This note lists a few places where one can ask R-related questions and get an answer, usually in no more than a few hours.
Anyone who has learnt a programming language has a history of questions that they have asked to:
- themselves – usually followed by a lot of documentation reading
- others, offline – hence the benefits of research labs and offices
- others, online – which is what this note is about.
The standard/traditional way of asking R-related questions has been through its mailing-lists, but other ways to ask (or answer) questions have become very popular.
Aside from being polite and open-minded, asking or answering programming questions online usually also requires providing a minimally reproducible example, or “Minimal Working Example“, or “reprex” – which is the name of a very helpful R package initiated by Jennifer C. Bryan, whose good humour and open-mindedness, visible on her Twitter account and in her many conference talks, are also exemplary.
Where 1. Stack Overflow, email lists
The “Getting Help with R” page describes both mailing-lists and Stack Overflow as the recommended places for R-related questions and answers:
Stack Overflow is a well organized and formatted site for help and discussions about programming. It has excellent searchability. Topics are tagged, and “r” is a very popular tag on the site with almost 150,000 questions (as of summer 2016). To go directly to R-related topics, visit http://stackoverflow.com/questions/tagged/r. For an example both of the value of the site’s organization and information that is very useful to R users, see “How to make a great R reproducible example?”, which is also mentioned above.
R Email Lists
The R Project maintains a number of subscription-based email lists for posing and answering questions about R, including the general R-help email list, the R-devel list for R code development, and R-package-devel list for developers of CRAN packages; lists for announcements about R and R packages; and a variety of more specialized lists. Before posing a question on one of these lists, please read the R mailing list instructions and the posting guide.
Where 2. Community forums
At least two R user communities also run forums, which are more practical to search and follow than mailing-lists, and which are not restricted to asking questions:
- RStudio Community – “A community for all things R and RStudio”
- rOpenSci Discuss – for R users interested in open science
Where 3. Twitter, GitHub
As mentioned in a previous note, Twitter is a great place to learn about recent R-related developments. It is also, in my view, a great place to interact with many R package developers, in a direct and inobtrusive way.
For longer conversations, opening issues on GitHub (or other code) repositories is probably more recommendable. GitHub issues host a wide variety of conversations, not just bug reports: reading them is often extremely informative.
Where 4. Reddit, Slack
A few more places might also be worth considering.
Although there is a dedicated Stack Exchange site for software recommendations, it might not be the best place to ask for (or read about) package recommendations. Perhaps Reddit might be a good place for those, and there are several R-focused subreddits that might suit one’s needs:
- r/rstats – “a place to post R stories, questions, and news”
- r/Rlanguage – a subreddit that “seeks new methods”
- r/rprogramming – for “anything related to R or statistics”
- r/RStudio – “a forum to discuss R”
: thanks again to R Weekly for mentioning this note.
: added the section on community forums, added a mention of Slack channels, and reorganised other sections.