I'm a little at odds on this--for production quality analyses, (and only for analyses) R is excellent.

However, in my experience, for the data munging required as a preliminary to the analyses, R is worse than bad. It's as if satan himself designed a language.

I find that what then happens is this: data scientists/statisticians/[your favorite word here] become reliant on programmers to clean/format the data to do the analyses.

This is all fine, but those same scientists are then put off learning python, where they could do all of their own munging, and probably 95% of the analysis they need to do, and where they could further add value by writing programs that are easier to production-alize.

Job security for those who know how to write production code, I guess.