[thegginthesky]

When I used R in University (majored in Applied Mathematics and Statistics) I was always awestruck at how every sort of novel modeling technique from GLM, to Beta Regressions, to GARCH, is all easily accessible for free, with proper academic paper and documentation, and with a cohesive standard support.

It was really useful to be able to apply most theory I was learning to actual research datasets. This is what I miss the most since moving to Python.

What I don't miss is R's terrible packaging system and how it made collaborating with colleagues near impossible. I can't count the amount of times I had to debug dependencies on others' script just to be able to move forward with some team project.

[CreRecombinase]

What didn't you like about the packaging system? Even if you hate R the language, R has among the most user-friendly, cross-plaform packaging systems I'm aware of.

[jhanschoo]

https://stackoverflow.com/questions/10947159/writing-robust-...

Historically, the conventional way to write R code was one that tended to result in shadowed names (and hence brittle code).

[Quasimoto3000]

R has actually come a long way on the environments front. Check out “renv” from the good people at RStudio.

Link: https://rstudio.github.io/renv/articles/renv.html