Generated and Adjusted Voting Data Summary Tables

📅 2023-08-19 — Session: Generated and Adjusted Voting Data Summary Tables

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

Session Goal:

The primary goal of this session was to generate and adjust summary tables for voting data, focusing on vote counts and percentages across different agrupaciones and circuitos.

Key Activities:

• Generating Summary Table: Steps were outlined to create a summary table for voting data, displaying vote counts and percentages for various agrupaciones in different circuitos.
• Error Handling: Addressed an error encountered during the execution of summary table generation, suggesting a retry for displaying results.
• Dataframe Reconstruction: Identified an oversight in the data dataframe, leading to a reconstruction before generating summary tables.
• Data Grouping and Pivoting: Utilized Python’s pandas library to group and pivot dataframes for analyzing voting data by sections, circuits, and groupings.
• Data Display Adjustment: Adjusted data processing to include distrito_nombre in the grouping and summarization, displaying tables for largest district sections.
• Data Iteration Correction: Corrected the method of iterating over DataFrames by switching from iteritems() to iterrows().
• Data Formatting Adjustment: Provided a Python code snippet to format summary tables, setting table titles based on single-value variables and adjusting percentage values for readability.

Achievements:

Successfully generated and adjusted summary tables for voting data, incorporating error handling, data reconstruction, and enhanced data formatting.

Pending Tasks:

• Further optimization of data processing methods for larger datasets.
• Implementation of automated error handling mechanisms for future tasks.