How can I use the pipe operator to pipe into replacement function like colnames()<-
?
Here's what I'm trying to do:
library(dplyr)
averages_df <-
group_by(mtcars, cyl) %>%
summarise(mean(disp), mean(hp))
colnames(averages_df) <- c("cyl", "disp_mean", "hp_mean")
averages_df
# Source: local data frame [3 x 3]
#
# cyl disp_mean hp_mean
# 1 4 105.1364 82.63636
# 2 6 183.3143 122.28571
# 3 8 353.1000 209.21429
But ideally it would be something like:
averages_df <-
group_by(mtcars, cyl) %>%
summarise(mean(disp), mean(hp)) %>%
add_colnames(c("cyl", "disp_mean", "hp_mean"))
Is there a way to do this without writing a specialty function each time?
The answers here are a start, but not exactly my question: Chaining arithmetic operators in dplyr
You could use colnames<-
or setNames
(thanks to @David Arenburg)
group_by(mtcars, cyl) %>%
summarise(mean(disp), mean(hp)) %>%
`colnames<-`(c("cyl", "disp_mean", "hp_mean"))
# or
# `names<-`(c("cyl", "disp_mean", "hp_mean"))
# setNames(., c("cyl", "disp_mean", "hp_mean"))
# cyl disp_mean hp_mean
# 1 4 105.1364 82.63636
# 2 6 183.3143 122.28571
# 3 8 353.1000 209.21429
Or pick an Alias
(set_colnames
) from magrittr
:
library(magrittr)
group_by(mtcars, cyl) %>%
summarise(mean(disp), mean(hp)) %>%
set_colnames(c("cyl", "disp_mean", "hp_mean"))
dplyr::rename
may be more convenient if you are only (re)naming a few out of many columns (it requires writing both the old and the new name; see @Richard Scriven's answer)