π 2023-05-21 β Session: Enhanced Python Data Analysis and Visualization
π 17:20β21:15
π·οΈ Labels: Python, Pandas, JSON, Data Visualization, Color Palette, Mapbox
π Project: Dev
β Priority: MEDIUM
Session Goal
The session aimed to enhance data analysis and visualization capabilities using Python, focusing on Pandas for data manipulation and JSON for data visualization.
Key Activities
- Data Analysis with Pandas: Implemented techniques to calculate percentages within grouped data using
groupbyandtransform. Excluded specific entries labeled βNO POSITIVOβ to refine vote calculations. - Aggregation Techniques: Utilized Pandas
aggfunction 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
colorsysandmatplotlib, including reverse order generation and interpolation between colors. - Mapbox Integration: Created and updated Mapbox style JSONs, modifying fill colors and uploading changes via API.
Achievements
- 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.
Pending Tasks
- Further refine JSON manipulation scripts to handle additional visualization parameters.
- Explore additional data visualization libraries for enhanced graphical outputs.