R-vs.-Python-for-Data-Science VS fasteR

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)