Enhanced Data Processing and Jupyter Notebook Automation

• Day: 2023-03-27
• Time: 17:10 to 18:05
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Data Processing, Jupyter, Automation, Python, Pandas

Description

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.

Evidence

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• event_ids: []