courage-analytics-glitch/Africa-Health-Analysis-WHO-Global-Health-Data

: Python analysis of Africa's health indicators using WHO Global Health Estimates data. Focus on leading causes of death, life expectancy by subregion, and Ghana benchmarking. Published on Kaggle. # Africa Health Analysis: WHO Global Health Data **Author:** Richard Courage Cobbinah | SetorCourage **Date:** June 2026 **Tools:** Python, Pandas, Matplotlib, Seaborn **Source:** WHO Global Health Estimates (2021) **Kaggle:** View Notebook --- ## Overview This project analyses health indicators across Africa using WHO Global Health Estimates data. The analysis focuses on leading causes of death, life expectancy by subregion, and benchmarks Ghana against regional comparators. --- ## Key Findings - Lower Respiratory Infections and Neonatal Conditions are the top two causes of death across Africa - Northern Africa leads all subregions with a life expectancy of 74.2 years - Central Africa has the lowest life expectancy at 56.9 years - Ghana's life expectancy sits at 64.1 years, below Northern and Southern Africa - Non-communicable diseases are rising as a proportion of total deaths --- ## Charts Produced - Chart 1: Leading Causes of Death in Africa (2021) - Chart 2: Life Expectancy by African Subregion (2021) --- ## Tools and Libraries | Tool | Purpose | |---|---| | Python | Core analysis | | Pandas | Data manipulation | | Matplotlib | Visualisation | | Seaborn | Chart styling | --- ## Connect - Kaggle: kaggle.com - LinkedIn: linkedin.com - GitHub: github.com