Enhanced Python Data Analysis and Visualization

Day: 2023-05-21
Time: 17:20 to 21:15
Project: Dev
Workspace: WP 2: Operational
Status: Completed
Priority: MEDIUM
Assignee: Matías Nehuen Iglesias
Tags: Python, Pandas, JSON, Data Visualization, Color Palette, Mapbox

Description

The session aimed to enhance data analysis and visualization capabilities using Python, focusing on Pandas for data manipulation and JSON for data visualization.

Data Analysis with Pandas: Implemented techniques to calculate percentages within grouped data using groupby and transform. Excluded specific entries labeled ‘NO POSITIVO’ to refine vote calculations.
Aggregation Techniques: Utilized Pandas agg function to aggregate votes and identify unique forces.
JSON Manipulation: Extracted and modified JSON objects to update visualization properties, specifically targeting fill colors in Mapbox styles.
Color Palette Generation: Developed Python functions to generate color palettes using colorsys and [[matplotlib]], including reverse order generation and interpolation between colors.
Mapbox Integration: Created and updated Mapbox style JSONs, modifying fill colors and uploading changes via API.

Successfully calculated and aggregated data using Pandas, enhancing data analysis workflows.
Developed robust color palette generation scripts for improved data visualization.
Implemented JSON manipulation techniques for dynamic visualization updates in Mapbox.

Further refine JSON manipulation scripts to handle additional visualization parameters.
Explore additional data visualization libraries for enhanced graphical outputs.

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