R dplyr: rename variables using string functions

dplyrrregexrename

(Somewhat related question: Enter new column names as string in dplyr's rename function)

In the middle of a dplyr chain (%>%), I would like to replace multiple column names with functions of their old names (using tolower or gsub, etc.)

library(tidyr); library(dplyr)
data(iris)
# This is what I want to do, but I'd like to use dplyr syntax
names(iris) <- tolower( gsub("\\.", "_", names(iris) ) )
glimpse(iris, 60)
# Observations: 150
# Variables:
#   $ sepal_length (dbl) 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6,...
#   $ sepal_width  (dbl) 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4,...
#   $ petal_length (dbl) 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4,...
#   $ petal_width  (dbl) 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3,...
#   $ species      (fctr) setosa, setosa, setosa, setosa, s...

# the rest of the chain:
iris %>% gather(measurement, value, -species) %>%
  group_by(species,measurement) %>%
  summarise(avg_value = mean(value)) 

I see ?rename takes the argument replace as a named character vector, with new names as values, and old names as names.

So I tried:

iris %>% rename(replace=c(names(iris)=tolower( gsub("\\.", "_", names(iris) ) )  ))

but this (a) returns Error: unexpected '=' in iris %>% ... and (b) requires referencing by name the data frame from the previous operation in the chain, which in my real use case I couldn't do.

iris %>% 
  rename(replace=c(    )) %>% # ideally the fix would go here
  gather(measurement, value, -species) %>%
  group_by(species,measurement) %>%
  summarise(avg_value = mean(value)) # I realize I could mutate down here 
                                     #  instead, once the column names turn into values, 
                                     #  but that's not the point
# ---- Desired output looks like: -------
# Source: local data frame [12 x 3]
# Groups: species
# 
#       species  measurement avg_value
# 1      setosa sepal_length     5.006
# 2      setosa  sepal_width     3.428
# 3      setosa petal_length     1.462
# 4      setosa  petal_width     0.246
# 5  versicolor sepal_length     5.936
# 6  versicolor  sepal_width     2.770
# ... etc ....  

Best Solution

This is a very late answer, on May 2017

As of dplyr 0.5.0.9004, soon to be 0.6.0, many new ways of renaming columns, compliant with the maggritr pipe operator %>%, have been added to the package.

Those functions are:

  • rename_all
  • rename_if
  • rename_at

There are many different ways of using those functions, but the one relevant to your problem, using the stringr package is the following:

df <- df %>%
  rename_all(
      funs(
        stringr::str_to_lower(.) %>%
        stringr::str_replace_all(., '\\.', '_')
      )
  )

And so, carry on with the plumbing :) (no pun intended).