Resolved Plotting and Data Processing Issues

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📅 2023-11-01 — Session: Resolved Plotting and Data Processing Issues

🕒 15:25–16:30
🏷️ Labels: Python, Data Visualization, Debugging, Code Optimization, Data Processing
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary objective of this session was to address and fix issues related to plotting functions and data processing in Python, focusing on group indexing in plotting, debugging Matplotlib scatter plots, and optimizing data processing code.

Key Activities

  • Fixing Group Indexing in Plotting Function: Adapted code to handle group indexing by summing votos_cantidad for each group, enhancing visual representation.
  • Debugging Matplotlib Scatter Plot: Conducted a systematic debugging process to resolve marker size issues, ensuring proper value checks and parameter adjustments.
  • Resolving Warnings in Scatter Function: Addressed warnings related to keyword arguments and array comparisons in Python plotting.
  • Streamlining Python Code: Reorganized data processing code into clear sections for aggregation, verification, merging, and analysis, improving readability and maintenance.
  • Electoral Data Analysis in Markdown: Provided a detailed guide for electoral data analysis, covering data preparation, verification, merging, and specific vote fraction calculations.

Achievements

  • Successfully fixed group indexing and marker size issues in plotting functions.
  • Resolved warnings in Python code, ensuring more robust and error-free execution.
  • Enhanced data processing code structure for better efficiency and maintainability.

Pending Tasks

  • Further testing of the optimized data processing code to ensure stability across different datasets.
  • Additional enhancements in plotting functions for more complex visualizations if needed.

Graph View

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