📅 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 nbconvertandfind, ensuring checkpoint files were excluded. - Command History and Execution: Utilized Unix command line tools to search command history and execute batch conversions using the
-execoption.
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.