Supercharge your R code with wrapr
I would like to demonstrate some helpful wrapr R notation tools that really neaten up your R code. Img: Christopher Ziemnowicz.
My advice on dplyr::mutate()
There are substantial differences between ad-hoc analyses (be they: machine learning research, data science contests, or other demonstrations) and production worthy systems. Roughly: ad-hoc analyses have to be correct only at the moment they are run (and often once they are correct, that is the last time they are run; […]
Is dplyr Easily Comprehensible?
dplyr is one of the most popular R packages. It is powerful and important. But is it in fact easily comprehensible?
More on “The Part-Time R-User”
I have some more thoughts on the topic: “the part-time R-user.”
Let’s Have Some Sympathy For The Part-time R User
When I started writing about methods for better "parametric programming" interfaces for dplyr for R dplyr users in December of 2016 I encountered three divisions in the audience: dplyr users who had such a need, and wanted such extensions. dplyr users who did not have such a need ("we always […]