Email Data Processing and Analysis

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📅 2025-02-17 — Session: Email Data Processing and Analysis

🕒 11:55–12:30
🏷️ Labels: Email Analysis, Data Cleaning, Python, Networkx, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to enhance the processing and analysis of email data using Python, focusing on timestamp handling and network analysis.

Key Activities

  • Developed one-liner computations using Pandas and NetworkX for email network analysis, including classifying communication types and identifying active users.
  • Parsed and standardized email date formats to UTC-3 using a Python script.
  • Streamlined DataFrame date cleaning in Python, improving readability and performance.
  • Fixed issues with naive datetime objects by converting them to timezone-aware objects in Argentina local time.
  • Resolved a NameError related to the missing pytz library by adding the necessary import.
  • Handled invalid email date formats using dateutil.parser for robust timestamp parsing.

Achievements

  • Successfully implemented solutions for email data cleaning and analysis, improving data quality and analytical capabilities.

Pending Tasks

  • Further testing and validation of the implemented scripts in different datasets.
  • Integration of these solutions into a larger data processing pipeline.

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