UEFA Euro Championship - Data Analysis Repository

Introduction

Welcome to the UEFA Euro Championship Data Analysis Repository!

This project aims to provide comprehensive insights into various aspects of the UEFA Euro Championship using interactive visualizations. Check out the webapp!

I have gathered all the data from past tournaments to build an interactive way to explore:

• Match performances,
• Tournament statistics, and
• Penalty card data

All data is presented through an intuitive web interface.

Motivation

The primary objective of this project is to demonstrate my ability to use Python, Streamlit, and advanced graphing libraries (Plotly) to build interactive visualizations.

I am rooting for Germany to win the championship in 2024, and this is my way of cheering for them!

See my blog post for more details!

Tools and Technologies Used

• Pandas
  • Of course, Pandas.
  • It is THE data manipulation and analysis library for Python.
  • It provides data structures and functions needed to clean, analyze, and visualize the data efficiently.
• Plotly
  • Plotly is an awesome graphing library to plot publication-quality graphs online.
  • These graphs are dynamic and interactive.
  • It's quite versatile, and I use it for several use cases.
• Streamlit
  • I used Streamlit to create the front-end to showcase my Plotly graphs.
  • Streamlit is originally a tool to build web applications with Python.

Overview of Each File

• In this section, I am briefly covering what each file does and how the plots are built.
• I have tried to keep all code sections as stand-alone and non-modular as possible. This allows me or anyone else to adapt them quickly for building other graphs and not spend time going through code clutter. You can just pick up a code block and modify it independently without impacting others.

100-Match_Performance.py

• This script visualizes match performance data, including total points, goals scored, and goals conceded by teams in the UEFA Euro Championship.
• Users can filter data to view the top teams and explore interactive bar charts that display the performance metrics.

200-Tournaments_Statistics.py

• This script focuses on tournament statistics, including the medals tally and host nations.
• Users can explore which teams have won the most medals and which nations have hosted the championship most frequently.
• I have used both bar charts and pie charts.

300-Penalty_Cards.py

• This script provides an analysis of penalty cards issued during the championship.
• It visualizes data on red cards and two-yellow cards across different rounds of the tournament.
• Users can explore which teams received the most penalty cards and in which stages they were most prevalent.

Acknowledgements

All code in this repository is made possible by the contributions of these open-source initiatives. I fully acknowledge their efforts and attribute the usage of their components to them:

• Pandas - Licensed under the BSD-3-Clause License
• Plotly - Licensed under the MIT License
• Wikipedia - Data licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License (CC BY-SA 3.0)
• Streamlit - Licensed under the Apache-2.0 License

Installation and Usage

To run this project locally, follow these steps:

1. Clone the repository:

git clone https://github.com/kanad13/UEFA-Euro-Data-Analysis.git

2. Navigate to the project directory:

cd UEFA-Euro-Data-Analysis

3. Install the required dependencies:

pip install -r requirements.txt

4. Run the Streamlit application:

streamlit run Welcome.py

Contributing

• No code is perfect.
• I am sure there will be bugs in my code or issues with the underlying data I have used.
• So please raise an issue or pull request to highlight it to me. I would really appreciate it!

License

This project is licensed under the MIT License. See the LICENSE file for more details.