code-cra7t/africa-climate-intelligence

# Africa Climate Intelligence **Emissions, warming, energy and development across 54 African countries.** Africa Climate Intelligence is a reproducible Streamlit data platform for exploring country-year climate and development indicators across Africa. It combines public-data engineering, statistical analysis, interactive visualization, transparent data-quality checks, and responsible climate communication. ## Central Research Question How do historical emissions, present-day emissions intensity, observed temperature change, development patterns, energy transition, and data coverage differ across African countries and regions? The project does not treat a simple country-level correlation between emissions and local temperature anomaly as proof of causation. Climate forcing is global and cumulative, and attribution requires methods beyond this descriptive dashboard. ## Setup ### Windows PowerShell ```powershell python -m venv .venv .venv\Scripts\Activate.ps1 python -m pip install --upgrade pip pip install -e ".[dev]" ``` ### macOS/Linux ```bash python -m venv .venv source .venv/bin/activate python -m pip install --upgrade pip pip install -e ".[dev]" ``` ## Data Pipeline ```bash python scripts/download_data.py python scripts/build_dataset.py python scripts/build_duckdb.py python scripts/audit_data.py ``` The main processed output is: ```text data/processed/africa_climate_panel.parquet ``` The core analytical grain is: ```text iso3 + year ``` ## Run The Application ```bash streamlit run app/Home.py ``` ## Quality Checks ```bash ruff format --check . ruff check . pytest python -m compileall app src scripts ``` ## Docker ```bash docker build -t africa-climate-intelligence . docker run --rm -p 8501:8501 africa-climate-intelligence ``` ## Architecture - `scripts/` contains reproducible pipeline entry points. - `src/aci/` contains ingestion, transformation, quality, and analysis code. - `app/` contains the Streamlit application, shared visual system, …