Weather Trend Analyzer

This dashboard enables you to analyze historical weather patterns using hourly and daily data from the Open-Meteo historical weather API.

Features

• Visualize temperature, humidity, precipitation, wind, and cloud cover trends.
• Perform correlation and seasonal decomposition analyses.
• Cluster similar weather patterns.
• Interactive visualizations with Plotly and Streamlit.
• Integrated Q&A on weather data using a retrieval-augmented generation (RAG) module.

Prerequisites

• Python 3.7 or later
• Required packages (see requirements.txt)
• A valid Google Maps API Key to resolve location names.
• Internet access to fetch weather data from the Open-Meteo API.

Usage

1. Clone the repository git clone https://www.github.com/Sanjeev-Kumar78/Weather_Trend_Analyzer.
2. Install dependencies:

   cd Weather_Trend_Analyzer
   pip install -r requirements.txt

3. Set your Google Maps API key in the st.secrets or as an environment variable.
4. Run the Streamlit app:

   streamlit run streamlit_app.py

5. On the sidebar:
   • Choose the data frequency (hourly or daily).
   • Select the date range. (For hourly data the range is limited to a maximum of 37 days.)
   • Input a location (as text or latitude/longitude).
6. Click Analyze Weather Data and explore the various visualizations and analyses provided.

Data Sources & Citations

• Weather data is sourced from Open-Meteo API.
• Additional datasets: ERA5 hourly data, ERA5-Land.
• Refer to the citations section in the app for detailed credits.

License

This project is open source under the MIT License.

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Made with ❤️ by Sanjeev Kumar