vscode-R VS fasteR

Oh - nice, thanks - so it looks like the interactive window is also possible, but not (yet) 'properly'/'officially' supported

https://github.com/REditorSupport/vscode-R/issues/1412

See here.

That one covers most of it but the fuller wiki is here - which is linked in that one. Often, for open source software, it’s worth looking at the GitHub/GitLab pages for documentation / links to documentation.

Nothing worked, even setting env variables etc and even setting the knit command as stated in this thread in the VSCode settings: Cannot find pandoc VSCode knit

R works very well in vscode using the vscode-r extension.

If you haven't used it recently, the R VSCode extention is at a state now where's it's much faster and performant than VS Code, especially with the radian addon as noted in the repo.

I'm not an RMarkdown user, but I do know that almost all of my R in VSCode setup came from following the advice of RenKun, and one of his more recent blog posts on his recommended extensions for running R in VSCode included Live Preview as an alternative way for rendering large RMarkdown files in VSCode. See also here.

I would give vscode with the R extension a go sometime if you fancy trying something other than vim (but if you're happy with vim just be happy with vim!).

Personally I would look to vscode with the vscode-r extension. It’s really nice and one of its reasons for existence is making it easier to work with R instances on a server. See here.

Everybody uses the Yuki Ueda extension, so just go here and follow the installation instructions for your operating system.

The good/bad news is that R has become so popular that there is a overabundance of resources you can use to learn it. Here are a few that helped me get started (though they may be dated at this point, ymmv): [1] [2] [3] [4] [5].

Start with fasteR, then move to Hands on Programming with R and R for Data Science. There is considerable overlap in the early chapters so don’t be afraid to skip parts. If you want to know more about the nuts and bolts of R then try Advanced R.

This tutorial is very good for starters. As is this book.

If you’re sure you need to be focussed on tidyverse then the seminal text would be R for Data Science. If you want even more basics than that then I would start with this link, and a book like Hands on Programming with R.

I’m taking a special topic ECS course and we use R here the profs quick start course https://github.com/matloff/fasteR

Recently I’ve favoured recommending this as one of the best ways to get up to speed with the main basics as quickly as possible. But be prepared that this really is just the start, and you will need to follow the recommendations here or elsewhere for further learning.

Check out his free course on GitHub where you'll see he walks you through getting right into learning R, keeping things simple by using the R Gui command line: https://github.com/matloff/fasteR

For R - the free book "R for Data Science", https://github.com/matloff/fasteR , and the data.table vignettes (I personally prefer using data.table than tidyverse, although there are some useful functions in tidyverse)