I would like to apply an ifelse function across multiple columns of my dataset and create new "rescored" columns. Here is a sample dataset:
data = data.frame(year = "2021",
month = sample(x = c(1:12), size = 10, replace = TRUE),
C1 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C2 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C3 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C4 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C5 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C6 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C7 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C8 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C9 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE),
C10 = sample(x = c('Off', 'Yes'), size = 10, replace = TRUE))
I would like to apply a function like this across all rows that begin with C:
rescored = data %>%
mutate(T1 = ifelse(C1 == "Off", 1,
ifelse(C1 == "Yes", 0, NA)))
My real dataset has 50 or more rows that need this function applied. Is there a simple way to do this? I've tried using variations on "across" in dplyr like below but haven't been successful. I'm sure there is also an "apply" option.
rescored = data %>%
mutate(across(C1:C50, ifelse(~ .x == "Off", 1,
ifelse(~.x == "Yes", 0, NA))))
Simply do this (You have to use twiddle ~ at the beginning of function statement and not before every argument.)
data %>%
mutate(across(starts_with('C'), ~ifelse( .x == "Off", 1,
ifelse(.x == "Yes", 0, NA))))
year month C1 C2 C3 C4 C5 C6 C7 C8 C9 C10
1 2021 1 1 0 0 1 1 0 0 1 1 1
2 2021 12 1 1 0 0 1 1 1 0 1 0
3 2021 10 1 0 1 0 0 1 0 0 1 1
4 2021 3 0 1 1 1 0 1 0 0 0 1
5 2021 11 1 0 1 1 1 0 1 0 0 0
6 2021 12 1 0 0 1 1 1 0 0 1 0
7 2021 4 0 0 0 1 1 0 1 0 1 0
8 2021 2 0 0 0 1 0 0 0 0 1 0
9 2021 3 0 0 1 0 0 1 0 0 1 0
10 2021 9 1 0 0 0 0 0 1 0 0 0
Or perhaps this, if you want to retain original columns
data %>%
mutate(across(starts_with('C'), ~ifelse( .x == "Off", 1, 0), .names = 'scr_{sub("C", "", .col)}'))
#> year month C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 scr_1 scr_2 scr_3 scr_4
#> 1 2021 7 Yes Yes Yes Off Yes Off Off Yes Yes Yes 0 0 0 1
#> 2 2021 11 Off Yes Yes Yes Yes Yes Off Yes Yes Yes 1 0 0 0
#> 3 2021 1 Yes Yes Off Off Yes Yes Yes Off Yes Yes 0 0 1 1
#> 4 2021 5 Yes Off Off Yes Yes Yes Yes Off Yes Yes 0 1 1 0
#> 5 2021 6 Off Off Yes Yes Off Off Off Yes Off Yes 1 1 0 0
#> 6 2021 12 Yes Yes Yes Off Off Yes Yes Yes Off Yes 0 0 0 1
#> 7 2021 1 Off Off Off Off Yes Off Off Off Yes Yes 1 1 1 1
#> 8 2021 1 Yes Yes Yes Off Off Yes Yes Off Off Yes 0 0 0 1
#> 9 2021 8 Off Yes Off Yes Off Off Yes Yes Yes Yes 1 0 1 0
#> 10 2021 10 Off Yes Off Yes Yes Off Off Yes Off Off 1 0 1 0
#> scr_5 scr_6 scr_7 scr_8 scr_9 scr_10
#> 1 0 1 1 0 0 0
#> 2 0 0 1 0 0 0
#> 3 0 0 0 1 0 0
#> 4 0 0 0 1 0 0
#> 5 1 1 1 0 1 0
#> 6 1 0 0 0 1 0
#> 7 0 1 1 1 0 0
#> 8 1 0 0 1 1 0
#> 9 1 1 0 0 0 0
#> 10 0 1 1 0 1 1
Created on 2021-05-15 by the reprex package (v2.0.0)