3.13 Pipes: Exposition Pipe

20210103 The exposition pipe %$%. is useful for commands that do not take a dataset as their argument but instead operates on vectors (such as columns from the dataset). An exposition pipe evaluates the following function within the context of the dataset passed to it, so that the variables of the dataset become available without the need to quote them. In our example we determine the correntlation between two columns, using stats::cor():

ds %>%
  filter(rainfall==0) %>%
  na.omit() %$%
  cor(min_temp, max_temp)
## [1] 0.7525428

Without an exposition pipe we might otherwise use base::with():

ds %>%
  filter(rainfall==0) %>%
  na.omit() %>%
  with(cor(min_temp, max_temp))
## [1] 0.7525428


Your donation will support ongoing development and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984.
Copyright © 1995-2021 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0.