R GUIs: Which one fits you?

[This article was first published on Statistical Graphics and more » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

The gap of the new “digital divide” between those who only use computers when they are as easy to use as iPads and smartphones and those who like (or at least accept) to type commands to perform jobs, seems to get bigger and bigger.

R – the lingua franca of statistical computing – is exactly such a command-line based language, reasonably well designed but still not GUI based at all. At this point GUIs are the only solution to make R accessible for “generation point-and-click” and bridge the divide.

Personally, I am happy to use all well designed GUIs but as well see the power of language based command line interfaces – you need to work with both to be most effective.
But let’s come to the comparison of the four different frontends for R (in lexicographic order) which try to do more than the built-in standard GUIs for the supported platforms:

(mouse-over the entries in the table to get more details)




R Studio

Technology JAVA tcl/tk KDE Qt
Installation simple simple painful easy
Approach IDE comprehensive comprehensive IDE
Interface SDI MDI (plus R) TDI MDI
Maturity 1.7-5 1.6-3 0.5.5 0.92.44
Console yes yes yes yes
CodeEditor yes no yes yes
Objbrowser yes no yes yes
DataEditor yes via fix() yes no
ModelBrws yes no no no
Logging console console extended console
Plugins via iWidgets yes yes no
Web-Client no no no yes

There are certainly more frontends and features (especially on the technical side) to consider, and not everybody will share my verdict on every point (which I even probably didn’t get completely right), but that’s what comments are for  …

My summary recommendations (regarding the four candidates) are:

  • working styles are very different such that many of the above mentioned issues may be pointless
  • for many of us the built-in GUIs are pretty good already, but differ from platform to platform (so you maybe want to avoid any further hassle)
  • if you are on a Mac, half of the choices are gone already …
  • those who really don’t like to “being helped” by your software, opt for the IDE approaches!
  • those who really don’t want to learn any of the R-syntax and are purely on a user level, use one of the comprehensive approaches – you still might not be too happy though
  • if you hate installation procedures, make sure to avoid RKWard (under Windows)
  • the sleekest GUI is definitely R Studio
  • if the webpage would be wider, I should have certainly mentioned Deducer, which is a comprehensive offspring of JGR.

To leave a comment for the author, please follow the link and comment on their blog: Statistical Graphics and more » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)