This repository contains Python code for analyzing FIFA player data and creating visualizations based on the data. The code is written in Jupyter Notebook and uses various libraries such as pandas, numpy, matplotlib, and seaborn.
The code utilizes a dataset named "players_20.csv" which contains FIFA player data. The dataset includes information about players' nationality, club, wages, shooting skills, defending skills, and more.
The code performs the following tasks:
- Imports the required libraries for data analysis and visualization.
- Reads the FIFA player data from the CSV file into a pandas DataFrame.
- Displays basic information about the dataset such as the first few rows, shape, and column labels.
- Analyzes and plots the top 10 countries with the most players using line, bar, histogram, and scatter plots.
- Creates visualizations for the highest paid players and top-rated players for shooting and defending skills.
- Provides specific analysis and plots for the Real Madrid club, including the highest paid players and top-rated players for shooting and defending skills within the club.
To run the code and reproduce the visualizations, follow these steps:
- Make sure you have Python installed on your machine.
- Install the required libraries by running the following command:
pip install pandas numpy matplotlib seaborn. - Download the "players_20.csv" dataset and place it in the same directory as the Python code file.
- Open the Python code file in a Jupyter Notebook or a similar environment.
- Execute the code cells one by one to perform the analysis and create the visualizations.
I have explored the data with different graphs. Some of them as follows:
Feel free to modify the code according to your needs and experiment with different analyses and visualizations based on the FIFA player data.
This code is released under the MIT License.
Please note that the dataset used in this code may have its own license and terms of use. Make sure to review and comply with the dataset license and terms when using the provided code.
The code provided is for educational and demonstration purposes only. It may not be suitable for production environments. Use it at your own risk.