erickm-pixel/ATU-Doping-Analysis

Analysis of Athletics Integrity Unit (AIU) doping violation cases with a focus on Kenya — built for clean sport education and anti-doping intervention insights. # ATU-Doping-Analysis Analysis of Athletics Integrity Unit (AIU) doping violation cases with a focus on Kenya — built for clean sport education and anti-doping intervention insights. # ATU Doping Cases Analysis — Kenya Focus ## Project Overview This project analyzes doping violation data from the Athletics Integrity Unit (AIU) covering track and field athletes globally, with a specific focus on Kenya's position in the global anti-doping landscape. ## Objectives - Analyze global doping trends across disciplines and countries - Identify patterns in Kenyan doping cases - Generate insights to inform clean sport education programs - Support evidence-based anti-doping interventions in Kenya ## Dataset - Source: Athletics Integrity Unit (AIU) - Records: 453 doping violation cases - Countries: 30+ nationalities - Disciplines: Track and field events ## Tools Used - Python (Pandas, Matplotlib, Seaborn) - Power BI (Interactive Dashboard) - Jupyter Notebook ## Key Findings - Kenya accounts for 32% of global cases - Long-distance running has the highest violation rate (54%) - Nearly equal gender split in Kenyan cases - The majority of violations occur between the ages 20 and 35 ## Project Structure ATU-Doping-Analysis-Kenya/ │ ├── ATU_Doping_Analysis_Kenya.ipynb # Main analysis notebook ├── ATU_Doping_Analysis_Kenya.html # Exported notebook ├── ATU_Doping_Cleaned.csv # Cleaned dataset ├── dashboard/ # Power BI screenshots └── README.md # Project documentation ## Dashboard Pages - Page 1: Global Overview - Page 2: Kenya Deep Dive - Page 3: Clean Sport Interventions ## Author Erick Mitere Sports Data Analyst | Kenya