GDP Growth Calculator Dashboard

A comprehensive Streamlit web application that calculates the required annual GDP growth rate for India to reach its target GDP by a specified year, with detailed demographic and economic analysis.

🎯 Purpose

This dashboard helps policymakers, economists, and researchers understand:

• The annual growth rate required for India to achieve its GDP targets
• Current vs. projected demographic trends
• Per capita GDP comparisons with other countries
• Population and dependency ratio analysis

📊 Features

1. GDP Growth Rate Calculator

• Calculates required annual growth rate using compound growth formula
• Compares with India's latest actual GDP growth rate
• Visual indicators (green/red) for performance comparison

2. Per Capita GDP Analysis

• Current vs. projected per capita GDP calculations
• Population projections using UN growth rates
• Country comparisons showing which nations have similar per capita GDP to India's projected values

3. Demographic Information

• Current Demographics: Population, median age, dependency ratio
• Population Categories: Young/Middle-aged/Aging population classification
• Dependency Levels: Low/Moderate/High dependency ratio interpretation
• Projected Demographics: Future population and median age projections

🏗️ Project Structure

thirtybyfortyseven/
├── growth_counter_dashboard.py    # Main Streamlit application
├── utils.py                       # Utility functions and API calls
├── requirements.txt               # Python dependencies
├── gdp-per-capita-by-country-2025.csv  # Country comparison data
└── README.md                      # This file

🔧 Technical Architecture

Main Application (growth_counter_dashboard.py)

• Streamlit Interface: User-friendly web interface
• Input Validation: Ensures positive values and future target years
• Error Handling: Graceful handling of API failures and calculation errors
• Responsive Layout: Multi-column design for better data presentation

Utility Functions (utils.py)

• API Integration: World Bank API for real-time economic and demographic data
• Data Processing: Population projections and demographic calculations
• Fallback Mechanisms: Reliable estimates when APIs are unavailable

📈 Data Sources

World Bank API Endpoints

• GDP Data: NY.GDP.MKTP.CD - India's current GDP in USD
• GDP Growth: NY.GDP.MKTP.KD.ZG - Latest GDP growth rate
• Population: SP.POP.TOTL - India's total population
• Dependency Ratio: SP.POP.DPND - Population dependency ratio
• Youth Population: SP.POP.0014.TO.ZS - Population under 14 (proxy for median age)

Local Data

• Country Comparisons: CSV file with GDP per capita data for 200+ countries
• Fallback Estimates: UN World Population Prospects data for median age

🧮 Key Calculations

Required Growth Rate

Growth Rate = 100 * (10^(log10(target_gdp / current_gdp) / years) - 1)

Population Projection

Uses UN growth rates:

• 2025: 1.0% annual growth
• 2030: 0.8% annual growth
• 2040: 0.5% annual growth
• Beyond: 0.3% annual growth

Median Age Estimation

Converts population under 14% to median age:

Estimated Median Age = 28.5 + (25 - under_14_percentage) * 0.3

Per Capita GDP

Per Capita GDP = Total GDP / Population

🚀 Installation & Setup

Prerequisites

• Python 3.8+
• pip package manager

Installation Steps

1. Clone or download the project

   git clone <repository-url>
   cd thirtybyfortyseven

2. Create virtual environment (recommended)

   python -m venv growth_dashboard_env
   source growth_dashboard_env/bin/activate  # On Windows: growth_dashboard_env\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Run the application

   streamlit run growth_counter_dashboard.py

5. Access the dashboard

   • Open your browser and go to http://localhost:8501
   • The dashboard will automatically open in your default browser

📋 Dependencies

Core Dependencies

• streamlit - Web application framework
• pandas - Data manipulation and analysis
• requests - HTTP library for API calls

🎮 Usage Guide

Basic Usage

1. Enter Current GDP: Use the default value or input India's current GDP in billion USD
2. Set Target GDP: Specify the desired GDP target in billion USD
3. Choose Target Year: Select the year by which you want to achieve the target
4. View Results: The dashboard will display:
   • Required annual growth rate
   • Comparison with current growth rate
   • Per capita GDP analysis
   • Demographic projections

Understanding the Results

• Green Indicators: Current performance meets or exceeds required growth
• Red Indicators: Current performance below required growth
• Population Categories:
  • Young Population: < 30 years median age
  • Middle-aged: 30-40 years median age
  • Aging Population: > 40 years median age
• Dependency Levels:
  • Low: < 50% dependency ratio
  • Moderate: 50-70% dependency ratio
  • High: > 70% dependency ratio

🔮 Future Enhancements

Potential Additions

• Interactive charts and visualizations
• Historical trend analysis
• Regional comparisons within India
• Sector-wise GDP analysis
• Export functionality for reports
• Mobile-responsive design improvements

Data Improvements

• Real-time median age data from World Bank
• More granular demographic projections
• Additional economic indicators
• International comparison enhancements

🤝 Contributing

Development Setup

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

Code Standards

• Follow PEP 8 style guidelines
• Add docstrings for new functions
• Include error handling
• Test API integrations

📄 License

This project is open source and available under the MIT License.

📞 Support

For questions, issues, or contributions:

• Create an issue in the repository
• Contact the development team
• Check the documentation for common solutions

🔗 Related Resources

• World Bank API Documentation
• UN World Population Prospects
• Streamlit Documentation
• Pandas Documentation

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Note: This dashboard is designed for educational and research purposes. For official economic analysis, please consult with professional economists and use official government data sources.