I will start:

a) as.Date(“2022-Jul-01”, format =“%Y-%b-%d”) will or will not work depending on os language

b) how R handles diacritics and encoding differently on Linux and on windows

c) Rstudio :D

4 points
*

Re: c) I will be a dirty shill for VSCode and R lol, example here. I find it much better for R shiny development, projects with multiple people and projects with multiple languages. Notebook support is less good out of the box, you will have to get a jupyter kernel set up - but I use scripts more so than notebooks anyway.

Anyway, onto the question! Base R. Yeah, I said it! Whenever I have a weird enough situation where tidyverse functions won’t work due to poor quality data, then I shed a single solemn tear and quietly wish I had done the project in python as I start writing a for loop in what will no doubt be the most hacky solution ever.

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3 points

Lack of gpu-enabled cross-platform functionality

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1 point

With C, Jetbrain’s DataSpell supports R, though it is primarily Python, and the EAP version is free, though you will have to reinstall every month.

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0 points
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Everything. R is an absolute disaster on a lot of aspects.

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2 points

utf Support under windows (which is not r’s fault) which might/will be (is already?) fixed

the rate at which packages change, sometimes breaking stuff (renv to the rescue)

how my place does not invest in proper integration but uses various scripts stored on a network drive with absolutely no documentation

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R Programming

!r_programming@programming.dev

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Please use this as a forum to discuss R, and learn more about it. If you have any questions about how to do specific things in R, this is the place to ask.

Getting Started

You can download R here.

You can download RStudio here. RStudio IDE, which is supported by Posit PBC, is a powerful and well-developed IDE for R. Other development environment options include Emacs addon Emacs Speak Statistics and VSCode.

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Other communities that may be of interest across the fediverse:

Please send @a_statistician a message to recommend additional communities to add to this list.

Learning resources:

  • R for Data Science - a good introductory book for learning R. Start here if you’re overwhelmed.
  • Big Book of R - collection of more than 500 online books/tutorials covering various aspects of R. Some links are to paid books with previews, but most links are to free online textbooks.

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