This project utilizes nba_api and Plotly to create a visualization and prediction model based on data from NBA players. The primary goal is to provide a tool for team managers and coaches to analyze player performance, compare stats, and make informed decisions for drafting, trading, and lineup selection.
- Fetch player data using
nba_api - Visualize Points-Per-Game (PPG) and Rebounds-Per-Game (RPG) using Plotly
- Interactive user interface with Streamlit
- Scalable to include data from various NBA teams and seasons
- Our app: A live demo of our app
- nba_api: An API for accessing NBA data
- Plotly: A graphing library to create interactive visualizations
- Streamlit: A framework to build interactive web apps with Python
- Clone the repository:
git clone https://github.com/man-bug/nba-study-103.git streamlit run app.py