NyakweaAnn/East-Africa-Food-Security-Analysis

Domain:

socioeconomicagriculture

Creator:

Nya

Host:

A longitudinal study (2006-2026) using Python and Power BI to analyze maize price volatility and market interdependence in the EAC # 🌍 East Africa Food Security Analysis (2006-2026) ### **A Longitudinal Study of Market Volatility in Kenya, Uganda, and Tanzania** ## **Project Overview** This project analyzes 20 years of regional food price volatility across the East African Community. Using humanitarian data from the World Food Programme (WFP), I engineered a dynamic decision-support tool to identify geospatial hotspots and longitudinal price trends for 331 distinct markets. ## **🛠️ Technical Implementation** * **Data Engineering:** Engineered a multi-stage ETL process to merge multi-national datasets. Resolved critical data-type mismatches in Power Query to ensure calculation integrity. * **Advanced Analytics (DAX):** Implemented **12-Month Moving Averages** to smooth seasonal volatility and created a custom **Calendar Table** for robust time-series intelligence. * **Mathematical Normalization:** Standardized unit-of-measure discrepancies (converting 90KG wholesale units to 1KG retail metrics) and normalized prices to USD for cross-border comparability. * **Geospatial Intelligence:** Leveraged coordinate data to build an interactive "Hotspot" interface, identifying vulnerable markets in real-time. ## 🧪 Exploratory Data Analysis (EDA) Before final dashboarding, I utilized **Python (Matplotlib/Pandas)** to prototype regional price correlations. This allowed for rapid testing of price-per-KG normalization across different market clusters. ## **📈 Key Insights Found** * **The 2022 Divergence:** While Tanzania and Uganda maintained relative price stability over the 20-year horizon, Kenya experienced a localized exponential spike in 2022. * **Regional Correlation:** Despite different national currencies, price spikes in staples like maize are highly synchronized across the EAC corridor, highlighting regional market interdependence. * **Data-First Integrity:** Identified and corrected a 90x scale error in raw data through unit normalization—a critical step for financ …

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