Nice R Code

Punning code better since 2013


  • Introduction to R
    • Included in R / RStudio (Help: R Help: “An introduction to R”). An hour or two spent reading this and following along will pay itself back over and over.
  • R help (mailing list)
    • All the experts are there so can be great, but can be scary, especially for newbies. Bad reputation, deservedly so, unfortunately.
  • “Special interest group” mailing lists
    • Most field specific, often friendlier (e.g. r-sig-phylo.
  • Stack overflow
    • R is hard to google for
    • Stack overflow makes searching easy by using tags.
    • Lots of good answers to stuff, so search well
  • Rseek
    • Also helps with the google problem, but can be clunky to use.
  • Your labgroup and peers
    • This is where the best support always happens. People in your lab have suffered through the same learning curve that you are, or have solved the same problem, or are interested in knowing how to solve the same problem. Talk to each other.
  • Various tutorial documents exist across the internet, of varying quality.
    • This recent one is nice, but very rapid and covers about 95% of everything you need to know (do note the filename, though)
    • Google R course
    • Nikhil Gopal’s guerilla guide to r
  • Hadley Wickham’s “devtools” wiki. More advanced, but nice when you’re looking to extend yourself.
  • The #rstats hashtag on twitter.
  • The online help built into R
    • There are extensive help pages for all functions: to access them, type ? before a command name (e.g. ?log), or use the help function (this time quoting the name) (help("log")).
    • Note that most of these help pages are quite terse and serve as a reference manual, not as tutorials. There are examples at the bottom of each page that are useful for seeing how functions are used. However, working out what function you need is often half the battle.
  • Also, see Scott Chamberlain’s list of R resources

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