsz+BlUOLbOezP00b6LSBTsc/JL9Y8osl1T8WkqZUnH3MPxcv3SQGgcE/f2q8dJMYvD/4U+Olm8S4P+rDZ9gVILc/5m1Zq2OCtz/+415zIWm6P+81F5KmVOo/XI/C9Shc8D92d3d3d3fXP6d/I5TR28o/y/dT46WbxD8dWmQ730/BP5kLSVMqzr4/CUlTKs4+vD+R7Xw/NV66P/T91HjpJrk/MHpb1uqYuD+EXQFyr7m4P+Dsw2fYFbg/QNKUirMPtz+zSQwCK4e2PyuHFtnO97M/GHYFyL3msj+xD59hV4C0PyJcj8L1KLQ/JIcW2c73sz9hggfzRP2zP+6LJb9Y8rM/Y62OCR7Msz9I8GCeqH+zP4lBYOXQIrM/qNUxwYN5sj9WHRM8mCeyP5KZmZmZmbE/9P3UeOkmsT/YQKcNdNqwP5+bxCCwcrA/bfbhM+wKsD/2VQ4tsp2vP3FM8GCeqK8/+qscWmQ7rz89KKO3Za2uP9ExwYN5oq4/FK5H4XoUrj+F+jdCGb2tP3npJjEIrKw/7poLSVMqrj9G1L8RyuitP0bUvxHK6K0/gaQpFWcfrj9BfrHkF0uuP2Dl0CLb+a4/SirOPnyGrT8QWDm0yHauPxkEVg4tsq0/2d3d3d3drT/FILByaJGtPxkEVg4tsq0/1YfPsCtArj8UrkfhehSuP0F+seQXS64/qvHSTWIQsD8MAiuHFtm2P6MpFWcfPsM/3SQGgZVDxz97W9bqmODBP1NVVVVVVcE//iqHFtnOxz9cj8L1KFzHP26EMnpb1sI/ZdgVIPeauz8D16NwPQq3PwPXo3A9Crc/A9ejcD0Ktz8pa3VM8GC2P2cSg8DKobU/cL6fGi/dtD92PzVeukm0P7vmQtKUirM/UJx9+Ay7sj+qALnXXEiyP6wrQO41F7I/AjptoNMGsj/KE/VvhDKyP/7jXnMhabI/yhP1b4Qysj/n+6nx0k2yPwRl9Las1bE/0JSKsw+fsT+PwvUoXI+yPxMv3SQGgbU/EGcfPsOuuD+v8/3UeOm+P625kDSl4sg/M+wKkHvNzT8zMzMzMzPLP90kBoGVQ88/oYzelrU60D/YQKcNdNrIP0NERERERMQ/+fAZdgXIwT9fV4Dcay7AP4GkKRVnH74/6TUXkqZUvD8TIPeaC0m7P/7jXnMhabo/sqzVMcGDuT+yrNUxwYO5PywkTak4+7g/hF0Bcq+5uD+Isw+fYVe4Px1pSsXZh7c/WeXQItv5tj+j8dJNYhC4Pyajt2Wtjrk/MzMzMzMzuz+QbhKDwMq5P+391HjpJrk/P0REREREvD8HHswT9W/AP51hV4Dca8I/AuRecyFpwj+T0duyVsfIP3yx5BdLfsU/EBERERERyT/i7MNn2BXQPyGwcmiR7cg/4hdLfrHkwz/7G6GM3pbBP4relrU6JsQ/aQOdNtBp1T/NzMzMzMzcP42XbhKDwNQ/lpmZmZmZzT956SYxCKzIPyJNqTj78MU/9n5qvHSTxD/kQtKUirPDPwwCK4cW2cY//iqHFtnOzz9l2BUg95rPPw7mifo3Qsk/c2iR7Xw/xT8xCKwcWmTDPx73mgtJU8I/iyW/WPKLwT93vp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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[11697]},\"__x__values_original\":{\"__ndarray__\":\"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Moreover, visualizing every single dot is not useful anymore at coarser zoom levels. " + "Working with such a data set on a local machine is not straightforward anymore, as this data set will consume a lot of memory to be handled by the default plotting libraries. Moreover, visualizing every single dot is not useful anymore at coarser zoom levels." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The package [datashader](https://bokeh.github.io/datashader-docs/index.html) provides a solution for this size of data sets and works together with other packages such as `Bokeh` and `Holoviews`." + "The package [datashader](https://datashader.org/) provides a solution for this size of data sets and works together with other packages such as `Bokeh` and `Holoviews`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The data from [the gull data set](https://zenodo.org/record/3541812#.XfZYcNko-V6) is downloaded and stored it in the `data` folder and is not part of the Github repository. For example, downloading the [2018 data set](https://zenodo.org/record/3541812/files/HG_OOSTENDE-acceleration-2018.csv?download=1) from Zenodo:" + "The data from [the gull data set](https://zenodo.org/record/3541812#.XfZYcNko-V6) is downloaded and stored it in the `data` folder and is not part of the Github repository. For example, after downloading the [2018 data set](https://zenodo.org/record/3541812/files/HG_OOSTENDE-gps-2018.csv?download=1) from Zenodo:" ] }, { @@ -146014,15 +1032,24 @@ "metadata": {}, "outputs": [], "source": [ - "import pandas as pd, holoviews as hv\n", + "import pandas as pd\n", + "import holoviews as hv\n", + "import hvplot.pandas \n", "from colorcet import fire\n", - "from datashader.utils import lnglat_to_meters\n", - "from holoviews.element.tiles import EsriImagery\n", - "from holoviews.operation.datashader import rasterize, shade\n", "\n", + "hv.extension('bokeh')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ "df = pd.read_csv('data/HG_OOSTENDE-gps-2018.csv', nrows=1_000_000, # for the live demo on my laptop, I just use 1_000_000 points\n", - " usecols=['location-long', 'location-lat', 'individual-local-identifier'])\n", - "df.loc[:,'location-long'], df.loc[:,'location-lat'] = lnglat_to_meters(df[\"location-long\"], df[\"location-lat\"])" + " usecols=['location-long', 'location-lat', \n", + " 'individual-local-identifier'])\n", + "df.head()" ] }, { @@ -146031,14 +1058,19 @@ "metadata": {}, "outputs": [], "source": [ - "hv.extension('bokeh')\n", - "\n", - "map_tiles = EsriImagery().opts(alpha=1.0, width=600, height=600, bgcolor='black')\n", - "points = hv.Points(df, ['location-long', 'location-lat'])\n", - "rasterized = shade(rasterize(points, x_sampling=1, y_sampling=1, \n", - " width=600, height=600), cmap=fire)\n", - "\n", - "map_tiles * rasterized" + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df.hvplot.points('location-long', 'location-lat', geo=True, tiles='ESRI', \n", + " datashade=True, aggregator='count', cmap=fire, project=True,\n", + " xlim=(-5, 5), ylim=(48, 53), frame_width=600)" ] }, { @@ -146153,8 +1185,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -146168,7 +1203,14 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } } }, "nbformat": 4, diff --git a/_solved/workflow_example_evaluation.ipynb b/_solved/workflow_example_evaluation.ipynb index 14daab2..46638dc 100644 --- a/_solved/workflow_example_evaluation.ipynb +++ b/_solved/workflow_example_evaluation.ipynb @@ -4,11 +4,18 @@ "cell_type": "code", "execution_count": 1, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "tags": [] + "collapsed": true + }, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true }, "outputs": [], "source": [ @@ -26,45 +33,22 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 3, + "metadata": {}, "outputs": [], "source": [ - "data = pd.read_csv(\"data/vmm_flowdata.csv\", parse_dates=True, index_col=0).dropna()" + "data = pd.read_csv(\"../data/vmm_flowdata.csv\", parse_dates=True, index_col=0).dropna()" ] }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", - "\n", "\n", " \n", " \n", @@ -125,7 +109,7 @@ "2009-01-01 12:00:00 0.140917 0.096167 0.017000" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -150,13 +134,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "tags": [] + "collapsed": true }, "outputs": [], "source": [ @@ -166,13 +146,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "tags": [] + "collapsed": true }, "outputs": [], "source": [ @@ -181,21 +157,16 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.0584130361517864" + "0.058413036151786404" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -213,13 +184,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "tags": [] + "collapsed": true }, "outputs": [], "source": [ @@ -252,21 +219,16 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.0584130361517864" + "0.058413036151786404" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -277,7 +239,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -311,13 +273,9 @@ " Notes\n", " -------\n", " Some information about your function,...\n", - " '''" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ + " '''\n", + "\n", + "\n", "## Making a plot function" ] }, @@ -337,24 +295,17 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 24, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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"text/plain": [ - "
" + "" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -410,9 +359,9 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 88, "metadata": { - "tags": [] + "collapsed": true }, "outputs": [], "source": [ @@ -440,29 +389,27 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 89, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Text(0, 0.5, 'Putting the label should not \\nbe inside my custom function')" + "" ] }, - "execution_count": 13, + "execution_count": 89, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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" + "" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -481,19 +428,17 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 92, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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"text/plain": [ - "
" + "" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -521,29 +466,27 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 50, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Text(0, 0.5, 'Putting the label should not \\nbe nside my custom function')" + "" ] }, - "execution_count": 15, + "execution_count": 50, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", 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" + "" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -604,7 +545,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 112, "metadata": {}, "outputs": [], "source": [ @@ -638,19 +579,17 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 113, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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" + "" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -661,19 +600,17 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 114, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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"text/plain": [ - "
" + "" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -694,7 +631,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "When satisfied about the function behavior: move it to a python (`.py`) file...\n" + "When satisfied about the function behavior: move it to a python (`.py`) file..." ] }, { @@ -737,13 +674,9 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 121, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "tags": [] + "collapsed": true }, "outputs": [], "source": [ @@ -759,24 +692,17 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 130, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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HkFO0xIFuJFr/vNwnDR9YpfdOtMonqfK9bTpv8iR99toPye9L+oYZAHqLZVeB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\n0AAAAABJRU5ErkJggg==\n", "text/plain": [ - "
" + "" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -837,19 +763,14 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "execution_count": 131, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Writing puretest.py\n" + "Overwriting puretest.py\n" ] } ], @@ -870,12 +791,7 @@ }, { "cell_type": "markdown", - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "source": [ "**Want to dive into the command line options?**\n", "* example with more advanced arguments: https://github.com/inbo/inbo-pyutils/blob/master/gbif/gbif_name_match/gbif_species_name_match.py\n", @@ -912,7 +828,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As an example: https://github.com/fluves/pywaterinfo" + "As an example: https://github.com/inbo/data-validator" ] }, { @@ -921,20 +837,16 @@ "source": [ "* Actually it is not that much more as a set of files in a folder accompanied with a `setup.py` file\n", "* register on [pypi](https://pypi.python.org/pypi) and people can install your code with: `pip install your_awesome_package_name`\n", - "* Take advantage of **unit testing**, **code coverage**,... the enlightning path of code development!\n" + "* Take advantage of **unit testing**, **code coverage**,... the enlightning path of code development!" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -948,7 +860,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/convert_notebooks.sh b/convert_notebooks.sh index fbb8384..6418b4e 100755 --- a/convert_notebooks.sh +++ b/convert_notebooks.sh @@ -10,19 +10,19 @@ declare -a arr=( #"04-reusing_code.ipynb" #"05-numpy.ipynb" #"python_rehearsal" - #"00-jupyter_introduction.ipynb" - #"pandas_01_data_structures.ipynb" - #"pandas_02_basic_operations.ipynb" - #"pandas_03a_selecting_data.ipynb" - #"pandas_03b_indexing.ipynb" - #"pandas_04_time_series_data.ipynb" - #"pandas_05_combining_datasets.ipynb" - #"pandas_06_groupby_operations.ipynb" - #"pandas_07_reshaping_data.ipynb" - #"pandas_08_missing_values.ipynb" - #"visualization_01_matplotlib.ipynb" - #"visualization_02_seaborn.ipynb" - #"visualization_03_landscape.ipynb" + "00-jupyter_introduction.ipynb" + "pandas_01_data_structures.ipynb" + "pandas_02_basic_operations.ipynb" + "pandas_03a_selecting_data.ipynb" + "pandas_03b_indexing.ipynb" + "pandas_04_time_series_data.ipynb" + "pandas_05_combining_datasets.ipynb" + "pandas_06_groupby_operations.ipynb" + "pandas_07_reshaping_data.ipynb" + "pandas_08_missing_values.ipynb" + "visualization_01_matplotlib.ipynb" + "visualization_02_seaborn.ipynb" + "visualization_03_landscape.ipynb" "case1_bike_count.ipynb" "case2_observations_processing.ipynb" "case2_observations_analysis.ipynb" diff --git a/img/matplotlib_oo.png b/img/matplotlib_oo.png new file mode 100644 index 0000000..022495c Binary files /dev/null and b/img/matplotlib_oo.png differ diff --git a/img/tidy_data_scheme.png b/img/tidy_data_scheme.png new file mode 100644 index 0000000..84e4a3d Binary files /dev/null and b/img/tidy_data_scheme.png differ diff --git a/notebooks/00-jupyter_introduction.ipynb b/notebooks/00-jupyter_introduction.ipynb index 53d826e..9431a77 100644 --- a/notebooks/00-jupyter_introduction.ipynb +++ b/notebooks/00-jupyter_introduction.ipynb @@ -2,19 +2,11 @@ "cells": [ { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "

Jupyter notebook INTRODUCTION

\n", "\n", - "\n", - "> *DS Data manipulation, analysis and visualisation in Python* \n", - "> *December, 2019*\n", - "\n", - "> *© 2016, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", + "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" ] @@ -22,15 +14,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "outputs": [], "source": [ "from IPython.display import Image\n", @@ -39,11 +23,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "
To run a cell: push the start triangle in the menu or type **SHIFT + ENTER/RETURN**\n", "![](../img/shiftenter.jpg)" @@ -58,22 +38,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "We will work in **Jupyter notebooks** during this course. A notebook is a collection of `cells`, that can contain different content:" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Code" ] @@ -81,15 +53,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Code cell, then we are using python\n", @@ -99,15 +63,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "DS = 10\n", @@ -123,33 +79,21 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Markdown" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "Text cells, using Markdown syntax. With the syntax, you can make text **bold** or *italic*, amongst many other things..." ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "* list\n", "* with\n", @@ -163,24 +107,16 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "Mathematical formulas can also be incorporated (LaTeX it is...)\n", "$$\\frac{dBZV}{dt}=BZV_{in} - k_1 .BZV$$\n", - "$$\\frac{dOZ}{dt}=k_2 .(OZ_{sat}-OZ) - k_1 .BZV$$\n" + "$$\\frac{dOZ}{dt}=k_2 .(OZ_{sat}-OZ) - k_1 .BZV$$" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "Or tables:\n", "\n", @@ -203,22 +139,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "Code can also be incorporated, but than just to illustrate:" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "```python\n", "BOT = 12\n", @@ -228,11 +156,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "See also: https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet" ] @@ -246,11 +170,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "You can also use HTML commands, just check this cell:\n", "

