The package also has many different API endpoints that it can hit. Each player and Team has an id, and this is generally the best way to identify them when making our API calls later.

The nba_api starts with static data on players and teams. The full Table of Contents is located here. In order to make use of this package, it helps to understand how it is structured. You should see something that looks like this after pressing Enter:Īfter installing, open your favorite IDE (I use Spyder) and we can get started. To install the code open the anaconda prompt, command prompt (windows), or terminal (mac), and type: pip install nba_api I recommend using Anaconda (platform) for most of your data science needs.

We start by installing the nba_api so that it can be used with our version of python. The package is well documented, so after this, you should be able to explore its features on your own. Much of the starter code is distilled from other sources, which I have included if you would like to learn more. After this tutorial, you should be able to install the nba_api module, get player stats, and get team stats. This is a huge package (hah) with many features, and this article should give you a basic understanding of how to use it and what is possible with it. This package is well maintained by Swar Patel, and has good engagement and usage. This is an extremely robust python module that allows you to directly access the NBA.com API.

In this article, I will show you the basics of using the nba_api module in python.

Download nba scores