I would like to use mutate to add new columns to a data.frame based on specific colums divided by another column and keep the originalname plus a fixed pattern.
mtcars$mpg_HorsePower = mtcars$mpg / mtcars$hp
mtcars$cyl_HorsePower = mtcars$cyl / mtcars$hp
mtcars$disp_HorsePower = mtcars$disp / mtcars$hp
head(mtcars)
# mpg cyl disp hp drat wt qsec vs am gear carb mpg_HorsePower cyl_HorsePower disp_HorsePower
# Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 0.1909091 0.05454545 1.454545
# Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 0.1909091 0.05454545 1.454545
# Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 0.2451613 0.04301075 1.161290
# Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 0.1945455 0.05454545 2.345455
# Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 0.1068571 0.04571429 2.057143
# Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 0.1723810 0.05714286 2.142857
I was hoping that something like this
mtcars %>%
mutate_at(vars(mpg:disp), funs(. / hp))
would work but does nothing.
Using dplyr::across you could achieve your desired result like so:
library(dplyr, w = FALSE)
mtcars2 <- mtcars %>%
mutate(across(mpg:disp, list(Horsepower = ~. / hp)))
head(mtcars2)
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
#> Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
#> mpg_Horsepower cyl_Horsepower disp_Horsepower
#> Mazda RX4 0.1909091 0.05454545 1.454545
#> Mazda RX4 Wag 0.1909091 0.05454545 1.454545
#> Datsun 710 0.2451613 0.04301075 1.161290
#> Hornet 4 Drive 0.1945455 0.05454545 2.345455
#> Hornet Sportabout 0.1068571 0.04571429 2.057143
#> Valiant 0.1723810 0.05714286 2.142857