Subtract and divide using one mutate_across function in dplyr

Question

I have a data set that looks like the iris data set.

  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa
4          4.6         3.1          1.5         0.2  setosa
5          5.0         3.6          1.4         0.2  setosa
6          5.4         3.9          1.7         0.4  setosa

I would like across Sepal.Length:Petal.Width to subtract each value with the number 2 and then divide the outcome by 4. How can I do this in one line with mutate_across in dplyr instead of two?

iris %>% 
  mutate(across(c(Sepal.Length:Petal.Width), ~. -2 )) %>% 
  mutate(across(c(Sepal.Length:Petal.Width), ~. /4 ))

score 6 · Accepted Answer · answered Jul 06 '21 at 11:05

library(dplyr, warn.conflicts = F)
iris %>%
  mutate(across(1:4, ~  (. - 2)/4))
#>     Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
#> 1          0.775       0.375       -0.150      -0.450     setosa
#> 2          0.725       0.250       -0.150      -0.450     setosa
#> 3          0.675       0.300       -0.175      -0.450     setosa
#> 4          0.650       0.275       -0.125      -0.450     setosa
#> 5          0.750       0.400       -0.150      -0.450     setosa
#> 6          0.850       0.475       -0.075      -0.400     setosa
#> 7          0.650       0.350       -0.150      -0.425     setosa
#> 8          0.750       0.350       -0.125      -0.450     setosa
#> 9          0.600       0.225       -0.150      -0.450     setosa
#> 10         0.725       0.275       -0.125      -0.475     setosa
.
.

^{Created on 2021-07-06 by the reprex package (v2.0.0)}

why can't this be `where(is.numeric)` – akrun Jul 06 '21 at 16:42 — akrun, Jul 06 '21 at 16:42
Can be. but OP wanted to shorten the code by 1 step. – AnilGoyal Jul 06 '21 at 16:45 — AnilGoyal, Jul 06 '21 at 16:45

score 4 · Answer 2 · answered Jul 06 '21 at 11:11

Subtraction and division functions can be directly applied to dataframes.

cols <- 1:4
iris[cols] <- (iris[cols] - 2)/4
head(iris)

#  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#1        0.775       0.375       -0.150       -0.45  setosa
#2        0.725       0.250       -0.150       -0.45  setosa
#3        0.675       0.300       -0.175       -0.45  setosa
#4        0.650       0.275       -0.125       -0.45  setosa
#5        0.750       0.400       -0.150       -0.45  setosa
#6        0.850       0.475       -0.075       -0.40  setosa

Thank you Ronak. Neat solutions as always – LDT Jul 06 '21 at 12:00 — LDT, Jul 06 '21 at 12:00

score 1 · Answer 3 · answered Jul 06 '21 at 11:10

1

Another solution is using mutate_at:

iris %>%
  mutate_at(vars('Sepal.Length':'Petal.Width'), funs((. - 2) * 4))

answered Jul 06 '21 at 11:10

denisafonin

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Note that `_if`, `_at`, `_all` have officially been "superseded" (slightly weaker than deprecated) in `dplyr`, and you're encouraged to use `across()` instead. See `vignette("colwise")` : " These functions solved a pressing need and are used by many people, but are now superseded. That means that they’ll stay around, but won’t receive any new features and will only get critical bug fixes." – hdkrgr Jul 06 '21 at 11:51

score 1 · Answer 4 · answered Jul 06 '21 at 16:41

1

An option with map_if

library(purrr)
library(dplyr)
map_if(iris, is.numeric, ~ (. - 2)/4) %>%
     bind_cols

answered Jul 06 '21 at 16:41

akrun

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score 0 · Answer 5 · answered Jul 06 '21 at 17:47

0

We can try base R option like below

cols <- which(sapply(iris, is.numeric))
iris[cols] <- (iris[cols] - 2) / 4

answered Jul 06 '21 at 17:47

ThomasIsCoding

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Subtract and divide using one mutate_across function in dplyr

5 Answers5