Use cheatsheets to refresh your memory and find new functions or plots.

  • In RStudio go to Help > Cheatsheets
    • Data Transformation - Helpful functions for cleaning and arranging your data.
    • Data Visualization - Great reference for all your ggplot’ing options.

From your browser

From within R

Find new packages and functions

  • Search packages in R with CRANsearcher
  • ROpenSci has packages and data for all types of environmental and “scientific” work.
  • For water the USGS shares water quality focused packages on GitHub.


Searching online

  • Google: include r or rstats + "the question"
  • Search or post on + the [r] tag

Inside R

  • Get function help and package info in R with ?arrange() or help(dplyr)



These are a few of the things we personally forget to do all the time and cause 90% of our errors. They’re good first checks if R starts throwing errors or behaving strangely.

  • Make sure all parentheses are balanced so that every opening ( has a corresponding closing ).
  • R doesn’t love \ backward slashes like Windows, check that they didn’t sneak into your expression somewhere. When in doubt use the / forward slash.
  • If you think you have completed typing your code, and instead of seeing the > command prompt at the console you see the + character instead. That’s a good sign that either R is still thinking very-very hard, or it is still waiting for you to complete your expression. You can hit Esc or Ctrl-C to force your way back to the console and try typing your code again.

  • R is very picking about spelling. So are meteorologists when talking about lighting storms.

  • In ggplot we build up plots one piece at a time by adding expressions to one another with the + character. When doing this, make sure the + goes at the end of each line, and not the beginning.

Put the + sign here to make ggplot happy:

ggplot(data = mpg, aes(x = displ, y = hwy)) +

Put it on the next line to make ggplot sad:

ggplot(data = mpg, aes(x = displ, y = hwy))
  + geom_point()

Error messages

Not all error messages are helpful or easy to interpret, but they do seem to be getting better in many R packages. When googling an error message it can help to put the entire message in quotes. For the error below we would search for "Error in fit[5, 100, ] : subscript out of bounds".