Agabaofficial/rwanda-poverty-risk-prediction

A data science project that uses Rwanda PHC5 2022 Census indicators to develop a district-level Poverty Risk Prediction Model based on housing quality, access to services, education, digital inclusion, health insurance, and agricultural characteristics. # Rwanda Poverty Risk Prediction Model This project uses Rwanda's Fifth Population and Housing Census (PHC5, 2022) to build a district-level Poverty Risk Prediction Model. The model analyzes indicators related to: - Housing quality - Access to water and sanitation - Electricity access - Asset ownership - Education - Internet access - Mobile phone ownership - Health insurance - Agricultural dependence The objective is to identify districts that are potentially at higher risk of poverty and provide evidence-based insights for policy makers, NGOs, researchers, and development partners. ## Data Source National Institute of Statistics of Rwanda (NISR) Population and Housing Census (PHC5), 2022 ## Methodology 1. Data Extraction 2. Data Cleaning 3. Feature Engineering 4. Exploratory Data Analysis 5. Poverty Risk Index Construction 6. Machine Learning Modeling 7. Visualization and Dashboard Development ## Technologies - Python - Pandas - NumPy - Scikit-Learn - Matplotlib - Seaborn - Plotly - Streamlit