Using across() to apply Recode then rescale variables

Question

I would like to first recode a value in a battery of questions and then rescale the results from 0 to 1. I read through here to learn how to apply sequential functions but my results are not rescaled.

var1<-sample(seq(1,11,1), size=100, replace=T)
var2<-sample(seq(1,11,1), size=100, replace=T)
library(tidyverse)
library(scales)
df<-data.frame(var1, var2)
df %>% 
  mutate(
    across(
      starts_with("var"), ~{
    scales::rescale(as.numeric(car::Recode(.x, "11=5"), to=c(0,1)))
    .x
  }
  ))

Consider using dplyr::recode() so you do not need another package dependency. — harre, Jun 06 '22 at 21:19

score 2 · Accepted Answer · answered Jun 06 '22 at 19:16

There are two issues with your code. First, you mis-placed on of your closing parentheses. Second you did not reassign the recoded and rescaled vector back to .x but instead return the original vector.

To fix both issues do:

df %>%
  mutate(
    across(
      starts_with("var"), ~ scales::rescale(as.numeric(car::Recode(.x, "11=5")), to = c(0, 1))
    )
  )
#>          var1      var2
#> 1   0.7777778 0.4444444
#> 2   0.1111111 0.0000000
#> 3   0.7777778 0.2222222
#> 4   0.3333333 0.7777778
#> 5   0.4444444 0.1111111
#> 6   0.4444444 0.7777778
#> 7   0.5555556 0.0000000
#> 8   1.0000000 0.5555556
#> 9   0.6666667 0.8888889
#> 10  1.0000000 0.3333333
#> 11  1.0000000 0.0000000
#> 12  0.0000000 1.0000000
#> 13  1.0000000 0.6666667
#> 14  0.5555556 1.0000000
#> 15  0.3333333 0.4444444
#> 16  0.4444444 0.4444444
#> 17  0.4444444 0.0000000
#> 18  0.3333333 0.3333333
#> 19  0.2222222 0.0000000
#> 20  0.4444444 0.0000000
#> 21  0.6666667 0.4444444
#> 22  0.6666667 0.4444444
#> 23  0.3333333 0.7777778
#> 24  0.5555556 0.6666667
#> 25  1.0000000 0.1111111
#> 26  0.1111111 0.1111111
#> 27  0.7777778 0.3333333
#> 28  0.4444444 1.0000000
#> 29  0.4444444 1.0000000
#> 30  0.8888889 0.8888889
#> 31  0.8888889 0.1111111
#> 32  0.4444444 0.6666667
#> 33  0.4444444 0.3333333
#> 34  0.7777778 0.3333333
#> 35  0.3333333 0.8888889
#> 36  0.1111111 0.8888889
#> 37  0.2222222 0.2222222
#> 38  0.3333333 0.4444444
#> 39  0.4444444 0.0000000
#> 40  0.4444444 0.6666667
#> 41  0.2222222 0.1111111
#> 42  0.3333333 0.1111111
#> 43  0.3333333 1.0000000
#> 44  0.7777778 0.5555556
#> 45  0.6666667 0.3333333
#> 46  1.0000000 0.6666667
#> 47  0.8888889 0.4444444
#> 48  0.5555556 0.5555556
#> 49  0.3333333 0.7777778
#> 50  0.5555556 0.8888889
#> 51  0.4444444 0.4444444
#> 52  0.1111111 0.0000000
#> 53  0.1111111 0.0000000
#> 54  0.5555556 0.4444444
#> 55  1.0000000 0.1111111
#> 56  0.6666667 0.4444444
#> 57  0.8888889 0.6666667
#> 58  0.6666667 0.3333333
#> 59  0.3333333 0.4444444
#> 60  0.6666667 0.5555556
#> 61  0.6666667 0.1111111
#> 62  0.5555556 0.1111111
#> 63  0.8888889 0.2222222
#> 64  0.5555556 0.7777778
#> 65  0.3333333 1.0000000
#> 66  0.4444444 0.4444444
#> 67  0.7777778 0.2222222
#> 68  0.5555556 0.2222222
#> 69  0.2222222 0.6666667
#> 70  0.7777778 0.1111111
#> 71  0.2222222 1.0000000
#> 72  0.1111111 1.0000000
#> 73  1.0000000 0.1111111
#> 74  0.4444444 0.4444444
#> 75  0.8888889 0.4444444
#> 76  0.6666667 0.2222222
#> 77  0.4444444 0.2222222
#> 78  0.8888889 0.6666667
#> 79  0.6666667 0.7777778
#> 80  0.3333333 0.7777778
#> 81  1.0000000 0.7777778
#> 82  0.2222222 0.0000000
#> 83  0.4444444 0.6666667
#> 84  0.1111111 0.4444444
#> 85  0.4444444 0.4444444
#> 86  0.8888889 0.4444444
#> 87  0.7777778 0.4444444
#> 88  0.7777778 0.8888889
#> 89  0.6666667 0.3333333
#> 90  0.1111111 0.2222222
#> 91  0.0000000 1.0000000
#> 92  0.4444444 0.7777778
#> 93  0.0000000 0.6666667
#> 94  0.3333333 0.4444444
#> 95  1.0000000 0.4444444
#> 96  0.4444444 0.0000000
#> 97  0.6666667 1.0000000
#> 98  0.8888889 0.6666667
#> 99  0.4444444 0.6666667
#> 100 0.1111111 0.3333333

Using across() to apply Recode then rescale variables

1 Answers1