This beginner project is focused on analyzing and visualizing NBA player statistics using Python. Below is a breakdown of the project files, the technologies, packages, and modules used, along with other useful considerations.

• nba_players.ipynb: A Jupyter Notebook that contains the script to fetch all active NBA player IDs using the nba_api. This script is essential for gathering the foundational data required for analysis and image retrieval.

• nba_stats.csv: A CSV file that stores basic statistics of NBA players for the current season. This file serves as input for various analysis tasks.

• nba_player_data_analysis.ipynb: A Jupyter Notebook dedicated to analyzing the data contained within nba_player_data.csv. It includes data cleaning, exploratory data analysis (EDA), and visualization sections to uncover insights about NBA players.

• nba_player_data.csv: A CSV file containing detailed statistics and biographical information for NBA players. This dataset is used for in-depth analysis in the nba_player_data_analysis.ipynb notebook.

• nba_stats_scraping.ipynb: A Jupyter Notebook that outlines the process of scraping NBA player statistics from the web. This notebook demonstrates how to collect additional data that might not be available through the nba_api.

• Python: The primary programming language used for analysis and data collection.
• Jupyter Notebook: An open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text.
• nba_api: An API client for the NBA statistics located at stats.nba.com, used to fetch player IDs and other statistical data.
• Pandas: A library providing high-performance, easy-to-use data structures, and data analysis tools.
• Plotly: Library used for creating static, animated, and interactive visualizations in Python.
• Requests: A simple HTTP library used for making requests to the web for scraping purposes.

To run the notebooks and scripts, ensure you have Python installed, then install the required packages using the following command:

pip install jupyterlab nba_api pandas plotly requests

To view and run the notebooks, start JupyterLab or Jupyter Notebook from the terminal:

jupyter lab

Or for Jupyter Notebook:

jupyter notebook

Navigate to the project directory and open the desired notebook file.

• Ensure that you comply with the terms of service for any APIs or websites from which you scrape data.
• The nba_api is used under the assumption that it is for personal or educational purposes; ensure your usage complies with any usage policies.
• This project is structured for educational purposes and may require modifications for commercial application.