Data Analysis and Code Refactoring for Vote Differences

📅 2023-08-21 — Session: Data Analysis and Code Refactoring for Vote Differences

🕒 00:00–00:40
🏷️ Labels: Data_Analysis, Python, Code_Refactoring, Geojson, Error_Correction
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to calculate vote differences between GB and IN, separate data based on these differences, correct data processing errors, and refactor code for GeoJSON processing.

Key Activities

• Vote Differences Calculation: Implemented a method to calculate vote differences between GB and IN for each ‘lista’ and place by pivoting a table and creating a new column.
• Data Separation: Developed a method to separate rows into two lists based on positive and negative GB-IN values, including a step-by-step implementation.
• Error Correction Strategy: Outlined a strategy for correcting data processing errors by separating rows based on GB-IN values and accumulating absolute differences.
• Context Request: Requested additional context on the diffs_sorted dataframe to proceed with accurate data analysis.
• Code Refactoring: Improved code structure by refactoring redundant code into reusable functions, ensuring explicit imports, and adding descriptive comments for processing and saving data to GeoJSON format.

Achievements

• Successfully calculated vote differences and separated data based on these values.
• Developed a strategy for error correction in data processing.
• Refactored code for better reusability and clarity in GeoJSON data processing.

Pending Tasks

• Provide additional context on the diffs_sorted dataframe to complete data analysis.