I really am curious why anything "R" and "Tutorial" gets massively upvoted to the Top 3 of HN like clockwork nowadays. I might have to restart my R tutorial screencasts since there appears to be a demand. :P

Same thing I was wondering. Is it simply that R is gaining popularity among a more mainstream audience, while it hasnt changed that much recently ?

A quick example of my own notebook which uses margittr/dplyr heavily to process Stack Overflow survey data: https://github.com/minimaxir/stack-overflow-survey/blob/mast...

However, I mean I just searched for an R script on kaggle and the first I found is this: https://www.kaggle.com/bpavlyshenko/grupo-bimbo-inventory-de...

From my experience that is a typical example (data.table is very common, but not so much dplyr and the pipes).

I looked through the recent/featured questions on stack overflow and cross validated and saw only "old school" R as well. For example: http://stats.stackexchange.com/questions/228800/

If I had to use R as a daily driver now it'd be like learning the language all over again. I could write it using the old ways, and u do that on the few occasions I have to, but it's no longer idiomatic at all

> library(codetools) > showTree(quote(1+23+45)) (+ (+ 1 ( 2 3)) (^ 4 5))

See also the R-to-LISP compiler: http://dan.corlan.net/R_to_common_lisp_translator/

http://swirlstats.com/

  > a[1-3]
  [1] 1 3
  > a[[1-3]]
  Error in a[[1 - 3]] : attempt to select more than one element

re: the Assignment operator http://www.studytrails.com/R/Core/AssignmentOperator.jsp

> However, there is a difference between the two operators. = is only allowed at the top level i.e. if the complete expression is written at the prompt. so = is not allowed in control structures. Here's an example:

      > if (aa=0) {print ("test")}
      Error: unexpected '=' in "if (aa="
      > aa
      Error: object 'aa' not found
      > if (bb<-0) {print ("test")}
      > bb
      [1] 0

http://adv-r.had.co.nz/Style.html

> Use <-, not =, for assignment.

(an assignment operator that isn't an equals sign is one of the things I miss most when switching away from R)

From the next chapter, Listing Objects: http://www.studytrails.com/R/Core/ListingObjects.jsp

> All entities in R are called objects. They can be arrays, numbers, strings, functions.

This may technically be the case, but any R tutorial that does not open up with what makes R different from other mainstream languages is doing the reader a major disservice. This Listing Objects chapters shows patterns that use R in ways that I haven't seen used in other R examples (beginner and advanced). Even if it's correct, what's the point in showing esoteric examples unless this tutorial is meant to teach R to someone interested in the design of languages?

Again, Wickham's Advanced R book handles this topic well (in fact, Advanced R is probably the best book you can read if you already know how to program -- it is incredibly accessible) in his early chapter on Data structures: http://adv-r.had.co.nz/Data-structures.html

> R’s base data structures can be organised by their dimensionality (1d, 2d, or nd) and whether they’re homogeneous (all contents must be of the same type) or heterogeneous (the contents can be of different types). This gives rise to the five data types most often used in data analysis...Almost all other objects are built upon these foundations. In the OO field guide you’ll see how more complicated objects are built of these simple pieces.

And this next sentence is the one thing I wished someone had printed out and stapled to my forehead before I started to learn R:

> Note that R has no 0-dimensional, or scalar types. Individual numbers or strings, which you might think would be scalars, are actually vectors of length one.

Maybe that's self-evident to other programmers, but even as someone who once programmed in MATLAB, I was stunningly ignorant I was of how every return value I interacted with was a vector, even a single simple string. In retrospect, the interactive shell alludes to this...but I didn't even bother looking up the details about the shell:

         > 2 + 2
         [1] 4
         > 'a'
         [1] "a"

I wish people would spend more time reading the official language reference instead of all these half-baked tutorials.

The HTML documentation is intimidating. Not that these are bad things. Science is complicated, and it needs complicated tools.

These tutorials allow(half-baked or not) a casual insight into to complex subject matter.

[0]: https://cran.r-project.org/manuals.html

If you are just doing interactive work RStudio and jupyter with well-stocked support libraries are about equivilant to me.

If you want to do something not all that popular (eg. conjoint analysis) or something cutting edge (duplicating recent research results), R is pretty much the only way to go.

Why? Shouldn't you be able to do that in Python (or MATLAB if that's your thing)?