Developed Modular Weighted Box Plot Functions in Python

• Day: 2023-08-18
• Time: 19:45 to 20:10
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Visualization, Modular Programming, Weighted Box Plot

Description

Session Goal

The session focused on enhancing data visualization techniques by developing modular functions for creating weighted box plots in Python.

Key Activities

• Created a step-by-step guide to generate weighted box plots using custom functions for weighted quartiles computation.
• Implemented a methodology for computing weighted quartiles by bins using Python, leveraging Pandas for data manipulation.
• Developed custom boxplot visualization techniques with Matplotlib, detailing visual elements.
• Implemented plot_scatter and plot_weighted_box functions for generating scatter and weighted box plots, respectively.
• Refactored the plot_scatter function to improve modularity and reusability by accepting parameters directly.
• Created a color dictionary for political groups to enhance plot aesthetics.
• Modularized the plot_weighted_box function by adding arguments for data input and binning, updating the code for weighted quantiles and box plot generation.

Achievements

• Successfully developed and refactored functions for creating modular and reusable data visualization components.
• Enhanced the flexibility and usability of plotting functions with parameterized inputs.

Pending Tasks

• Further testing and validation of the modular functions with diverse datasets to ensure robustness and accuracy in different scenarios.

Evidence

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• event_ids: []