dion-nekesa/kenya-food-price-volatility

An automated early-warning telemetry pipeline using UN WFP market data to detect localized staple food price volatility (>20% MoM surges) across Kenya for proactive MEAL and humanitarian response. # Kenya Food Security Early Warning System 🌾📊 *Automated Price Volatility & Market Risk Analytics Pipeline* ## Project Overview Humanitarian food assistance is frequently reactive—interventions are often mobilized after drought or economic shocks have already compromised household stability. This project builds an automated early-warning telemetry pipeline using official **UN World Food Programme (WFP)** market data. By tracking monthly price trajectories for staple crops across Kenyan counties, the pipeline isolates market anomalies where local prices jump by >20% month-over-month. --- ## Key Analytical Takeaways * **Staple Price Sensitivity:** White Maize shows extreme price elasticity during drought cycles, experiencing localized surges over 20% in arid and semi-arid regions. * **Proactive Interventions:** Market anomalies serve as leading indicators for food insecurity, enabling Monitoring, Evaluation, Accountability, and Learning (MEAL) teams to allocate micro-grants and emergency relief early. * **Regional Disparities:** Primary agricultural producer regions maintain relative price stability, whereas net-consumer counties encounter severe compounding price spikes during global supply chain or climate shocks. --- ## Visual Analytics --- ## Technical Stack * **Language:** Python 3.x * **Libraries:** Pandas (Data Transformation & Time Series Analysis), Matplotlib & Seaborn (Visual Analytics) * **Data Source:** UN OCHA Humanitarian Data Exchange (HDX) / WFP Market Monitor --- ## How to Run the Analysis 1. Clone the repository: ```bash git clone github.com cd kenya-food-price-volatility