This guide serves as an update to my original nflscrapR Python Guide. A new R library has been created, appropriately titled nflfastR, which speeds up the process of scraping new play by play data.
Using Jupyter Notebooks or Jupyter Lab, which come pre-installed with Anaconda is typically the best way to work with data in Python. This guide assumes you are using the Ananconda distribution and therefore already have the required packages installed. If you are not using the Anaconda distribution, install the required libraries mentioned throughout the guide. Once Anaconda has been downloaded and installed, open the Anaconda Navigator. Click launch on the Jupyter Notebook or Jupyter Lab section which will open in your browser.
Since the nflfastR data is largely the same as nflscrapR, the process to analyze and plot it is nearly identical.