Enhanced Email Data Processing with Python

1 min read

📅 2025-02-17 — Session: Enhanced Email Data Processing with Python

🕒 12:00–12:30
🏷️ Labels: Python, Data Cleaning, Email Processing, Network Analysis
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary objective of this session was to enhance the processing of email data by implementing efficient data cleaning and analysis techniques using Python.

Key Activities

  • Developed one-liner computations using Pandas and NetworkX to analyze email networks, focusing on communication classification, active user identification, and detecting automated emails.
  • Implemented a Python script to clean and standardize messy email timestamps to UTC-3, improving data consistency.
  • Streamlined DataFrame date cleaning processes by optimizing Python code to eliminate unnecessary variable assignments.
  • Resolved issues with naive datetime objects by converting them to timezone-aware objects in Argentina local time.
  • Fixed a NameError related to the missing pytz library by adding the necessary import statement for time zone handling.
  • Addressed invalid email date formats using dateutil.parser to ensure robust timestamp parsing and conversion.

Achievements

  • Successfully enhanced the email data processing pipeline with improved data cleaning and analysis techniques.
  • Resolved key errors and optimized code for better performance and accuracy.

Pending Tasks

  • Further testing of the implemented solutions in a production environment to ensure robustness and reliability.

Graph View

Backlinks