shejinyem-glitch/Nigerian-Produce-Price-Forecasting.

Nigerian Produce Price Forecasting. The problem I am addressing is the volatility of prices of agricultural and perishable food products in Nigeria. The goal of this project is to use historical price data to forecast future produce prices. # DS-01: Nigerian Produce Price Forecasting ## Project Overview This project was developed as part of the 3MTT Data Science track under the project brief: **DS-01 — Produce Price Forecasting** Perishable produce prices can be highly volatile, making it difficult for farmers, traders, consumers and policymakers to anticipate future prices. The objective of this Minimum Viable Product (MVP) is to use historical Nigerian food-price data and machine-learning techniques to forecast the next month's onion price. ## Problem Statement Produce prices fluctuate over time due to changes in supply, demand, seasonality, market conditions and other economic factors. A useful forecasting system can provide an estimate of future prices and help stakeholders make more informed decisions. ## MVP Objective The MVP forecasts the next month's onion closing price using historical price information and engineered time-series features. ## Dataset The supplied dataset contains monthly Nigerian food-price observations. ### Dataset characteristics * Country: Nigeria * Frequency: Monthly * Period: January 2007 to August 2026 * Number of records: 4,012 * Products: Multiple food commodities * Currency: NGN * Main price fields: * Open * High * Low * Close ### Important dataset limitation The supplied dataset contains **onion observations but does not contain tomato observations**. Therefore, this MVP focuses on **onion price forecasting**. The same pipeline can be applied to tomato prices when suitable tomato observations are added to the dataset. ## Project Features The MVP implements: 1. Data preparation 2. Exploratory data analysis 3. Feature engineering 4. Time-based train/test splitting 5. Random Forest forecasting 6. Model evaluation 7. Baseline comparison 8. Feature importance analysis 9. Next-month price forecasting ## Feature Engineering The following features were created: ### Calendar features …