📅 2023-11-02 — Session: Developed Boxplot Visualization for Voting Patterns
🕒 02:30–02:55
🏷️ Labels: Python, Data Visualization, Seaborn, Matplotlib, Voting Analysis
📂 Project: Dev
⭐ Priority: MEDIUM
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.