Enhanced CSV processing and DataFrame comparison

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📅 2023-02-13 — Session: Enhanced CSV processing and DataFrame comparison

🕒 20:40–22:30
🏷️ Labels: Python, Dataframe, CSV, Performance, Error Handling
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal: The session aimed to enhance Python scripts for CSV processing and DataFrame comparison, focusing on performance measurement and error handling.

Key Activities:

  • Utilized %timeit and %time magic commands in IPython Notebook to measure execution time for code snippets.
  • Modified CSV processing code to handle OSError by checking and creating output directories as needed.
  • Implemented file copying techniques using Python’s os, shutil, and glob libraries.
  • Explored the replace method in pandas DataFrame for value mapping without introducing NaN values.
  • Developed methods to compare DataFrames and count column differences, highlighting changes and common differences.
  • Created code snippets to identify and print differences between DataFrames, excluding NaN values.

Achievements:

  • Successfully integrated performance profiling into CSV processing scripts.
  • Improved error handling in file operations.
  • Enhanced DataFrame comparison techniques to provide more insightful data analysis.

Pending Tasks:

  • Further optimize the CSV processing script for larger datasets.
  • Explore additional methods for DataFrame comparison to improve accuracy and performance.

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