National Economic Data Analysis Platform (NEDAP)

A comprehensive economic data assessment and prediction system for researchers, economists, and policy makers.

Features • Quick Start • Architecture • API • Contributing • License

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🌐 Language | 语言

English | 中文

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📊 Features

Core Functionality

Feature	Description
📈 Indicator Inference	Input economic indicators to automatically infer related metrics (e.g., fiscal deficit rate, debt ratio)
🔮 Teaching Models	Preset economic models (Phillips Curve, Okun's Law, Cobb-Douglas) for educational purposes
🗺️ Regional Analysis	North-South, East-West economic comparison and convergence testing
📥 Data Collection	Automated scraping from official sources (Ministry of Finance, NBS, Customs, PBC)
📊 Visualization	Interactive charts and dashboards with Plotly

Data Sources

Source	Code	Description
Ministry of Finance	mof	Fiscal revenue, expenditure, debt data
National Bureau of Statistics	nbs	GDP, CPI, employment, population
Customs Administration	customs	Import/export trade data
People's Bank of China	pbc	Monetary supply, interest rates

Inference Indicators

• Fiscal: fiscal_deficit, deficit_rate, debt_ratio, tax_revenue
• Regional: gini_coefficient, theil_index, convergence_coefficient
• Income: urban_rural_ratio, gini_urban, labor_share
• Industrial: industrial_upgrading_index, hoffmann_coefficient
• Innovation: rd_intensity, patent_output, innovation_efficiency

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🚀 Quick Start

Prerequisites

• Python 3.10+
• Git

Installation

# Clone the repository
git clone https://github.com/your-repo/national_stats.git
cd national_stats

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/Mac
# or
venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

Running the Application

# Start backend (Terminal 1)
uvicorn backend.main:app --reload --port 8001

# Start frontend (Terminal 2)
streamlit run app/streamlit_app.py

Access Points

Service	URL
Frontend	http://localhost:8501
API Docs	http://localhost:8001/docs
ReDoc	http://localhost:8001/redoc
Health Check	http://localhost:8001/health

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🏗️ Architecture

national_stats/
├── app/                        # Streamlit Frontend
│   ├── streamlit_app.py        # Main application
│   └── i18n.py                 # Internationalization
│
├── backend/                    # FastAPI Backend
│   ├── main.py                 # Application entry
│   ├── core/
│   │   └── config.py           # Configuration
│   ├── models/
│   │   ├── database.py         # SQLAlchemy models
│   │   └── schemas.py          # Pydantic schemas
│   ├── api/routes/
│   │   ├── data.py             # Data management
│   │   ├── inference.py        # Indicator inference
│   │   └── scrape.py           # Web scraping
│   └── services/
│       └── scraper/            # Scraper implementations
│
├── core/                       # Core Analysis Models
│   └── models/
│       ├── fiscal.py          # Fiscal analysis
│       ├── regional.py        # Regional analysis
│       ├── income.py          # Income distribution
│       ├── industrial.py      # Industrial structure
│       └── innovation.py      # Innovation metrics
│
├── tests/                      # Test Suite
├── docs/                       # Documentation
└── scripts/                    # Utility Scripts

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📡 API Documentation

Main Endpoints

Method	Endpoint	Description
GET	/api/v1/indicators/	List all indicators
POST	/api/v1/inference/calculate	Calculate indicator inference
GET	/api/v1/inference/available_indicators	Get available indicators
POST	/api/v1/scrape/	Scrape data from source
GET	/api/v1/scrape/status	Get scraper status
GET	/health	Health check

Example Request

curl -X POST http://localhost:8001/api/v1/inference/calculate \
  -H "Content-Type: application/json" \
  -d '{
    "input_indicators": {
      "expenditure": 250000,
      "revenue": 200000,
      "gdp": 1200000
    },
    "target_indicator": "deficit_rate",
    "method": "linear"
  }'

Example Response

{
  "predicted_value": 4.1667,
  "predicted_unit": "%",
  "confidence_interval": [3.9583, 4.375],
  "method_used": "linear",
  "input_indicators": {
    "expenditure": 250000.0,
    "revenue": 200000.0,
    "gdp": 1200000.0
  },
  "target_indicator": "deficit_rate"
}

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🧪 Testing

# Run all tests
pytest tests/ -v

# Run with coverage
pytest tests/ --cov=backend --cov-report=html

# Run specific test file
pytest tests/test_fiscal.py -v

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🔧 Configuration

Environment variables (optional):

Variable	Default	Description
DATABASE_URL	sqlite:///./national_stats.db	Database connection
API_PORT	8001	Backend port
CORS_ORIGINS	*	CORS allowed origins

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👥 Contributing

Contributions are welcome! Please read our Contributing Guide before submitting PRs.

Development Setup

# Install dev dependencies
pip install -r requirements.txt
pip install pytest pytest-cov black flake8

# Run linting
black backend/ app/ tests/

# Run tests
pytest tests/ -v

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📄 License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

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🙏 Acknowledgments

• Official data sources: Ministry of Finance, National Bureau of Statistics, Customs Administration, People's Bank of China
• Built with: FastAPI, Streamlit, Plotly, SQLAlchemy, Pandas, NumPy

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📬 Contact

• Issue Tracker: https://github.com/your-repo/national_stats/issues
• Email: contact@example.com

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National Economic Data Analysis Platform
_{Built for economists, researchers, and policy makers}