Rename multiple columns by names

Someone should have asked this already, but I couldn't find an answer. Say I have:

x = data.frame(q=1,w=2,e=3, ...and many many columns...)  

what is the most elegant way to rename an arbitrary subset of columns, whose position I don't necessarily know, into some other arbitrary names?

e.g. Say I want to rename "q" and "e" into "A" and "B", what is the most elegant code to do this?

Obviously, I can do a loop:

oldnames = c("q","e")
newnames = c("A","B")
for(i in 1:2) names(x)[names(x) == oldnames[i]] = newnames[i]

But I wonder if there is a better way? Maybe using some of the packages? (plyr::rename etc.)

Solution 1:

setnames from the data.tablepackage will work on data.frames or data.tables

library(data.table)
d <- data.frame(a=1:2,b=2:3,d=4:5)
setnames(d, old = c('a','d'), new = c('anew','dnew'))
d


 #   anew b dnew
 # 1    1 2    4
 # 2    2 3    5

Note that changes are made by reference, so no copying (even for data.frames!)

Solution 2:

With dplyr you would do:

library(dplyr)

df = data.frame(q = 1, w = 2, e = 3)
    
df %>% rename(A = q, B = e)

#  A w B
#1 1 2 3

Or if you want to use vectors, as suggested by @Jelena-bioinf:

library(dplyr)

df = data.frame(q = 1, w = 2, e = 3)

oldnames = c("q","e")
newnames = c("A","B")

df %>% rename_at(vars(oldnames), ~ newnames)

#  A w B
#1 1 2 3

L. D. Nicolas May suggested a change given rename_at is being superseded by rename_with:

df %>% 
  rename_with(~ newnames[which(oldnames == .x)], .cols = oldnames)

#  A w B
#1 1 2 3

Solution 3:

Another solution for dataframes which are not too large is (building on @thelatemail answer):

x <- data.frame(q=1,w=2,e=3)

> x
  q w e
1 1 2 3

colnames(x) <- c("A","w","B")

> x
  A w B
1 1 2 3

Alternatively, you can also use:

names(x) <- c("C","w","D")

> x
  C w D
1 1 2 3

Furthermore, you can also rename a subset of the columnnames:

names(x)[2:3] <- c("E","F")

> x
  C E F
1 1 2 3

Solution 4:

Here is the most efficient way I have found to rename multiple columns using a combination of purrr::set_names() and a few stringr operations.

library(tidyverse)

# Make a tibble with bad names
data <- tibble(
    `Bad NameS 1` = letters[1:10],
    `bAd NameS 2` = rnorm(10)
)

data 
# A tibble: 10 x 2
   `Bad NameS 1` `bAd NameS 2`
   <chr>                 <dbl>
 1 a                    -0.840
 2 b                    -1.56 
 3 c                    -0.625
 4 d                     0.506
 5 e                    -1.52 
 6 f                    -0.212
 7 g                    -1.50 
 8 h                    -1.53 
 9 i                     0.420
 10 j                     0.957

# Use purrr::set_names() with annonymous function of stringr operations
data %>%
    set_names(~ str_to_lower(.) %>%
                  str_replace_all(" ", "_") %>%
                  str_replace_all("bad", "good"))

# A tibble: 10 x 2
   good_names_1 good_names_2
   <chr>               <dbl>
 1 a                  -0.840
 2 b                  -1.56 
 3 c                  -0.625
 4 d                   0.506
 5 e                  -1.52 
 6 f                  -0.212
 7 g                  -1.50 
 8 h                  -1.53 
 9 i                   0.420
10 j                   0.957