This is a data analysis project on the National Basketball Association (NBA) using Python. The data was collected from the official NBA website and is used to perform exploratory data analysis and visualizations to gain insights into the NBA.
The following packages are required to run the code in this repository:
- pandas
- numpy
- matplotlib
- seaborn
You can install them using pip by running the following command:
pip install pandas numpy matplotlib seaborn
The dataset used in this project contains information on the players, teams, and games in the NBA from the 2019-2020 season. The data was collected from the official NBA website and includes information on player statistics such as points per game, rebounds per game, assists per game, and more.
The repository contains a Jupyter Notebook (nba_data_analysis.ipynb) that contains the code and visualizations for this project. The notebook is divided into several sections:
- Data Cleaning and Preprocessing
- Exploratory Data Analysis
- Data Visualization
This project provides an overview of the NBA data from the 2019-2020 season using exploratory data analysis and visualizations. The insights gained from this analysis can be used to better understand the players, teams, and games in the NBA.