Please note that this post is, yes, “under construction” as I compile various notes from across my file system and decide what’s worth keeping here and what’s going into the virtual trash bin.
If, like me, you are not very familiar with R and thus you do not readily grasp how
pandas brings much of R’s coolness to Python data analysis workflows, then having the occasional overview and/or cheat sheet on hand is useful.
For overviews, I found the following really helpful in understanding how
pandas organizes data and the methods available for working with it:
For quick tips that border on almost being cheat sheets, there is Chris Albon’s “Technical Notes on Using Data Science & Artificial Intelligence to Fight for Something That Matters”, at the bottom of which is a compendium of great tutorials and tips on using pandas. (And as you scroll, you glimpse a lot of other really useful stuff as well.)