Analysis of Football Data using Python Libraries

This project is focused on analyzing football data using various Python libraries and tools. The goal is to gain insights into different aspects of the game, such as player performance, team statistics, and match outcomes, by leveraging the power of data analysis.

Features 1)Data collection
2)Data preprocessing
3)Exploratory Data Analysis (EDA)
4)Team analysis
5)Player performance analysis

Dependencies

The project relies on several Python libraries, including:

1)Pandas: For data manipulation and analysis.
2)NumPy: For efficient numerical computations.
3)Matplotlib: For creating static visualizations.
4)Seaborn: For enhanced data visualizations.
5)Jupyter Notebook: For creating and running code notebooks.