What is the best introduction to R for beginners with no previous programming experience?
Is this the correct way to create a list values?
How to create a correlation matrix without using the data source to call each variable?
Help with function convert.inp in RMark
How to assign categorical variables to specific rows of data
Error in file.choose() file choice cancelled
Mutate and replace strings to new column
Multiple scatterplot in one graph & multiple Facet_wrap plots
I’m obviously biased but I’d like to also suggest my Computerworld Beginner’s Guide to R at https://www.computerworld.com/article/2497143/business-intelligence/business-intelligence-beginner-s-guide-to-r-introduction.html
I found The Art of R Programming to be good for helping me figure out what people with programming backgrounds were talking about when I started. Good book if you are already committed to learning R.
If I meet some one who is considering learning R, I usually direct them to R for Cats for an intro.
I think, if you’re using R4DS with no programming experience, some kind of class structure is likely necessary. As it says in the prerequisites:
I’ve been doing some amount of programming for about 2/3rds of my life at this point, so I have trouble getting into the mindset of no programming experience at this point, but I think this rings true. However, a dedicated learner with a good human resource could probably handle it.
That said, I’m not entirely convinced that R is the good place to start if you are a brand new programmer. Base R is a bit obtuse and full of dragons, while tidyverse-ish programming is so new and evolving rapidly. R is also approaching Perl 5 for TMTOWTDI-ishness, which is great from my perspective but can be highly confusing for someone that can’t judge whether the method that they’ve found is really a “good” way to do it.
Thank you for all the links. I’m doing a short course where r4ds and Stat545 is a big source of inspiration. Since time is short I would like for people to be familiar with RStudio and the very basics. I was suggested swirl on twitter and I think it could be a good fit as participants are forced to install and use R beforehand, it’s for the very basics and it can be completed in reasonable time.
No bias at all. You won’t believe how many I have send the link to your intro. It’s been a favourite for a long time.
STAT545? Never heard of it…
Legit one of my most visited pages on the internet…
These are all wicked resources.
I will recommend R Programming for Data Science by Roger Peng, which is something of a companion to Coursera’s R Programming course. It starts with an R history lesson of sorts, which many newcomers appreciate (standing on the shoulders of giants and all that).
For those with no prior programming experience, I would probably (no-one hit me) advocate for this one before R4DS, because it guides you in right from the point of installing the software.
When it comes time to actually brave R in the flesh, I found swirl great for just getting practice using the real thing.
haha, yes! I’m constantly doing “thing I need to do in R” + “Jenny Bryan”
Another alternative that worked for me is to find a course focused on something else (such as an introduction to analytics or machine learning) that uses R and assumes low/no prior experience with the language. It’s a steeper learning curve than following resources purely intended for teaching the fundamentals of R, but it gives you practical experience using it. You can then use the beginner language resources to focus on areas you don’t understand.
Two courses I enjoyed whilst learning R were
Yes! Selectively adding “hadley” or “yihui” to searches can be very effective as well!
Agree. I often suggest both this and R4DS and explain the difference in approach.
I found vignettes for the various tidyverse packages (and data.table) along with various blogs found through twitter #rstats and http://blog.revolutionanalytics.com/ the most useful to allow me to copy and adapt examples initially.
I highly recommend DataCamp’s Intro to R. Its a great course and allows you to test your skills along the way.
That’s the target audience of my book: https://www.manning.com/books/data-munging-with-r
I’m taking a slow approach to teaching the programming concepts from the ground up framed by common data analysis in R. I’ve incorporated as many pain points as I could gather from experience and community suggestions so someone coming from a spreadsheet world can get pretty confident & competant by the end of it.
Time will tell if I’ve done it well, but feedback so far is positive.