Research data in python thoughts

[jack89roberts]

A few thoughts I had after teaching part of research data in python:

• Consider replacing/modifying the Earthquakes example (and a lot of the first half) to be an analysis in pandas (#12), maybe similar in style to some of the software carpentries lessons.
• Add visualisation exercises.
• Add an exercise using NumPy broadcasting. Probably remove the mind-bending example of recreating matrix multiplication with broadcasting.
• Boids example is very hard to explain the various components of, although it's a really cool example. Could it be modified to be simpler (maybe including exercises so students build it up themselves)?
• To accommodate all the above, maybe reduce the amount of time spent on directly interacting with/parsing different file formats. E.g. Maybe just one/two notebooks on reading text files, JSON and YAML (CSVs dealt with in pandas). But keep something about interacting with the internet.

[jemrobinson]

@jack89roberts Would you be interested in adding some of this material before we next teach this course (Jan 2022)? I've split the first two modules into three and I imagine this could fit into either Module 2: Intermediate Python or Module 3: Research Data in Python.

[jack89roberts]

I'm happy to have a look after the RDS course has finished (in a couple of weeks) @jemrobinson, but I'll be on leave from mid-December so I won't have a huge amount of time to make changes.