Readings: Doing SQL-y Things in R

The goal of these readings is to learn how R can help you quickly get data refined into the format and structure that allows you to focus on and answer your key journalistic questions.


Introduction to dplyr (I didn’t originally assign this, but it’s good.)

Read pp. 50-70, 93-108,  of R Programming for Data Science.

You may also find these these videos and exercises useful.

You might also find it very helpful to make for yourself a “vocab list” with these words and definitions (as they’re used in the context of R):

  • dplyr
  • package
  • select
  • filter
  • arrange
  • rename
  • mutate
  • summarize
  • the pipe operator
  • subsetting
  • loops
  • lapply
  • sapply
  • tapply
  • mapply


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