I am trying to rename multiple variables at once using Dplyr. Here is what the data looks like:
ID Satisfaction_Baseline Satisfaction_FollowUp Satisfaction_Exit
1 1 3 4
2 5 5 5
3 5 3 4
4 5 3 2
5 5 3 5
There is a lot of variables that have '_Baseline', '_FollowUp' and '_Exit'. I really would like a shorthand way to rename variables at once so the data looks more like this:
ID Satisfaction_1 Satisfaction_2 Satisfaction_3
1 1 3 4
2 5 5 5
3 5 3 4
4 5 3 2
5 5 3 5
I tried this:
rename(D_wide, Satisfaction_1 = Satisfaction_Baseline)
This works... but I wanted to know if there was a succinct way to write this piece of code so every variable that ends with '_Baseline', '_FollowUp' and '_Exit' end with '_1', '_2' and '_3'. Thank you!
1) dplyr Since there are only a small number of keywords (Baseline, FollowUp and Exit) we can simply pipe the second argument of rename_with through three sub calls. If the keywords do not appear in other column names as is the situation here we could optionally omit the $ signs.
library(dplyr)
df %>%
rename_with(. %>%
sub("Baseline$", 1, .) %>%
sub("FollowUp$", 2, .) %>%
sub("Exit$", 3, .)
)
giving
ID Satisfaction_1 Satisfaction_2 Satisfaction_3
1 1 1 3 4
2 2 5 5 5
3 3 5 3 4
4 4 5 3 2
5 5 5 3 5
2) purrr Alternately the same code works with set_names in place of rename_with . In this case dplyr is not used.
library(purrr)
df %>%
set_names(. %>%
sub("Baseline$", 1, .) %>%
sub("FollowUp$", 2, .) %>%
sub("Exit$", 3, .)
)
3) Base R To ensure that we only need to write df once at the beginning so as to maintain the left to right nature of the pipe create a list with a single component data. Then we can use data multiple times in the following line.
df |>
list(data = _) |>
with(setNames(data, names(data) |>
sub("Baseline$", 1, x = _) |>
sub("FollowUp$", 2, x = _) |>
sub("Exit$", 3, x = _)
))
4) Reduce This Base R variation uses Reduce with a list L whose names are the keywords and whose values are to replace them. Then use Reduce to repeatedly apply sub.
L <- list(Baseline = 1, FollowUp = 2, Exit = 3)
df |>
list(data = _) |>
with(setNames(data,
Reduce(\(x, nm) sub(nm, L[[nm]], x), names(L), init = names(data))))
5) gsubfn Create a list L as in (4) whose names are the keywords and whose values are to replace them. Then use setNames with new names computed using gsubfn. Pass gsubfn a pattern that matches substrings not containing underscore and ending at the end of the string. It will look for matches to that pattern and any that equal a name in L will be replaced by the corresponding value in L.
library(gsubfn)
L <- list(Baseline = 1, FollowUp = 2, Exit = 3)
df |>
list(data = _) |>
with(setNames(data, gsubfn("[^_]+$", L, names(data))))
The input in reproducible form:
df <- data.frame(
ID = 1:5,
Satisfaction_Baseline = rep(c(1L, 5L), c(1L, 4L)),
Satisfaction_FollowUp = c(3L, 5L, 3L, 3L, 3L),
Satisfaction_Exit = c(4L, 5L, 4L, 2L, 5L)
)