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https://github.com/ehtisham-sadiq/olympics-data-analysis
The "Olympics Data Analysis" project is an end-to-end exploration of historical Olympic Games data using Python data visualization techniques. This project aims to uncover interesting insights and trends from a comprehensive dataset of Olympic Games, providing a deeper understanding of the world's most significant sporting event.
https://github.com/ehtisham-sadiq/olympics-data-analysis
data-visualization heroku matplotlib plotly python3 seaborn streamlit
Last synced: about 2 months ago
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The "Olympics Data Analysis" project is an end-to-end exploration of historical Olympic Games data using Python data visualization techniques. This project aims to uncover interesting insights and trends from a comprehensive dataset of Olympic Games, providing a deeper understanding of the world's most significant sporting event.
- Host: GitHub
- URL: https://github.com/ehtisham-sadiq/olympics-data-analysis
- Owner: ehtisham-sadiq
- Created: 2022-08-20T09:33:41.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-18T13:40:49.000Z (about 1 year ago)
- Last Synced: 2023-10-18T14:42:32.781Z (about 1 year ago)
- Topics: data-visualization, heroku, matplotlib, plotly, python3, seaborn, streamlit
- Language: Python
- Homepage:
- Size: 5.19 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# olympics-data-analysis-web-app
### Key Topics Covered
- **Data Cleaning:** The project begins with thorough data cleaning, handling missing values, and ensuring data consistency to prepare it for analysis.
- **Data Visualization:** Utilizing Python libraries such as Matplotlib and Seaborn, the project employs a variety of visualizations, including bar charts, line plots, scatter plots, and heatmaps to represent data patterns.
- **Historical Trends:** Explore historical trends in Olympic participation, analyze the number of events over the years, and visualize the growth of the Games.
- **Country Analysis:** Investigate the performance of different countries in the Olympics and visualize their medal counts over time.
- **Athlete Insights:** Discover insights into the achievements of Olympic athletes, their age distributions, and the impact of gender on medal counts.
- **Sports and Events:** Analyze popular sports and events, showcasing their growth and participation.
### A Streamlit web application for the analysis of olympics dataset
  
• This repository consists of files required to deploy a ___Machine Learning Web App___ created with ___Streamlit___ on ___Heroku___ platform.
• If you want to view the deployed model, click on the following link:
Deployed at: _https://oda-ehtisham.herokuapp.com/_
• If you are searching for __Code__, __Algorithms used__ and __Accuracy__ of the model.. you won't find it here. Click the link mentioned below for the same:
Link: _https://github.com/bsef19m521/Olympics-Data-Analysis_
• Please do ⭐ the repository, if it helped you in anyway.
• A glimpse of the web app:
_**----- Important Note -----**_
• If you encounter this webapp as shown in the picture given below, it is occuring just because **free dynos for this particular month provided by Heroku have been completely used.** _You can access the webpage on 1st of the next month._
• Sorry for the inconvenience.
