Hodal66/Crop-Price-Forecasting-in-Rwanda-using-Time-Series-Modeling

Predicting future prices of staple crops like beans, maize, and bananas in Rwanda using WFP food price data and time-series forecasting models (Prophet, ARIMA), supported by Power BI visualizations. --- ##🌾 Crops Prices Prediction in Rwanda --- ## Introduction This project predicts the prices of various food commodities in Rwanda using historical data. It involves data collection, cleaning, exploratory data analysis, modeling, and visualization of results. It also includes Power BI reports for policy-making and decision support. --- A complete pipeline for **predicting food prices in Rwanda** using historical data from the World Food Programme, with visual insights powered by **Power BI** and predicting models using **Facebook Prophet**. ## 📁 Project Structure ````markdown ```bash PROJECT_ON_CROPS_PRICES_FORECAST_RWANDA/ │ ├── data/ │ ├── processed/ │ │ ├── cleaned_food_prices.csv │ │ └── processed_food_prices.csv │ └── raw/ │ └── wfp_food_prices_rwa.csv │ ├── notebooks/ │ └── eda_visualization.ipynb │ ├── power_bi/ │ └── MuhetoHodal_Powerbi_Exam_Report.pbix │ ├── predictions/ │ ├── all_commodity_predictions.csv │ ├── all_commodity_predictions_1.csv │ └── all_commodity_predictions_2.csv │ ├── reports/ │ ├── output_images_visualization/ │ ├── power_bi_screen_shoots/ │ └── screen_shoots/ │ ├── 1_clean_food_prices_data.py ├── 2_train_model_to_predict_all_commodities.py ├── .gitignore └── README.md ```` --- ## 📌 Objective To build a machine learning pipeline that predicts the prices of food commodities in Rwanda and provides actionable insights for: * Farmers (to determine best times to sell) * Policymakers (for intervention and price control) * Traders and Investors (to identify market trends) --- ## 🧾 Dataset Description * **Source**: World Food Programme (WFP) Rwanda dataset * **File**: `wfp_food_prices_rwa.csv` * **Content**: Prices of various food items by market, date, and unit --- ## 🧹 Data Processing Steps | Step | Description | | ------------------ | ------------------------------------------------------ | | 🔸 Raw Data Import | Loaded from `data/raw/wf …