html-adapted titel with <h3>

\n", @@ -259,11 +179,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "## Headings of different sizes: section\n", "### subsection\n", @@ -272,44 +188,28 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Raw Text" ] }, { "cell_type": "raw", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "Cfr. any text editor" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "# Notebook handling ESSENTIALS" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Completion: TAB\n", "![](../img/tabbutton.jpg)" @@ -317,11 +217,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "* The **TAB** button is essential: It provides you all **possible actions** you can do after loading in a library *AND* it is used for **automatic autocompletion**:" ] @@ -329,15 +225,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "outputs": [], "source": [ "import os\n", @@ -347,15 +235,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "my_very_long_variable_name = 3" @@ -363,22 +243,14 @@ }, { "cell_type": "raw", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "my_ + TAB" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Help: SHIFT + TAB\n", "![](../img/shift-tab.png)" @@ -386,27 +258,15 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ - "* The **SHIFT-TAB** combination is ultra essential to get information/help about the current operation " + "* The **SHIFT-TAB** combination is ultra essential to get information/help about the current operation" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "round(3.2)" @@ -415,15 +275,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "import os\n", @@ -433,15 +285,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "# An alternative is to put a question mark behind the command\n", @@ -450,29 +294,17 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "
\n", - " EXERCISE: What happens if you put two question marks behind the command?\n", + " EXERCISE 1: What happens if you put two question marks behind the command?\n", "
" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "import glob\n", @@ -481,16 +313,12 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## *edit* mode to *command* mode\n", "\n", - "* *edit* mode means you're editing a cell, i.e. with your cursor inside a cell to type content --> green colored side\n", - "* *command* mode means you're NOT editing(!), i.e. NOT with your cursor inside a cell to type content --> blue colored side\n", + "* *edit* mode means you're editing a cell, i.e. with your cursor inside a cell to type content\n", + "* *command* mode means you're NOT editing(!), i.e. NOT with your cursor inside a cell to type content\n", "\n", "To start editing, click inside a cell or \n", "\"Key\n", @@ -501,11 +329,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## new cell A-bove\n", "\"Key\n", @@ -515,11 +339,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## new cell B-elow\n", "\"Key\n", @@ -529,44 +349,28 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## CTRL + SHIFT + C" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "Just do it!" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## Trouble..." ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "
\n", " NOTE: When you're stuck, or things do crash: \n", @@ -579,11 +383,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "* **Stackoverflow** is really, really, really nice!\n", "\n", @@ -592,22 +392,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "* Google search is with you!" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "
**REMEMBER**: To run a cell: push the start triangle in the menu or type **SHIFT + ENTER**\n", "![](../img/shiftenter.jpg)" @@ -615,22 +407,14 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "# some MAGIC..." ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## `%psearch`" ] @@ -638,15 +422,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "%psearch os.*dir" @@ -654,11 +430,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "## `%%timeit`" ] @@ -666,15 +438,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "%%timeit\n", @@ -687,15 +451,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "import numpy as np" @@ -704,15 +460,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "%%timeit\n", @@ -738,11 +486,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "subslide" - } - }, + "metadata": {}, "source": [ "## `%lsmagic`" ] @@ -750,15 +494,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "%lsmagic" @@ -766,11 +502,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ "# Let's get started!" ] @@ -778,15 +510,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "from IPython.display import FileLink, FileLinks" @@ -795,15 +519,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - }, - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "outputs": [], "source": [ "FileLinks('.', recursive=False)" @@ -811,11 +527,7 @@ }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "fragment" - } - }, + "metadata": {}, "source": [ "The follow-up notebooks provide additional background (largely adopted from the [scientific python notes](http://www.scipy-lectures.org/), which you can explore on your own to get more background on the Python syntax if specific elements would not be clear. \n", "\n", @@ -824,8 +536,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -839,7 +554,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/notebooks/_solutions/case2_observations_processing14.py b/notebooks/_solutions/case2_observations_processing14.py index e666188..fcdc80b 100644 --- a/notebooks/_solutions/case2_observations_processing14.py +++ b/notebooks/_solutions/case2_observations_processing14.py @@ -1 +1 @@ -plot_data = pd.read_excel("data/plot_location.xlsx", skiprows=3, index_col=0) \ No newline at end of file +species_data = pd.read_csv("data/species.csv", sep=";") \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing15.py b/notebooks/_solutions/case2_observations_processing15.py index 95b17c1..fc30029 100644 --- a/notebooks/_solutions/case2_observations_processing15.py +++ b/notebooks/_solutions/case2_observations_processing15.py @@ -1,15 +1 @@ -def transform_utm_to_wgs(row): - """Converts the x and y coordinates - - Parameters - ---------- - row : pd.Series - Single DataFrame row - - Returns - ------- - pd.Series with longitude and latitude - """ - transformer = Transformer.from_crs("EPSG:32612", "epsg:4326") - - return pd.Series(transformer.transform(row['xutm'], row['yutm'])) \ No newline at end of file +species_data.loc[species_data["species_id"] == "NE", "species_id"] = "NA" \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing16.py b/notebooks/_solutions/case2_observations_processing16.py index c3cebdb..fb17e68 100644 --- a/notebooks/_solutions/case2_observations_processing16.py +++ b/notebooks/_solutions/case2_observations_processing16.py @@ -1,2 +1,2 @@ -# test the new function on a single row of the DataFrame -transform_utm_to_wgs(plot_data.loc[0]) \ No newline at end of file +survey_data_species = pd.merge(survey_data_decoupled, species_data, how="left", # LEFT OR INNER? + left_on="species", right_on="species_id") \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing17.py b/notebooks/_solutions/case2_observations_processing17.py index 98a4938..e666188 100644 --- a/notebooks/_solutions/case2_observations_processing17.py +++ b/notebooks/_solutions/case2_observations_processing17.py @@ -1 +1 @@ -plot_data.apply(transform_utm_to_wgs, axis=1) \ No newline at end of file +plot_data = pd.read_excel("data/plot_location.xlsx", skiprows=3, index_col=0) \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing18.py b/notebooks/_solutions/case2_observations_processing18.py index 5bb1350..95b17c1 100644 --- a/notebooks/_solutions/case2_observations_processing18.py +++ b/notebooks/_solutions/case2_observations_processing18.py @@ -1 +1,15 @@ -plot_data[["decimalLongitude" ,"decimalLatitude"]] = plot_data.apply(transform_utm_to_wgs, axis=1) \ No newline at end of file +def transform_utm_to_wgs(row): + """Converts the x and y coordinates + + Parameters + ---------- + row : pd.Series + Single DataFrame row + + Returns + ------- + pd.Series with longitude and latitude + """ + transformer = Transformer.from_crs("EPSG:32612", "epsg:4326") + + return pd.Series(transformer.transform(row['xutm'], row['yutm'])) \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing19.py b/notebooks/_solutions/case2_observations_processing19.py index 22da847..c3cebdb 100644 --- a/notebooks/_solutions/case2_observations_processing19.py +++ b/notebooks/_solutions/case2_observations_processing19.py @@ -1 +1,2 @@ -plot_data_selection = plot_data[["plot", "decimalLongitude", "decimalLatitude"]] \ No newline at end of file +# test the new function on a single row of the DataFrame +transform_utm_to_wgs(plot_data.loc[0]) \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing20.py b/notebooks/_solutions/case2_observations_processing20.py index 4217078..98a4938 100644 --- a/notebooks/_solutions/case2_observations_processing20.py +++ b/notebooks/_solutions/case2_observations_processing20.py @@ -1,2 +1 @@ -survey_data_plots = pd.merge(survey_data_decoupled, plot_data_selection, - how="left", on="plot") \ No newline at end of file +plot_data.apply(transform_utm_to_wgs, axis=1) \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing21.py b/notebooks/_solutions/case2_observations_processing21.py index fcdc80b..5bb1350 100644 --- a/notebooks/_solutions/case2_observations_processing21.py +++ b/notebooks/_solutions/case2_observations_processing21.py @@ -1 +1 @@ -species_data = pd.read_csv("data/species.csv", sep=";") \ No newline at end of file +plot_data[["decimalLongitude" ,"decimalLatitude"]] = plot_data.apply(transform_utm_to_wgs, axis=1) \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing22.py b/notebooks/_solutions/case2_observations_processing22.py index fc30029..22da847 100644 --- a/notebooks/_solutions/case2_observations_processing22.py +++ b/notebooks/_solutions/case2_observations_processing22.py @@ -1 +1 @@ -species_data.loc[species_data["species_id"] == "NE", "species_id"] = "NA" \ No newline at end of file +plot_data_selection = plot_data[["plot", "decimalLongitude", "decimalLatitude"]] \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing23.py b/notebooks/_solutions/case2_observations_processing23.py index c3e7fb2..8a0da80 100644 --- a/notebooks/_solutions/case2_observations_processing23.py +++ b/notebooks/_solutions/case2_observations_processing23.py @@ -1,2 +1,2 @@ -survey_data_species = pd.merge(survey_data_plots, species_data, how="left", # LEFT OR INNER? - left_on="species", right_on="species_id") \ No newline at end of file +survey_data_plots = pd.merge(survey_data_species, plot_data_selection, + how="left", on="plot") \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing25.py b/notebooks/_solutions/case2_observations_processing25.py index 8235e4d..4114c43 100644 --- a/notebooks/_solutions/case2_observations_processing25.py +++ b/notebooks/_solutions/case2_observations_processing25.py @@ -1,2 +1,2 @@ #%%timeit -unique_species = survey_data_species[["genus", "species"]].drop_duplicates().dropna() \ No newline at end of file +unique_species = survey_data_plots[["genus", "species"]].drop_duplicates().dropna() \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing26.py b/notebooks/_solutions/case2_observations_processing26.py index d43a56d..c8abcfc 100644 --- a/notebooks/_solutions/case2_observations_processing26.py +++ b/notebooks/_solutions/case2_observations_processing26.py @@ -1,3 +1,3 @@ #%%timeit unique_species = \ - survey_data_species.groupby(["genus", "species"]).first().reset_index()[["genus", "species"]] \ No newline at end of file + survey_data_plots.groupby(["genus", "species"]).first().reset_index()[["genus", "species"]] \ No newline at end of file diff --git a/notebooks/_solutions/case2_observations_processing31.py b/notebooks/_solutions/case2_observations_processing31.py index 946b941..7f24832 100644 --- a/notebooks/_solutions/case2_observations_processing31.py +++ b/notebooks/_solutions/case2_observations_processing31.py @@ -1,2 +1,2 @@ -survey_data_completed = pd.merge(survey_data_species, unique_species_annotated, +survey_data_completed = pd.merge(survey_data_plots, unique_species_annotated, how='left', on= ["genus", "species"]) \ No newline at end of file diff --git a/notebooks/_solutions/case3_bacterial_resistance_lab_experiment1.py b/notebooks/_solutions/case3_bacterial_resistance_lab_experiment1.py index 9e74af0..9de4aae 100644 --- a/notebooks/_solutions/case3_bacterial_resistance_lab_experiment1.py +++ b/notebooks/_solutions/case3_bacterial_resistance_lab_experiment1.py @@ -1,5 +1,4 @@ -tidy_experiment = main_experiment.melt(id_vars=['AB_r', 'Bacterial_genotype', 'Phage_t', - 'Survival_72h', 'PhageR_72h', 'experiment_ID'], +tidy_experiment = main_experiment.melt(id_vars=['Bacterial_genotype', 'Phage_t', 'experiment_ID'], value_vars=['OD_0h', 'OD_20h', 'OD_72h'], var_name='experiment_time_h', value_name='optical_density', ) diff --git a/notebooks/_solutions/case3_bacterial_resistance_lab_experiment13.py b/notebooks/_solutions/case3_bacterial_resistance_lab_experiment13.py index bd55f9a..0169fd7 100644 --- a/notebooks/_solutions/case3_bacterial_resistance_lab_experiment13.py +++ b/notebooks/_solutions/case3_bacterial_resistance_lab_experiment13.py @@ -1,5 +1,5 @@ sns.set_style("ticks") -g = sns.FacetGrid(falcor, row="Phage", aspect=3, height=3) +g = sns.FacetGrid(data=falcor, row="Phage", aspect=3, height=3) g.map(errorbar, "Bacterial_genotype", "log10 Mc", "log10 LBc", "log10 UBc") \ No newline at end of file diff --git a/notebooks/_solutions/case3_bacterial_resistance_lab_experiment2.py b/notebooks/_solutions/case3_bacterial_resistance_lab_experiment2.py index ec708cc..652bc76 100644 --- a/notebooks/_solutions/case3_bacterial_resistance_lab_experiment2.py +++ b/notebooks/_solutions/case3_bacterial_resistance_lab_experiment2.py @@ -1,3 +1,6 @@ sns.set_style("white") -sns.displot(tidy_experiment, x="optical_density", - color='grey', edgecolor='white') \ No newline at end of file +histplot = sns.displot(data=tidy_experiment, x="optical_density", + color='grey', edgecolor='white') + +histplot.fig.suptitle("Optical density distribution") +histplot.axes[0][0].set_ylabel("Frequency"); \ No newline at end of file diff --git a/notebooks/_solutions/case4_air_quality_processing11.py b/notebooks/_solutions/case4_air_quality_processing11.py index 55d9554..39b7cd9 100644 --- a/notebooks/_solutions/case4_air_quality_processing11.py +++ b/notebooks/_solutions/case4_air_quality_processing11.py @@ -1,2 +1,3 @@ -data_files = glob.glob("data/*0008001*") +data_folder = Path("./data") +data_files = list(data_folder.glob("*0008001*")) data_files \ No newline at end of file diff --git a/notebooks/_solutions/pandas_01_data_structures5.py b/notebooks/_solutions/pandas_01_data_structures5.py index 11d616d..afc218b 100644 --- a/notebooks/_solutions/pandas_01_data_structures5.py +++ b/notebooks/_solutions/pandas_01_data_structures5.py @@ -1 +1 @@ -df['Fare'].plot(kind='box') \ No newline at end of file +df['Fare'].plot(kind='box') # or .plot.box() \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data10.py b/notebooks/_solutions/pandas_03a_selecting_data10.py index 769a558..b1f567b 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data10.py +++ b/notebooks/_solutions/pandas_03a_selecting_data10.py @@ -1,2 +1 @@ -def get_surname(name): - return name.split(",")[0] \ No newline at end of file +df[df['Surname'].str.len() > 15] \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data11.py b/notebooks/_solutions/pandas_03a_selecting_data11.py index e88d798..f6496cf 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data11.py +++ b/notebooks/_solutions/pandas_03a_selecting_data11.py @@ -1 +1 @@ -df['Name'].apply(get_surname) \ No newline at end of file +len(titles) \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data12.py b/notebooks/_solutions/pandas_03a_selecting_data12.py index fe5e609..d244d2b 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data12.py +++ b/notebooks/_solutions/pandas_03a_selecting_data12.py @@ -1 +1 @@ -df['Surname'] = df['Name'].apply(get_surname) \ No newline at end of file +titles.sort_values('year').head(2) \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data13.py b/notebooks/_solutions/pandas_03a_selecting_data13.py index baffb75..0673ed7 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data13.py +++ b/notebooks/_solutions/pandas_03a_selecting_data13.py @@ -1,2 +1 @@ -# alternative using an "inline" lambda function -df['Surname'] = df['Name'].apply(lambda x: x.split(',')[0]) \ No newline at end of file +len(titles[titles['title'] == 'Hamlet']) \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data14.py b/notebooks/_solutions/pandas_03a_selecting_data14.py index 0f9cd76..d5b91f8 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data14.py +++ b/notebooks/_solutions/pandas_03a_selecting_data14.py @@ -1,2 +1 @@ -# alternative solution with pandas' string methods -df['Surname'] = df['Name'].str.split(",").str.get(0) \ No newline at end of file +titles[titles['title'] == 'Treasure Island'].sort_values('year') \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data15.py b/notebooks/_solutions/pandas_03a_selecting_data15.py index 6580d2b..6a90954 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data15.py +++ b/notebooks/_solutions/pandas_03a_selecting_data15.py @@ -1 +1 @@ -df[df['Surname'].str.startswith('Williams')] \ No newline at end of file +len(titles[(titles['year'] >= 1950) & (titles['year'] <= 1959)]) \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data16.py b/notebooks/_solutions/pandas_03a_selecting_data16.py index b1f567b..4736084 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data16.py +++ b/notebooks/_solutions/pandas_03a_selecting_data16.py @@ -1 +1 @@ -df[df['Surname'].str.len() > 15] \ No newline at end of file +len(titles[titles['year'] // 10 == 195]) \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data17.py b/notebooks/_solutions/pandas_03a_selecting_data17.py index f6496cf..81e1340 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data17.py +++ b/notebooks/_solutions/pandas_03a_selecting_data17.py @@ -1 +1 @@ -len(titles) \ No newline at end of file +inception = cast[cast['title'] == 'Inception'] \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data18.py b/notebooks/_solutions/pandas_03a_selecting_data18.py index d244d2b..0326615 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data18.py +++ b/notebooks/_solutions/pandas_03a_selecting_data18.py @@ -1 +1 @@ -titles.sort_values('year').head(2) \ No newline at end of file +len(inception[inception['n'].isna()]) \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data19.py b/notebooks/_solutions/pandas_03a_selecting_data19.py index 0673ed7..59d4b10 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data19.py +++ b/notebooks/_solutions/pandas_03a_selecting_data19.py @@ -1 +1 @@ -len(titles[titles['title'] == 'Hamlet']) \ No newline at end of file +inception['n'].isna().sum() \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data20.py b/notebooks/_solutions/pandas_03a_selecting_data20.py index d5b91f8..8f8f362 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data20.py +++ b/notebooks/_solutions/pandas_03a_selecting_data20.py @@ -1 +1 @@ -titles[titles['title'] == 'Treasure Island'].sort_values('year') \ No newline at end of file +len(inception[inception['n'].notna()]) \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data21.py b/notebooks/_solutions/pandas_03a_selecting_data21.py index 6a90954..03b0185 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data21.py +++ b/notebooks/_solutions/pandas_03a_selecting_data21.py @@ -1 +1,3 @@ -len(titles[(titles['year'] >= 1950) & (titles['year'] <= 1959)]) \ No newline at end of file +titanic = cast[(cast['title'] == 'Titanic') & (cast['year'] == 1997)] +titanic = titanic[titanic['n'].notna()] +titanic.sort_values('n') \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data22.py b/notebooks/_solutions/pandas_03a_selecting_data22.py index 4736084..255c57d 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data22.py +++ b/notebooks/_solutions/pandas_03a_selecting_data22.py @@ -1 +1,4 @@ -len(titles[titles['year'] // 10 == 195]) \ No newline at end of file +brad = cast[cast['name'] == 'Brad Pitt'] +brad = brad[brad['year'] // 10 == 199] +brad = brad[brad['n'] == 2] +brad.sort_values('year') \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data7.py b/notebooks/_solutions/pandas_03a_selecting_data7.py index ca64194..c5ac162 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data7.py +++ b/notebooks/_solutions/pandas_03a_selecting_data7.py @@ -1,2 +1 @@ -name = df['Name'][0] -name \ No newline at end of file +name.split(",")[0] \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data8.py b/notebooks/_solutions/pandas_03a_selecting_data8.py index b82d464..88b6ea4 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data8.py +++ b/notebooks/_solutions/pandas_03a_selecting_data8.py @@ -1 +1,2 @@ -name.split(",") \ No newline at end of file +df['Surname'] = df['Name'].str.split(",").str.get(0) +df['Surname'] \ No newline at end of file diff --git a/notebooks/_solutions/pandas_03a_selecting_data9.py b/notebooks/_solutions/pandas_03a_selecting_data9.py index c5ac162..6580d2b 100644 --- a/notebooks/_solutions/pandas_03a_selecting_data9.py +++ b/notebooks/_solutions/pandas_03a_selecting_data9.py @@ -1 +1 @@ -name.split(",")[0] \ No newline at end of file +df[df['Surname'].str.startswith('Williams')] \ No newline at end of file diff --git a/notebooks/_solutions/pandas_06_groupby_operations25.py b/notebooks/_solutions/pandas_06_groupby_operations25.py index 286b82f..3f02ba2 100644 --- a/notebooks/_solutions/pandas_06_groupby_operations25.py +++ b/notebooks/_solutions/pandas_06_groupby_operations25.py @@ -1,2 +1,2 @@ -cast['n_total'] = cast.groupby(['title', 'year'])['n'].transform('max') # transform will return an element for each row, so the max value is given to the whole group +cast['n_total'] = cast.groupby(['title', 'year'])['n'].transform('size') # transform will return an element for each row, so the size value is given to the whole group cast.head() \ No newline at end of file diff --git a/notebooks/_solutions/visualization_01_matplotlib1.py b/notebooks/_solutions/visualization_01_matplotlib1.py new file mode 100644 index 0000000..e5b149f --- /dev/null +++ b/notebooks/_solutions/visualization_01_matplotlib1.py @@ -0,0 +1,5 @@ +fig, ax = plt.subplots(figsize=(12, 4)) + +ax.plot(data, color='darkgrey') +ax.set_xlabel('days since start'); +ax.set_ylabel('measured value'); \ No newline at end of file diff --git a/notebooks/_solutions/visualization_01_matplotlib2.py b/notebooks/_solutions/visualization_01_matplotlib2.py new file mode 100644 index 0000000..02a9dcd --- /dev/null +++ b/notebooks/_solutions/visualization_01_matplotlib2.py @@ -0,0 +1,9 @@ +dates = pd.date_range("2021-01-01", periods=100, freq="D") + +fig, ax = plt.subplots(figsize=(12, 4)) + +ax.plot(dates, data, color='darkgrey') +ax.axhspan(ymin=-5, ymax=5, color='green', alpha=0.2) + +ax.set_xlabel('days since start'); +ax.set_ylabel('measured value'); \ No newline at end of file diff --git a/notebooks/_solutions/visualization_01_matplotlib3.py b/notebooks/_solutions/visualization_01_matplotlib3.py new file mode 100644 index 0000000..0398da5 --- /dev/null +++ b/notebooks/_solutions/visualization_01_matplotlib3.py @@ -0,0 +1,4 @@ +fig, ax = plt.subplots(figsize=(12, 4)) + +ax.bar(dates[-10:], data[-10:], color='darkgrey') +ax.bar(dates[-6], data[-6], color='orange') \ No newline at end of file diff --git a/notebooks/_solutions/visualization_01_matplotlib4.py b/notebooks/_solutions/visualization_01_matplotlib4.py new file mode 100644 index 0000000..5ade26d --- /dev/null +++ b/notebooks/_solutions/visualization_01_matplotlib4.py @@ -0,0 +1,2 @@ +fig, ax = plt.subplots() +flowdata.mean().plot.bar(ylabel="mean discharge", ax=ax) \ No newline at end of file diff --git a/notebooks/_solutions/visualization_01_matplotlib5.py b/notebooks/_solutions/visualization_01_matplotlib5.py new file mode 100644 index 0000000..58a598a --- /dev/null +++ b/notebooks/_solutions/visualization_01_matplotlib5.py @@ -0,0 +1,6 @@ +fig, (ax0, ax1) = plt.subplots(1, 2, constrained_layout=True) + +flowdata.min().plot.bar(ylabel="min discharge", ax=ax0) +flowdata.max().plot.bar(ylabel="max discharge", ax=ax1) + +fig.suptitle(f"Minimal and maximal discharge from {flowdata.index[0]:%Y-%m-%d} till {flowdata.index[-1]:%Y-%m-%d}"); \ No newline at end of file diff --git a/notebooks/_solutions/visualization_01_matplotlib6.py b/notebooks/_solutions/visualization_01_matplotlib6.py new file mode 100644 index 0000000..e001221 --- /dev/null +++ b/notebooks/_solutions/visualization_01_matplotlib6.py @@ -0,0 +1,16 @@ +alarm_level = 20 +max_datetime, max_value = flowdata["LS06_347"].idxmax(), flowdata["LS06_347"].max() + +fig, ax = plt.subplots(figsize=(18, 4)) +flowdata["LS06_347"].plot(ax=ax) + +ax.axhline(y=alarm_level, color='red', linestyle='-', alpha=0.8) +ax.annotate('Alarm level', xy=(flowdata.index[0], alarm_level), + xycoords="data", xytext=(10, 10), textcoords="offset points", + color="red", fontsize=12) +ax.annotate(f"Flood event on {max_datetime:%Y-%m-%d}", + xy=(max_datetime, max_value), xycoords='data', + xytext=(-30, -30), textcoords='offset points', + arrowprops=dict(facecolor='black', shrink=0.05), + horizontalalignment='right', verticalalignment='bottom', + fontsize=12) \ No newline at end of file diff --git a/notebooks/case1_bike_count.ipynb b/notebooks/case1_bike_count.ipynb index 99ccaae..57e0a9c 100644 --- a/notebooks/case1_bike_count.ipynb +++ b/notebooks/case1_bike_count.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Bike count data

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -72,7 +69,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 1**\n", "\n", "- Read the csv file from the url into a DataFrame `df`, the delimiter of the data is `;`\n", "- Inspect the first and last 5 rows, and check the number of observations\n", @@ -93,7 +90,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -104,10 +103,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -118,10 +116,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -132,10 +129,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -146,10 +142,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -176,7 +171,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 2**\n", "\n", "Pre-process the data:\n", "\n", @@ -200,10 +195,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -214,7 +208,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -225,7 +221,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -236,7 +234,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -246,11 +246,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "df2.head()" @@ -266,11 +262,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(10, 6))\n", @@ -307,11 +299,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "%timeit -n 1 -r 1 pd.to_datetime(combined, dayfirst=True)" @@ -327,11 +315,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "%timeit pd.to_datetime(combined, format=\"%d/%m/%Y %H:%M\")" @@ -363,7 +347,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 3**\n", "\n", "Write a function `process_bike_count_data(df)` that performs the processing steps as done above for an input Pandas DataFrame and returns the updated DataFrame.\n", "\n", @@ -378,7 +362,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -388,11 +374,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "df_raw = pd.read_csv(\"data/fietstellingencoupure.csv\", sep=';')\n", @@ -477,11 +459,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "pd.Series(df.index).diff()" @@ -497,11 +475,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "pd.Series(df.index).diff().value_counts()" @@ -519,11 +493,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "df.describe()" @@ -542,7 +512,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 4**\n", "\n", "Create a new Pandas Series `df_both` which contains the sum of the counts of both directions.\n", "\n", @@ -557,10 +527,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -573,7 +542,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 5**\n", "\n", "Using the `df_both` from the previous exercise, create a new Series `df_quiet` which contains only those intervals for which less than 5 cyclists passed in both directions combined\n", "\n", @@ -588,7 +557,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -601,7 +572,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 6**\n", "\n", "Using the original data `df`, select only the intervals for which less than 3 cyclists passed in one or the other direction. Hence, less than 3 cyclists towards the center or less than 3 cyclists towards Mariakerke.\n", "\n", @@ -617,10 +588,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -640,7 +610,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 7**\n", "\n", "What is the average number of bikers passing each 15 min?\n", "\n", @@ -655,10 +625,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -671,7 +640,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 8**\n", "\n", "What is the average number of bikers passing each hour?\n", "\n", @@ -687,10 +656,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -703,7 +671,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 9**\n", "\n", "What are the 10 highest peak values observed during any of the intervals for the direction towards the center of Ghent?\n", "\n", @@ -718,10 +686,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -734,7 +701,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 10**\n", "\n", "What is the maximum number of cyclist that passed on a single day calculated on both directions combined?\n", "\n", @@ -751,7 +718,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -762,7 +731,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -773,10 +744,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -787,8 +757,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "tags": [] + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -815,7 +786,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 11**\n", "\n", "How does the long-term trend look like? Calculate monthly sums and plot the result.\n", "\n", @@ -831,10 +802,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -847,7 +817,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 12**\n", "\n", "Let's have a look at some short term patterns. For the data of the first 3 weeks of January 2014, calculate the hourly counts and visualize them.\n", "\n", @@ -862,7 +832,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -873,10 +845,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -887,10 +858,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -910,7 +880,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 13**\n", "\n", "- Select a subset of the dataset from 2013-12-31 12:00:00 until 2014-01-01 12:00:00 and assign the result to a new variable `newyear`\n", "- Plot the selected data `newyear`.\n", @@ -927,7 +897,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -938,10 +910,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -952,10 +923,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -973,10 +943,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1019,11 +988,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "df_daily.groupby(df_daily.index.dayofweek).mean().plot(kind='bar')" @@ -1039,11 +1004,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "df_hourly.groupby(df_hourly.index.hour).mean().plot()" @@ -1084,11 +1045,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "ax = df_monthly.groupby(df_monthly.index.month).mean().plot()\n", @@ -1107,8 +1064,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1122,7 +1082,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.8.12" }, "nav_menu": {}, "toc": { diff --git a/notebooks/case2_observations_analysis.ipynb b/notebooks/case2_observations_analysis.ipynb index 1b904cf..11037fb 100644 --- a/notebooks/case2_observations_analysis.ipynb +++ b/notebooks/case2_observations_analysis.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Observation data - analysis

