KObungu/Karamoja_Food_Security_Project

This project develops an interactive visualization tool to help NGOs prioritize food security interventions in Karamoja, Uganda, by analyzing 2017 satellite data on sorghum and maize yields alongside population data. # 🌾 Karamoja Crop Yield & Food Security Analysis (2017) ## 📌 Project Overview This project analyzes crop yield and food security patterns in the Karamoja region of Uganda using district-level agricultural and population data. The goal was to understand where food insecurity risks are highest by examining crop productivity, population pressure, and per capita production. This project combines data cleaning in Python, geographic mapping, and dashboard design in Tableau to support practical, data-driven decision-making. --- ## 🎯 Problem Statement Karamoja is one of Uganda’s most food-insecure regions. From the data and background research, some key contributing factors include: - Low agricultural productivity - Recurring drought conditions - Uneven distribution of crop yields - Heavy reliance on maize and sorghum Because resources are limited, decision-makers need clear insights to know where to prioritize support. --- ## 🎯 Objectives - Analyze maize and sorghum yields by district - Evaluate production per capita (food availability per person) - Assess the relationship between population and productivity - Develop an interactive dashboard for stakeholders ## 🧠 What I Did ### 1️⃣ Data Cleaning I cleaned and merged crop yield data with population data using Pandas. This involved checking for missing values and ensuring district names matched correctly. ### 2️⃣ Creating New Metrics To better understand food availability, I calculated **production per capita**. This helped show how much food is available per person in each district. ### 3️⃣ Visualization & Analysis I created: - District-level yield maps - Bar charts comparing maize and sorghum yields - Production per capita comparisons - A yield vs population analysis These visuals helped reveal patterns that were not obvious from raw numbers alone. ### 4️⃣ Dashboard Development Finally, I built an interactive Tableau dashboard so stakeholders can explore the data dynamically. --- ## 🛠 Tools & Technolog …