📅 2023-11-02 — Session: Enhanced Data Visualization Techniques in Python
🕒 03:00–03:30
🏷️ Labels: Python, Matplotlib, Seaborn, Data Visualization, Boxplot, Annotations
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to enhance data visualization techniques using Python, specifically focusing on Matplotlib and Seaborn libraries.
Key Activities
- Customized the placement of boxplots in Matplotlib to overcome Seaborn’s limitations, including handling missing data points.
- Implemented conditional x-axis ticks and labels for subplots in Matplotlib, allowing for dynamic adjustments based on row indices.
- Added annotations and epigraphs to graphs to highlight voting trends, particularly in the AMBA region, using Matplotlib and Seaborn.
- Developed a structured epigraph template for analyzing vote distributions by income and party in Argentina, emphasizing geographical and socioeconomic patterns.
- Adjusted graph sizes and spacing using Matplotlib and Seaborn to improve data visualization aesthetics.
Achievements
- Successfully implemented advanced customization of boxplots and subplots in Matplotlib.
- Enhanced graph annotation techniques to provide clearer insights into voting data.
- Improved overall graph presentation and layout for better visual communication.
Pending Tasks
- Further exploration of advanced visualization techniques for more complex datasets.