Understanding the difference between warnings and errors

• A warning is an indication that the data or arguments isn't quite what the function expected.

  • You can usually run the code, but you should be careful about it and verify the output.

• An error means that the code can't execute at all given what you have given the function.

  • Errors can be difficult to understand, which is why...

Googling is StandaRd pRactice foR eRRors

The first thing I do when I encounter an error is to search for the error. I usually start with Google.

I don't know everything, and the odds are that I made a mistake in understanding the documentation.

There are some resources that I especially check (in order):

• google "question + rcran" (i.e "hist rcran" or "make a boxplot ggplot")
• google error in quotes (i.e. "Evaluation error: invalid type (closure) for variable '*'")
• RStudio Community (for tidyverse)
• Stack Overflow #r tag
• Biostars (for Bioinformatics)
• The package's github page (especially issues)
• Advanced search github for your function name to see examples or search the error

Have someone else look at your code

• We all have blind spots
• Someone else can more easily find the misplaced {}, (), or misspellings

Usually, the error you're looking for is at the bottom

There will usually be a bunch of errors generated, but

The one you're interested in is usually the last one.

Where do I ask for help?

I'm trying to be as helpful as I can, but I can't answer all of your questions.

The following communities are extremely helpful to beginners:

• R for Data Science Online Learning Community
  • Join here: http://r4ds.io/join
  • Join the slack channel!
• Rstudio community
  • to pick on my friend/coworker Emile, an example
• twitter #rstats

dplyr cheatsheet

dplyr cheatsheet

dplyr cheatsheet

Old version: https://rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf

New version: https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-transformation.pdf

(tidyr has been separated into a separate cheetsheet: https://www.rstudio.com/resources/cheatsheets/)