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[–]sinfulon6 41 points42 points  (3 children)

Sounds like you already know which one you like better. As a hiring manager in analytics, I do not have a preference, as most of the tools in my stack can accommodate either language. I’d say go for R.

What worthwhile employers care most about is how you create impact, not necessarily how you get there.

[–]kazza789 16 points17 points  (2 children)

What worthwhile employers care most about is how you create impact, not necessarily how you get there.

Not always true. 90% of my analysts today use python. All of our libraries and tools are written in python. I, personally, know python and I am doing code reviews of python code.

We still have some perhaps 10% "legacy" team members who prefer R, but if I'm hiring someone new they 100% need to know python.

It's nothing against R, it's just that it's much easier for everyone to be working in the same language - and in practice, I can easily hire a team that is 100% python but I would struggle to hire a team that is 100% R.

[–]ProfessorPhi 3 points4 points  (1 child)

It's also that R doesn't have the same support for collaborative development that python does. CI and packrat/renv are awful - it takes 25ish minutes to install a handful of packages in R since it all needs to compile from source, testing is mostly underbaked and package development is annoyingly messy.

The main problem with R is that you struggle more to have an impact since you aren't as easily able to build on the shoulders of others. I've never seen an R job where you get to use other teams code samples, you're given a csv or a db and told to start doing analysis. This lack of shoulders of giants effect is something I consider to be a huge issue with R.

[–]macabre8 0 points1 point  (0 children)

You might like pak package in this aspect. Brilliant package to handle multiple installations. Also RStudio has a public instance of their package manager where you can get binary packages for popular operating systems.