This is an index of notebooks I’ve made over the years to explore topics using the Jupyter notebook. Some of these are hosted here, some elsewhere. These are the ones I think are most interesting.

2017.01.26 — Analyzing League of Legends match data using datreant
My colleague Alyssa Adams had collected League of Legends match data from Riot Games’ public API, and she had been using datreant to make it relatively easy to get started asking complicated questions of data while keeping it structured in a traditional filesystem. She asked if I would give a demo of using datreant to her research group, so I put together this notebook. In it, we explore questions around the effect of banning certain characters from use in a match on the match result.
2016.05.09 — Intermediate Python with Pandas
I prepared this notebook for a Software Carpentry workshop at UCSF in which learners had some programming experience, if not necessarily in Python. I pulled together material from two existing lessons to make it, giving both a (rapid) introduction to Python while also immediately getting into the use of pandas to pull insights from a real-ish dataset.
2015.07.28 — Making Prettier Plots
I made this notebook to serve as a primer for new students in the Beckstein Lab, on how to produce quality, publication-ready plots using Python, in particular matplotlib and seaborn. Since what’s currently vogue in data visualization changes rapidly, the detailed bits of this notebook may not stand the test of time for long, but it includes some of the rather timeless insights of Edward Tufte in motivating its decisions.
2015.05.27 — Software Carpentry python lesson at Oklahoma State University
This was my working notebook from my first Software Carpentry workshop, in which I taught a two-part lesson on basic Python. Although (almost) everything in this notebook was covered in a live session, I cleaned it up and added commentary after-the-fact to make it clear as a standalone notebook.

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