📅 2023-08-19 — Session: Enhanced Voting Data Summary Table Generation

🕒 23:00–23:20
🏷️ Labels: Python, Data Analysis, Pandas, Voting Data, Summary Tables
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to develop a robust method for generating summary tables that display vote counts and percentages for different agrupaciones across various circuitos, facilitating comparison.

Key Activities

  • Generating Summary Tables: Initiated the creation of summary tables to display voting data.
  • Error Handling: Addressed errors in table generation by implementing a retry mechanism.
  • Dataframe Reconstruction: Identified the need to reconstruct the data dataframe to ensure accurate table generation.
  • Data Grouping and Pivoting: Utilized Python’s pandas library to group and pivot data effectively, focusing on sections, circuits, and groupings.
  • Displaying Tables: Adjusted data processing to include distrito_nombre for enhanced grouping and summarization.
  • Correcting Iteration Methods: Improved DataFrame iteration by switching from iteritems() to iterrows().
  • Formatting and Display Adjustments: Enhanced table readability by setting titles and adjusting percentage display.

Achievements

  • Successfully generated and displayed summary tables for voting data, incorporating error handling and data reconstruction.
  • Improved data manipulation techniques using pandas for more accurate and readable outputs.

Pending Tasks

  • Further optimize the data processing pipeline for efficiency and scalability.
  • Investigate additional error handling strategies to prevent future execution issues.