The Olympic Data Analysis App is a data-driven project that explores 120 years of Olympic history using data visualization techniques. The app cleans, processes, and analyzes historical Olympic data to extract meaningful insights about athletes, countries, sports, and trends in the Olympics over time.
Data Cleaning & Preprocessing: Handled missing values, duplicates, and inconsistent data.
Exploratory Data Analysis (EDA): Derived key insights from 120 years of Olympic data.
Data Visualization: Used graphs, charts, and heatmaps to analyze trends and distributions.
Country & Sport Analysis: Studied performance trends of different countries and sports over time.
Athlete Performance Insights: Identified the most successful athletes and their contributions.
Gender Participation Trends: Explored the evolution of gender participation in the Olympics.
Medal Distribution: Analyzed medal-winning patterns across various Olympic events.
Python (for data analysis and processing)
Pandas, NumPy (for data manipulation)
Matplotlib, Seaborn, Plotly (for interactive and static visualizations)
Jupyter Notebook / Streamlit (for interactive data exploration and visualization)
Power BI / Tableau (optional for dashboarding)
The dataset consists of 120 years of Olympic data, including information about:
Athletes
Countries
Events
Medals
Sports
Gender participation
Clone the repository:
git clone https://github.com/your-username/olympic-data-analysis.git
Navigate to the project directory:
cd olympic-data-analysisInstall dependencies:
pip install -r requirements.txt
Run the analysis script or interactive dashboard:
streamlit run app.py
OR, for Jupyter Notebook users:
jupyter notebook
The United States and China have consistently been top medal-winning countries.
Men dominated early Olympic Games, but gender equality has improved over the years.
Certain sports like swimming and athletics have had the most medals awarded.
Some athletes have won multiple gold medals, showcasing outstanding performances.
Adding machine learning models to predict medal winners based on past trends.
Implementing real-time updates for upcoming Olympics.
Enhancing visualizations with interactive dashboards using Power BI/Tableau.
Feel free to fork this repository and contribute to improve this project! If you have any suggestions, open an issue or create a pull request.
For any queries or collaborations, reach out via: