This project performs a data analysis on a dataset of football players obtained from Kaggle. The analysis includes visualizations and insights about the players' characteristics and performance.
Football player data analysis is a crucial task for clubs and sports analysts, providing valuable insights into player performance and aiding in decision-making. This project uses a Kaggle dataset to explore and analyze various aspects of football players.
The dataset used in this project was obtained from Kaggle and contains detailed information about football players, including attributes such as age, nationality, club, position, skills, and more.
- Data Source: Kaggle - Football Players Data
- Data Description: This comprehensive dataset offers detailed information on approximately 17,000 FIFA football players, meticulously scraped from SoFIFA.com, which will be explored and visualized in this project.
The analysis includes the following steps:
- Data Exploration: General overview of the dataset and descriptive statistics.
- Data Cleaning: Handling missing and inconsistent values.
- Exploratory Analysis: Visualizations to identify patterns and insights.
4. Predictive Modeling: Application of machine learning models (if applicable).
- Conclusions: Summary of key findings and recommendations.
This project is licensed under the MIT License - see the LICENSE file for details.
Alexandre Cardoso - cardoso.estudo1@gmail.com
LinkedIn: Alex Cardoso
Thank you for checking out this project! If you have any questions or suggestions, feel free to reach out.