Enhanced ATE Line Plotting Functions in Python

📅 2023-02-22 — Session: Enhanced ATE Line Plotting Functions in Python

🕒 03:05–03:50
🏷️ Labels: Python, Data Visualization, ATE, Function Modification, Seaborn
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The goal of this session was to enhance Python functions for plotting Average Treatment Effect (ATE) lines, making them more flexible and dynamic for data visualization tasks.

Key Activities

• Defined a function to calculate and plot ATE_f using seaborn, focusing on box plot visualization.
• Developed a function to generate scatterplots with ATE lines, including error bars for standard deviations.
• Created the add_ATE_line function to integrate ATE lines into plots, with examples of usage.
• Modified the add_ATE_line function to accept arrays for plotting multiple ATE lines based on unique sweep parameter values.
• Enhanced the add_ATE_line function to support dynamic parameter sweeping, allowing flexible plotting based on various parameters.
• Updated the add_ATE_line function to include default parameters for plotting ATE values against a specified sweep parameter.

Achievements

• Successfully implemented and modified functions for plotting ATE lines, improving flexibility and usability for data visualization tasks in Python.

Pending Tasks

• Further testing and validation of the modified functions in diverse datasets to ensure robustness and accuracy.