📅 2025-10-23 — Session: Enhanced Email Data Processing and Analysis
🕒 17:30–17:55
🏷️ Labels: Email, EDA, Python, Data Processing, Pandas
📂 Project: Dev
Session Goal
The session aimed to improve email data processing and analysis through various Python script enhancements and algorithm improvements.
Key Activities
- Developed a Python script for filtering and analyzing email threads, focusing on excluding newsletters and spam and generating outputs for candidate threads, people involved, and digest inputs.
- Resolved a KeyError issue in pandas DataFrames during merges by implementing a robust code patch that ensures proper datetime handling and validation.
- Applied a patch for normalizing email addresses and filtering threads, emphasizing case normalization and self-exclusion.
- Enhanced the algorithm for identifying the ‘top person’ in email threads by prioritizing incoming messages.
- Improved exploratory data analysis (EDA) by adding non-invasive columns for identity recognition and thread statistics.
- Proposed enhancements to email data architecture through sidecars for tracking message interactions and normalizing contact information.
Achievements
- Successfully implemented email thread filtering and analysis scripts.
- Resolved pandas merge issues, preventing KeyErrors.
- Improved email normalization and filtering processes.
- Enhanced ‘top person’ selection algorithm in email threads.
- Advanced EDA capabilities with new column additions.
- Suggested architectural improvements for email data management.
Pending Tasks
- Further testing and validation of the enhanced email data architecture with sidecars.
- Continuous refinement of the ‘top person’ selection algorithm based on real-world data feedback.