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -41,7 +38,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 1**\n", "\n", "- Read in the `survey_data_completed.csv` file and save the resulting `DataFrame` as variable `survey_data_processed` (if you did not complete the previous notebook, a version of the csv file is available in the `data` folder).\n", "- Interpret the 'eventDate' column directly as python `datetime` objects and make sure the 'occurrenceID' column is used as the index of the resulting DataFrame (both can be done at once when reading the csv file using parameters of the `read_csv` function)\n", @@ -62,7 +59,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -73,7 +72,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -84,7 +85,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -111,7 +114,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 2**\n", "\n", "How many records in the data set have no information about the `species`? Use the `isna()` method to find out.\n", "\n", @@ -127,7 +130,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -140,7 +145,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 3**\n", "\n", "How many duplicate records are present in the dataset? Use the method `duplicated()` to check if a row is a duplicate.\n", "\n", @@ -155,7 +160,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -168,9 +175,9 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 4**\n", "\n", - "- Select all duplicate data by filtering the `observations` data and assign the result to a new variable `duplicate_observations`. The `duplicated()` method provides an `keep` argument define which duplicates (if any) to mark.\n", + "- Select all duplicate data by filtering the `observations` data and assign the result to a new variable `duplicate_observations`. The `duplicated()` method provides a `keep` argument define which duplicates (if any) to mark.\n", "- Sort the `duplicate_observations` data on both the columns `eventDate` and `verbatimLocality` and show the first 9 records.\n", "\n", "
Hints\n", @@ -185,7 +192,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -198,7 +207,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 5**\n", "\n", "- Exclude the duplicate values (i.e. keep the first occurrence while removing the other ones) from the `observations` data set and save the result as `survey_data_unique`. Use the `drop duplicates()` method from Pandas.\n", "- How many observations are still left in the data set?\n", @@ -215,7 +224,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -226,7 +237,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -239,7 +252,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 6**\n", "\n", "Use the `dropna()` method to find out:\n", "\n", @@ -258,7 +271,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -271,7 +286,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 7**\n", "\n", "Filter the `survey_data_unique` data and select only those records that do not have a `species` while having information on the `sex`. Store the result as variable `not_identified`.\n", "\n", @@ -287,7 +302,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -357,7 +374,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 8**\n", "\n", "- Select the observations for which the `taxa` is equal to 'Rabbit', 'Bird' or 'Reptile'. Assign the result to a variable `non_rodent_species`. Use the `isin` method for the selection.\n", "\n", @@ -372,7 +389,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -394,7 +413,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 9**\n", "\n", "Select the observations for which the `name` starts with the characters 'r' (make sure it does not matter if a capital character is used in the 'taxa' name). Call the resulting variable `r_species`.\n", "\n", @@ -410,7 +429,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -441,7 +462,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 10**\n", "\n", "Select the observations that are not Birds. Call the resulting variable non_bird_species.\n", "\n", @@ -456,7 +477,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -478,7 +501,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 11**\n", "\n", "Select the __Bird__ (taxa is Bird) observations from 1985-01 till 1989-12 using the `eventDate` column. Call the resulting variable `birds_85_89`.\n", "\n", @@ -494,7 +517,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -512,7 +537,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -525,7 +552,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 12**\n", "\n", "- Drop the observations for which no 'weight' (`wgt` column) information is available.\n", "- On the filtered data, compare the median weight for each of the species (use the `name` column)\n", @@ -544,7 +571,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -555,7 +584,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -575,7 +606,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 13**\n", "\n", "Which 8 species (use the `name` column to identify the different species) have been observed most over the entire data set?\n", "\n", @@ -590,7 +621,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -601,7 +634,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -614,7 +649,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 14**\n", "\n", "- What is the number of different species in each of the `verbatimLocality` plots? Use the `nunique` method. Assign the output to a new variable `n_species_per_plot`.\n", "- Define a Matplotlib `Figure` (`fig`) and `Axes` (`ax`) to prepare a plot. Make an horizontal bar chart using Pandas `plot` function linked to the just created Matplotlib `ax`. Each bar represents the `species per plot/verbatimLocality`. Change the y-label to 'Plot number'.\n", @@ -631,7 +666,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -644,7 +681,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 15**\n", "\n", "- What is the number of plots (`verbatimLocality`) each of the species have been observed in? Assign the output to a new variable `n_plots_per_species`. Sort the counts from low to high.\n", "- Make an horizontal bar chart using Pandas `plot` function to show the number of plots each of the species was found (using the `n_plots_per_species` variable).\n", @@ -660,7 +697,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -673,7 +712,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 16**\n", "\n", "- Starting from the `survey_data`, calculate the amount of males and females present in each of the plots (`verbatimLocality`). The result should return the counts for each of the combinations of `sex` and `verbatimLocality`. Assign to a new variable `n_plot_sex` and ensure the counts are in a column named \"count\".\n", "- Use `pivot` to convert the `n_plot_sex` DataFrame to a new DataFrame with the `verbatimLocality` as index and `male`/`female` as column names. Assign to a new variable `pivoted`.\n", @@ -691,7 +730,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -702,7 +743,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -712,9 +755,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "metadata": {}, "outputs": [], "source": [ "pivoted.head()" @@ -742,7 +783,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 17**\n", "\n", "Recreate the previous plot with the `catplot` function from the Seaborn library starting from `n_plot_sex`.\n", "\n", @@ -759,7 +800,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -772,7 +815,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 18**\n", "\n", "Recreate the previous plot with the `catplot` function from the Seaborn library directly starting from `survey_data`.\n", "\n", @@ -789,7 +832,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -802,7 +847,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 19**\n", "\n", "- Make a summary table with the number of records of each of the species in each of the plots (also called `verbatimLocality`). Each of the species `name`s is a row index and each of the `verbatimLocality` plots is a column name.\n", "- Using the Seaborn documentation to make a heatmap.\n", @@ -818,7 +863,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -829,7 +876,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -849,7 +898,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 20**\n", "\n", "Make a plot visualizing the evolution of the number of observations for each of the individual __years__ (i.e. annual counts) using the `resample` method.\n", "\n", @@ -865,7 +914,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -885,16 +936,16 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 21**\n", "\n", "- Create a table, called `heatmap_prep`, based on the `survey_data` DataFrame with the row index the individual years, in the column the months of the year (1-> 12) and as values of the table, the counts for each of these year/month combinations.\n", - "- Using the seaborn documentation make a heatmap starting from the `heatmap_prep` variable.\n", + "- Using the seaborn documentation, make a heatmap starting from the `heatmap_prep` variable.\n", "\n", "
Hints\n", "\n", "- The `.dt` accessor can be used to get the `year`, `month`,... from a `datetime` column\n", "- Use `pivot_table` and provide the years to `index` and the months to `columns`. Do not forget to `count` the number for each combination (`aggfunc`).\n", - "- `resample` needs an aggregation function on how to combine the values within a single 'group' (in this case data within a year). In this example, we want to know the `size` of each group, i.e. the number of records within each year.\n", + "- Seaborn has an `heatmap` function which requires a short-form DataFrame, comparable to giving each element in a table a color value.\n", "\n", "
" ] @@ -903,7 +954,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -937,7 +990,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 22**\n", "\n", "Plot using Pandas `plot` function the number of records for `Dipodomys merriami` for each month of the year (January (1) -> December (12)), aggregated over all years.\n", "\n", @@ -953,7 +1006,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -964,7 +1019,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -977,7 +1034,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 23**\n", "\n", "Plot, for the species 'Dipodomys merriami', 'Dipodomys ordii', 'Reithrodontomys megalotis' and 'Chaetodipus baileyi', the monthly number of records as a function of time during the monitoring period. Plot each of the individual species in a separate subplot and provide them all with the same y-axis scale\n", "\n", @@ -994,7 +1051,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1005,7 +1064,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1016,7 +1077,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1029,9 +1092,17 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 24**\n", "\n", - "Recreate the same plot as in the previous exercise using Seaborn `relplot` functon with the `month_evolution` variable." + "Recreate the same plot as in the previous exercise using Seaborn `relplot` functon with the `month_evolution` variable.\n", + " \n", + "
Hints\n", + "\n", + "- We want to have the `counts` as a function of `eventDate`, so link these columns to y and x respectively.\n", + "- To create subplots in Seaborn, the usage of _facetting_ (splitting data sets to multiple facets) is used by linking a column name to the `row`/`col` parameter. \n", + "- Using `height` and `widht`, the figure size can be optimized.\n", + " \n", + "
" ] }, { @@ -1045,7 +1116,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1063,7 +1136,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1076,7 +1151,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 25**\n", "\n", "Plot the annual amount of occurrences for each of the 'taxa' as a function of time using Seaborn. Plot each taxa in a separate subplot and do not share the y-axis among the facets.\n", "\n", @@ -1093,7 +1168,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1104,7 +1181,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1117,7 +1196,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 26**\n", "\n", "The observations where taken by volunteers. You wonder on which day of the week the most observations where done. Calculate for each day of the week (`dayofweek`) the number of observations and make a bar plot.\n", "\n", @@ -1132,7 +1211,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1149,8 +1230,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1164,7 +1248,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/notebooks/case2_observations_processing.ipynb b/notebooks/case2_observations_processing.ipynb index 6526cd9..3a80a33 100644 --- a/notebooks/case2_observations_processing.ipynb +++ b/notebooks/case2_observations_processing.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Observation data - data cleaning and enrichment

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -117,7 +114,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 1**\n", "\n", "- How many individual records (occurrences) does the survey data set contain?\n", "\n", @@ -128,7 +125,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -171,9 +170,9 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 2**\n", "\n", - "- Add a new column, `datasetName`, to the survey data set with `datasetname` as value for all of the records (static value for the entire data set)\n", + "Add a new column, `datasetName`, to the survey data set with `datasetname` as value for all of the records (static value for the entire data set)\n", "\n", "
Hints\n", "\n", @@ -189,7 +188,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -200,7 +201,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Cleaning the sex_char column into a DwC called [sex](http://rs.tdwg.org/dwc/terms/#sex) column" + "### Cleaning the `sex_char` column into a DwC called [sex](http://rs.tdwg.org/dwc/terms/#sex) column" ] }, { @@ -209,7 +210,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 3**\n", "\n", "- Get a list of the unique values for the column `sex_char`.\n", "\n", @@ -226,7 +227,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -279,14 +282,14 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 4**\n", "\n", "- Express the mapping of the values (e.g. `M` -> `male`) into a Python dictionary object with the variable name `sex_dict`. `Z` values correspond to _Not a Number_, which can be defined as `np.nan`.\n", "- Use the `sex_dict` dictionary to replace the values in the `verbatimSex` column to the new values and save the mapped values in a new column 'sex' of the DataFrame.\n", "\n", "
Hints\n", "\n", - "- A dictionary is a Python standard library data structure - no Pandas magic involved when you need a key/value mapping.\n", + "- A dictionary is a Python standard library data structure, see https://docs.python.org/3/tutorial/datastructures.html#dictionaries - no Pandas magic involved when you need a key/value mapping.\n", "- When you need to replace values, look for the Pandas method `replace`.\n", "\n", "
\n", @@ -298,7 +301,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -309,7 +314,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -345,7 +352,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 5**\n", "\n", "- Make a horizontal bar chart comparing the number of male, female and unknown (`NaN`) records in the data set.\n", "\n", @@ -363,7 +370,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -540,7 +549,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 6**\n", "\n", "- Use the function `solve_double_field_entry` to update the `survey_data` by decoupling the double entries. Save the result as a variable `survey_data_decoupled`.\n", "\n", @@ -557,7 +566,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -698,7 +709,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 7**\n", "\n", "- Make a selection of `survey_data_decoupled` containing those records that can not correctly be interpreted as date values and save the resulting `DataFrame` as a new variable `trouble_makers`\n", "\n", @@ -715,7 +726,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -778,7 +791,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 8**\n", "\n", "- Assign in the `DataFrame` `survey_data_decoupled` all of the troublemakers `day` values the value 30 instead of 31.\n", "\n", @@ -797,7 +810,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -827,7 +842,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 9**\n", "\n", "- Check the number of observations for each year. Create a horizontal bar chart with the number of rows/observations for each year.\n", "\n", @@ -846,7 +861,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -857,7 +874,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -911,7 +930,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 10**\n", "\n", "- Create a horizontal bar chart with the number of records for each year (cfr. supra), but without using the column `year`, using the `eventDate` column directly.\n", "\n", @@ -928,7 +947,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -948,7 +969,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 11**\n", "\n", "- Create a bar chart with the number of records for each day of the week (`dayofweek`)\n", "\n", @@ -966,7 +987,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1018,21 +1041,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 2. Add coordinates from the plot locations" + "## 2. Add species names to dataset" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Loading the coordinate data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The individual plots are only identified by a `plot` identification number. In order to provide sufficient information to external users, additional information about the coordinates should be added. The coordinates of the individual plots are saved in another file: `plot_location.xlsx`. We will use this information to further enrich our data set and add the Darwin Core Terms `decimalLongitude` and `decimalLatitude`." + "The column `species` only provides a short identifier in the survey overview. The name information is stored in a separate file `species.csv`. We want our data set to include this information, read in the data and add it to our survey data set:" ] }, { @@ -1041,13 +1057,13 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 12**\n", "\n", - "- Read the excel file 'plot_location.xlsx' and store the data as the variable `plot_data`, with 3 columns: plot, xutm, yutm.\n", + "- Read in the 'species.csv' file and save the resulting `DataFrame` as variable `species_data`.\n", "\n", "
Hints\n", "\n", - "- Pandas read methods all have a similar name, `read_...`.\n", + "- Check the delimiter (`sep`) parameter of the `read_csv` function.\n", "\n", "
\n", "\n", @@ -1058,7 +1074,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1071,71 +1089,75 @@ "metadata": {}, "outputs": [], "source": [ - "plot_data.head()" + "species_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Transforming to other coordinate reference system" + "### Fix a wrong acronym naming" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "These coordinates are in meters, more specifically in the [UTM 12 N](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system) coordinate system. However, the agreed coordinate representation for Darwin Core is the [World Geodetic System 1984 (WGS84)](http://spatialreference.org/ref/epsg/wgs-84/).\n", - "\n", - "As this is not a GIS course, we will shortcut the discussion about different projection systems, but provide an example on how such a conversion from `UTM12N` to `WGS84` can be performed with the projection toolkit `pyproj` and by relying on the existing EPSG codes (a registry originally setup by the association of oil & gas producers)." + "When reviewing the metadata, you see that in the data-file the acronym `NE` is used to describe `Neotoma albigula`, whereas in the [metadata description](http://esapubs.org/archive/ecol/E090/118/Portal_rodent_metadata.htm), the acronym `NA` is used." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "First, we define out two projection systems, using their corresponding EPSG codes:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from pyproj import Transformer" + "
\n", + "\n", + "**EXERCISE 13**\n", + "\n", + "- Convert the value of 'NE' to 'NA' by using Boolean indexing/Filtering for the `species_id` column.\n", + "\n", + "
Hints\n", + "\n", + "- To assign a new value, use the `loc` operator.\n", + "- With `loc`, specify both the selecting for the rows and for the columns (`df.loc[row_indexer, column_indexer] = ..`).\n", + "\n", + "
\n", + "\n", + "
" ] }, { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, "outputs": [], "source": [ - "transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")" + "# %load _solutions/case2_observations_processing15.py" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The reprojection can be done by the function `transform` of the projection toolkit, providing the coordinate systems and a set of x, y coordinates. For example, for a single coordinate, this can be applied as follows:" + "### Merging surveys and species" ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "transformer.transform(681222.131658, 3.535262e+06)" + "As we now prepared the two series, we can combine the data, using again the `pd.merge` operation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Such a transformation is a function not supported by Pandas itself (it is in https://geopandas.org/). In such an situation, we want to _apply_ a custom function to _each row of the DataFrame_. Instead of writing a `for` loop to do this for each of the coordinates in the list, we can `.apply()` this function with Pandas." + "We want to add the data of the species to the survey data, in order to see the full species names in the combined data table." ] }, { @@ -1144,69 +1166,77 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 14**\n", "\n", - "Apply the pyproj function `transform` to plot_data, using the columns `xutm` and `yutm` and save the resulting output in 2 new columns, called `decimalLongitude` and `decimalLatitude`:\n", - "\n", - "- Create a function `transform_utm_to_wgs` that takes a row of a `DataFrame` and returns a `Series` of two elements with the longitude and latitude.\n", - "- Test this function on the first row of `plot_data`\n", - "- Now `apply` this function on all rows (use the `axis` parameter correct)\n", - "- Assign the result of the previous step to `decimalLongitude` and `decimalLatitude` columns\n", + "Combine the DataFrames `survey_data_plots` and the `DataFrame` `species_data` by adding the corresponding species information (name, class, kingdom,..) to the individual observations. Assign the output to a new variable `survey_data_species`.\n", "\n", "
Hints\n", "\n", - "- Convert the output of the transformer to a Series before returning (`pd.Series(....)`)\n", - "- A convenient way to select a single row is using the `.loc[0]` operator.\n", - "- `apply` can be used for both rows (`axis` 1) as columns (`axis` 0).\n", - "- To assign two columns at once, you can use a similar syntax as for selecting multiple columns with a list of column names (`df[['col1', 'col2']]`).\n", - "\n", - "
\n", + "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", + "- Take into account that our key-column is different for `species_data` and `survey_data_plots`, respectively `species` and `species_id`. The `pd.merge()` function has `left_on` and `right_on` keywords to specify the name of the column in the left and right `DataFrame` to merge on.\n", "\n", - "
" + "
" ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing15.py" + "# %load _solutions/case2_observations_processing16.py" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "clear_cell": true - }, + "metadata": {}, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing16.py" + "len(survey_data_species) # check length after join operation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The join is ok, but we are left with some redundant columns and wrong naming:" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "clear_cell": true - }, + "metadata": {}, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing17.py" + "survey_data_species.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We do not need the columns `species_x` and `species_id` column anymore, as we will use the scientific names from now on:" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "clear_cell": true - }, + "metadata": {}, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing18.py" + "survey_data_species = survey_data_species.drop([\"species_x\", \"species_id\"], axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The column `species_y` could just be named `species`:" ] }, { @@ -1215,48 +1245,48 @@ "metadata": {}, "outputs": [], "source": [ - "plot_data.head()" + "survey_data_species = survey_data_species.rename(columns={\"species_y\": \"species\"})" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": null, "metadata": {}, + "outputs": [], "source": [ - "The above function `transform_utm_to_wgs` you have created is a very specific function that knows the structure of the `DataFrame` you will apply it to (it assumes the 'xutm' and 'yutm' column names). We could also make a more generic function that just takes a X and Y coordinate and returns the `Series` of converted coordinates (`transform_utm_to_wgs2(X, Y)`).\n", - "\n", - "An alternative to apply such a custom function to the `plot_data` `DataFrame` is the usage of the `lambda` construct, which lets you specify a function on one line as an argument:\n", - "\n", - " transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")\n", - " plot_data.apply(lambda row : transformer.transform(row['xutm'], row['yutm']), axis=1)" + "survey_data_species.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "len(survey_data_species)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", - "\n", - "__WARNING__\n", - "\n", - "Do not abuse the usage of the `apply` method, but always look for an existing Pandas function first as these are - in general - faster!\n", - "\n", - "
" + "## 3. Add coordinates from the plot locations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Join the coordinate information to the survey data set" + "### Loading the coordinate data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We can extend our survey data set with this coordinate information. Making the combination of two data sets based on a common identifier is completely similar to the usage of `JOIN` operations in databases. In Pandas, this functionality is provided by [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/merging.html#database-style-DataFrame-joining-merging).\n", - "\n", - "In practice, we have to add the columns `decimalLongitude`/`decimalLatitude` to the current data set `survey_data_decoupled`, by using the plot identification number as key to join." + "The individual plots are only identified by a `plot` identification number. In order to provide sufficient information to external users, additional information about the coordinates should be added. The coordinates of the individual plots are saved in another file: `plot_location.xlsx`. We will use this information to further enrich our data set and add the Darwin Core Terms `decimalLongitude` and `decimalLatitude`." ] }, { @@ -1265,13 +1295,13 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 15**\n", "\n", - "- Extract only the columns to join to our survey dataset: the `plot` identifiers, `decimalLatitude` and `decimalLongitude` into a new variable named `plot_data_selection`\n", + "- Read the excel file 'plot_location.xlsx' and store the data as the variable `plot_data`, with 3 columns: plot, xutm, yutm.\n", "\n", "
Hints\n", "\n", - "- To select multiple columns, use a `list` of column names, e.g. `df[[\"my_col1\", \"my_col2\"]]`\n", + "- Pandas read methods all have a similar name, `read_...`.\n", "\n", "
\n", "\n", @@ -1282,40 +1312,54 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing19.py" + "# %load _solutions/case2_observations_processing17.py" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", - "\n", - "**EXERCISE**\n", - "\n", - "Combine the `DataFrame` `plot_data_selection` and the `DataFrame` `survey_data_decoupled` by adding the corresponding coordinate information to the individual observations using the `pd.merge()` function. Assign the output to a new variable `survey_data_plots`.\n", - "\n", - "
Hints\n", - "\n", - "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", - "- The key-column is the `plot`.\n", + "### Transforming to other coordinate reference system" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These coordinates are in meters, more specifically in the [UTM 12 N](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system) coordinate system. However, the agreed coordinate representation for Darwin Core is the [World Geodetic System 1984 (WGS84)](http://spatialreference.org/ref/epsg/wgs-84/).\n", "\n", - "
" + "As this is not a GIS course, we will shortcut the discussion about different projection systems, but provide an example on how such a conversion from `UTM12N` to `WGS84` can be performed with the projection toolkit `pyproj` and by relying on the existing EPSG codes (a registry originally setup by the association of oil & gas producers)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we define out two projection systems, using their corresponding EPSG codes:" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "clear_cell": true - }, + "metadata": {}, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing20.py" + "from pyproj import Transformer" ] }, { @@ -1324,14 +1368,14 @@ "metadata": {}, "outputs": [], "source": [ - "survey_data_plots.head()" + "transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The plot locations need to be stored with the variable name `verbatimLocality` indicating the identifier as integer value of the plot:" + "The reprojection can be done by the function `transform` of the projection toolkit, providing the coordinate systems and a set of x, y coordinates. For example, for a single coordinate, this can be applied as follows:" ] }, { @@ -1340,21 +1384,14 @@ "metadata": {}, "outputs": [], "source": [ - "survey_data_plots = survey_data_plots.rename(columns={'plot': 'verbatimLocality'})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Add species names to dataset" + "transformer.transform(681222.131658, 3.535262e+06)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The column `species` only provides a short identifier in the survey overview. The name information is stored in a separate file `species.csv`. We want our data set to include this information, read in the data and add it to our survey data set:" + "Such a transformation is a function not supported by Pandas itself (it is in https://geopandas.org/). In such an situation, we want to _apply_ a custom function to _each row of the DataFrame_. Instead of writing a `for` loop to do this for each of the coordinates in the list, we can `.apply()` this function with Pandas." ] }, { @@ -1363,13 +1400,21 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 16**\n", "\n", - "- Read in the 'species.csv' file and save the resulting `DataFrame` as variable `species_data`.\n", + "Apply the pyproj function `transform` to plot_data, using the columns `xutm` and `yutm` and save the resulting output in 2 new columns, called `decimalLongitude` and `decimalLatitude`:\n", + "\n", + "- Create a function `transform_utm_to_wgs` that takes a row of a `DataFrame` and returns a `Series` of two elements with the longitude and latitude.\n", + "- Test this function on the first row of `plot_data`\n", + "- Now `apply` this function on all rows (use the `axis` parameter correct)\n", + "- Assign the result of the previous step to `decimalLongitude` and `decimalLatitude` columns\n", "\n", "
Hints\n", "\n", - "- Check the delimiter (`sep`) parameter of the `read_csv` function.\n", + "- Convert the output of the transformer to a Series before returning (`pd.Series(....)`)\n", + "- A convenient way to select a single row is using the `.loc[0]` operator.\n", + "- `apply` can be used for both rows (`axis` 1) as columns (`axis` 0).\n", + "- To assign two columns at once, you can use a similar syntax as for selecting multiple columns with a list of column names (`df[['col1', 'col2']]`).\n", "\n", "
\n", "\n", @@ -1380,86 +1425,98 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing21.py" + "# %load _solutions/case2_observations_processing18.py" ] }, { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, "outputs": [], "source": [ - "species_data.head()" + "# %load _solutions/case2_observations_processing19.py" ] }, { - "cell_type": "markdown", - "metadata": {}, + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], "source": [ - "### Fix a wrong acronym naming" + "# %load _solutions/case2_observations_processing20.py" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "# %load _solutions/case2_observations_processing21.py" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, + "outputs": [], "source": [ - "When reviewing the metadata, you see that in the data-file the acronym `NE` is used to describe `Neotoma albigula`, whereas in the [metadata description](http://esapubs.org/archive/ecol/E090/118/Portal_rodent_metadata.htm), the acronym `NA` is used." + "plot_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", + "The above function `transform_utm_to_wgs` you have created is a very specific function that knows the structure of the `DataFrame` you will apply it to (it assumes the 'xutm' and 'yutm' column names). We could also make a more generic function that just takes a X and Y coordinate and returns the `Series` of converted coordinates (`transform_utm_to_wgs2(X, Y)`).\n", "\n", - "**EXERCISE**\n", + "An alternative to apply such a custom function to the `plot_data` `DataFrame` is the usage of the `lambda` construct, which lets you specify a function on one line as an argument:\n", "\n", - "- Convert the value of 'NE' to 'NA' by using Boolean indexing/Filtering for the `species_id` column.\n", + " transformer = Transformer.from_crs(\"EPSG:32612\", \"epsg:4326\")\n", + " plot_data.apply(lambda row : transformer.transform(row['xutm'], row['yutm']), axis=1)\n", "\n", - "
Hints\n", "\n", - "- To assign a new value, use the `loc` operator.\n", - "- With `loc`, specify both the selecting for the rows and for the columns (`df.loc[row_indexer, column_indexer] = ..`).\n", + "
\n", "\n", - "
\n", + "__WARNING__\n", + "\n", + "Do not abuse the usage of the `apply` method, but always look for an existing Pandas function first as these are - in general - faster!\n", "\n", "
" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# %load _solutions/case2_observations_processing22.py" - ] - }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Merging surveys and species" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As we now prepared the two series, we can combine the data, using again the `pd.merge` operation." + "### Join the coordinate information to the survey data set" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We want to add the data of the species to the survey data, in order to see the full species names in the combined data table." + "We can extend our survey data set with this coordinate information. Making the combination of two data sets based on a common identifier is completely similar to the usage of `JOIN` operations in databases. In Pandas, this functionality is provided by [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/merging.html#database-style-DataFrame-joining-merging).\n", + "\n", + "In practice, we have to add the columns `decimalLongitude`/`decimalLatitude` to the current data set `survey_data_decoupled`, by using the plot identification number as key to join." ] }, { @@ -1468,59 +1525,61 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 17**\n", "\n", - "Combine the `DataFrame` `survey_data_plots` and the `DataFrame` `species_data` by adding the corresponding species information (name, class, kingdom,..) to the individual observations. Assign the output to a new variable `survey_data_species`.\n", + "- Extract only the columns to join to our survey dataset: the `plot` identifiers, `decimalLatitude` and `decimalLongitude` into a new variable named `plot_data_selection`\n", "\n", "
Hints\n", "\n", - "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", - "- Take into account that our key-column is different for `species_data` and `survey_data_plots`, respectively `species` and `species_id`. The `pd.merge()` function has `left_on` and `right_on` keywords to specify the name of the column in the left and right `DataFrame` to merge on.\n", + "- To select multiple columns, use a `list` of column names, e.g. `df[[\"my_col1\", \"my_col2\"]]`\n", "\n", - "
" + "
\n", + "\n", + "
" ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/case2_observations_processing23.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "len(survey_data_species) # check length after join operation" + "# %load _solutions/case2_observations_processing22.py" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The join is ok, but we are left with some redundant columns and wrong naming:" + "
\n", + "\n", + "**EXERCISE 18**\n", + "\n", + "Combine the `DataFrame` `plot_data_selection` and the `DataFrame` `survey_data_decoupled` by adding the corresponding coordinate information to the individual observations using the `pd.merge()` function. Assign the output to a new variable `survey_data_plots`.\n", + "\n", + "
Hints\n", + "\n", + "- This is an example of a database JOIN operation. Pandas provides the `pd.merge` function to join two data sets using a common identifier.\n", + "- The key-column is the `plot`.\n", + "\n", + "
" ] }, { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, "outputs": [], "source": [ - "survey_data_species.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We do not need the columns `species_x` and `species_id` column anymore, as we will use the scientific names from now on:" + "# %load _solutions/case2_observations_processing23.py" ] }, { @@ -1529,32 +1588,14 @@ "metadata": {}, "outputs": [], "source": [ - "survey_data_species = survey_data_species.drop([\"species_x\", \"species_id\"], axis=1)" + "survey_data_plots.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The column `species_y` could just be named `species`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "survey_data_species = survey_data_species.rename(columns={\"species_y\": \"species\"})" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "survey_data_species.head()" + "The plot locations need to be stored with the variable name `verbatimLocality` indicating the identifier as integer value of the plot:" ] }, { @@ -1563,7 +1604,7 @@ "metadata": {}, "outputs": [], "source": [ - "len(survey_data_species)" + "survey_data_plots = survey_data_plots.rename(columns={'plot': 'verbatimLocality'})" ] }, { @@ -1579,7 +1620,7 @@ "metadata": {}, "outputs": [], "source": [ - "survey_data_species.to_csv(\"interim_survey_data_species.csv\", index=False)" + "survey_data_plots.to_csv(\"interim_survey_data_species.csv\", index=False)" ] }, { @@ -1696,7 +1737,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 19**\n", "\n", "- Write a function, called `name_match` that takes the `genus`, the `species` and the option to perform a strict matching or not as inputs, performs a matching with the GBIF name matching API and return the received message as a dictionary.\n", "\n", @@ -1707,7 +1748,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1789,7 +1832,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 20**\n", "\n", "- Extract the unique combinations of genus and species in the `survey_data_species` using the function `drop_duplicates()`. Save the result as the variable `unique_species` and remove the `NaN` values using `.dropna()`.\n", "\n", @@ -1800,7 +1843,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1822,7 +1867,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 21**\n", "\n", "- Extract the unique combinations of genus and species in the `survey_data_species` using `groupby`. Save the result as the variable `unique_species`.\n", "\n", @@ -1840,7 +1885,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1862,7 +1909,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 22**\n", "\n", "- Combine the columns genus and species to a single column with the complete name, save it in a new column named 'name'\n", "\n", @@ -1873,7 +1920,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1938,7 +1987,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 23**\n", "\n", "- Convert the dictionary `species_annotated` into a pandas DataFrame with the row index the key-values corresponding to `unique_species` and the column headers the output columns of the API response. Save the result as the variable `df_species_annotated`.\n", "\n", @@ -1956,7 +2005,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1985,7 +2036,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 24**\n", "\n", "- Subselect the columns 'class', 'kingdom', 'order', 'phylum', 'scientificName', 'status' and 'usageKey' from the DataFrame `df_species_annotated`. Save it as the variable `df_species_annotated_subset`\n", "\n", @@ -1996,7 +2047,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2018,7 +2071,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 25**\n", "\n", "- Join the `df_species_annotated_subset` information to the `unique_species` overview of species. Save the result as variable `unique_species_annotated`.\n", "
" @@ -2028,7 +2081,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2050,7 +2105,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 26**\n", "\n", "- Join the `unique_species_annotated` data to the `survey_data_species` data set, using both the genus and species column as keys. Save the result as the variable `survey_data_completed`.\n", "\n", @@ -2061,7 +2116,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -2099,7 +2156,7 @@ "metadata": {}, "outputs": [], "source": [ - "survey_data_completed.to_csv(\"survey_data_completed.csv\", index=False)" + "survey_data_completed.to_csv(\"survey_data_completed_.csv\", index=False)" ] }, { @@ -2122,6 +2179,9 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/notebooks/case3_bacterial_resistance_lab_experiment.ipynb b/notebooks/case3_bacterial_resistance_lab_experiment.ipynb index da1e4b2..e3b3c91 100644 --- a/notebooks/case3_bacterial_resistance_lab_experiment.ipynb +++ b/notebooks/case3_bacterial_resistance_lab_experiment.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - Bacterial resistance experiment

