Blood-Group-Analysis

🩸 Blood Type Distribution Dashboard

Project Overview

This dashboard provides an interactive visualization of global blood type distributions. It allows users to explore blood type prevalence across different countries and continents, offering insights into regional variations and identifying the rarest blood types in different geographical areas.

Features

• Interactive Visualizations: Explore blood type distributions through various chart types:
  • Choropleth maps showing global distribution of selected blood types
  • Bar charts comparing blood type prevalence across countries
  • Pie charts displaying blood type proportions by continent
  • Gauge charts highlighting the rarest blood types in selected regions

• Filtering Capabilities: Filter data by:

  • Specific blood type (O+, A+, B+, AB+, O-, A-, B-, AB-)
  • Continent (Africa, Asia, Europe, North America, South America, Oceania)

• Data Table: View the complete dataset with detailed information about blood type distributions, population statistics, and diversity indices.

Dataset

The dashboard uses a comprehensive dataset (processed_blood_type_data_with_continent.csv) containing:

• Blood type distribution percentages for 126 countries
• Population data
• Continental classifications
• Rarest blood type per country
• Blood type diversity index

Technical Implementation

This project is built using:

• Dash: Python framework for building web applications
• Plotly: Interactive visualization library
• Pandas: Data manipulation and analysis
• Bootstrap Components: For responsive UI design

The application features a clean, gradient-themed interface with a responsive layout that adapts to different screen sizes.

Key Insights

From the data visualizations, users can discover:

• AB- is the rarest blood type in most countries globally
• Blood type distributions vary significantly by continent, with distinct patterns in Asia, Europe, and Africa
• O+ is the most common blood type worldwide, with particularly high prevalence in South American countries
• European countries generally show higher blood type diversity compared to other regions

Getting Started

1. Ensure you have Python installed (3.7+ recommended)
2. Install required packages:

   pip install dash dash-bootstrap-components pandas plotly
   

3. Run the application:

   python app.py
   

4. Open your browser and navigate to http://127.0.0.1:8050/

Future Enhancements

Potential improvements for future versions:

• Add time-series data to track changes in blood type distributions
• Implement predictive analytics for blood supply management
• Add correlation analysis with genetic and demographic factors
• Create user authentication for personalized dashboards

License

This project is available for educational and research purposes.

Acknowledgments

Data sourced from global blood type distribution statistics and processed for visualization purposes.