Earlier quoted context omitted.
R is pretty pointless though. Unless you want to rewrite everything between prototyping in R and real deployment with a real language, you are better off writing in Python.
That right there is what I am talking about. I make a point and people have to attack that that the language is pointless when it is the number one language in that domain, which just happened the last two years. Why would you ever have to rewrite the code? Python isn't faster and has less function then R and if you want you can just drop a few lines of Python in a cell of a Notebook. I like Python and its a good cho…
That's not true though, R doesn't have anywhere near the ecosystem that Python does for Natural Language Processing, Web Frameworks, Machine Learning, Computer Algebra and Symbolic Reasoning, Systems Programming, Image Processing, Document Processing, and other things I don't know about but if I needed something else then I can use Python confidently that there will be good packages for them with a community around it.
The entirety of R's unique mindshare is that it has a million variations on linear regression and contingency table tests. And frankly they're all so simple to implement that if you can't be bothered to learn how to implement it in 2 lines of Python then you probably don't know what your program is actually doing.
R is something that caught on because it made its statistics package top-level, saving keystrokes for statistics and bio-statistics professors who never needed anything else and didn't know how to otherwise program. It's unique syntax has lead their poor students to have to learn C-family syntax many years after they could have been working and being productive with it.
Now some companies are accommodating R for their entry-level data scientist positions in order to hire cheaper help that can't find better options, but their skills are limited by being disconnected from the rest of the programming world in both packages and syntax.