📅 2023-03-27 — Session: Enhanced Data Processing and Jupyter Notebook Automation

🕒 17:10–18:05
🏷️ Labels: Data Processing, Jupyter, Automation, Python, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to improve data processing capabilities and automate the conversion of Jupyter notebooks into different formats.

Key Activities

  • Code Comparison: Reviewed and compared old and new versions of data processing code, focusing on enhancements such as merging with country shapes and creating unique identifiers.
  • DataFrame Modifications: Implemented modifications to DataFrames using Pandas and GeoPandas, including exploding geographical columns and adding new columns like even_split_totalamt.
  • Data Cleaning: Applied methods to clean data by removing commas and converting strings to floats.
  • Jupyter Notebook Conversion: Automated the conversion of Jupyter notebooks to PDF and HTML formats using command-line tools like jupyter nbconvert and find, ensuring checkpoint files were excluded.
  • Command History and Execution: Utilized Unix command line tools to search command history and execute batch conversions using the -exec option.

Achievements

  • Successfully enhanced data processing scripts for better functionality and integration.
  • Automated the conversion of Jupyter notebooks, improving workflow efficiency.

Pending Tasks

  • Review and optimize the automation scripts for further efficiency gains.