clementafangama-gif/wash-africa-analysis

An analysis of WASH access across 45 Sub-Saharan African countries using WHO/UNICEF JMP 2025 data # Community Water and Sanitation Access Analysis in Sub-Saharan Africa ## Project Overview This project analyses access to water, sanitation, and hygiene (WASH) services across 45 Sub-Saharan African countries using the WHO/UNICEF Joint Monitoring Programme (JMP) 2025 global dataset. The analysis covers 25 years of data from 2000 to 2024 and explores access levels, rural-urban disparities, sub-regional comparisons, and progress over time. This is Project 2 in a series of NGO and research analytics portfolio projects by Clement Etim, a freelance data analyst specializing in social impact analytics. --- ## Key Findings - 70.2% of the regional population has access to basic water — but only 28.9% have safely managed water - Fewer than half the population (40.0%) has basic sanitation access - Only 27.6% have access to a basic handwashing facility, hygiene is the most neglected WASH pillar - The average rural-urban gap in basic water access is 28 percentage points - Conflict-affected states consistently record the lowest access rates across all three indicators - Ethiopia reduced open defecation by 55.6 percentage points, the most dramatic improvement in the region --- ## Tools Used - Python (pandas, matplotlib, seaborn): data cleaning and EDA - Power BI Desktop: interactive dashboard - WHO/UNICEF JMP 2025: primary dataset --- ## Repository Structure wash-africa-analysis/ ├── data/ │ └── clean/ ← Cleaned datasets (CSV and Excel) ├── notebooks/ ← Jupyter notebooks (cleaning and EDA) ├── visuals/ ← Charts exported from Python ├── dashboard/ ← Power BI dashboard screenshot └── report/ ← Final analysis report (PDF) --- ## Project Workflow 1. Data extraction and cleaning (Python) 2. Exploratory data analysis and visualisation (Python) 3. Interactive dashboard (Power BI) 4. Written analysis report --- ## Data Source WHO/UNICEF Joint …