mutate_at on multiple sets of columns with different functions

Question

I defined functions that have to be applied to different sets of dataframe columns. For example, mtcars I want to apply as.integer() function to columns c("mpg", "cyl") and as.logical() to c("vs", "am")

library(dplyr)

mtcars %>% 
  mutate_at(c("mpg", "cyl"), as.integer) %>% 
  mutate_at(c("vs", "am"), as.logical)

What is the practice, preferably with tidyverse, to save this column sets with corresponding functions and apply them without using mutate_at multiple times.

Answer 1

This is the way I would approach it. Result is a list of matrices that can be used to further overwrite existing columns or create new ones or be used as stand-alone data object.

vars <- list(van = c("mpg", "cyl"),
             tu = c("vs", "am"))
funk <- list(van = as.integer,
             tu = as.logical)

mapply(FUN = function(v, f) {
  sapply(mtcars[, v], FUN = f)
}, v = vars, f = funk, SIMPLIFY = FALSE)

$van
      mpg cyl
 [1,]  21   6
 [2,]  21   6
 [3,]  22   4
 [4,]  21   6
 [5,]  18   8
 ...
$tu
         vs    am
 [1,] FALSE  TRUE
 [2,] FALSE  TRUE
 [3,]  TRUE  TRUE
 [4,]  TRUE FALSE
 [5,] FALSE FALSE
 ...

To overwrite existing columns, you can use "the dreaded" for loop. :)

mtcars[colnames(out$van)] <- out$van
mtcars[colnames(out$tu)] <- out$tu
# in generalized form
for (i in seq_along(out)) {
  mtcars[colnames(out[[i]])] <- out[[i]]
}

> head(mtcars)
                  mpg cyl disp  hp drat    wt  qsec    vs    am gear carb
Mazda RX4          21   6  160 110 3.90 2.620 16.46 FALSE  TRUE    4    4
Mazda RX4 Wag      21   6  160 110 3.90 2.875 17.02 FALSE  TRUE    4    4
Datsun 710         22   4  108  93 3.85 2.320 18.61  TRUE  TRUE    4    1
Hornet 4 Drive     21   6  258 110 3.08 3.215 19.44  TRUE FALSE    3    1
Hornet Sportabout  18   8  360 175 3.15 3.440 17.02 FALSE FALSE    3    2
Valiant            18   6  225 105 2.76 3.460 20.22  TRUE FALSE    3    1

Or do everything in one loop (shorter).

for (i in seq_along(vars)) {
  cls <- vars[[i]]
  f <- funk[[i]]

  mtcars[, cls] <- sapply(mtcars[, cls], FUN = f)
}

> head(mtcars)
                  mpg cyl disp  hp drat    wt  qsec    vs    am gear carb
Mazda RX4          21   6  160 110 3.90 2.620 16.46 FALSE  TRUE    4    4
Mazda RX4 Wag      21   6  160 110 3.90 2.875 17.02 FALSE  TRUE    4    4
Datsun 710         22   4  108  93 3.85 2.320 18.61  TRUE  TRUE    4    1
Hornet 4 Drive     21   6  258 110 3.08 3.215 19.44  TRUE FALSE    3    1
Hornet Sportabout  18   8  360 175 3.15 3.440 17.02 FALSE FALSE    3    2
Valiant            18   6  225 105 2.76 3.460 20.22  TRUE FALSE    3    1

Answer 2

I was about to propose the same approach used by @Roman Lustrik in the last part of his answer, but that got done in between my typing:). While I was here I thought I could give some love to R's switch() function which also does the job.

for (i in colnames(mtcars)) {
    mtcars[, i] = switch(i,
                         mpg = as.integer(mtcars[, i]),
                         cyl = as.integer(mtcars[, i]),
                         vs = as.logical(mtcars[, i]),
                         am = as.logical(mtcars[, i]))
}

> head(mtcars)
                  mpg cyl    vs    am
Mazda RX4          21   6 FALSE  TRUE
Mazda RX4 Wag      21   6 FALSE  TRUE
Datsun 710         22   4  TRUE  TRUE
Hornet 4 Drive     21   6  TRUE FALSE
Hornet Sportabout  18   8 FALSE FALSE
Valiant            18   6  TRUE FALSE

EDIT:

Since the switch() function has side the side effect of removing columns if not given a default value, and the OP asking to retain all columns... here is the solution:

for (i in colnames(mtcars)) {
    mtcars[, i] = switch(i,
                         mpg = as.integer(mtcars[, i]),
                         cyl = as.integer(mtcars[, i]),
                         vs = as.logical(mtcars[, i]),
                         am = as.logical(mtcars[, i]),
                         mtcars[, i]) # just add a default option
}

> head(mtcars)
                  mpg cyl disp  hp drat    wt  qsec    vs    am gear carb
Mazda RX4          21   6  160 110 3.90 2.620 16.46 FALSE  TRUE    4    4
Mazda RX4 Wag      21   6  160 110 3.90 2.875 17.02 FALSE  TRUE    4    4
Datsun 710         22   4  108  93 3.85 2.320 18.61  TRUE  TRUE    4    1
Hornet 4 Drive     21   6  258 110 3.08 3.215 19.44  TRUE FALSE    3    1
Hornet Sportabout  18   8  360 175 3.15 3.440 17.02 FALSE FALSE    3    2
Valiant            18   6  225 105 2.76 3.460 20.22  TRUE FALSE    3    1