← All projects Exploratory analysis · CASE STUDY
EDA - Olympics Dataset An exploratory data analysis project on 120+ years of Olympic history using Python, pandas, matplotlib, and seaborn. The dataset contains 70,000 athlete-event records spanning from 1896 to 2016, covering both Summer and Winter Olympics with detailed athlete demographics, event information, and medal outcomes.
Goals
Transition from data cleaning into exploratory data analysis and visualization
Uncover patterns in Olympic participation, gender representation, and medal distribution
Analyze how athlete physical attributes vary across sports and genders
Practice storytelling with data using matplotlib and seaborn
Process
Removed 383 duplicate records and assessed missing values across all columns
Analyzed medal distribution, participation growth, and gender trends over 120 years
Compared physical attributes (age, height, weight) across sports and between genders
Created 5 visualizations including line charts, stacked area charts, and box plots
Insights
86% of Olympic athletes never won a medal — competition at the Olympics is extremely fierce
Female participation grew from near zero in the 1890s to ~40% of all athletes by 2016
Medal winners are on average 2.7cm taller than non-medalists — suggesting a slight physical edge
Age varies dramatically by sport — gymnasts peak at ~20 years while sailors and shooters compete well into their 30s
This case study documents a portfolio analysis. Findings describe this dataset and should be interpreted within its limitations.
Dataset source ↗ Explore more projects