[freehorse]

It is a trade-off and a sweet spot has a lot to do with the specific context and background. Run speed matters a lot when the difference is between having to run your code on a dataset for half an hour vs through the whole night. Once you have prototyped your code, you are gonna use it more and more (not to mention runs in order to tweak parameters or validate results), and R's speed is not satisfying enough for my work. Python matlab are easy and fast enough to program in, and much faster for tasks that are computing-heavy. If I was getting into C I would not have saved as much time as I would have put into learning how run eg parallel tasks there safely. Moreover, R is not necessarily faster to program, always; real (ie tidyverse-style) R is quite idiosyncratic, if you come from a programming and not from a statistics background probably it will take more time to learn than it is worth unless it is sth important in your work environment.