commit-live-students · aksmungekar · Nov 17, 2018 · Nov 17, 2018 · Nov 17, 2018 · Nov 17, 2018
diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
diff --git a/q01_calculate_statistics/__pycache__/__init__.cpython-36.pyc b/q01_calculate_statistics/__pycache__/__init__.cpython-36.pyc
diff --git a/q01_calculate_statistics/__pycache__/build.cpython-36.pyc b/q01_calculate_statistics/__pycache__/build.cpython-36.pyc
diff --git a/q01_calculate_statistics/build.py b/q01_calculate_statistics/build.py
@@ -1,11 +1,19 @@
+# %load q01_calculate_statistics/build.py
 # Default Imports
 import numpy as np
 import pandas as pd
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
-sale_price = data.loc[:, "SalePrice"]
+sale_price = data.loc[:, 'SalePrice']
+
+def calculate_statistics():
+    Mean=sale_price.mean()
+    Median=sale_price.median()
+    Mode=sale_price.mode()[0]
+    return Mean,Median,Mode
+
+calculate_statistics()
+
 
 
-# Return mean,median & mode for the SalePrice Column
-# Write your code here
 
diff --git a/q01_calculate_statistics/tests/__pycache__/__init__.cpython-36.pyc b/q01_calculate_statistics/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q01_calculate_statistics/tests/__pycache__/test_q01_plot.cpython-36.pyc b/q01_calculate_statistics/tests/__pycache__/test_q01_plot.cpython-36.pyc
diff --git a/q02_plot/__pycache__/__init__.cpython-36.pyc b/q02_plot/__pycache__/__init__.cpython-36.pyc
diff --git a/q02_plot/__pycache__/build.cpython-36.pyc b/q02_plot/__pycache__/build.cpython-36.pyc
diff --git a/q02_plot/build.py b/q02_plot/build.py
@@ -1,3 +1,4 @@
+# %load q02_plot/build.py
 # Default Imports
 import pandas as pd
 import matplotlib.pyplot as plt
@@ -7,6 +8,19 @@
 dataframe = pd.read_csv('data/house_prices_multivariate.csv')
 sale_price = dataframe.loc[:, 'SalePrice']
 
+def plot():
+    dataframe = pd.read_csv('data/house_prices_multivariate.csv')
+    sale_price = dataframe.loc[:, 'SalePrice']
+    plt.hist(sale_price, bins=60)
+    plt.axvline(x=sale_price.mean(),color='red',linestyle='--',label='Mean')
+    plt.axvline(x=sale_price.median(),color='black',linestyle='--',label='Median')
+    plt.axvline(x=sale_price.mode()[0],color='orange',linestyle='--',label='Mode')
+
+    plt.legend(loc=0)
+
+    plt.show()
+
+plot()
+
 
-# Draw the plot for the mean, median and mode for the dataset
 
diff --git a/q02_plot/tests/__pycache__/__init__.cpython-36.pyc b/q02_plot/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q02_plot/tests/__pycache__/test_q02_plot.cpython-36.pyc b/q02_plot/tests/__pycache__/test_q02_plot.cpython-36.pyc
diff --git a/q03_pearson_correlation/__pycache__/__init__.cpython-36.pyc b/q03_pearson_correlation/__pycache__/__init__.cpython-36.pyc
diff --git a/q03_pearson_correlation/__pycache__/build.cpython-36.pyc b/q03_pearson_correlation/__pycache__/build.cpython-36.pyc
diff --git a/q03_pearson_correlation/build.py b/q03_pearson_correlation/build.py
@@ -1,9 +1,14 @@
+# %load q03_pearson_correlation/build.py
 # Default Imports
 import pandas as pd
+from scipy.stats.stats import pearsonr
+
+
+def correlation():
+    dataframe_1 = pd.read_csv('data/house_prices_multivariate.csv')
+    dataframe_2 = pd.read_csv('data/house_prices_copy.csv')
+    return pearsonr(dataframe_1.SalePrice, dataframe_2.SalePrice)[0]
+
 
-dataframe_1 = pd.read_csv('data/house_prices_multivariate.csv')
-dataframe_2 = pd.read_csv('data/house_prices_copy.csv')
 
 
-# Return the correlation value between the SalePrice column for the two loaded datasets
-# Your code here
diff --git a/q03_pearson_correlation/tests/__pycache__/__init__.cpython-36.pyc b/q03_pearson_correlation/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q03_pearson_correlation/tests/__pycache__/test_q03_correlation.cpython-36.pyc b/q03_pearson_correlation/tests/__pycache__/test_q03_correlation.cpython-36.pyc
diff --git a/q04_spearman_correlation/__pycache__/__init__.cpython-36.pyc b/q04_spearman_correlation/__pycache__/__init__.cpython-36.pyc
diff --git a/q04_spearman_correlation/__pycache__/build.cpython-36.pyc b/q04_spearman_correlation/__pycache__/build.cpython-36.pyc
diff --git a/q04_spearman_correlation/build.py b/q04_spearman_correlation/build.py
@@ -1,8 +1,16 @@
+# %load q04_spearman_correlation/build.py
 # Default Import
 import pandas as pd
+from scipy.stats import spearmanr
+
+
+def spearman_correlation():
+    dataframe_1 = pd.read_csv('data/house_prices_multivariate.csv')
+    dataframe_2 = pd.read_csv('data/house_prices_copy.csv')
+    return spearmanr(dataframe_1.SalePrice,dataframe_2.SalePrice)[0]
+
+
+
 
-dataframe_1 = pd.read_csv('data/house_prices_multivariate.csv')
-dataframe_2 = pd.read_csv('data/house_prices_copy.csv')
 
-# Your code here
 
diff --git a/q04_spearman_correlation/tests/__pycache__/__init__.cpython-36.pyc b/q04_spearman_correlation/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q04_spearman_correlation/tests/__pycache__/test_q04_spearman_correlation.cpython-36.pyc b/q04_spearman_correlation/tests/__pycache__/test_q04_spearman_correlation.cpython-36.pyc