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python*\n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -56,6 +53,13 @@ "## Reading and processing the data" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The data for this use case contains the evolution of different bacteria populations when combined with different phage treatments (viruses). The evolution of the bacterial population is measured by using the __optical density__ (OD) at 3 moments during the experiment: at the start (0h), after 20h and at the end (72h)." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -98,16 +102,12 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "main_experiment = pd.read_excel(\"data/Dryad_Arias_Hall_v3.xlsx\",\n", " sheet_name=\"Main experiment\")\n", - "main_experiment" + "main_experiment = main_experiment.drop(columns=[\"AB_r\", \"Survival_72h\", \"PhageR_72h\"]) # focus on specific subset for this use case)" ] }, { @@ -120,11 +120,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "falcor = pd.read_excel(\"data/Dryad_Arias_Hall_v3.xlsx\", sheet_name=\"Falcor\",\n", @@ -164,11 +160,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "main_experiment[\"experiment_ID\"] = [\"ID_\" + str(idx) for idx in range(len(main_experiment))]\n", @@ -181,9 +173,9 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "**EXERCISE 1**:\n", "\n", - "Convert the columns `OD_0h`, `OD_20h` and `OD_72h` to a long format with the values stored in a column `optical_density` and the time in the experiment as `experiment_time_h`. Save the variable as tidy_experiment\n", + "Convert the columns `OD_0h`, `OD_20h` and `OD_72h` to a long format with the values stored in a column `optical_density` and the time in the experiment as `experiment_time_h`. Save the variable as `tidy_experiment`.\n", "\n", "
Hints\n", "\n", @@ -199,10 +191,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -219,11 +210,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "tidy_experiment.head()" @@ -235,11 +222,16 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "**EXERCISE 2**:\n", "\n", "* Make a histogram using the [Seaborn package](https://seaborn.pydata.org/index.html) to visualize the distribution of the `optical_density`\n", "* Change the overall theme to any of the available Seaborn themes\n", "* Change the border color of the bars to `white` and the fill color of the bars to `grey`\n", + " \n", + "Using Matplotlib, further adjust the histogram:\n", + " \n", + "- Add a Figure title \"Optical density distribution\".\n", + "- Overwrite the y-axis label to \"Frequency\".\n", "\n", "
Hints\n", "\n", @@ -247,10 +239,10 @@ "- There are five preset seaborn themes: `darkgrid`, `whitegrid`, `dark`, `white`, and `ticks`.\n", "- Make sure to set the theme before creating the graph.\n", "- Seaborn relies on Matplotlib to plot the individual bars, so the available parameters (`**kwargs`) to adjust the bars that can be passed (e.g. `color` and `edgecolor`) are enlisted in the [matplotlib.axes.Axes.bar](https://matplotlib.org/3.3.2/api/_as_gen/matplotlib.axes.Axes.bar.html) documentation.\n", + "- The output of a Seaborn plot is an object from which the Matplotlib `Figure` and `Axes` can be accessed, respectively `snsplot.fig` and `snsplot.axes`. Note that the `axes` are always returned as a 2x2 array of Axes (also if it only contains a single element).\n", "\n", "
\n", "\n", - "\n", "
" ] }, @@ -258,10 +250,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -274,7 +265,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 3**\n", "\n", "Use a Seaborn `violin plot` to check the distribution of the `optical_density` in each of the experiment time phases (`experiment_time_h` in the x-axis).\n", "\n", @@ -290,10 +281,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -306,7 +296,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 4**\n", "\n", "For each `Phage_t` in an individual subplot, use a `violin plot` to check the distribution of the `optical_density` in each of the experiment time phases (`experiment_time_h`)\n", "\n", @@ -322,10 +312,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -338,7 +327,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 5**\n", "\n", "Create a summary table of the __average__ `optical_density` with the `Bacterial_genotype` in the rows and the `experiment_time_h` in the columns\n", "\n", @@ -353,10 +342,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -374,10 +362,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -390,10 +377,10 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 6**\n", "\n", "- Calculate for each combination of `Bacterial_genotype`, `Phage_t` and `experiment_time_h` the mean `optical_density` and store the result as a DataFrame called `density_mean` (tip: use `reset_index()` to convert the resulting Series to a DataFrame).\n", - "- Based on `density_mean`, make a _barplot_ of the (mean) values for each `Bacterial_genotype`, with for each `Bacterial_genotype` an individual bar and with each `Phage_t` in a different color/hue (i.e. grouped bar chart).\n", + "- Based on `density_mean`, make a _barplot_ of the mean optical density for each `Bacterial_genotype`, with for each `Bacterial_genotype` an individual bar and with each `Phage_t` in a different color/hue (i.e. grouped bar chart).\n", "- Use the `experiment_time_h` to split into subplots. As we mainly want to compare the values within each subplot, make sure the scales in each of the subplots are adapted to its own data range, and put the subplots on different rows.\n", "- Adjust the size and aspect ratio of the Figure to your own preference.\n", "- Change the color scale of the bars to another Seaborn palette.\n", @@ -413,7 +400,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -424,10 +413,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -453,11 +441,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "falcor.head()" @@ -469,7 +453,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 7**\n", "\n", "We will first reproduce 'Figure 2' without the error bars:\n", "\n", @@ -491,7 +475,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -502,10 +488,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -527,7 +512,7 @@ "source": [ "
\n", "\n", - "**EXERCISE**\n", + "**EXERCISE 8**\n", "\n", "Reproduce 'Figure 2' with the error bars using the information from [this Stackoverflow thread](https://stackoverflow.com/questions/38385099/adding-simple-error-bars-to-seaborn-factorplot). You do not have to adjust the order of the categories in the x-axis.\n", "\n", @@ -545,7 +530,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -556,7 +543,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -567,10 +556,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -587,8 +575,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -602,7 +593,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/case4_air_quality_analysis.ipynb b/notebooks/case4_air_quality_analysis.ipynb index f54cd04..66124c7 100644 --- a/notebooks/case4_air_quality_analysis.ipynb +++ b/notebooks/case4_air_quality_analysis.ipynb @@ -6,9 +6,6 @@ "source": [ "

CASE - air quality data of European monitoring stations (AirBase)

\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -245,7 +242,7 @@ "source": [ "
\n", "\n", - "EXERCISE:\n", + "EXERCISE 1:\n", "\n", "
    \n", "
  • Create a tidy version of this dataset data_tidy, ensuring the result has new columns 'station' and 'no2'.
    • \n", @@ -259,7 +256,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -270,7 +269,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -281,7 +282,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -328,7 +331,7 @@ "source": [ "
    \n", "\n", - "EXERCISE:\n", + "EXERCISE 2:\n", "\n", "
      \n", "
    • Plot the monthly mean and median concentration of the 'FR04037' station for the years 2009 - 2013 in a single figure/ax
      • \n", @@ -340,7 +343,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -351,7 +356,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -364,7 +371,7 @@ "source": [ "
      \n", "\n", - "EXERCISE\n", + "EXERCISE 3\n", "\n", "
        \n", "
      • Make a violin plot for January 2011 until August 2011 (check out the documentation to improve the plotting settings)
        • \n", @@ -380,7 +387,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -391,7 +400,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -402,7 +413,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -415,7 +428,7 @@ "source": [ "
        \n", "\n", - "EXERCISE\n", + "EXERCISE 4\n", "\n", "
          \n", "
        • Make a bar plot with pandas of the mean of each of the stations in the year 2012 (check the documentation of Pandas plot to adapt the rotation of the labels) and make sure all bars have the same color.
          • \n", @@ -431,7 +444,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -444,7 +459,7 @@ "source": [ "
          \n", "\n", - "EXERCISE: Did the air quality improve over time?\n", + "EXERCISE 5: Did the air quality improve over time?\n", "\n", "
            \n", "
          • For the data from 1999 till the end, plot the yearly averages
            • \n", @@ -460,7 +475,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -521,7 +538,7 @@ "source": [ "
            \n", "\n", - "EXERCISE\n", + "EXERCISE 6\n", "\n", "
              \n", "
            • How does the typical yearly profile (typical averages for the different months over the years) look like for the different stations? (add a 'month' column as a first step)
              • \n", @@ -534,7 +551,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -570,7 +589,7 @@ "source": [ "
              \n", "\n", - "EXERCISE\n", + "EXERCISE 7\n", "\n", "
                \n", "
              • Plot the weekly 95% percentiles of the concentration in 'BETR801' and 'BETN029' for 2011
                • \n", @@ -583,7 +602,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -594,7 +615,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -607,7 +630,7 @@ "source": [ "
                \n", "\n", - "EXERCISE\n", + "EXERCISE 8\n", "\n", "
                  \n", "
                • Plot the typical diurnal profile (typical hourly averages) for the different stations taking into account the whole time period.
                  • \n", @@ -620,7 +643,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -633,7 +658,7 @@ "source": [ "
                  \n", "\n", - "__EXERCISE__\n", + "__EXERCISE 9__\n", "\n", "What is the difference in the typical diurnal profile between week and weekend days? (and visualise it)\n", "\n", @@ -654,7 +679,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -665,7 +692,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -676,7 +705,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -687,7 +718,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -698,7 +731,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -709,7 +744,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -738,7 +775,7 @@ "source": [ "
                  \n", "\n", - "__EXERCISE__\n", + "__EXERCISE 10__\n", "\n", "Calculate the correlation between the different stations (check in the documentation, google \"pandas correlation\" or use the magic function %psearch)\n", "\n", @@ -749,7 +786,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -762,7 +801,7 @@ "source": [ "
                  \n", "\n", - "__EXERCISE__\n", + "__EXERCISE 11__\n", "\n", "Count the number of exceedances of hourly values above the European limit 200 µg/m3 for each year and station after 2005. Make a barplot of the counts. Add an horizontal line indicating the maximum number of exceedances (which is 18) allowed per year?\n", "\n", @@ -783,7 +822,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -794,7 +835,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -805,7 +848,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -834,7 +879,7 @@ "source": [ "
                  \n", "\n", - "__EXERCISE__\n", + "__EXERCISE 12__\n", " \n", "Perform the following actions for the station `'FR04012'` only:\n", "\n", @@ -853,7 +898,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -864,7 +911,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -875,7 +924,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -888,7 +939,7 @@ "source": [ "
                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 13:\n", "\n", "
                    \n", "
                  • Create a Figure with two subplots (axes), for which both axis are shared
                    • \n", @@ -903,7 +954,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -914,7 +967,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -927,7 +982,7 @@ "source": [ "
                    \n", "\n", - "EXERCISE\n", + "EXERCISE 14\n", "\n", "
                      \n", "
                    • Make a selection of the original dataset of the data in January 2009, call the resulting variable subset
                      • \n", @@ -946,7 +1001,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -957,7 +1014,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -968,7 +1027,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -979,7 +1040,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -992,7 +1055,7 @@ "source": [ "
                      \n", "\n", - "__EXERCISE__\n", + "__EXERCISE 15__\n", "\n", "The maximum daily, 8 hour mean, should be below 100 µg/m³. What is the number of exceedances of this limit for each year/station?\n", " \n", @@ -1012,7 +1075,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1023,7 +1088,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1036,7 +1103,7 @@ "source": [ "
                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 16:\n", "\n", "
                        \n", "
                      • Visualize the typical week profile for station 'BETR801' as boxplots (where the values in one boxplot are the daily means for the different weeks for a certain day of the week).

                        • \n", @@ -1062,7 +1129,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1073,7 +1142,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1091,7 +1162,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1109,7 +1182,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1120,7 +1195,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1130,8 +1207,11 @@ ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1145,7 +1225,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/notebooks/case4_air_quality_processing.ipynb b/notebooks/case4_air_quality_processing.ipynb index a237d92..979c8cb 100644 --- a/notebooks/case4_air_quality_processing.ipynb +++ b/notebooks/case4_air_quality_processing.ipynb @@ -6,9 +6,6 @@ "source": [ "

                        CASE - air quality data of European monitoring stations (AirBase)

                        \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -110,7 +107,7 @@ "source": [ "
                        \n", "\n", - "EXERCISE:

                        Clean up this dataframe by using more options of `pd.read_csv` (see its [docstring](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html))\n", + "EXERCISE 1:

                        Clean up this dataframe by using more options of `pd.read_csv` (see its [docstring](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html))\n", "\n", "
                          \n", "
                        • specify the correct delimiter
                          • \n", @@ -135,7 +132,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -146,7 +145,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -166,9 +167,11 @@ "source": [ "
                          \n", "\n", - "EXERCISE:\n", - "

                          \n", - "Drop all 'flag' columns ('flag1', 'flag2', ...)" + "**EXERCISE 2**:\n", + "\n", + "Drop all 'flag' columns ('flag1', 'flag2', ...)\n", + "\n", + "
                          " ] }, { @@ -185,7 +188,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -232,7 +237,7 @@ "source": [ "
                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 3:\n", "\n", "

                          \n", "\n", @@ -314,7 +319,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -332,7 +339,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -343,7 +352,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -361,7 +372,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -372,7 +385,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -383,7 +398,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -444,7 +461,7 @@ "source": [ "
                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 4:\n", "\n", "
                            \n", "
                          • Write a function read_airbase_file(filename, station), using the above steps the read in and process the data, and that returns a processed timeseries.
                            • \n", @@ -484,7 +501,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -529,9 +548,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "clear_cell": false - }, + "metadata": {}, "outputs": [], "source": [ "test = read_airbase_file(filename, station)\n", @@ -551,30 +568,36 @@ "source": [ "
                            \n", "\n", - "EXERCISE:\n", + "**EXERCISE 5**:\n", "\n", - "
                              \n", - "
                            • Use the glob.glob function to list all 4 AirBase data files that are included in the 'data' directory, and call the result data_files.
                              • \n", - "
                            \n", + "Use the [pathlib module](https://docs.python.org/3/library/pathlib.html) `Path` class in combination with the `glob` method to list all 4 AirBase data files that are included in the 'data' directory, and call the result `data_files`.\n", + "\n", + "
                            Hints\n", + "\n", + "- The pathlib module provides a object oriented way to handle file paths. First, create a `Path` object of the data folder, `pathlib.Path(\"./data\")`. Next, apply the `glob` function to extract all the files containing `*0008001*` (use wildcard * to say \"any characters\"). The output is a Python generator, which you can collect as a `list()`.\n", + "\n", + "
                            \n", + "\n", + " \n", "
                            " ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "clear_cell": false - }, + "metadata": {}, "outputs": [], "source": [ - "import glob" + "from pathlib import Path" ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -587,7 +610,7 @@ "source": [ "
                            \n", "\n", - "EXERCISE:\n", + "EXERCISE 6:\n", "\n", "
                              \n", "
                            • Loop over the data files, read and process the file using our defined function, and append the dataframe to a list.
                              • \n", @@ -601,7 +624,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -612,7 +637,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -656,8 +683,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -671,7 +701,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { diff --git a/notebooks/pandas_01_data_structures.ipynb b/notebooks/pandas_01_data_structures.ipynb index be91128..7a037cb 100644 --- a/notebooks/pandas_01_data_structures.ipynb +++ b/notebooks/pandas_01_data_structures.ipynb @@ -7,9 +7,6 @@ "source": [ "

                              01 - Pandas: Data Structures

                              \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -137,7 +134,7 @@ "metadata": {}, "outputs": [], "source": [ - "df.groupby('Pclass')['Survived'].aggregate(lambda x: x.sum() / len(x)).plot(kind='bar')" + "df.groupby('Pclass')['Survived'].aggregate(lambda x: x.sum() / len(x)).plot.bar()" ] }, { @@ -434,7 +431,7 @@ "metadata": {}, "outputs": [], "source": [ - "countries['population'].plot(kind='barh')" + "countries['population'].plot.barh() # or .plot(kind='barh')" ] }, { @@ -444,10 +441,12 @@ "source": [ "
                              \n", "\n", - "**EXERCISE**:\n", + "**EXERCISE 1**:\n", "\n", - "* You can play with the `kind` keyword of the `plot` function in the figure above: 'line', 'bar', 'hist', 'density', 'area', 'pie', 'scatter', 'hexbin', 'box'\n", + "* You can play with the `kind` keyword or accessor of the `plot` method in the figure above: 'line', 'bar', 'hist', 'density', 'area', 'pie', 'scatter', 'hexbin', 'box'\n", "\n", + "Note: doing `df.plot(kind=\"bar\", ...)` or `df.plot.bar(...)` is exactly equivalent. You will see both ways in the wild.\n", + " \n", "
                              " ] }, @@ -570,7 +569,7 @@ "source": [ "
                              \n", "\n", - "**EXERCISE**:\n", + "**EXERCISE 2**:\n", "\n", "* Read the CVS file (available at `data/titanic.csv`) into a pandas DataFrame. Call the result `df`.\n", "\n", @@ -582,7 +581,9 @@ "execution_count": null, "id": "d4d97581", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -596,7 +597,7 @@ "source": [ "
                              \n", "\n", - "**EXERCISE**:\n", + "**EXERCISE 3**:\n", "\n", "* Quick exploration: show the first 5 rows of the DataFrame.\n", "\n", @@ -608,7 +609,9 @@ "execution_count": null, "id": "0a9f577b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -622,7 +625,7 @@ "source": [ "
                              \n", "\n", - "**EXERCISE**:\n", + "**EXERCISE 4**:\n", "\n", "* How many records (i.e. rows) has the titanic dataset?\n", "\n", @@ -639,7 +642,9 @@ "execution_count": null, "id": "fb5b5ee1", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -652,7 +657,7 @@ "metadata": {}, "source": [ "
                              \n", - " EXERCISE:\n", + " EXERCISE 5:\n", "\n", "* Select the 'Age' column (remember: we can use the [] indexing notation and the column label).\n", "\n", @@ -664,7 +669,9 @@ "execution_count": null, "id": "55994761", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -677,7 +684,7 @@ "metadata": {}, "source": [ "
                              \n", - " EXERCISE:\n", + " EXERCISE 6:\n", "\n", "* Make a box plot of the Fare column.\n", "\n", @@ -689,7 +696,9 @@ "execution_count": null, "id": "6ff00b82", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -703,7 +712,7 @@ "source": [ "
                              \n", " \n", - "**EXERCISE**:\n", + "**EXERCISE 7**:\n", "\n", "* Sort the rows of the DataFrame by 'Age' column, with the oldest passenger at the top. Check the help of the `sort_values` function and find out how to sort from the largest values to the lowest values\n", "\n", @@ -715,7 +724,9 @@ "execution_count": null, "id": "c0e64aab", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -736,8 +747,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -751,7 +765,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/pandas_02_basic_operations.ipynb b/notebooks/pandas_02_basic_operations.ipynb index 9c1deb9..a4007e8 100644 --- a/notebooks/pandas_02_basic_operations.ipynb +++ b/notebooks/pandas_02_basic_operations.ipynb @@ -7,9 +7,7 @@ "source": [ "

