[closed]

Articles like these are interesting, but what surprises me is that they rarely set up a holistic use case, so most debates imagine how long it would take an expert user to use each tool. But time constraints (eg spent coding) separates expert from novice performance in many domains.

FWIW I have 2020 set aside to implement siuba, a python port of the popular R library dplyr (siuba runs on top of pandas, but also can generate SQL). A huge source of inspiration has been screencasts by Dave Robinson using R to analyze data he's never seen before lightning fast.

Has anyone seen similar screencasts with pandas? I suspect it's not possible (given some constraints on its interface), but would love to be wrong here, because I'd like to keep all my work in python :o.

Expert R screencasts: https://youtu.be/NY0-IFet5AM

Siuba: https://github.com/machow/siuba

[sixhobbits]

David Robinson is great and you won't easily find material of the quality he produces elsewhere.

Take a look at Jake Vanderplas and Joel Grus's stuff for a general 'people doing cool things with Python' theme, but not quite comparable.