[dcreater]

I was a huge fan of RStudio and was pretty much the biggest reason I used R. But then I realized how bad R is, syntactically, and how much more useful Python and it's ecosystem are. Then I discovered VS code and Jupyter notebooks in VS code which completely sealed the deal. So unless you are in need of specific R data science packages, Python seems like the way to go. I'm quite excited to try Positron!

[wdkrnls]

R has the best syntax of any language I have used. What I hate about R is not the syntax, its all the functionality inside it that was written in hairy C and FORTRAN style. Unfortunately, any system gets written on top of by programmers of legacy systems. The syntax and semantics of R are probably the most elegant of any language I have used. The rules are extremely simple, logical, and transparent and are largely inherited from Scheme. The amount of power it gives developers is unparalleled outside of Common Lisp. So much can be redefined by users. It really is at its core a LISP wrapped in C clothing, but better because few people working on R care at all about compiler optimization. Instead, they all care about late binding and introspection so programmers can figure out what their code is doing. If speed is needed, use C++ (Rcpp). However, in practice R is usually fast enough. Somehow the R developers understood Knuth's proverb that premature optimization was the root of all evil (and wasted effort), but the rest of the world forgot.

[extr]

I don't know. I bought into the Python hype and after a few years I've found myself missing R. If you're using the full python ecosystem more power to you...but for straight up data analysis and statistics, R is unbeatable.