                              02 - Pandas: Basic operations on Series and DataFrames

                              \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -304,11 +302,10 @@ "metadata": {}, "source": [ "
                              \n", - "EXERCISE:\n", "\n", - "
                                \n", - "
                              • What is the average age of the passengers?
                                • \n", - "
                              \n", + "**EXERCISE 1**\n", + "\n", + "What is the average age of the passengers?\n", "\n", "
                              " ] @@ -318,7 +315,9 @@ "execution_count": null, "id": "a49adcdf", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -331,11 +330,11 @@ "metadata": {}, "source": [ "
                              \n", - "EXERCISE:\n", "\n", - "
                                \n", - "
                              • Plot the age distribution of the titanic passengers
                                • \n", - "
                              \n", + "**EXERCISE 2**\n", + "\n", + "Plot the age distribution of the titanic passengers\n", + "\n", "
                              " ] }, @@ -344,7 +343,9 @@ "execution_count": null, "id": "5127f39d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -357,14 +358,17 @@ "metadata": {}, "source": [ "
                              \n", - "EXERCISE:\n", "\n", - "
                                \n", - "
                              • What is the survival rate? (the relative number of people that survived)
                                • \n", - "
                              \n", - "
                              \n", + "**EXERCISE 3**\n", + "\n", + "What is the survival rate? (the relative number of people that survived)\n", "\n", - "Note: the 'Survived' column indicates whether someone survived (1) or not (0).\n", + "
                              Hints\n", + "\n", + "- the 'Survived' column indicates whether someone survived (1) or not (0).\n", + "\n", + "
                              \n", + " \n", "
                              " ] }, @@ -373,7 +377,9 @@ "execution_count": null, "id": "2a64e341", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -385,7 +391,9 @@ "execution_count": null, "id": "2875859b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -398,11 +406,11 @@ "metadata": {}, "source": [ "
                              \n", - "EXERCISE:\n", "\n", - "
                                \n", - "
                              • What is the maximum Fare? And the median?
                                • \n", - "
                              \n", + "**EXERCISE 4**\n", + "\n", + "What is the maximum Fare? And the median?\n", + "\n", "
                              " ] }, @@ -411,7 +419,9 @@ "execution_count": null, "id": "458f4a30", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -423,7 +433,9 @@ "execution_count": null, "id": "636facca", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -437,11 +449,16 @@ "source": [ "
                              \n", "\n", - "EXERCISE:\n", + "**EXERCISE 5**\n", + " \n", + "Calculate the 75th percentile (`quantile`) of the Fare price \n", + " \n", + "
                              Hints\n", + "\n", + "- look in the 'docstring' how to specify the percentile, either range [0, 1] or [0, 100]\n", + "\n", + "
                              \n", "\n", - "
                                \n", - "
                              • Calculate the 75th percentile (`quantile`) of the Fare price (Tip: look in the docstring how to specify the percentile)
                                • \n", - "
                              \n", "
                              " ] }, @@ -450,7 +467,9 @@ "execution_count": null, "id": "bc9dfb6b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -463,11 +482,11 @@ "metadata": {}, "source": [ "
                              \n", - "EXERCISE:\n", "\n", - "
                                \n", - "
                              • Calculate the normalized Fares (normalized relative to its mean), and add this as a new column ('Fare_normalized') to the DataFrame.
                                • \n", - "
                              \n", + "**EXERCISE 6**\n", + "\n", + "Calculate the normalized Fares (normalized relative to its mean), and add this as a new column ('Fare_normalized') to the DataFrame.\n", + "\n", "
                              " ] }, @@ -476,7 +495,9 @@ "execution_count": null, "id": "4a532ab5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -488,7 +509,9 @@ "execution_count": null, "id": "4173bb04", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -501,10 +524,16 @@ "metadata": {}, "source": [ "
                              \n", + "\n", + "**EXERCISE 7**\n", + "\n", + "* Calculate the log of the Fares. \n", " \n", - "**EXERCISE**:\n", + "
                              Hints\n", "\n", - "* Calculate the log of the Fares. Tip: check the `np.log` function.\n", + "- check the `np.log` function.\n", + "\n", + "
                              \n", "\n", "
                              " ] @@ -514,7 +543,9 @@ "execution_count": null, "id": "2cf6819c", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -720,8 +751,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -735,7 +769,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/pandas_03a_selecting_data.ipynb b/notebooks/pandas_03a_selecting_data.ipynb index 1caf27f..00a7d54 100644 --- a/notebooks/pandas_03a_selecting_data.ipynb +++ b/notebooks/pandas_03a_selecting_data.ipynb @@ -7,9 +7,7 @@ "source": [ "

                              03 - Pandas: Indexing and selecting data - part I

                              \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -374,7 +372,7 @@ "source": [ "
                              \n", "\n", - "EXERCISE:\n", + "EXERCISE 1:\n", "\n", "
                                \n", "
                              • Select all rows for male passengers and calculate the mean age of those passengers. Do the same for the female passengers.
                                • \n", @@ -387,7 +385,9 @@ "execution_count": null, "id": "e50cb2c4", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -399,7 +399,9 @@ "execution_count": null, "id": "c424a94d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -411,7 +413,9 @@ "execution_count": null, "id": "5cf61518", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -433,7 +437,7 @@ "source": [ "
                                \n", "\n", - "EXERCISE:\n", + "EXERCISE 2:\n", "\n", "
                                  \n", "
                                • How many passengers older than 70 were on the Titanic?
                                  • \n", @@ -446,7 +450,9 @@ "execution_count": null, "id": "ae3c0cb0", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -458,7 +464,9 @@ "execution_count": null, "id": "1aa352c5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -472,7 +480,7 @@ "source": [ "
                                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 3:\n", "\n", "
                                    \n", "
                                  • Select the passengers that are between 30 and 40 years old?
                                    • \n", @@ -485,7 +493,9 @@ "execution_count": null, "id": "3ce55041", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -494,18 +504,20 @@ }, { "cell_type": "markdown", - "id": "3650db50", + "id": "6e55f240-02ea-4643-bd0f-e505fa923576", "metadata": {}, "source": [ "
                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 4:\n", "\n", - "Split the 'Name' column on the `,` extract the first part (the surname), and add this as new column 'Surname'.\n", + "For a single string `name = 'Braund, Mr. Owen Harris'`, split this string (check the `split()` method of a string) and get the first element of the resulting list.\n", + " \n", + "
                                    Hints\n", "\n", - "* Get the first value of the 'Name' column.\n", - "* Split this string (check the `split()` method of a string) and get the first element of the resulting list.\n", - "* Write the previous step as a function, and 'apply' this function to each element of the 'Name' column (check the `apply()` method of a Series).\n", + "- No Pandas in this exercise, just standard Python.\n", + " \n", + "
                                    \n", "\n", "
                                    " ] @@ -513,97 +525,61 @@ { "cell_type": "code", "execution_count": null, - "id": "e32eb3f4", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# %load _solutions/pandas_03a_selecting_data7.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a674a798", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# %load _solutions/pandas_03a_selecting_data8.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "32f648d8", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# %load _solutions/pandas_03a_selecting_data9.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cc6320be", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# %load _solutions/pandas_03a_selecting_data10.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eb7cf472", - "metadata": { - "clear_cell": true - }, + "id": "2982bedf-0f71-4f90-a705-8da6aa9bb3a1", + "metadata": {}, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data11.py" + "name = 'Braund, Mr. Owen Harris'" ] }, { "cell_type": "code", "execution_count": null, - "id": "b7a4fd64", + "id": "0a8b177f-9596-458a-a455-4c3e64b1e4dd", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data12.py" + "# %load _solutions/pandas_03a_selecting_data7.py" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "04dde698", - "metadata": { - "clear_cell": true - }, - "outputs": [], + "cell_type": "markdown", + "id": "3650db50", + "metadata": {}, "source": [ - "# %load _solutions/pandas_03a_selecting_data13.py" + "
                                    \n", + "\n", + "EXERCISE 5:\n", + " \n", + "Convert the solution of the previous exercise to all strings of the `Name` column at once. Split the 'Name' column on the `,`, extract the first part (the surname), and add this as new column 'Surname'. \n", + " \n", + "
                                    Hints\n", + "\n", + "- Pandas uses the `str` accessor to use the string methods such as `split`, e.g. `.str.split(...)`\n", + "- The [`.str.get()`](https://pandas.pydata.org/docs/reference/api/pandas.Series.str.get.html#pandas.Series.str.get) can be used to get the n-th element of a list, which is what the `str.split()` returns. This is the equivalent of selecting an element of a single list (`a_list[i]`) but then for all values of the Series.\n", + "- One can chain multiple `.str` methods, e.g. `str.SOMEMETHOD(...).str.SOMEOTHERMETHOD(...)`.\n", + " \n", + "
                                    \n", + "\n", + "
                                    " ] }, { "cell_type": "code", "execution_count": null, - "id": "8e47f04d", + "id": "1c33284b-86de-434c-9ac6-3ee4008afc3b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data14.py" + "# %load _solutions/pandas_03a_selecting_data8.py" ] }, { @@ -613,7 +589,7 @@ "source": [ "
                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 6:\n", "\n", "
                                      \n", "
                                    • Select all passenger that have a surname starting with 'Williams'.
                                      • \n", @@ -626,11 +602,13 @@ "execution_count": null, "id": "d0769ddf", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data15.py" + "# %load _solutions/pandas_03a_selecting_data9.py" ] }, { @@ -640,7 +618,7 @@ "source": [ "
                                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 7:\n", "\n", "
                                        \n", "
                                      • Select all rows for the passengers with a surname of more than 15 characters.
                                        • \n", @@ -654,11 +632,13 @@ "execution_count": null, "id": "8653927c", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data16.py" + "# %load _solutions/pandas_03a_selecting_data10.py" ] }, { @@ -674,7 +654,7 @@ "id": "49d05bde", "metadata": {}, "source": [ - "For the quick ones among you, here are some more exercises with some larger dataframe with film data. These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so all credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKajNMa1pfSzN6Q3M) and [`cast.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKal9UYTJSR2ZhSW8) and put them in the `/notebooks/data` folder." + "For the quick ones among you, here are some more exercises with some larger dataframe with film data. These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so all credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/titles.csv) and [`cast.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/cast.csv) and put them in the `/notebooks/data` folder." ] }, { @@ -706,7 +686,7 @@ "source": [ "
                                        \n", "\n", - "EXERCISE:\n", + "EXERCISE 8:\n", "\n", "
                                          \n", "
                                        • How many movies are listed in the titles dataframe?
                                          • \n", @@ -720,11 +700,13 @@ "execution_count": null, "id": "101bc9c2", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data17.py" + "# %load _solutions/pandas_03a_selecting_data11.py" ] }, { @@ -734,7 +716,7 @@ "source": [ "
                                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 9:\n", "\n", "
                                            \n", "
                                          • What are the earliest two films listed in the titles dataframe?
                                            • \n", @@ -747,11 +729,13 @@ "execution_count": null, "id": "9a875b47", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data18.py" + "# %load _solutions/pandas_03a_selecting_data12.py" ] }, { @@ -761,7 +745,7 @@ "source": [ "
                                            \n", "\n", - "EXERCISE:\n", + "EXERCISE 10:\n", "\n", "
                                              \n", "
                                            • How many movies have the title \"Hamlet\"?
                                              • \n", @@ -774,11 +758,13 @@ "execution_count": null, "id": "9083845a", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data19.py" + "# %load _solutions/pandas_03a_selecting_data13.py" ] }, { @@ -788,7 +774,7 @@ "source": [ "
                                              \n", "\n", - "EXERCISE:\n", + "EXERCISE 11:\n", "\n", "
                                                \n", "
                                              • List all of the \"Treasure Island\" movies from earliest to most recent.
                                                • \n", @@ -801,11 +787,13 @@ "execution_count": null, "id": "973b11d5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data20.py" + "# %load _solutions/pandas_03a_selecting_data14.py" ] }, { @@ -815,7 +803,7 @@ "source": [ "
                                                \n", "\n", - "EXERCISE:\n", + "EXERCISE 12:\n", "\n", "
                                                  \n", "
                                                • How many movies were made from 1950 through 1959?
                                                  • \n", @@ -828,11 +816,13 @@ "execution_count": null, "id": "8d516c1e", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data21.py" + "# %load _solutions/pandas_03a_selecting_data15.py" ] }, { @@ -840,11 +830,13 @@ "execution_count": null, "id": "2634393f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data22.py" + "# %load _solutions/pandas_03a_selecting_data16.py" ] }, { @@ -854,7 +846,7 @@ "source": [ "
                                                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 13:\n", "\n", "
                                                    \n", "
                                                  • How many roles in the movie \"Inception\" are NOT ranked by an \"n\" value?
                                                    • \n", @@ -867,11 +859,13 @@ "execution_count": null, "id": "bcabb630", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data23.py" + "# %load _solutions/pandas_03a_selecting_data17.py" ] }, { @@ -879,11 +873,13 @@ "execution_count": null, "id": "6e0011f2", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data24.py" + "# %load _solutions/pandas_03a_selecting_data18.py" ] }, { @@ -891,11 +887,13 @@ "execution_count": null, "id": "3ea078b8", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data25.py" + "# %load _solutions/pandas_03a_selecting_data19.py" ] }, { @@ -905,7 +903,7 @@ "source": [ "
                                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 14:\n", "\n", "
                                                      \n", "
                                                    • But how many roles in the movie \"Inception\" did receive an \"n\" value?
                                                      • \n", @@ -918,11 +916,13 @@ "execution_count": null, "id": "bf63c5c4", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data26.py" + "# %load _solutions/pandas_03a_selecting_data20.py" ] }, { @@ -932,7 +932,7 @@ "source": [ "
                                                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 15:\n", "\n", "
                                                        \n", "
                                                      • Display the cast of the \"Titanic\" (the most famous 1997 one) in their correct \"n\"-value order, ignoring roles that did not earn a numeric \"n\" value.
                                                        • \n", @@ -945,11 +945,13 @@ "execution_count": null, "id": "a2b4032d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data27.py" + "# %load _solutions/pandas_03a_selecting_data21.py" ] }, { @@ -959,7 +961,7 @@ "source": [ "
                                                        \n", "\n", - "EXERCISE:\n", + "EXERCISE 16:\n", "\n", "
                                                          \n", "
                                                        • List the supporting roles (having n=2) played by Brad Pitt in the 1990s, in order by year.
                                                          • \n", @@ -972,11 +974,13 @@ "execution_count": null, "id": "84f1580b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "# %load _solutions/pandas_03a_selecting_data28.py" + "# %load _solutions/pandas_03a_selecting_data22.py" ] }, { @@ -994,6 +998,9 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/notebooks/pandas_03b_indexing.ipynb b/notebooks/pandas_03b_indexing.ipynb index 78bae2f..0a7cb63 100644 --- a/notebooks/pandas_03b_indexing.ipynb +++ b/notebooks/pandas_03b_indexing.ipynb @@ -7,9 +7,6 @@ "source": [ "

                                                          03 - Pandas: Indexing and selecting data - part II

                                                          \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -274,7 +271,7 @@ "metadata": {}, "source": [ "
                                                          \n", - "EXERCISE:\n", + "EXERCISE 1:\n", "\n", "

                                                          \n", "

                                                            \n", @@ -290,7 +287,9 @@ "execution_count": null, "id": "e86eb675", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -303,7 +302,7 @@ "metadata": {}, "source": [ "
                                                            \n", - "EXERCISE:\n", + "EXERCISE 2:\n", "\n", "
                                                              \n", "
                                                            • Select the capital and the population column of those countries where the density is larger than 300
                                                              • \n", @@ -316,7 +315,9 @@ "execution_count": null, "id": "2ea77b99", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -330,7 +331,7 @@ "source": [ "
                                                              \n", "\n", - "EXERCISE:\n", + "EXERCISE 3:\n", "\n", "
                                                                \n", "
                                                              • Add a column 'density_ratio' with the ratio of the population density to the average population density for all countries.
                                                                • \n", @@ -343,7 +344,9 @@ "execution_count": null, "id": "d26f9a2d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -357,7 +360,7 @@ "source": [ "
                                                                \n", "\n", - "EXERCISE:\n", + "EXERCISE 4:\n", "\n", "
                                                                  \n", "
                                                                • Change the capital of the UK to Cambridge
                                                                  • \n", @@ -370,7 +373,9 @@ "execution_count": null, "id": "35eea480", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -383,7 +388,7 @@ "metadata": {}, "source": [ "
                                                                  \n", - "EXERCISE:\n", + "EXERCISE 5:\n", "\n", "
                                                                    \n", "
                                                                  • Select all countries whose population density is between 100 and 300 people/km²
                                                                    • \n", @@ -396,13 +401,93 @@ "execution_count": null, "id": "d2dc714d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ "# %load _solutions/pandas_03b_indexing5.py" ] }, + { + "cell_type": "markdown", + "id": "b90acfd6", + "metadata": {}, + "source": [ + "The next exercise uses the titanic data set:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ddfcaa02", + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"data/titanic.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87877ee1", + "metadata": {}, + "outputs": [], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "markdown", + "id": "4e9e8655", + "metadata": {}, + "source": [ + "
                                                                    \n", + "\n", + "EXERCISE 6:\n", + "\n", + "* Select all rows for male passengers and calculate the mean age of those passengers. Do the same for the female passengers. Do this now using `.loc`.\n", + "\n", + "
                                                                    " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a55e2ce", + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "# %load _solutions/pandas_03b_indexing6.py" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a351c467", + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "# %load _solutions/pandas_03b_indexing7.py" + ] + }, + { + "cell_type": "markdown", + "id": "31d49399", + "metadata": {}, + "source": [ + "We will later see an easier way to calculate both averages at the same time with `groupby`." + ] + }, { "cell_type": "markdown", "id": "7f26d7b3", @@ -602,83 +687,12 @@ "\n", "
                                                                  " ] - }, - { - "cell_type": "markdown", - "id": "b90acfd6", - "metadata": {}, - "source": [ - "# Exercises using the Titanic dataset" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ddfcaa02", - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.read_csv(\"data/titanic.csv\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "87877ee1", - "metadata": {}, - "outputs": [], - "source": [ - "df.head()" - ] - }, - { - "cell_type": "markdown", - "id": "4e9e8655", - "metadata": {}, - "source": [ - "
                                                                  \n", - "\n", - "EXERCISE:\n", - "\n", - "* Select all rows for male passengers and calculate the mean age of those passengers. Do the same for the female passengers. Do this now using `.loc`.\n", - "\n", - "
                                                                  " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9a55e2ce", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# %load _solutions/pandas_03b_indexing6.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a351c467", - "metadata": { - "clear_cell": true - }, - "outputs": [], - "source": [ - "# %load _solutions/pandas_03b_indexing7.py" - ] - }, - { - "cell_type": "markdown", - "id": "31d49399", - "metadata": {}, - "source": [ - "We will later see an easier way to calculate both averages at the same time with groupby." - ] } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/notebooks/pandas_04_time_series_data.ipynb b/notebooks/pandas_04_time_series_data.ipynb index 5aa71b2..1760f3d 100644 --- a/notebooks/pandas_04_time_series_data.ipynb +++ b/notebooks/pandas_04_time_series_data.ipynb @@ -7,9 +7,6 @@ "source": [ "

                                                                  04 - Pandas: Working with time series data

                                                                  \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -675,7 +672,7 @@ "source": [ "
                                                                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 1:\n", "\n", "
                                                                    \n", "
                                                                  • select all data starting from 2012
                                                                    • \n", @@ -688,7 +685,9 @@ "execution_count": null, "id": "1701f43d", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -702,7 +701,7 @@ "source": [ "
                                                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 2:\n", "\n", "
                                                                      \n", "
                                                                    • select all data in January for all different years
                                                                      • \n", @@ -715,7 +714,9 @@ "execution_count": null, "id": "3d61b665", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -729,7 +730,7 @@ "source": [ "
                                                                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 3:\n", "\n", "
                                                                        \n", "
                                                                      • select all data in April, May and June for all different years
                                                                        • \n", @@ -742,7 +743,9 @@ "execution_count": null, "id": "8e2cf035", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -756,7 +759,7 @@ "source": [ "
                                                                        \n", "\n", - "EXERCISE:\n", + "EXERCISE 4:\n", "\n", "
                                                                          \n", "
                                                                        • select all 'daytime' data (between 8h and 20h) for all days
                                                                          • \n", @@ -769,7 +772,9 @@ "execution_count": null, "id": "760a4912", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -854,7 +859,7 @@ "source": [ "
                                                                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 5:\n", "\n", "
                                                                            \n", "
                                                                          • Plot the monthly standard deviation of the columns
                                                                            • \n", @@ -867,7 +872,9 @@ "execution_count": null, "id": "037f5b47", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -881,7 +888,7 @@ "source": [ "
                                                                            \n", "\n", - "EXERCISE:\n", + "EXERCISE 6:\n", "\n", "
                                                                              \n", "
                                                                            • Plot the monthly mean and median values for the years 2011-2012 for 'L06_347'

                                                                              • \n", @@ -897,7 +904,9 @@ "execution_count": null, "id": "edf270bf", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -911,7 +920,7 @@ "source": [ "
                                                                              \n", "\n", - "EXERCISE:\n", + "EXERCISE 7:\n", "\n", "
                                                                                \n", "
                                                                              • plot the monthly mininum and maximum daily average value of the 'LS06_348' column
                                                                                • \n", @@ -924,7 +933,9 @@ "execution_count": null, "id": "c0557860", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -936,7 +947,9 @@ "execution_count": null, "id": "20126280", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -949,7 +962,7 @@ "metadata": {}, "source": [ "
                                                                                \n", - "EXERCISE:\n", + "EXERCISE 8:\n", "\n", "
                                                                                  \n", "
                                                                                • Make a bar plot of the mean of the stations in year of 2013
                                                                                  • \n", @@ -963,7 +976,9 @@ "execution_count": null, "id": "e0a18e44", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -972,8 +987,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -987,7 +1005,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/pandas_05_combining_datasets.ipynb b/notebooks/pandas_05_combining_datasets.ipynb index 7c9f80f..0c2c4c1 100644 --- a/notebooks/pandas_05_combining_datasets.ipynb +++ b/notebooks/pandas_05_combining_datasets.ipynb @@ -5,11 +5,9 @@ "id": "be5c9d31", "metadata": {}, "source": [ - "

                                                                                  05 - Pandas: Combining datasets Part I - concat

                                                                                  \n", + "

