birukb-turing/climate-challenge-week0

African Climate Trend Analysis — COP32 Preparatory EDA (10 Academy Week 0) # African Climate Trend Analysis — Week 0 Challenge Exploratory analysis of historical climate data from **Ethiopia, Kenya, Sudan, Tanzania, and Nigeria** (NASA POWER, 2015–2026) in support of Ethiopia's data-driven position ahead of **COP32**. --- ## Project Structure ``` climate-challenge-week0/ ├── .github/workflows/ci.yml # GitHub Actions CI ├── .gitignore ├── requirements.txt ├── README.md ├── data/ # ← gitignored; place raw & cleaned CSVs here ├── notebooks/ │ ├── ethiopia_eda.ipynb │ ├── kenya_eda.ipynb │ ├── sudan_eda.ipynb │ ├── tanzania_eda.ipynb │ ├── nigeria_eda.ipynb │ └── compare_countries.ipynb ├── app/ │ ├── main.py # Streamlit dashboard │ └── utils.py ├── scripts/ │ └── README.md ├── src/ └── tests/ ``` --- ## Reproducing the Environment ### Prerequisites - Python 3.11+ - `git` ### 1. Clone the repository ```bash git clone github.com cd climate-challenge-week0 ``` ### 2. Create and activate a virtual environment ```bash python -m venv venv source venv/bin/activate # macOS / Linux # venv\Scripts\activate # Windows ``` ### 3. Install dependencies ```bash pip install -r requirements.txt ``` ### 4. Add data files Download the NASA POWER CSVs (Ethiopia, Kenya, Sudan, Tanzania, Nigeria) and place them in the `data/` directory: ``` data/ ├── ethiopia.csv ├── kenya.csv ├── sudan.csv ├── tanzania.csv └── nigeria.csv ``` > **Note:** The `data/` directory is listed in `.gitignore` and must never be committed to GitHub. ### 5. Run the notebooks ```bash jupyter notebook notebooks/ ``` ### 6. Launch the Streamlit dashboard ```bash streamlit run app/main.py ``` --- ## Dataset | Column | Unit | Description | |---|---|---| | YEAR | – | Year of observation | | DOY | – | Day of year (1–365/366) | | T2M | °C | Mean daily air temperature at 2 m | | T2M_MAX | °C | Maximum daily temperature at 2 m | | T2M_MIN | °C | Minimum daily temp …