We will start by finding and analyzing relevant data in a Jupyter notebook. We will drag-and-drop our notebook cells into a grid layout, and publish it as a standalone web app. We will add interactivity to our notebook and redeploy our app as we iterate.

See http://bit.ly/29QutMB for a complete overview and video of the finished application.

Attendees should bring a laptop with a modern web browser preinstalled. We will provide the software and hosting necessary to complete the tutorial. All of the tutorial material will be made available on GitHub for review after the session. We will assume attendees are familiar with Jupyter Notebook and common libraries in the Python scientific ecosystem (e.g., pandas).