China Commodity Price Dashboard

A Streamlit web application to view and analyze commodity prices in China over the past 5 years. The app fetches real-time and historical data from Chinese commodity exchanges (SHFE and DCE) with prices displayed in RMB.

Features

• Interactive Price Charts: View time-series price data with interactive Plotly charts
• Multiple Commodities: Track copper, PVC, aluminum, steel, and zinc prices
• Price Comparisons: Compare multiple commodities on the same chart
• Statistics Panel: View key metrics including average, min/max prices, volatility, and percentage changes
• Trend Analysis: Moving averages and trend indicators
• Data Caching: Local caching to improve performance and reduce API calls
• RMB Pricing: All prices displayed in Chinese Yuan (RMB)

Supported Commodities

• Copper (cu) - Shanghai Futures Exchange (SHFE)
• Aluminum (al) - Shanghai Futures Exchange (SHFE)
• Zinc (zn) - Shanghai Futures Exchange (SHFE)
• Steel/Rebar (rb) - Shanghai Futures Exchange (SHFE)
• PVC (v) - Dalian Commodity Exchange (DCE)

Installation

1. Clone or download this repository

2. Install required dependencies:

pip install -r requirements.txt

Usage

1. Run the Streamlit application:

streamlit run app.py

2. The app will open in your default web browser

3. Use the sidebar to:

   • Select commodities to display
   • Choose date range (default: last 5 years)
   • Toggle statistics and trend analysis
   • Adjust moving average period

4. View interactive charts, statistics, and trend analysis in the main panel

Data Source

This application uses the akshare library to fetch commodity futures data from:

• Shanghai Futures Exchange (SHFE): For metals (copper, aluminum, zinc, steel)
• Dalian Commodity Exchange (DCE): For PVC

All prices are in RMB (Chinese Yuan) as provided by the exchanges.

Data Caching

The application caches fetched data locally in the data_cache/ directory to:

• Reduce API calls
• Improve load times
• Work offline with previously fetched data

Cache files are automatically created and reused when the same commodity and date range are requested.

Requirements

• Python 3.7+
• streamlit >= 1.28.0
• pandas >= 2.0.0
• plotly >= 5.17.0
• akshare >= 1.11.0
• requests >= 2.31.0

Notes

• Internet connection required for initial data fetching
• Data availability depends on akshare library and exchange data availability
• Some historical data may have limitations based on exchange records
• The app handles API rate limits and errors gracefully

License

This project is provided as-is for educational and informational purposes.