© Thomas Mailund 2019
Thomas MailundR Data Science Quick Referencehttps://doi.org/10.1007/978-1-4842-4894-2_7

7. Manipulating Data Frames: dplyr

Thomas Mailund1 
Aarhus, Denmark
The dplyr package resembles the functionality in the purrr package, but it is designed for manipulating data frames. It will be loaded with the tidyverse package , but you can also load it using

The usual way that you use dplyr is similar to how you use purrr. You string together a sequence of actions in a pipeline, with the actions separated by the %>% operator. The difference between the two packages is that the purrr functions work on sequences, while the dplyr functions work on data frames.

This package is huge and more functionality is added in each new ...

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