The NBA Player Statistic Explorer is a data analysis and visualization project focused on the National Basketball Association (NBA). This project aims to provide an interactive and informative platform for basketball enthusiasts analysts and fans to explore and understand NBA player statistics team performance and standings.

• Player Statistics: Access and analyze detailed statistics for NBA players including metrics such as points scored rebounds assists steals blocks field goal percentage and more. Users can search and compare for specific players and visualize their performance over time.
• Interactive Data Visualization: The project leverages data visualization libraries such as Matplotlib and Seaborn to create interactive charts and graphs. Users can explore player and team performance visually making it easier to spot trends and patterns.
• Streamlit App: The entire project is deployed as a Streamlit web application making it accessible via a web browser. Users can interact with the app's user-friendly interface input their preferences and view statistics and visualizations in real-time.

Overall the NBA Player Statistic Explorer project aims to offer an engaging and informative experience for NBA enthusiasts. It provides a platform to gain insights into player and team performance follow the latest standings and explore the exciting world of NBA basketball through data-driven analysis and visualization.

https://nba-player-statistic-explorer.streamlit.app/

Technologies used in the project:

• Python
• BeautifulSoup
• Streamlit
• base64
• Numpy
• Pandas
• Seaborn