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Hexagon and Pie Chart Visualization with Bokeh

Overview

This project visualizes state-wise data using an interactive hexagon plot and a corresponding dynamic pie chart. The visualization updates in real-time based on user interaction. Selecting a state from the hexagon plot triggers a pie chart update to show the distribution of subcategories for the selected state.

Features

  • Hexagon Plot:

    • Interactive hexagons representing states.
    • State abbreviations displayed at hexagon centroids.
    • Dynamic tooltip displaying state names.

  • Dynamic Pie Chart:

    • Displays the subcategory distribution for a selected state.
    • Color-coded segments using the Pastel1 palette.
    • Percentage labels dynamically calculated and displayed for each segment.

Data Sources

1. Synthetic Data (synthetic_df)

The synthetic dataset represents state-wise subcategories and counts:

  • Columns:
    • state: Names of states.
    • subcategory: Categories (e.g., "Education", "Health").
    • Count: Numerical value indicating the count for each subcategory in a state.

2. Geographic Data (hex_df)

The geographic dataset includes state-wise coordinates:

  • Columns:
    • State: Names of states.
    • X: X-coordinates for hexagon centroids.
    • Y: Y-coordinates for hexagon centroids.
    • Abbreviation: Two-letter state abbreviations.

These datasets are merged in the visualization logic to link subcategory data with geographic coordinates for hexagon plotting.

Installation

Prerequisites

  • Python 3.7 or later
  • Required libraries: Bokeh, Pandas

Installation Steps

  1. Clone the repository: 
    git clone https://github.com/your-username/hexagon-pie-chart.git
cd hexagon-pie-chart