From 5d9cee913cd5ddaa12c9e2d1ed12a801945c331d Mon Sep 17 00:00:00 2001 From: Colin Harrison Date: Fri, 1 Aug 2025 19:14:40 -0700 Subject: [PATCH] Add jail workflows operator documentation --- ...perator-property-edit-frame.component.html | 614 ++++++++++++++++++ 1 file changed, 614 insertions(+) diff --git a/core/gui/src/app/workspace/component/property-editor/operator-property-edit-frame/operator-property-edit-frame.component.html b/core/gui/src/app/workspace/component/property-editor/operator-property-edit-frame/operator-property-edit-frame.component.html index 1f2c2963f29..5c4c9d1fec7 100644 --- a/core/gui/src/app/workspace/component/property-editor/operator-property-edit-frame/operator-property-edit-frame.component.html +++ b/core/gui/src/app/workspace/component/property-editor/operator-property-edit-frame/operator-property-edit-frame.component.html @@ -47,6 +47,150 @@ nzTheme="outline" [nzPopoverContent]="PythonLambdaPopContent" class="question-circle-button"> + + + + + + + + + + + + + + + + You can add a new column by: @@ -80,6 +224,476 @@
  • Typing in the expression as True if tuple_["Unit Price"] > 500 else False
    •  + + You can cast the type of existing columns by: + + Available data types include: + +
    + Example: Convert a text column "Age" containing numbers to integer type
    + Operations: + +
    + Note: Type casting may fail if the source data cannot be converted to the target type (e.g., + converting "abc" to integer).
    + Ensure your data is compatible with the target type. +     + + + You can load data from a CSV file by: + + File format options: + +
    + Example: Load a CSV file with headers and comma-separated values
    + Operations: + +
    + Note: Make sure your CSV file is properly formatted and accessible. Large files may take longer to + process. +     + + + You can select and reorder columns by: + + Drop Option: + + Column operations: + +
    + Example: Keep only "state", "year", and "custody_tot" columns and rename "custody_tot" to "Total"
    + Operations: + +     + + + You can join two datasets by: + + Join types explained: + +
    + Example: Join annual and quarterly prison data on custody_tot values using inner join
    + Operations: + +
    + Note: Make sure the join attributes have compatible data types and meaningful matching values for + the best results. +     + + + You can filter rows based on conditions by: + + Available operators include: + +
    + Example: Filter to show only data for Alabama
    + Operations: + +
    + Multiple Conditions: Use the Predicates section to add multiple filter conditions.
    + All predicates are combined with OR logic - a row passes through if it matches + ANY of the conditions. +     + + + You can perform aggregations by: + + Available aggregation functions: + +
    + Example: Calculate total mortality and average custody statistics
    + Operations: + +
    + Multiple Aggregations: You can add multiple aggregation functions to calculate different + statistics.
    + Each aggregation will create a new column in the output with the specified result attribute name. +     + + + You can sort your data by: + + Domain configuration: + +
    + Example: Sort data by year from 2013 to 2020
    + Operations: + +
    +     + + You can filter data using regular expressions by: + + Common regex patterns: + +
    + Example: Keep only end-of-year data (dates containing "15-31")
    + Operations: + +
    +     + + + You can render HTML content by: + + +
    + Example: Display formatted mortality statistics in HTML
    + Operations: + +
    +     + + + You can create custom R functions by: + + Configuration options: + +
    + Example: Process mortality data with custom R calculations
    + Operations: + +
    + R Code Editor: Write any R code to transform, analyze, or create new data columns.
    +     + + + You can create custom Python functions by: + + Configuration options: + +
    + Example: Process mortality data and create new calculated columns
    + Operations: + +
    + Python Code Editor: Write any Python code to transform, analyze, or create new data columns.
    +     + + + You can create dumbbell plots by: + + Plot configuration: + +
    + Example: Compare confidence intervals across state boundaries
    + Operations: + +
    + Use Case: Dumbbell plots are ideal for comparing ranges, confidence intervals, or before/after + values.
    + Legend: Enable "Show Legend" to help users understand different elements in the plot. +     + + + You can create nested tables by: + + Nested table structure: + +
    + Example: Create nested table with demographics and statistics sections
    + Operations: + +     + + + You can create line charts by: + + Chart configuration: + +
    + Example: Plot death rates over time by age group
    + Operations: + +     + + + You can sort your data by: + +
    + Example: Sort by year (newest first)
    + +     + + + You can create bar charts by: + + Chart configuration: + +
    + Example: Compare regional percentages with a bar chart
    + Operations: + +