This Streamlit web app performs data analysis on the Olympics dataset. It provides insights into medal tallies, overall statistics, country-wise analysis, and athlete-wise analysis. The app is designed to explore and visualize trends and patterns in the data.
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data folder:
athlete_events.csv: Contains the main dataset with information about athletes and their performances.noc_regions.csv: Contains information about NOC (National Olympic Committee) regions.
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app.py: Main application script written in Streamlit. It uses the Streamlit library for creating a web interface and pandas, plotly, matplotlib, seaborn for data analysis and visualization.
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helper.py: Helper functions for data processing and analysis. It includes functions for fetching medal tallies, creating line charts over time, generating heatmaps, and more.
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preprocessor.py: Contains a preprocessing function to clean and modify the dataset.
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Clone the Repository:
git clone https://github.com/hardikjp7/Olympics-Data-Analysis-with-Deployment.git cd Olympics-Data-Analysis-with-Deployment -
Install Dependencies:
pip install -r requirements.txt
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Execute the Streamlit app:
streamlit run app.py -
Access the app through the provided URL in the terminal.
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Medal Tally: Select the year and country to view the corresponding medal tally.
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Overall Analysis: Explore overall statistics, including the number of editions, host cities, sports, events, athletes, and participating nations over time.
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Country-wise Analysis: Analyze medal tallies and top athletes for a specific country.
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Athlete-wise Analysis: Explore the distribution of athlete ages, successful athletes, and height vs weight for different sports.
- The app uses the Olympics dataset (
athlete_events.csv) and the NOC regions dataset (noc_regions.csv). - Make sure to have the required Python libraries installed.
Feel free to explore and modify the code to suit your needs. Happy analyzing!