                                                                                  Pandas: Combining datasets Part I - concat

                                                                                  \n", + "\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -201,6 +199,21 @@ "Assume we have some similar data as in `countries`, but for a set of different countries:" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce79b16e-ea96-4845-9104-9a18be4de526", + "metadata": {}, + "outputs": [], + "source": [ + "data = {'country': ['Belgium', 'France', 'Germany', 'Netherlands', 'United Kingdom'],\n", + " 'population': [11.3, 64.3, 81.3, 16.9, 64.9],\n", + " 'area': [30510, 671308, 357050, 41526, 244820],\n", + " 'capital': ['Brussels', 'Paris', 'Berlin', 'Amsterdam', 'London']}\n", + "countries = pd.DataFrame(data)\n", + "countries" + ] + }, { "cell_type": "code", "execution_count": null, @@ -290,189 +303,255 @@ }, { "cell_type": "markdown", - "id": "b01819a6", + "id": "b361359f-e464-4094-b16f-fc6dbf22ee6b", "metadata": {}, "source": [ - "## Combining columns - ``pd.concat`` with ``axis=1``" + "
                                                                                  \n", + "\n", + "**NOTE**:\n", + "\n", + "A typical use case of `concat` is when you create (or read) multiple DataFrame with a similar structure in a loop, and then want to combine this list of DataFrames into a single DataFrame.\n", + "\n", + "For example, assume you have a folder of similar CSV files (eg the data per day) you want to read and combine, this would look like:\n", + "\n", + "```python\n", + "import pathlib\n", + "\n", + "data_files = pathlib.Path(\"data_directory\").glob(\"*.csv\")\n", + "\n", + "dfs = []\n", + "\n", + "for path in data_files:\n", + " temp = pd.read_csv(path)\n", + " dfs.append(temp)\n", + "\n", + "df = pd.concat(dfs)\n", + "```\n", + "
                                                                                  \n", + "Important: append to a list (not DataFrame), and concat this list at the end after the loop!\n", + "\n", + "
                                                                                  " ] }, { "cell_type": "markdown", - "id": "79eebe9b", + "id": "970012f2", "metadata": {}, "source": [ - "![](../img/pandas/schema-concat1.svg)" + "# Joining data with `pd.merge`" ] }, { "cell_type": "markdown", - "id": "5c855df6", + "id": "78e1b973", "metadata": {}, "source": [ - "Assume we have another DataFrame for the same countries, but with some additional statistics:" + "Using `pd.concat` above, we combined datasets that had the same columns. But, another typical case is where you want to add information of a second dataframe to a first one based on one of the columns they have in common. That can be done with [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html).\n", + "\n", + "Let's look again at the titanic passenger data, but taking a small subset of it to make the example easier to grasp:" ] }, { "cell_type": "code", "execution_count": null, - "id": "7f4613a7", + "id": "e00931e6", "metadata": {}, "outputs": [], "source": [ - "data = {'country': ['Belgium', 'France', 'Netherlands'],\n", - " 'GDP': [496477, 2650823, 820726],\n", - " 'area': [8.0, 9.9, 5.7]}\n", - "country_economics = pd.DataFrame(data).set_index('country')\n", - "country_economics" + "df = pd.read_csv(\"data/titanic.csv\")\n", + "df = df.loc[:9, ['Survived', 'Pclass', 'Sex', 'Age', 'Fare', 'Embarked']]" ] }, { "cell_type": "code", "execution_count": null, - "id": "3105e789", + "id": "37dcebb7", "metadata": {}, "outputs": [], "source": [ - "pd.concat([countries, country_economics], axis=1)" + "df" ] }, { "cell_type": "markdown", - "id": "64f7a2dc", + "id": "4ae11628", "metadata": {}, "source": [ - "`pd.concat` matches the different objects based on the index:" + "Assume we have another dataframe with more information about the 'Embarked' locations:" ] }, { "cell_type": "code", "execution_count": null, - "id": "763667a5", + "id": "35e5b529", "metadata": {}, "outputs": [], "source": [ - "countries2 = countries.set_index('country')" + "locations = pd.DataFrame({'Embarked': ['S', 'C', 'N'],\n", + " 'City': ['Southampton', 'Cherbourg', 'New York City'],\n", + " 'Country': ['United Kindom', 'France', 'United States']})" ] }, { "cell_type": "code", "execution_count": null, - "id": "6c3a72d7", + "id": "94906138", "metadata": {}, "outputs": [], "source": [ - "countries2" + "locations" + ] + }, + { + "cell_type": "markdown", + "id": "1ebb09a0", + "metadata": {}, + "source": [ + "We now want to add those columns to the titanic dataframe, for which we can use `pd.merge`, specifying the column on which we want to merge the two datasets:" ] }, { "cell_type": "code", "execution_count": null, - "id": "07814fa5", + "id": "571b126f", "metadata": {}, "outputs": [], "source": [ - "pd.concat([countries2, country_economics], axis=1)" + "pd.merge(df, locations, on='Embarked', how='left')" ] }, { "cell_type": "markdown", - "id": "970012f2", + "id": "4b1df56c", "metadata": {}, "source": [ - "# Joining data with `pd.merge`" + "In this case we use `how='left` (a \"left join\") because we wanted to keep the original rows of `df` and only add matching values from `locations` to it. Other options are 'inner', 'outer' and 'right' (see the [docs](http://pandas.pydata.org/pandas-docs/stable/merging.html#brief-primer-on-merge-methods-relational-algebra) for more on this, or this visualization: https://joins.spathon.com/)." ] }, { "cell_type": "markdown", - "id": "78e1b973", + "id": "e3b5ad11-9387-46e9-a8f1-64fe61446358", "metadata": {}, "source": [ - "Using `pd.concat` above, we combined datasets that had the same columns or the same index values. But, another typical case if where you want to add information of second dataframe to a first one based on one of the columns. That can be done with [`pd.merge`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html).\n", - "\n", - "Let's look again at the titanic passenger data, but taking a small subset of it to make the example easier to grasp:" + "## Combining columns - ``pd.concat`` with ``axis=1``" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "e00931e6", + "cell_type": "markdown", + "id": "5b8e016e-5e29-42a6-bd30-26bdda19ec22", "metadata": {}, - "outputs": [], "source": [ - "df = pd.read_csv(\"data/titanic.csv\")\n", - "df = df.loc[:9, ['Survived', 'Pclass', 'Sex', 'Age', 'Fare', 'Embarked']]" + "We can use `pd.merge` to combine the columns of two DataFrame based on a common column. If our two DataFrames already have equivalent rows, we can also achieve this basic case using `pd.concat` with specifying `axis=1` (or `axis=\"columns\"`)." ] }, { - "cell_type": "code", - "execution_count": null, - "id": "37dcebb7", + "cell_type": "markdown", + "id": "1e24ffc4-d651-4fbb-bdcf-5a42c6ddb1bd", "metadata": {}, - "outputs": [], "source": [ - "df" + "![](../img/pandas/schema-concat1.svg)" ] }, { "cell_type": "markdown", - "id": "4ae11628", + "id": "fa045a3c-119a-4463-affe-b8282c415bd3", "metadata": {}, "source": [ - "Assume we have another dataframe with more information about the 'Embarked' locations:" + "Assume we have another DataFrame for the same countries, but with some additional statistics:" ] }, { "cell_type": "code", "execution_count": null, - "id": "35e5b529", + "id": "13cabbdd-51b3-47d6-b9f8-d0c60fd63fea", "metadata": {}, "outputs": [], "source": [ - "locations = pd.DataFrame({'Embarked': ['S', 'C', 'Q', 'N'],\n", - " 'City': ['Southampton', 'Cherbourg', 'Queenstown', 'New York City'],\n", - " 'Country': ['United Kindom', 'France', 'Ireland', 'United States']})" + "data = {'country': ['Belgium', 'France', 'Germany', 'Netherlands', 'United Kingdom'],\n", + " 'population': [11.3, 64.3, 81.3, 16.9, 64.9],\n", + " 'area': [30510, 671308, 357050, 41526, 244820],\n", + " 'capital': ['Brussels', 'Paris', 'Berlin', 'Amsterdam', 'London']}\n", + "countries = pd.DataFrame(data)\n", + "countries" ] }, { "cell_type": "code", "execution_count": null, - "id": "94906138", + "id": "7f4613a7", "metadata": {}, "outputs": [], "source": [ - "locations" + "data = {'country': ['Belgium', 'France', 'Netherlands'],\n", + " 'GDP': [496477, 2650823, 820726],\n", + " 'area': [8.0, 9.9, 5.7]}\n", + "country_economics = pd.DataFrame(data).set_index('country')\n", + "country_economics" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3105e789", + "metadata": {}, + "outputs": [], + "source": [ + "pd.concat([countries, country_economics], axis=1)" ] }, { "cell_type": "markdown", - "id": "1ebb09a0", + "id": "17e2c658-8343-4142-a995-3fb8de9ede08", "metadata": {}, "source": [ - "We now want to add those columns to the titanic dataframe, for which we can use `pd.merge`, specifying the column on which we want to merge the two datasets:" + "`pd.concat` matches the different objects based on the index:" ] }, { "cell_type": "code", "execution_count": null, - "id": "571b126f", + "id": "763667a5", "metadata": {}, "outputs": [], "source": [ - "pd.merge(df, locations, on='Embarked', how='left')" + "countries2 = countries.set_index('country')" ] }, { - "cell_type": "markdown", - "id": "4b1df56c", + "cell_type": "code", + "execution_count": null, + "id": "6c3a72d7", "metadata": {}, + "outputs": [], + "source": [ + "countries2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07814fa5", + "metadata": {}, + "outputs": [], "source": [ - "In this case we use `how='left` (a \"left join\") because we wanted to keep the original rows of `df` and only add matching values from `locations` to it. Other options are 'inner', 'outer' and 'right' (see the [docs](http://pandas.pydata.org/pandas-docs/stable/merging.html#brief-primer-on-merge-methods-relational-algebra) for more on this)." + "pd.concat([countries2, country_economics], axis=\"columns\")" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c420d1a6-5cf6-4efa-868d-0c591459e4e1", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -486,7 +565,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/pandas_06_groupby_operations.ipynb b/notebooks/pandas_06_groupby_operations.ipynb index f7839fa..11fc1da 100644 --- a/notebooks/pandas_06_groupby_operations.ipynb +++ b/notebooks/pandas_06_groupby_operations.ipynb @@ -7,9 +7,7 @@ "source": [ "

                                                                                  06 - Pandas: \"Group by\" operations

                                                                                  \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -227,7 +225,7 @@ "source": [ "
                                                                                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 1:\n", "\n", "
                                                                                    \n", "
                                                                                  • Using groupby(), calculate the average age for each sex.
                                                                                    • \n", @@ -240,7 +238,9 @@ "execution_count": null, "id": "613ddc81", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -254,7 +254,7 @@ "source": [ "
                                                                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 2:\n", "\n", "
                                                                                      \n", "
                                                                                    • Calculate the average survival ratio for all passengers.
                                                                                      • \n", @@ -267,7 +267,9 @@ "execution_count": null, "id": "970c2e54", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -281,7 +283,7 @@ "source": [ "
                                                                                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 3:\n", "\n", "
                                                                                        \n", "
                                                                                      • Calculate this survival ratio for all passengers younger than 25 (remember: filtering/boolean indexing).
                                                                                        • \n", @@ -294,7 +296,9 @@ "execution_count": null, "id": "6f8e4b59", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -308,7 +312,7 @@ "source": [ "
                                                                                        \n", "\n", - "EXERCISE:\n", + "EXERCISE 4:\n", "\n", "
                                                                                          \n", "
                                                                                        • What is the difference in the survival ratio between the sexes?
                                                                                          • \n", @@ -321,7 +325,9 @@ "execution_count": null, "id": "0ae49b3f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -335,7 +341,7 @@ "source": [ "
                                                                                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 5:\n", "\n", "
                                                                                            \n", "
                                                                                          • Make a bar plot of the survival ratio for the different classes ('Pclass' column).
                                                                                            • \n", @@ -348,7 +354,9 @@ "execution_count": null, "id": "6daf3916", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -362,7 +370,7 @@ "source": [ "
                                                                                            \n", "\n", - "**EXERCISE**:\n", + "**EXERCISE 6**:\n", "\n", "* Make a bar plot to visualize the average Fare payed by people depending on their age. The age column is divided is separate classes using the `pd.cut()` function as provided below.\n", "\n", @@ -373,9 +381,7 @@ "cell_type": "code", "execution_count": null, "id": "bb9d51c0", - "metadata": { - "clear_cell": false - }, + "metadata": {}, "outputs": [], "source": [ "df['AgeClass'] = pd.cut(df['Age'], bins=np.arange(0,90,10))" @@ -386,7 +392,9 @@ "execution_count": null, "id": "5baf6965", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -519,7 +527,7 @@ "id": "7e3afc02", "metadata": {}, "source": [ - "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKajNMa1pfSzN6Q3M) and [`cast.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKal9UYTJSR2ZhSW8) and put them in the `/data` folder." + "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/titles.csv) and [`cast.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/cast.csv) and put them in the `/notebooks/data` folder." ] }, { @@ -576,7 +584,7 @@ "source": [ "
                                                                                            \n", "\n", - "EXERCISE:\n", + "EXERCISE 7:\n", "\n", "
                                                                                              \n", "
                                                                                            • Using `groupby()`, plot the number of films that have been released each decade in the history of cinema.
                                                                                              • \n", @@ -589,7 +597,9 @@ "execution_count": null, "id": "ffe929fb", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -601,7 +611,9 @@ "execution_count": null, "id": "6afdc68a", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -615,7 +627,7 @@ "source": [ "
                                                                                              \n", "\n", - "EXERCISE:\n", + "EXERCISE 8:\n", "\n", "
                                                                                                \n", "
                                                                                              • Use `groupby()` to plot the number of 'Hamlet' movies made each decade.
                                                                                                • \n", @@ -628,7 +640,9 @@ "execution_count": null, "id": "37d8a053", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -642,7 +656,7 @@ "source": [ "
                                                                                                \n", "\n", - "EXERCISE:\n", + "EXERCISE 9:\n", "\n", "
                                                                                                  \n", "
                                                                                                • For each decade, plot all movies of which the title contains \"Hamlet\".
                                                                                                  • \n", @@ -655,7 +669,9 @@ "execution_count": null, "id": "265aabfe", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -669,7 +685,7 @@ "source": [ "
                                                                                                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 10:\n", "\n", "
                                                                                                    \n", "
                                                                                                  • List the 10 actors/actresses that have the most leading roles (n=1) since the 1990's.
                                                                                                    • \n", @@ -682,7 +698,9 @@ "execution_count": null, "id": "d47f2c0f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -694,7 +712,9 @@ "execution_count": null, "id": "a7f5a63b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -708,7 +728,7 @@ "source": [ "
                                                                                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 11:\n", "\n", "
                                                                                                      \n", "
                                                                                                    • In a previous exercise, the number of 'Hamlet' films released each decade was checked. Not all titles are exactly called 'Hamlet'. Give an overview of the titles that contain 'Hamlet' and an overview of the titles that start with 'Hamlet', each time providing the amount of occurrences in the data set for each of the movies
                                                                                                      • \n", @@ -721,7 +741,9 @@ "execution_count": null, "id": "651bce19", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -733,7 +755,9 @@ "execution_count": null, "id": "9cf43c6b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -747,7 +771,7 @@ "source": [ "
                                                                                                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 12:\n", "\n", "
                                                                                                        \n", "
                                                                                                      • List the 10 movie titles with the longest name.
                                                                                                        • \n", @@ -760,7 +784,9 @@ "execution_count": null, "id": "5ab64a23", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -772,7 +798,9 @@ "execution_count": null, "id": "2f51c366", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -786,7 +814,7 @@ "source": [ "
                                                                                                        \n", "\n", - "EXERCISE:\n", + "EXERCISE 13:\n", "\n", "
                                                                                                          \n", "
                                                                                                        • How many leading (n=1) roles were available to actors, and how many to actresses, in each year of the 1950s?
                                                                                                          • \n", @@ -799,7 +827,9 @@ "execution_count": null, "id": "fd57aac5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -813,7 +843,7 @@ "source": [ "
                                                                                                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 14:\n", "\n", "
                                                                                                            \n", "
                                                                                                          • What are the 11 most common character names in movie history?
                                                                                                            • \n", @@ -826,7 +856,9 @@ "execution_count": null, "id": "b97feb82", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -840,7 +872,7 @@ "source": [ "
                                                                                                            \n", "\n", - "EXERCISE:\n", + "EXERCISE 15:\n", "\n", "
                                                                                                              \n", "
                                                                                                            • Plot how many roles Brad Pitt has played in each year of his career.
                                                                                                              • \n", @@ -853,7 +885,9 @@ "execution_count": null, "id": "4057c09f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -867,7 +901,7 @@ "source": [ "
                                                                                                              \n", "\n", - "EXERCISE:\n", + "EXERCISE 16:\n", "\n", "
                                                                                                                \n", "
                                                                                                              • What are the 10 most occurring movie titles that start with the words 'The Life'?
                                                                                                                • \n", @@ -880,7 +914,9 @@ "execution_count": null, "id": "c3c80c4f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -894,7 +930,7 @@ "source": [ "
                                                                                                                \n", "\n", - "EXERCISE:\n", + "EXERCISE 17:\n", "\n", "
                                                                                                                  \n", "
                                                                                                                • Which actors or actresses were most active in the year 2010 (i.e. appeared in the most movies)?
                                                                                                                  • \n", @@ -907,7 +943,9 @@ "execution_count": null, "id": "a38a3d15", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -921,7 +959,7 @@ "source": [ "
                                                                                                                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 18:\n", "\n", "
                                                                                                                    \n", "
                                                                                                                  • Determine how many roles are listed for each of 'The Pink Panther' movies.
                                                                                                                    • \n", @@ -934,7 +972,9 @@ "execution_count": null, "id": "d80c0f2b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -948,7 +988,7 @@ "source": [ "
                                                                                                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 19:\n", "\n", "
                                                                                                                      \n", "
                                                                                                                    • List, in order by year, each of the movies in which 'Frank Oz' has played more than 1 role.
                                                                                                                      • \n", @@ -961,7 +1001,9 @@ "execution_count": null, "id": "2a8f6351", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -975,7 +1017,7 @@ "source": [ "
                                                                                                                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 20:\n", "\n", "
                                                                                                                        \n", "
                                                                                                                      • List each of the characters that Frank Oz has portrayed at least twice.
                                                                                                                        • \n", @@ -988,7 +1030,9 @@ "execution_count": null, "id": "c38ff395", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1002,11 +1046,17 @@ "source": [ "
                                                                                                                        \n", "\n", - "EXERCISE:\n", + "**EXERCISE 21**\n", + "\n", + "Add a new column to the `cast` DataFrame that indicates the number of roles for each movie. \n", + " \n", + "
                                                                                                                        Hints\n", + "\n", + "- [Transformation](https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#transformation) returns an object that is indexed the same (same size) as the one being grouped.\n", + "\n", + "
                                                                                                                        \n", + " \n", "\n", - "
                                                                                                                          \n", - "
                                                                                                                        • Add a new column to the `cast` DataFrame that indicates the number of roles for each movie. [Hint](http://pandas.pydata.org/pandas-docs/stable/groupby.html#transformation)
                                                                                                                          • \n", - "
                                                                                                                        \n", "
                                                                                                                        " ] }, @@ -1015,7 +1065,9 @@ "execution_count": null, "id": "77eee4f6", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1029,7 +1081,7 @@ "source": [ "
                                                                                                                        \n", "\n", - "EXERCISE:\n", + "EXERCISE 22:\n", "\n", "
                                                                                                                          \n", "
                                                                                                                        • Calculate the ratio of leading actor and actress roles to the total number of leading roles per decade.
                                                                                                                          • \n", @@ -1044,7 +1096,9 @@ "execution_count": null, "id": "708d707b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1056,7 +1110,9 @@ "execution_count": null, "id": "ddbac330", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1068,7 +1124,9 @@ "execution_count": null, "id": "7cf5a472", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1082,7 +1140,7 @@ "source": [ "
                                                                                                                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 23:\n", "\n", "
                                                                                                                            \n", "
                                                                                                                          • In which years the most films were released?
                                                                                                                            • \n", @@ -1095,7 +1153,9 @@ "execution_count": null, "id": "a5867953", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1109,7 +1169,7 @@ "source": [ "
                                                                                                                            \n", "\n", - "EXERCISE:\n", + "EXERCISE 24:\n", "\n", "
                                                                                                                              \n", "
                                                                                                                            • How many leading (n=1) roles were available to actors, and how many to actresses, in the 1950s? And in 2000s?
                                                                                                                              • \n", @@ -1122,7 +1182,9 @@ "execution_count": null, "id": "1caad935", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1134,7 +1196,9 @@ "execution_count": null, "id": "fe757699", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -1143,6 +1207,9 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/notebooks/pandas_07_reshaping_data.ipynb b/notebooks/pandas_07_reshaping_data.ipynb index 353fdd3..37c2c9b 100644 --- a/notebooks/pandas_07_reshaping_data.ipynb +++ b/notebooks/pandas_07_reshaping_data.ipynb @@ -7,9 +7,7 @@ "source": [ "

                                                                                                                              07 - Pandas: Reshaping data

                                                                                                                              \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -24,7 +22,8 @@ "source": [ "import pandas as pd\n", "import numpy as np\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" ] }, { @@ -299,7 +298,7 @@ "id": "a83de3ae", "metadata": {}, "source": [ - "# Pivot tables - aggregating while pivoting" + "## Pivot tables - aggregating while pivoting" ] }, { @@ -383,6 +382,14 @@ "pd.crosstab(index=df['Sex'], columns=df['Pclass'])" ] }, + { + "cell_type": "markdown", + "id": "20524f03-4971-465f-b610-73c39a89be49", + "metadata": {}, + "source": [ + "## Exercises" + ] + }, { "cell_type": "markdown", "id": "5916201b", @@ -392,7 +399,7 @@ "source": [ "
                                                                                                                              \n", "\n", - "EXERCISE:\n", + "EXERCISE 1:\n", "\n", "
                                                                                                                                \n", "
                                                                                                                              • Make a pivot table with the survival rates for Pclass vs Sex.
                                                                                                                                • \n", @@ -405,7 +412,9 @@ "execution_count": null, "id": "f1c056b4", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -417,7 +426,9 @@ "execution_count": null, "id": "d2137b87", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -433,7 +444,7 @@ "source": [ "
                                                                                                                                \n", "\n", - "EXERCISE:\n", + "EXERCISE 2:\n", "\n", "
                                                                                                                                  \n", "
                                                                                                                                • Make a table of the median Fare payed by aged/underaged vs Sex.
                                                                                                                                  • \n", @@ -446,7 +457,9 @@ "execution_count": null, "id": "a369f84c", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -458,7 +471,9 @@ "execution_count": null, "id": "a32d5f69", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -475,10 +490,10 @@ }, { "cell_type": "markdown", - "id": "399ca374", + "id": "5251dca0-9e04-4f5b-91d4-f24b35443e2f", "metadata": {}, "source": [ - "The `melt` function performs the inverse operation of a `pivot`. This can be used to make your frame longer, i.e. to make a *tidy* version of your data." + "The `melt` function performs the inverse operation of a `pivot`." ] }, { @@ -507,7 +522,7 @@ "id": "850d7dbe", "metadata": {}, "source": [ - "Assume we have a DataFrame like the above. The observations (the average Fare people payed) are spread over different columns. In a tidy dataset, each observation is stored in one row. To obtain this, we can use the `melt` function:" + "Assume we have a DataFrame like the above. The observations (the average Fare people payed) are spread over different columns. To make sure each value is in its own row, we can use the `melt` function:" ] }, { @@ -540,6 +555,107 @@ "pd.melt(pivoted, id_vars=['Sex']) #, var_name='Pclass', value_name='Fare')" ] }, + { + "cell_type": "markdown", + "id": "399ca374", + "metadata": {}, + "source": [ + "## Tidy data\n", + "\n", + "`melt `can be used to make a dataframe longer, i.e. to make a *tidy* version of your data. In a [tidy dataset](https://vita.had.co.nz/papers/tidy-data.pdf) (also sometimes called 'long-form' data or 'denormalized' data) each observation is stored in its own row and each column contains a single variable:\n", + "\n", + "![](../img/tidy_data_scheme.png)\n", + "\n", + "Consider the following example with measurements in different Waste Water Treatment Plants (WWTP):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0e50cec8-1244-43c6-b14e-f06e32deacc3", + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.DataFrame({\n", + " 'WWTP': ['Destelbergen', 'Landegem', 'Dendermonde', 'Eeklo'],\n", + " 'Treatment A': [8.0, 7.5, 8.3, 6.5],\n", + " 'Treatment B': [6.3, 5.2, 6.2, 7.2]\n", + "})\n", + "data" + ] + }, + { + "cell_type": "markdown", + "id": "71ca855d-552a-4c04-9a07-fa5ea30bf3a2", + "metadata": {}, + "source": [ + "This data representation is not \"tidy\":\n", + "\n", + "- Each row contains two observations of pH (each from a different treatment)\n", + "- 'Treatment' (A or B) is a variable not in its own column, but used as column headers" + ] + }, + { + "cell_type": "markdown", + "id": "19252f37-e9c7-46b3-9e69-718312f4dabe", + "metadata": {}, + "source": [ + "We can `melt` the data set to tidy the data:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "11ac8b4f-942a-4711-a689-8a66960fbbdc", + "metadata": {}, + "outputs": [], + "source": [ + "data_long = pd.melt(data, id_vars=[\"WWTP\"], \n", + " value_name=\"pH\", var_name=\"Treatment\")\n", + "data_long" + ] + }, + { + "cell_type": "markdown", + "id": "09f947e8-70dd-485c-9c25-0125d22b3f9d", + "metadata": {}, + "source": [ + "The usage of the tidy data representation has some important benefits when working with `groupby` or data visualization libraries such as Seaborn:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "93d18784-c36a-4845-9bf9-d8855e4a7d69", + "metadata": {}, + "outputs": [], + "source": [ + "data_long.groupby(\"Treatment\")[\"pH\"].mean() # switch to `WWTP`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dd2a72f7-695d-4411-9fec-989d358d76ab", + "metadata": {}, + "outputs": [], + "source": [ + "sns.catplot(data=data, x=\"WWTP\", y=\"...\", hue=\"...\", kind=\"bar\") # this doesn't work that easily" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "507af344-ec3d-40d2-a407-cfa732a5670e", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "sns.catplot(data=data_long, x=\"WWTP\", y=\"pH\", \n", + " hue=\"Treatment\", kind=\"bar\") # switch `WWTP` and `Treatment`" + ] + }, { "cell_type": "markdown", "id": "5b2c8ee2", @@ -672,6 +788,14 @@ "df.head()" ] }, + { + "cell_type": "markdown", + "id": "43fe898c-8bf3-4819-ac2a-de07a948cec3", + "metadata": {}, + "source": [ + "## Exercises" + ] + }, { "cell_type": "code", "execution_count": null, @@ -690,7 +814,7 @@ "source": [ "
                                                                                                                                  \n", "\n", - "EXERCISE:\n", + "EXERCISE 3:\n", "\n", "
                                                                                                                                    \n", "
                                                                                                                                  • Get the same result as above based on a combination of `groupby` and `unstack`
                                                                                                                                    • \n", @@ -705,7 +829,9 @@ "execution_count": null, "id": "0fee61fb", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -725,7 +851,7 @@ "id": "45ce16c2", "metadata": {}, "source": [ - "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKajNMa1pfSzN6Q3M) and [`cast.csv`](https://drive.google.com/open?id=0B3G70MlBnCgKal9UYTJSR2ZhSW8) and put them in the `/data` folder." + "These exercises are based on the [PyCon tutorial of Brandon Rhodes](https://github.com/brandon-rhodes/pycon-pandas-tutorial/) (so credit to him!) and the datasets he prepared for that. You can download these data from here: [`titles.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/titles.csv) and [`cast.csv`](https://course-python-data.s3.eu-central-1.amazonaws.com/cast.csv) and put them in the `/notebooks/data` folder." ] }, { @@ -757,7 +883,7 @@ "source": [ "
                                                                                                                                    \n", "\n", - "EXERCISE:\n", + "EXERCISE 4:\n", "\n", "
                                                                                                                                      \n", "
                                                                                                                                    • Plot the number of actor roles each year and the number of actress roles each year over the whole period of available movie data.
                                                                                                                                      • \n", @@ -770,7 +896,9 @@ "execution_count": null, "id": "97cd998b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -782,7 +910,9 @@ "execution_count": null, "id": "165b1114", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -794,7 +924,9 @@ "execution_count": null, "id": "831a9220", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -808,7 +940,7 @@ "source": [ "
                                                                                                                                      \n", "\n", - "EXERCISE:\n", + "EXERCISE 5:\n", "\n", "
                                                                                                                                        \n", "
                                                                                                                                      • Plot the number of actor roles each year and the number of actress roles each year. Use kind='area' as plot type
                                                                                                                                        • \n", @@ -821,7 +953,9 @@ "execution_count": null, "id": "6426434f", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -835,7 +969,7 @@ "source": [ "
                                                                                                                                        \n", "\n", - "EXERCISE:\n", + "EXERCISE 6:\n", "\n", "
                                                                                                                                          \n", "
                                                                                                                                        • Plot the fraction of roles that have been 'actor' roles each year over the whole period of available movie data.
                                                                                                                                          • \n", @@ -848,7 +982,9 @@ "execution_count": null, "id": "391718f5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -862,7 +998,7 @@ "source": [ "
                                                                                                                                          \n", "\n", - "EXERCISE:\n", + "EXERCISE 7:\n", "\n", "
                                                                                                                                            \n", "
                                                                                                                                          • Define a year as a \"Superman year\" when films of that year feature more Superman characters than Batman characters. How many years in film history have been Superman years?
                                                                                                                                            • \n", @@ -875,7 +1011,9 @@ "execution_count": null, "id": "d49401d5", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -887,7 +1025,9 @@ "execution_count": null, "id": "8c75667b", "metadata": { - "clear_cell": true + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -896,8 +1036,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -911,7 +1054,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/pandas_08_missing_values.ipynb b/notebooks/pandas_08_missing_values.ipynb index 871fbd5..b51f6e6 100644 --- a/notebooks/pandas_08_missing_values.ipynb +++ b/notebooks/pandas_08_missing_values.ipynb @@ -7,9 +7,7 @@ "source": [ "

                                                                                                                                            08 - Pandas: Working with missing data

                                                                                                                                            \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", + "\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -335,8 +333,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -350,7 +351,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/notebooks/visualization_01_matplotlib.ipynb b/notebooks/visualization_01_matplotlib.ipynb index eeb8a4b..814532d 100644 --- a/notebooks/visualization_01_matplotlib.ipynb +++ b/notebooks/visualization_01_matplotlib.ipynb @@ -6,12 +6,9 @@ "source": [ "

                                                                                                                                            Visualization - Matplotlib

                                                                                                                                            \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", - "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", + "> *© 2021, Joris Van den Bossche and Stijn Van Hoey. Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", - "---\n" + "---" ] }, { @@ -43,15 +40,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", + "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, @@ -59,7 +52,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## - dry stuff - The matplotlib `Figure`, `axes` and `axis`\n", + "## - dry stuff - The matplotlib `Figure`, `Axes` and `Axis`\n", "\n", "At the heart of **every** plot is the figure object. The \"Figure\" object is the top level concept which can be drawn to one of the many output formats, or simply just to screen. Any object which can be drawn in this way is known as an \"Artist\" in matplotlib.\n", "\n", @@ -69,12 +62,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "fig = plt.figure()\n", @@ -94,36 +82,13 @@ "There is no limit on the number of Axes artists which can exist on a Figure artist. Let's go ahead and create a figure with a single Axes artist, and show it using pyplot:" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, - "outputs": [], - "source": [ - "ax = plt.axes()" - ] - }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "type(ax)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "type(ax.xaxis), type(ax.yaxis)" + "ax = plt.axes()" ] }, { @@ -152,12 +117,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "x = np.linspace(0, 5, 10)\n", @@ -175,43 +135,48 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**1. pyplot style: plt...** (you will see this a lot for code online!)" + "**1. pyplot style: plt.** (you will see this a lot for code online!)" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "plt.plot(x, y, '-')" + "ax = plt.plot(x, y, '-')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**2. creating objects**" + "**2. object oriented**" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ + "from matplotlib import ticker" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.linspace(0, 5, 10)\n", + "y = x ** 10\n", + "\n", "fig, ax = plt.subplots()\n", - "ax.plot(x, y, '-')" + "ax.plot(x, y, '-')\n", + "ax.set_title(\"My data\")\n", + "\n", + "ax.yaxis.set_major_formatter(ticker.FormatStrFormatter(\"%.1f\"))" ] }, { @@ -224,12 +189,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "fig, ax1 = plt.subplots()\n", @@ -241,6 +201,15 @@ "ax2.plot(x, y*2, 'r-')" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And also Matplotlib advices the object oriented style:\n", + "\n", + "![](../img/matplotlib_oo.png)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -250,7 +219,7 @@ "REMEMBER:\n", "\n", "
                                                                                                                                              \n", - "
                                                                                                                                            • Use the object oriented power of Matplotlib!
                                                                                                                                              • \n", + "
                                                                                                                                            • Use the object oriented power of Matplotlib
                                                                                                                                              • \n", "
                                                                                                                                            • Get yourself used to writing fig, ax = plt.subplots()
                                                                                                                                              • \n", "
                                                                                                                                            \n", "
                                                                                                                                          " @@ -259,12 +228,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "fig, ax = plt.subplots()\n", @@ -282,12 +246,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "x = np.linspace(-1, 0, 100)\n", @@ -301,8 +260,10 @@ "ax.plot(x, x**3, color='0.8', linestyle='--', label='power 3')\n", "\n", "ax.vlines(x=-0.75, ymin=0., ymax=0.8, color='0.4', linestyle='-.') \n", + "ax.fill_between(x=x, y1=x**2, y2=1.1*x**2, color='0.85')\n", + "\n", "ax.axhline(y=0.1, color='0.4', linestyle='-.')\n", - "ax.fill_between(x=[-1, 1.1], y1=[0.65], y2=[0.75], color='0.85')\n", + "ax.axhspan(ymin=0.65, ymax=0.75, color='0.95')\n", "\n", "fig.suptitle('Figure title', fontsize=18, \n", " fontweight='bold')\n", @@ -317,11 +278,16 @@ "ax.text(0.5, 0.2, 'Text centered at (0.5, 0.2)\\nin data coordinates.',\n", " horizontalalignment='center', fontsize=14)\n", "\n", - "ax.text(0.5, 0.5, 'Text centered at (0.5, 0.5)\\nin Figure coordinates.',\n", + "ax.text(0.5, 0.5, 'Text centered at (0.5, 0.5)\\nin relative Axes coordinates.',\n", " horizontalalignment='center', fontsize=14, \n", " transform=ax.transAxes, color='grey')\n", "\n", - "ax.legend(loc='upper right', frameon=True, ncol=2, fontsize=14)" + "ax.annotate('Text pointing at (0.0, 0.75)', xy=(0.0, 0.75), xycoords=\"data\",\n", + " xytext=(20, 40), textcoords=\"offset points\",\n", + " horizontalalignment='left', fontsize=14,\n", + " arrowprops=dict(facecolor='black', shrink=0.05, width=1))\n", + "\n", + "ax.legend(loc='lower right', frameon=True, ncol=2, fontsize=14)" ] }, { @@ -340,6 +306,135 @@ "For more information on legend positioning, check [this post](http://stackoverflow.com/questions/4700614/how-to-put-the-legend-out-of-the-plot) on stackoverflow!" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exercises" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For these exercises we will use some random generated example data (as a Numpy array), representing daily measured values:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data = np.random.randint(-2, 3, 100).cumsum()\n", + "data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
                                                                                                                                          \n", + "\n", + "**EXERCISE 1**\n", + "\n", + "Make a line chart of the `data` using Matplotlib. The figure should be 12 (width) by 4 (height) in inches. Make the line color 'darkgrey' and provide an x-label ('days since start') and a y-label ('measured value').\n", + " \n", + "Use the object oriented approach to create the chart.\n", + "\n", + "
                                                                                                                                          Hints\n", + "\n", + "- When Matplotlib only receives a single input variable, it will interpret this as the variable for the y-axis\n", + "- Check the cheat sheet above for the functions.\n", + "\n", + "
                                                                                                                                          \n", + "\n", + "
                                                                                                                                          " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "# %load _solutions/visualization_01_matplotlib1.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
                                                                                                                                          \n", + "\n", + "**EXERCISE 2**\n", + "\n", + "The data represents each a day starting from Jan 1st 2021. Create an array (variable name `dates`) of the same length as the original data (length 100) with the corresponding dates ('2021-01-01', '2021-01-02',...). Create the same chart as in the previous exercise, but use the `dates` values for the x-axis data.\n", + " \n", + "Mark the region inside `[-5, 5]` with a green color to show that these values are within an acceptable range.\n", + "\n", + "
                                                                                                                                          Hints\n", + "\n", + "- As seen in notebook `pandas_04_time_series_data`, Pandas provides a useful function `pd.date_range` to create a set of datetime values. In this case 100 values with `freq=\"D\"`.\n", + "- Make sure to understand the difference between `axhspan` and `fill_between`, which one do you need?\n", + "- When adding regions, adding an `alpha` level is mostly a good idea.\n", + "\n", + "
                                                                                                                                          \n", + "\n", + "
                                                                                                                                          " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "# %load _solutions/visualization_01_matplotlib2.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
                                                                                                                                          \n", + "\n", + "**EXERCISE 3**\n", + "\n", + "Compare the __last ten days__ ('2021-04-01' till '2021-04-10') in a bar chart using darkgrey color. For the data on '2021-04-01', use an orange bar to highlight the measurement on this day.\n", + "\n", + "
                                                                                                                                          Hints\n", + "\n", + "- Select the last 10 days from the `data` and `dates` variable, i.e. slice [-10:].\n", + "- Similar to a `plot` method, Matplotlib provides a `bar` method.\n", + "- By plotting a single orange bar on top of the grey bars with a second bar chart, that one is highlithed.\n", + "\n", + "
                                                                                                                                          \n", + "\n", + "
                                                                                                                                          " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], + "source": [ + "# %load _solutions/visualization_01_matplotlib3.py" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -373,12 +468,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "plt.style.available" @@ -387,17 +477,12 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "x = np.linspace(0, 10)\n", "\n", - "with plt.style.context('seaborn'): # 'seaborn', ggplot', 'bmh', 'grayscale', 'seaborn-whitegrid', 'seaborn-muted'\n", + "with plt.style.context('seaborn-whitegrid'): # 'seaborn', ggplot', 'bmh', 'grayscale', 'seaborn-whitegrid', 'seaborn-muted'\n", " fig, ax = plt.subplots()\n", " ax.plot(x, np.sin(x) + x + np.random.randn(50))\n", " ax.plot(x, np.sin(x) + 0.5 * x + np.random.randn(50))\n", @@ -414,15 +499,10 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "plt.style.use('seaborn-whitegrid')" + "plt.style.use('seaborn')" ] }, { @@ -440,13 +520,73 @@ "\n", "REMEMBER:\n", "\n", - "
                                                                                                                                            \n", - "
                                                                                                                                          • If you just want quickly a good-looking plot, use one of the available styles (plt.style.use('...'))
                                                                                                                                            • \n", - "
                                                                                                                                          • Otherwise, the object-oriented way of working makes it possible to change everything!
                                                                                                                                            • \n", - "
                                                                                                                                          \n", + "* If you just want **quickly a good-looking plot**, use one of the available styles (`plt.style.use('...')`)\n", + "* Otherwise, creating `Figure` and `Axes` objects makes it possible to change everything!\n", + "\n", "
                                                                                                                                        " ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Advanced subplot configuration" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The function to setup a Matplotlib Figure we have seen up to now, `fig, ax = plt.subplots()`, supports creating both a single plot and multiple subplots with a regular number of rows/columns:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig, ax = plt.subplots(2, 3, figsize=(5, 5))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A typical issue when plotting multiple elements in the same Figure is the overlap of the subplots. A straight-forward approach is using a larger Figure size, but this is not always possible and does not make the content independent from the Figure size. Matplotlib provides the usage of a [__constrained-layout__](https://matplotlib.org/stable/tutorials/intermediate/constrainedlayout_guide.html) to fit plots within your Figure cleanly." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig, ax = plt.subplots(2, 3, figsize=(5, 5), constrained_layout=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "When more advanced layout configurations are required, the usage of the [gridspec](https://matplotlib.org/stable/api/gridspec_api.html#module-matplotlib.gridspec) module is a good reference. See [gridspec demo](https://matplotlib.org/stable/gallery/userdemo/demo_gridspec03.html#sphx-glr-gallery-userdemo-demo-gridspec03-py) for more information. A useful shortcut to know about is the [__string-shorthand__](https://matplotlib.org/stable/tutorials/provisional/mosaic.html#string-short-hand) to setup subplot layouts in a more intuitive way, e.g." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "axd = plt.figure(constrained_layout=True).subplot_mosaic(\n", + " \"\"\"\n", + " ABD\n", + " CCD\n", + " \"\"\"\n", + ")\n", + "axd;" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -456,12 +596,7 @@ }, { "cell_type": "markdown", - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "source": [ "What we have been doing while plotting with Pandas:" ] @@ -469,12 +604,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "import pandas as pd" @@ -483,12 +613,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "flowdata = pd.read_csv('data/vmm_flowdata.csv', \n", @@ -499,15 +624,10 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "out = flowdata.plot() # print type()" + "flowdata.plot.line() # remark default plot() is a line plot" ] }, { @@ -534,15 +654,10 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "flowdata.plot(figsize=(16, 6)) # SHIFT + TAB this!" + "flowdata.plot(figsize=(16, 6), ylabel=\"Discharge m3/s\") # SHIFT + TAB this!" ] }, { @@ -555,12 +670,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(16, 6))\n", @@ -585,17 +695,13 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "axs = flowdata.plot(subplots=True, sharex=True,\n", " figsize=(16, 8), colormap='viridis', # Dark2\n", - " fontsize=15, rot=0)" + " fontsize=15, rot=0)\n", + "axs[0].set_title(\"EXAMPLE\");" ] }, { @@ -608,12 +714,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "from matplotlib import cm\n", @@ -640,7 +741,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Is already a bit harder ;-)" + "Is already a bit harder ;-). Pandas provides as set of default configurations on top of Matplotlib." ] }, { @@ -656,20 +757,15 @@ "metadata": {}, "outputs": [], "source": [ - "fig, ax = plt.subplots() #prepare a Matplotlib figure\n", + "fig, (ax0, ax1) = plt.subplots(2, 1) #prepare a Matplotlib figure\n", "\n", - "flowdata.plot(ax=ax) # use Pandas for the plotting" + "flowdata.plot(ax=ax0) # use Pandas for the plotting" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(15, 5)) #prepare a matplotlib figure\n", @@ -685,46 +781,34 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(16, 6)) #provide with matplotlib 2 axis\n", + "fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(16, 6)) #provide with matplotlib 2 axis\n", "\n", - "flowdata[[\"L06_347\", \"LS06_347\"]].plot(ax=ax1) # plot the two timeseries of the same location on the first plot\n", - "flowdata[\"LS06_348\"].plot(ax=ax2, color='0.2') # plot the other station on the second plot\n", + "flowdata[[\"L06_347\", \"LS06_347\"]].plot(ax=ax0) # plot the two timeseries of the same location on the first plot\n", + "flowdata[\"LS06_348\"].plot(ax=ax1, color='0.7') # plot the other station on the second plot\n", "\n", "# further adapt with matplotlib\n", - "ax1.set_ylabel(\"L06_347\")\n", - "ax2.set_ylabel(\"LS06_348\")\n", - "ax2.legend()" + "ax0.set_ylabel(\"L06_347\")\n", + "ax1.set_ylabel(\"LS06_348\")\n", + "ax1.legend()" ] }, { "cell_type": "markdown", - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", " Remember: \n", "\n", - "
                                                                                                                                          \n", - "
                                                                                                                                        • You can do anything with matplotlib, but at a cost... stackoverflow
                                                                                                                                          • \n", - " \n", - "
                                                                                                                                        • The preformatting of Pandas provides mostly enough flexibility for quick analysis and draft reporting. It is not for paper-proof figures or customization
                                                                                                                                          • \n", - "
                                                                                                                                        \n", - "
                                                                                                                                        \n", + "* You can do anything with matplotlib, but at a cost... stackoverflow\n", + "* The preformatting of Pandas provides mostly enough flexibility for quick analysis and draft reporting. It is not for paper-proof figures or customization\n", "\n", "If you take the time to make your perfect/spot-on/greatest-ever matplotlib-figure: Make it a reusable function!\n", + " \n", + "`fig.savefig()` to save your Figure object! \n", "\n", "
                                                                                                                                        " ] @@ -733,115 +817,147 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "An example of such a reusable function to plot data:" + "## Exercise" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "%%file plotter.py \n", - "#this writes a file in your directory, check it(!)\n", + "flowdata = pd.read_csv('data/vmm_flowdata.csv', \n", + " index_col='Time', \n", + " parse_dates=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "flowdata.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
                                                                                                                                        \n", "\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.dates as mdates\n", + "**EXERCISE 4**\n", "\n", - "from matplotlib import cm\n", - "from matplotlib.ticker import MaxNLocator\n", + "Pandas supports different types of charts besides line plots, all available from `.plot.xxx`, e.g. `.plot.scatter`, `.plot.bar`,... Make a bar chart to compare the mean discharge in the three measurement stations L06_347, LS06_347, LS06_348. Add a y-label 'mean discharge'. To do so, prepare a Figure and Axes with Matplotlib and add the chart to the created Axes.\n", "\n", - "def vmm_station_plotter(flowdata, label=\"flow (m$^3$s$^{-1}$)\"):\n", - " colors = [cm.viridis(x) for x in np.linspace(0.0, 1.0, len(flowdata.columns))] # list comprehension to set up the color sequence\n", + "
                                                                                                                                        Hints\n", "\n", - " fig, axs = plt.subplots(3, 1, figsize=(16, 8))\n", + "* You can either use Pandas `ylabel` parameter to set the label or add it with Matploltib `ax.set_ylabel()`\n", + "* To link an Axes object with Pandas output, pass the Axes created by `fig, ax = plt.subplots()` as parameter to the Pandas plot function.\n", + "
                                                                                                                                        \n", "\n", - " for ax, col, station in zip(axs, colors, flowdata.columns):\n", - " ax.plot(flowdata.index, flowdata[station], label=station, color=col) # this plots the data itself\n", - " \n", - " ax.legend(fontsize=15)\n", - " ax.set_ylabel(label, size=15)\n", - " ax.yaxis.set_major_locator(MaxNLocator(4)) # smaller set of y-ticks for clarity\n", - " \n", - " if not ax.get_subplotspec().is_last_row(): # hide the xticklabels from the none-lower row x-axis\n", - " ax.xaxis.set_ticklabels([])\n", - " ax.xaxis.set_major_locator(mdates.YearLocator())\n", - " else: # yearly xticklabels from the lower x-axis in the subplots\n", - " ax.xaxis.set_major_locator(mdates.YearLocator())\n", - " ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))\n", - " ax.tick_params(axis='both', labelsize=15, pad=8) # enlarge the ticklabels and increase distance to axis (otherwise overlap)\n", - " return fig, axs" + "
                                                                                                                                        " ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "from plotter import vmm_station_plotter\n", - "# fig, axs = vmm_station_plotter(flowdata)" + "# %load _solutions/visualization_01_matplotlib4.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
                                                                                                                                        \n", + "\n", + "**EXERCISE 5**\n", + "\n", + "To compare the stations data, make two subplots next to each other:\n", + " \n", + "- In the left subplot, make a bar chart of the minimal measured value for each of the station.\n", + "- In the right subplot, make a bar chart of the maximal measured value for each of the station. \n", + "\n", + "Add a title to the Figure containing 'Minimal and maximal discharge from 2009-01-01 till 2013-01-02'. Extract these dates from the data itself instead of hardcoding it.\n", + "\n", + "
                                                                                                                                        Hints\n", + "\n", + "- One can directly unpack the result of multiple axes, e.g. `fig, (ax0, ax1) = plt.subplots(1, 2,..` and link each of them to a Pands plot function.\n", + "- Remember the remark about `constrained_layout=True` to overcome overlap with subplots?\n", + "- A Figure title is called `suptitle` (which is different from an Axes title)\n", + "- f-strings ([_formatted string literals_](https://docs.python.org/3/tutorial/inputoutput.html#formatted-string-literals)) is a powerful Python feature (since Python 3.6) to use variables inside a string, e.g. `f\"some text with a {variable:HOWTOFORMAT}\"` (with the format being optional).\n", + "
                                                                                                                                        \n", + "\n", + "
                                                                                                                                        " ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "run_control": { - "frozen": false, - "read_only": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ - "fig, axs = vmm_station_plotter(flowdata, \n", - " label=\"NO$_3$ (mg/l)\")\n", - "fig.suptitle('Ammonium concentrations in the Maarkebeek', fontsize='17')\n", - "fig.savefig('ammonium_concentration.pdf')" + "# %load _solutions/visualization_01_matplotlib5.py" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "
                                                                                                                                        \n", + "
                                                                                                                                        \n", "\n", - "**NOTE**\n", + "**EXERCISE 6**\n", "\n", - "- Let your hard work pay off, write your own custom functions!\n", + "Make a line plot of the discharge measurements in station `LS06_347`. \n", + " \n", + "The main event on November 13th caused a flood event. To support the reader in the interpretation of the graph, add the following elements:\n", + " \n", + "- Add an horizontal red line at 20 m3/s to define the alarm level.\n", + "- Add the text 'Alarm level' in red just above the alarm levl line.\n", + "- Add an arrow pointing to the main peak in the data (event on November 13th) with the text 'Flood event on 2020-11-13'\n", + " \n", + "Check the Matplotlib documentation on [annotations](https://matplotlib.org/stable/gallery/text_labels_and_annotations/annotation_demo.html#annotating-plots) for the text annotation\n", + "\n", + "
                                                                                                                                        Hints\n", + "\n", + "- The horizontal line is explained in the cheat sheet in this notebook.\n", + "- Whereas `ax.text` would work as well for the 'alarm level' text, the `annotate` method provides easier options to shift the text slightly relative to a data point.\n", + "- Extract the main peak event by filtering the data on the maximum value. Different approaches are possible, but the `max()` and `idxmax()` methods are a convenient option in this case.\n", + "\n", + "
                                                                                                                                        \n", "\n", "
                                                                                                                                        " ] }, { - "cell_type": "markdown", - "metadata": {}, + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "nbtutor-solution" + ] + }, + "outputs": [], "source": [ - "
                                                                                                                                        \n", - "\n", - "**Remember** \n", - "\n", - "`fig.savefig()` to save your Figure object!\n", - "\n", - "
                                                                                                                                        " + "# %load _solutions/visualization_01_matplotlib6.py" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "# Need more matplotlib inspiration? " + "# Need more matplotlib inspiration?" ] }, { @@ -860,18 +976,31 @@ "source": [ "
                                                                                                                                        \n", "\n", - "**Remember**\n", + "**Galleries!**\n", "\n", - "- matplotlib gallery is an important resource to start from\n", - "- Matplotlib has some great [cheat sheets](https://github.com/matplotlib/cheatsheets) available\n", + "Galleries are great to get inspiration, see the plot you want, and check the code how it is created:\n", + " \n", + "* [matplotlib gallery](https://matplotlib.org/stable/gallery/index.html)\n", + "* [seaborn gallery](https://seaborn.pydata.org/examples/index.html)\n", + "* [python Graph Gallery](https://python-graph-gallery.com/)\n", "\n", "
                                                                                                                                        " ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -885,7 +1014,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { @@ -903,6 +1032,13 @@ "right": "1657px", "top": "106px", "width": "212px" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } } }, "nbformat": 4, diff --git a/notebooks/visualization_02_seaborn.ipynb b/notebooks/visualization_02_seaborn.ipynb index 2abd28a..acce5c9 100644 --- a/notebooks/visualization_02_seaborn.ipynb +++ b/notebooks/visualization_02_seaborn.ipynb @@ -2,62 +2,40 @@ "cells": [ { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "

