I'm a heavy user of R, and I like using it a lot. But the language has lots of traps for beginners: code idioms that look correct but are subtly wrong. For example, if you need to iterate over the indices of a vector X, the obvious thing to do is 1:length(X), looks fine and works fine until you happen to pass a 0-length vector, and then it explodes. Similarly, the obvious way to select a subset of rows i and a subset of columns j from a matrix is X[i,j]. But that's wrong too, because if either i or j has length 1, you get a vector instead of a matrix. And I don't even remember off the top of my head what happens if either or both of i and j has length 0. The R Inferno[1] is essentially a big collection of cases like this.

None of this makes R a bad language, in my opinion. R is far from the only language with surprising edge cases like this. People say that R is designed for statistical analysis more than general programming, but I don't think that's exactly true either. Certainly it excels in writing code for statistical analysis, but I've used R a lot more than that, and I plan to continue. It's a perfectly fine general-use scripting language.

I think the real reason R gets such a bad reputation is that a lot of people writing and publishing R code aren't programmers by trade. And you know what? That's fine. Because I'd much rather work in a community that values and celebrates the publishing of code than one that shames people for releasing their code because it's "not good enough".

[1]: https://www.burns-stat.com/pages/Tutor/R_inferno.pdf