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.

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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.

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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.

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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