                                                                                                                                        Visualization - Seaborn

                                                                                                                                        \n", + "

                                                                                                                                        Visualisation: Seaborn

                                                                                                                                        \n", + "\n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", - "---\n" + "---" ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "deletable": true, - "editable": true, - "run_control": { - "frozen": false, - "read_only": false - }, "tags": [] }, "outputs": [], "source": [ + "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "# Seaborn" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true, - "run_control": { - "frozen": false, - "read_only": false - } - }, + "metadata": {}, "source": [ - "> Seaborn is a library for making attractive and **informative statistical** graphics in Python. It is built **on top of Matplotlib** and tightly integrated with the PyData stack, including **support for Numpy and Pandas** data structures and statistical routines from scipy and statsmodels.\n", - "\n", "[Seaborn](https://seaborn.pydata.org/) is a Python data visualization library:\n", "\n", "* Built on top of Matplotlib, but providing\n", @@ -71,12 +49,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "deletable": true, - "editable": true, - "run_control": { - "frozen": false, - "read_only": false - }, "tags": [] }, "outputs": [], @@ -86,20 +58,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "## Introduction" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "We will use the Titanic example data set:" ] @@ -108,8 +74,6 @@ "cell_type": "code", "execution_count": null, "metadata": { - "deletable": true, - "editable": true, "tags": [] }, "outputs": [], @@ -120,13 +84,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "titanic.head()" @@ -134,48 +92,32 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Let's consider following question:\n", - ">*For each class at the Titanic, how many people survived and how many died?*" + ">*For each class at the Titanic and each gender, what was the average age?*" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "Hence, we should define the *size/count* of respectively the zeros (died) and ones (survived) groups of column `Survived`, also grouped by the `Pclass`. In Pandas terminology:" + "Hence, we should define the *mean* of the male and female groups of column `Survived` in combination with the groups of the `Pclass` column. In Pandas terminology:" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "survived_stat = titanic.groupby([\"Pclass\", \"Survived\"]).size().rename('count').reset_index()\n", - "survived_stat\n", - "# Remark: the `rename` syntax is to provide the count column with a column name " + "age_stat = titanic.groupby([\"Pclass\", \"Sex\"])[\"Age\"].mean().reset_index()\n", + "age_stat" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Providing this data in a bar chart with pure Pandas is still partly supported:" ] @@ -183,36 +125,24 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "survived_stat.plot(x='Survived', y='count', kind='bar')\n", + "age_stat.plot(kind='bar')\n", "## A possible other way of plotting this could be using groupby again: \n", - "# survived_stat.groupby('Pclass').plot(x='Survived', y='count', kind='bar') # (try yourself by uncommenting)" + "#age_stat.groupby('Pclass').plot(x='Sex', y='Age', kind='bar') # (try yourself by uncommenting)" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "but with mixed results. The default Pandas plotting functionalities are not sufficient." + "but with mixed results." ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__Seaborn__ provides another level of abstraction to visualize such *grouped* plots with different categories:" ] @@ -220,136 +150,82 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "sns.catplot(data=survived_stat, \n", - " x=\"Survived\", y=\"count\", \n", + "sns.catplot(data=age_stat, \n", + " x=\"Sex\", y=\"Age\", \n", " col=\"Pclass\", kind=\"bar\")" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, - "source": [ - "Moreover, these `count` operations are embedded in Seaborn (similar to other 'Grammar of Graphics' packages such as ggplot in R and Plotnine/Altair in Python). We can do these operations directly on the original `titanic` data set in a single coding step:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, - "outputs": [], - "source": [ - "sns.catplot(data=titanic, \n", - " x=\"Survived\", \n", - " col=\"Pclass\", kind=\"count\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Check here for a short recap about `tidy` data." ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", "**Remember**\n", "\n", - "- Seaborn is especially suitable for these so-called tidy DataFrame representations.\n", + "- Seaborn is especially suitbale for these so-called tidy dataframe representations.\n", "- The [Seaborn tutorial](https://seaborn.pydata.org/tutorial/data_structure.html#long-form-vs-wide-form-data) provides a very good introduction to tidy (also called _long-form_) data. \n", - "- You can use __Pandas column names__ as input for the visualization functions of Seaborn.\n", + "- You can use __Pandas column names__ as input for the visualisation functions of Seaborn.\n", "\n", "
                                                                                                                                        " ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "## Interaction with Matplotlib" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Seaborn builds on top of Matplotlib/Pandas, adding an additional layer of convenience. \n", "\n", "Topic-wise, Seaborn provides three main modules, i.e. type of plots:\n", "\n", - "- __relational__: understanding how variables in a data set relate to each other\n", - "- __distribution__: specialize in representing the distribution of data points\n", + "- __relational__: understanding how variables in a dataset relate to each other\n", + "- __distribution__: specialize in representing the distribution of datapoints\n", "- __categorical__: visualize a relationship involving categorical data (i.e. plot something _for each category_)\n", "\n", - "In 'technical' terms, when working with Seaborn functions, it is important to understand which level of Matplotlib object they operate, as `Axes-level` or `Figure-level`: \n", - "\n", - "- __axes-level__ functions plot data onto a single `matplotlib.pyplot.Axes` object and return the `Axes`\n", - "- __figure-level__ functions return a Seaborn object, `FacetGrid`, which is a `matplotlib.pyplot.Figure`\n", - "\n", - "_Remember the Matplotlib `Figure`, `axes` and `axis` anatomy explained in [visualization_01_matplotlib](visualization_01_matplotlib.ipynb)?_\n", - "\n", - "Each plot module has a single `Figure`-level function, which offers a unitary interface to its various `Axes`-level functions. The organization looks like this:" + "The organization looks like this:" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "![](../img/seaborn_overview_modules.png)" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, + "source": [ + "We first check out the top commands of each of the types of plots: `relplot`, `displot`, `catplot`, each returning a Matplotlib `Figure`:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ "### Figure level functions" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Let's start from: _What is the relation between Age and Fare?_" ] @@ -357,13 +233,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "# A relation between variables in a Pandas DataFrame -> `relplot`\n", @@ -372,10 +242,7 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Extend to: _Is the relation between Age and Fare different for people how survived?_" ] @@ -383,26 +250,16 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "# Include the 'survived' variable (column name) into the plot function to define the color\n", "sns.relplot(data=titanic, x=\"Age\", y=\"Fare\",\n", " hue=\"Survived\")" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Extend to: _Is the relation between Age and Fare different for people how survived and/or the gender of the passengers?_" ] @@ -410,16 +267,9 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "# Include the 'sex' variable (column name) into the plot function to split into subplots\n", "age_fare = sns.relplot(data=titanic, x=\"Age\", y=\"Fare\",\n", " hue=\"Survived\",\n", " col=\"Sex\")" @@ -427,24 +277,15 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "The function returns a Seaborn `FacetGrid`, which is directly related to a Matplotlib `Figure`:" + "The function returns a Seaborn `FacetGrid`, which is related to a Matplotlib `Figure`:" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "type(age_fare), type(age_fare.fig)" @@ -452,24 +293,15 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "In the last example, we are dealing here with 2 subplots. Hence, the `FacetGrid` consists of two Matplotlib `Axes`:" + "As we are dealing here with 2 subplots, the `FacetGrid` consists of two Matplotlib `Axes`:" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "age_fare.axes, type(age_fare.axes.flatten()[0])" @@ -477,20 +309,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Hence, we can still apply all the power of Matplotlib, but start from the convenience of Seaborn." ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", @@ -507,8 +333,7 @@ { "cell_type": "markdown", "metadata": { - "deletable": true, - "editable": true + "tags": [] }, "source": [ "### Axes level functions" @@ -516,10 +341,21 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, + "source": [ + "In 'technical' terms, when working with Seaborn functions, it is important to understand which level they operate, as `Axes-level` or `Figure-level`: \n", + "\n", + "- __axes-level__ functions plot data onto a single `matplotlib.pyplot.Axes` object and return the `Axes`\n", + "- __figure-level__ functions return a Seaborn object, `FacetGrid`, which is a `matplotlib.pyplot.Figure`\n", + "\n", + "Remember the Matplotlib `Figure`, `axes` and `axis` anatomy explained in [visualization_01_matplotlib](visualization_01_matplotlib.ipynb)? \n", + "\n", + "Each plot module has a single `Figure`-level function (top command in the scheme), which offers a unitary interface to its various `Axes`-level functions (." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ "We can ask the same question: _Is the relation between Age and Fare different for people how survived?_" ] @@ -527,30 +363,16 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "scatter_out = sns.scatterplot(data=titanic, \n", - " x=\"Age\", y=\"Fare\", \n", - " hue=\"Survived\")" + "scatter_out = sns.scatterplot(data=titanic, x=\"Age\", y=\"Fare\", hue=\"Survived\")" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "type(scatter_out)" @@ -558,20 +380,15 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "But we can't use the `col`/`row` options for faceting:" + "But we can't use the `col`/`row` options for facetting:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "deletable": true, - "editable": true, "tags": [] }, "outputs": [], @@ -581,10 +398,7 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "We can use these functions to create custom combinations of plots:" ] @@ -592,13 +406,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(10, 6))\n", @@ -608,12 +416,9 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "__Note__ Check the similarity with the _best of both worlds_ approach:\n", + "__Note!__ Check the similarity with the _best of both worlds_ approach:\n", "\n", "1. Prepare with Matplotlib\n", "2. Plot using Seaborn \n", @@ -622,10 +427,7 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", @@ -641,33 +443,68 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, + "source": [ + "### Summary statistics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Aggregations such as `count`, `mean` are embedded in Seaborn (similar to other 'Grammar of Graphics' packages such as ggplot in R and plotnine/altair in Python). We can do these operations directly on the original `titanic` data set in a single coding step:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.catplot(data=titanic, x=\"Survived\", col=\"Pclass\", \n", + " kind=\"count\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To use another statistical function to apply on each of the groups, use the `estimator`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.catplot(data=titanic, x=\"Sex\", y=\"Age\", col=\"Pclass\", kind=\"bar\", \n", + " estimator=np.mean)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ "## (OPTIONAL) exercises" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", - "**EXERCISE**\n", + "**EXERCISE 1**\n", "\n", "- Make a histogram of the age, split up in two subplots by the `Sex` of the passengers.\n", - "- Place both subplots underneath each other. \n", + "- Put both subplots underneath each other. \n", "- Use the `height` and `aspect` arguments of the plot function to adjust the size of the figure.\n", " \n", "
                                                                                                                                        Hints\n", "\n", "- When interested in a histogram, i.e. the distribution of data, use the `displot` module\n", - "- A split into subplots is requested using a variable of the DataFrame (faceting), so use the `Figure`-level function instead of the `Axes` level functions.\n", + "- A split into subplots is requested using a variable of the DataFrame (facetting), so use the `Figure`-level function instead of the `Axes` level functions.\n", "- Link a column name to the `row` argument for splitting into subplots row-wise.\n", "\n", "
                                                                                                                                        " @@ -677,12 +514,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -691,18 +525,15 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", - "**EXERCISE**\n", + "**EXERCISE 2**\n", "\n", "Make a violin plot showing the `Age` distribution for each `Sex` in each of the `Pclass` categories:\n", " \n", - "- Use a different color for the `Age`.\n", + "- Use a different color for the `Sex`.\n", "- Use the `Pclass` to make a plot for each of the classes along the `x-axis`\n", "- Check the behavior of the `split` argument and apply it to compare male/female.\n", "- Use the `sns.despine` function to remove the boundaries around the plot. \n", @@ -718,12 +549,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -734,12 +562,9 @@ "cell_type": "code", "execution_count": null, "metadata": { - "clear_cell": true, - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } + "tags": [ + "nbtutor-solution" + ] }, "outputs": [], "source": [ @@ -748,30 +573,21 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "## Some more Seaborn functionalities to remember" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "Whereas the `relplot`, `catplot` and `displot` represent the main components of the Seaborn library, more plotting functions are available. You can check the [gallery](https://seaborn.pydata.org/examples/index.html) yourself, but let's introduce a few of them:" + "Whereas the `relplot`, `catplot` and `displot` represent the main components of the Seaborn library, more useful functions are available. You can check the [gallery](https://seaborn.pydata.org/examples/index.html) yourself, but let's introduce a few rof them:" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__jointplot()__ and __pairplot()__\n", "\n", @@ -781,13 +597,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "# joined distribution plot\n", @@ -798,35 +608,22 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "sns.pairplot(data=titanic[[\"Age\", \"Fare\", \"Sex\"]], \n", - " hue=\"Sex\") # Also called scattermatrix plot" + "sns.pairplot(data=titanic[[\"Age\", \"Fare\", \"Sex\"]], hue=\"Sex\") # Also called scattermatrix plot" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__heatmap()__" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Plot rectangular data as a color-encoded matrix." ] @@ -834,13 +631,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "titanic_age_summary = titanic.pivot_table(columns=\"Pclass\", index=\"Sex\", \n", @@ -851,34 +642,22 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ - "sns.heatmap(titanic_age_summary, cmap=\"Reds\")" + "sns.heatmap(data=titanic_age_summary, cmap=\"Reds\")" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "__lmplot() regressions__" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "`Figure` level function to generate a regression model fit across a FacetGrid:" ] @@ -886,13 +665,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "deletable": true, - "editable": true, - "jupyter": { - "outputs_hidden": false - } - }, + "metadata": {}, "outputs": [], "source": [ "g = sns.lmplot(\n", @@ -903,20 +676,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "# Need more Seaborn inspiration? " + "# Need more Seaborn inspiration?" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", @@ -929,30 +696,21 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "# Recap: what is `tidy`?" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "If you're wondering what *tidy* data representations are, you can read the scientific paper by Hadley Wickham, http://vita.had.co.nz/papers/tidy-data.pdf. \n", "\n", @@ -961,10 +719,7 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "Compare:\n", "\n", @@ -995,20 +750,14 @@ }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ - "This is sometimes also referred as *short* versus *long* format for a specific variable... Seaborn (and other grammar of graphics libraries) work better on `tidy` (long format) data, as it better supports `groupby`-like transactions." + "This is sometimes also referred as *short* versus *long* format for a specific variable... Seaborn (and other grammar of graphics libraries) work better on `tidy` (long format) data, as it better supports `groupby`-like transactions!" ] }, { "cell_type": "markdown", - "metadata": { - "deletable": true, - "editable": true - }, + "metadata": {}, "source": [ "
                                                                                                                                        \n", "\n", @@ -1020,15 +769,17 @@ "- Each observation forms a row\n", "- Each type of observational unit forms a table.\n", "\n", - "
                                                                                                                                        \n", - "\n" + "
                                                                                                                                        " ] } ], "metadata": { "celltoolbar": "Nbtutor - export exercises", + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1042,7 +793,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "nav_menu": {}, "toc": { @@ -1060,6 +811,13 @@ "right": "1657px", "top": "106px", "width": "212px" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } } }, "nbformat": 4, diff --git a/notebooks/visualization_03_landscape.ipynb b/notebooks/visualization_03_landscape.ipynb index c3e9731..32d68b9 100644 --- a/notebooks/visualization_03_landscape.ipynb +++ b/notebooks/visualization_03_landscape.ipynb @@ -6,9 +6,6 @@ "source": [ "

                                                                                                                                        Visualization - Python's Visualization Landscape

                                                                                                                                        \n", "\n", - "> *DS Data manipulation, analysis and visualization in Python* \n", - "> *May/June, 2021*\n", - ">\n", "> *© 2021, Joris Van den Bossche and Stijn Van Hoey (, ). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n", "\n", "---" @@ -38,7 +35,7 @@ "To run the large data set section, additional package installations are required:\n", "\n", "```\n", - "conda install -c conda-forge datashader holoviews\n", + "conda install -c conda-forge datashader holoviews geoviews\n", "```\n", "\n", "To run the 'bokeh-pandas' backend:\n", @@ -46,7 +43,7 @@ "```\n", "conda install -c patrikhlobil pandas-bokeh\n", "```\n", - "---\n" + "---" ] }, { @@ -114,9 +111,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "metadata": {}, "outputs": [], "source": [ "with plt.style.context('seaborn-whitegrid'): # context manager for styling the figure\n", @@ -303,7 +298,7 @@ "| Works well with Pandas | Works well with Pandas |\n", "| Built on top of [Matplotlib](https://matplotlib.org/) | Built on top of [Vega-lite](https://vega.github.io/vega-lite/) |\n", "| Python-clone of the R package `ggplot` | Plot specification to define a vega-lite 'JSON string' |\n", - "| Static plots | Web/interactive plots |\n" + "| Static plots | Web/interactive plots |" ] }, { @@ -420,9 +415,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [] - }, + "metadata": {}, "outputs": [], "source": [ "import altair as alt" @@ -994,14 +987,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## You're data sets are HUGE?" + "## Your data sets are HUGE?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "When you're working with a lot of records, the visualization of the individual points does not always make sense as there are simply to many dots overlapping each other (check [this](https://bokeh.github.io/datashader-docs/user_guide/1_Plotting_Pitfalls.html) notebook for a more detailed explanation)." + "When you are working with a lot of records, the visualization of the individual points does not always make sense as there are simply to many dots overlapping each other (check [this](https://datashader.org/user_guide/Plotting_Pitfalls.html) notebook for a more detailed explanation)." ] }, { @@ -1016,21 +1009,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Working with such a data set on a local machine is not straightforward anymore, as this data set will consume a lot of memory to be handled by the default plotting libraries. Moreover, visualizing every single dot is not useful anymore at coarser zoom levels. " + "Working with such a data set on a local machine is not straightforward anymore, as this data set will consume a lot of memory to be handled by the default plotting libraries. Moreover, visualizing every single dot is not useful anymore at coarser zoom levels." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The package [datashader](https://bokeh.github.io/datashader-docs/index.html) provides a solution for this size of data sets and works together with other packages such as `Bokeh` and `Holoviews`." + "The package [datashader](https://datashader.org/) provides a solution for this size of data sets and works together with other packages such as `Bokeh` and `Holoviews`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The data from [the gull data set](https://zenodo.org/record/3541812#.XfZYcNko-V6) is downloaded and stored it in the `data` folder and is not part of the Github repository. For example, downloading the [2018 data set](https://zenodo.org/record/3541812/files/HG_OOSTENDE-acceleration-2018.csv?download=1) from Zenodo:" + "The data from [the gull data set](https://zenodo.org/record/3541812#.XfZYcNko-V6) is downloaded and stored it in the `data` folder and is not part of the Github repository. For example, after downloading the [2018 data set](https://zenodo.org/record/3541812/files/HG_OOSTENDE-gps-2018.csv?download=1) from Zenodo:" ] }, { @@ -1039,15 +1032,24 @@ "metadata": {}, "outputs": [], "source": [ - "import pandas as pd, holoviews as hv\n", + "import pandas as pd\n", + "import holoviews as hv\n", + "import hvplot.pandas \n", "from colorcet import fire\n", - "from datashader.utils import lnglat_to_meters\n", - "from holoviews.element.tiles import EsriImagery\n", - "from holoviews.operation.datashader import rasterize, shade\n", "\n", + "hv.extension('bokeh')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ "df = pd.read_csv('data/HG_OOSTENDE-gps-2018.csv', nrows=1_000_000, # for the live demo on my laptop, I just use 1_000_000 points\n", - " usecols=['location-long', 'location-lat', 'individual-local-identifier'])\n", - "df.loc[:,'location-long'], df.loc[:,'location-lat'] = lnglat_to_meters(df[\"location-long\"], df[\"location-lat\"])" + " usecols=['location-long', 'location-lat', \n", + " 'individual-local-identifier'])\n", + "df.head()" ] }, { @@ -1056,14 +1058,19 @@ "metadata": {}, "outputs": [], "source": [ - "hv.extension('bokeh')\n", - "\n", - "map_tiles = EsriImagery().opts(alpha=1.0, width=600, height=600, bgcolor='black')\n", - "points = hv.Points(df, ['location-long', 'location-lat'])\n", - "rasterized = shade(rasterize(points, x_sampling=1, y_sampling=1, \n", - " width=600, height=600), cmap=fire)\n", - "\n", - "map_tiles * rasterized" + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df.hvplot.points('location-long', 'location-lat', geo=True, tiles='ESRI', \n", + " datashade=True, aggregator='count', cmap=fire, project=True,\n", + " xlim=(-5, 5), ylim=(48, 53), frame_width=600)" ] }, { @@ -1178,8 +1185,11 @@ } ], "metadata": { + "jupytext": { + "formats": "ipynb,md:myst" + }, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1193,7 +1203,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": {