📅 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
datadataframe 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_nombrefor enhanced grouping and summarization. - Correcting Iteration Methods: Improved DataFrame iteration by switching from
iteritems()toiterrows(). - 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.