📅 2023-08-22 — Session: Enhanced Python data processing and visualization
🕒 19:30–21:10
🏷️ Labels: Python, Data Processing, Visualization, Elections, Code Optimization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal:
The session aimed to enhance Python data processing capabilities, handle specific error cases, and improve visualization techniques for electoral data analysis.
Key Activities:
- Handling Empty Arrays in Quantile Computation: A solution was implemented to address errors arising from computing quantiles with empty arrays by adding checks for non-empty arrays before performing calculations.
- Modularizing Code for Data Processing: The Python code was optimized by modularizing repeated code into functions and using loops for combinations, specifically for saving data in GeoJSON format.
- Análisis de Agrupaciones Electorales por Región: Developed a Python procedure to analyze electoral groupings by region and section, calculating vote percentages for elections in 2019 and 2023.
- Generación de Presentaciones en Markdown: Created Python scripts to generate Markdown presentations with tables of votes and percentages organized by region and section for the 2019 and 2023 elections.
- Visualización de Votos y Porcentajes por Sección: Implemented a Python script to visualize votes and percentages by section, filtering data to highlight unique combinations and relevant information.
Achievements:
- Successfully handled errors related to empty arrays in quantile calculations.
- Improved code structure and efficiency through modularization.
- Developed comprehensive data analysis and visualization tools for electoral data.
Pending Tasks:
- Further testing and validation of the visualization scripts to ensure accuracy and reliability.
- Exploration of additional data sets for broader analysis.