The Olympic Games are one of the largest and most celebrated sporting events in the world, bringing together athletes from all nations to compete across a wide range of disciplines. This project aims to analyze historical Olympic data to discover patterns, trends, and insights about athlete performance, country-wise achievements, and the evolution of the Games over time.
The dataset used is sourced from publicly available historical data of the Olympic Games. It typically includes:
- Athlete-level details: name, age, gender, nationality, sport, event, and medal won Olympic.
- Event data: year, city
- Medal information: gold, silver, bronze
- Cleaning, processing and EDA on real-world dataset using Pandas and NumPy
- Visualizations using Matplotlib
- Country-wise and year-wise medal trend analysis
- Athlete-level breakdown of medals and events
- Insightful answers to key analytical questions
- Well-organized Python files for easy understanding
- Python – Core programming language for data analysis
- Pandas – Data manipulation and cleaning
- Matplotlib – Data visualization (static plots)
- CSV – Dataset file format
| File Name | Description |
|---|---|
README.md |
Provides a detailed overview of the project, including its objectives, methodology, key features, technologies used, and instructions for usage. |
athlete_count.sql |
Contains a SQL query designed to extract and analyze the total number of athletes participating in each Olympic edition, enabling insights into participation trends over time. |
top_10_sports.py |
Python script developed to visualize top ten sports based on athlete participation. Useful for highlighting the most popular disciplines in the Olympic Games. |
gender.sql |
This SQL query focuses on gender-based participation analysis, offering a perspective on the evolution of male and female athlete representation. |
men_women.py |
Python script to visualize overall medal distribution using the sorted data. |
country medal.sql |
Includes a SQL query that retrieves medal counts categorized by country. This helps in evaluating the performance of various nations. |
medals.py |
A Python script used for loading, processing, and visualizing medal distribution data. It supports exploratory data analysis and helps derive meaningful interpretations. |