use %>% with replacement functions like colnames()<-

Alex Coppock picture Alex Coppock · Jan 23, 2015 · Viewed 38.9k times · Source

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

Answer

Henrik picture Henrik · Jan 23, 2015

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)