Enhanced Python Data Analysis and Visualization

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📅 2023-05-21 — Session: Enhanced Python Data Analysis and Visualization

🕒 17:20–21:15
🏷️ Labels: Python, Pandas, JSON, Data Visualization, Color Palette, Mapbox
📂 Project: Dev

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 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.

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.

Graph View

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