An interactive, data-driven dashboard built with Plotly Dash, visualizing key climate indicators:
- Global Temperature Trends
- CO₂ Emissions by Country
- Sea Level Rise
- Correlation Analysis between temperature, emissions, and sea level
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Modular Pages
/temperature– choropleth & bar charts/emissions– emission comparison by year/sea_level– historical trends, seasonal patterns, projections/correlation– time series, correlation matrix, scatter, dashboard view
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Interactive Controls
- Year slider to adjust year
- Tabs & dropdowns for choosing chart types and regions
- Range sliders for filtering date spans
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Insights Panels Automated text summaries highlighting key statistics (e.g., hottest country, rate of change).
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Responsive Design Styled with Bootstrap and Poppins font, mobile-friendly layout, custom color themes.
- Python 3.8+
- Dash & Plotly for interactive visualizations
- Dash Bootstrap Components for UI
- Pandas, NumPy, SciPy for data processing
- Gunicorn web server (for production)
├── index.py # App entrypoint & router
├── pages/
│ ├── homepage.py
│ ├── temperature.py
│ ├── emissions.py
│ ├── sea_level.py
│ └── correlation.py
├── assets/style.css
├── requirements.txt
└── README.md
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Clone the repo
git clone https://github.com/SSI02/CS661_Project.git cd CS661_Project -
Create a virtual environment (optional but recommended)
python3 -m venv venv source venv/bin/activate # Linux/macOS venv\Scripts\activate # Windows
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Install dependencies
pip install -r requirements.txt
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Run the app
python index.py
Then open
http://127.0.0.1:8050in your browser.
Access the deployed dashboard here:
https://climate-dashboard-ybix.onrender.com/
- Fork the repo
- Create a feature branch:
git checkout -b feature/foo - Commit changes:
git commit -m 'Add foo feature' - Push to branch:
git push origin feature/foo - Open a Pull Request
Please follow the existing code style, add tests if applicable, and keep assets under 100 MB per file.
Project Link: https://github.com/SSI02/CS661_Project