zeedOracle/nigeria-inflation-dashboard

# 🇳🇬 Nigeria Inflation Dashboard An interactive dashboard that visualizes historical Nigerian inflation data and generates a short-term forecast using an ARIMA time-series model. Built to demonstrate: data pipeline → economic modeling → interactive visualization → deployment. **Live demo →** *nigeria-inflation-dashboard… ## What it does - Pulls annual inflation data (consumer prices, % change) for Nigeria from the World Bank Open Data API - Fits an ARIMA model on the historical series - Forecasts inflation for the next N years (adjustable in the sidebar) - Displays everything in an interactive Streamlit dashboard ## Tech stack - **Python** — data pipeline and modeling - **pandas** — data wrangling - **statsmodels** — ARIMA forecasting - **Streamlit** — dashboard UI - **Plotly** — interactive charting ## Project structure ``` econometrics-project/ ├── data/ │ ├── fetch_data.py # pulls data from World Bank API │ └── inflation.csv # generated after running fetch_data.py ├── app.py # Streamlit dashboard ├── model.py # ARIMA forecasting logic ├── requirements.txt └── README.md ``` ## Running it locally ```bash # 1. Clone the repo git clone github.com /nigeria-inflation-dashboard.git cd nigeria-inflation-dashboard # 2. Create and activate a virtual environment python -m venv venv venv\Scripts\activate # Windows # source venv/bin/activate # macOS/Linux # 3. Install dependencies pip install -r requirements.txt # 4. Fetch the data python data/fetch_data.py # 5. Run the dashboard streamlit run app.py ``` ## Roadmap / possible extensions - Swap in NBS monthly CPI data for finer-grained forecasts (World Bank data is annual only) - Add exogenous variables (exchange rate, oil price) to the model - Compare ARIMA vs Prophet vs SARIMA forecasts side-by-side - Add a "what-if" scenario slider (e.g. shock exchange rate, see projected impact) ## Data source World Bank …