An interactive dashboard built using Streamlit, Plotly, and ARIMA time series modeling to visualize and forecast CO₂ emissions by country. The project allows users to upload datasets, filter by country and year, view trends, and forecast future emissions.
- 📈 Time Series Forecasting of global CO₂ emissions using ARIMA
- 🌐 World Map Visualization (Choropleth) of average emissions by country
- 📊 Line Chart of Country-Wise Emissions Trends
- 📥 Downloadable CSV of filtered data
- 📅 Year Range and Country Filters via sidebar
- 📄 Descriptive interface with Markdown and metric summaries
| Tool/Library | Purpose |
|---|---|
| Python | Core programming language |
| Streamlit | Dashboard UI and frontend |
| Pandas | Data loading, cleaning, manipulation |
| Plotly | Interactive charts and maps |
| Matplotlib | Line plots for forecast visualization |
| Statsmodels (ARIMA) | Time series forecasting |
- Clone the repo
git clone https://github.com/ishita-si/Global-Climate-Change-Dashboard.git
cd Global-Climate-Change-Dashboard- Install dependencies
pip install -r requirements.txt- Run the Streamlit app
streamlit run app.pyOur World In Data - CO2 Dataset
- Significant variation in emission trends across countries
- Forecast shows upward trend continuing in many nations
- Emissions data can inform policy, awareness, and change
Pull requests are welcome! If you have suggestions or want to extend the dashboard (e.g., add LSTM or Prophet models), feel free to fork and contribute.
For queries or collaboration, feel free to reach out via GitHub or [Gmail - [email protected]].