Developed Boxplot Visualization for Voting Patterns

• Day: 2023-11-02
• Time: 02:30 to 02:55
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Visualization, Seaborn, Matplotlib, Voting Analysis

Description

Session Goal

The session aimed to develop and refine a set of Python scripts to create visualizations comparing voting patterns across different agglomerates, specifically focusing on agglomerates 32 and 33.

Key Activities

• Developed Python scripts using Seaborn and Matplotlib to visualize voting patterns in a 2x3 grid of boxplots.
• Modified code to fix indentation issues and ensure accurate plotting within loop structures.
• Customized boxplots to include Spanish labels, adjusted legends, and ensured x-axis tick labels displayed correctly from 0 to 9.
• Addressed legend issues by creating custom handles using Matplotlib patches.

Achievements

• Successfully created visualizations that compare voting patterns between specific agglomerates and others, with clear differentiation by income levels.
• Solved technical issues related to code execution and visualization accuracy.

Pending Tasks

• Further refinement of the visualization scripts to enhance clarity and insight extraction for future analyses.

Evidence

• source_file=2023-11-02.sessions.jsonl, line_number=2, event_count=0, session_id=0882ad838df47fdce57bf0551f5bb6160096e7b7b2edf1b4c47dea749066724f
• event_ids: []