chandagalabuzi/Uganda-Food-Price-Analysis

Data analysis project exploring food price inflation, regional disparities, and pricing trends in Uganda using World Food Programme market data. 🍲📊 UGANDA FOOD PRICE ANALYSIS: INFLATION, REGIONAL TRENDS, AND COMMODITY DYNAMICS 📌 Problem Statement Food prices play a critical role in food security, household welfare, and economic stability, particularly in developing countries such as 🇺🇬 Uganda, where many households depend on locally purchased food and agriculture for their livelihoods. Rising inflation, regional market disparities, supply chain disruptions, and economic shocks can significantly affect the affordability and accessibility of essential food commodities. However, understanding how food prices vary across regions, commodity categories, and time remains a challenge without structured data analysis. This project uses data-driven methods to analyze food price dynamics in Uganda in order to: - Identify inflation trends over time - Explore regional price differences - Understand commodity-level price behavior - Determine key factors influencing food prices 📊 Dataset Source This project uses food price data from the World Food Programme (WFP) Price Database for Uganda: 🔗 data.humdata.org The dataset contains market-level records of food commodities collected across different regions and markets over multiple years. 🧾 Key Features: Commodity type and food category Market and regional location Dates of price collection Prices in UGX and USD Geographic coordinates (latitude & longitude) This enables: - Temporal analysis - Spatial (regional) analysis - Statistical and econometric modeling 🛠️ Tools Used 🐍 Python — data analysis and statistical modeling 📓 Google Colab — interactive notebook development 🧹 Pandas — data cleaning and manipulation 🔢 NumPy — numerical computations 📊 Matplotlib & Seaborn — data visualization 📉 Statsmodels — regression and statistical analysis 🐙 GitHub — version control and project hosting 🔍 Key Analyses - Exploratory analysis of food commodity and category distributions - Time series analysis of food pri …