Concisely assign vector output of a function to multiple variables in dplyr

Question

I am trying to assign the vector output (i.e. greater than length 1) of a function to multiple columns in a single operation (or at least as concisely as possible).

Take the range() function for example which returns as output a numeric vector of length 2 denoting the minimum and maximum, respectively. Let's say I want to compute the range() per group and assign the output to two columns min and max.

My current approach is combining summarize followed by manually adding a key and then re-shaping to wide format:

library(magrittr)

# create data
df <- dplyr::tibble(group = rep(letters[1:3], each = 3),
                    x = rpois(9, 10))

df
#> # A tibble: 9 x 2
#>   group     x
#>   <chr> <int>
#> 1 a         8
#> 2 a        12
#> 3 a         8
#> 4 b         9
#> 5 b        14
#> 6 b         9
#> 7 c        11
#> 8 c         6
#> 9 c        12

# summarize gives two lines per group
range_df <- df %>% 
  dplyr::group_by(group) %>% 
  dplyr::summarize(range = range(x)) %>% 
  dplyr::ungroup()

range_df
#> # A tibble: 6 x 2
#>   group range
#>   <chr> <int>
#> 1 a         8
#> 2 a        12
#> 3 b         9
#> 4 b        14
#> 5 c         6
#> 6 c        12

# add key and reshape
range_df %>% 
  dplyr::mutate(key = rep(c("min", "max"), 3)) %>% 
  tidyr::pivot_wider(names_from = key, values_from = range)
#> # A tibble: 3 x 3
#>   group   min   max
#>   <chr> <int> <int>
#> 1 a         8    12
#> 2 b         9    14
#> 3 c         6    12

Is there a more elegant / concise alternative to this?

Edit:

Ideally the alternative solution could handle an arbitrary number of outputs (e.g. if the function returns an output with length 3 then 3 variables should be created).

score 2 · Answer 1 · answered Feb 10 '23 at 16:55

# Writw a small function that does the job:

library(tidyverse)
f <- function(x){
  setNames(data.frame(t(range(x))), c('min', 'max'))
}

df %>%
  summarise(across(x, f, .unpack = TRUE), .by=group)
#> # A tibble: 3 × 3
#>   group x_min x_max
#>   <chr> <int> <int>
#> 1 a        10    13
#> 2 b         7    10
#> 3 c        10    12

If you are using older version of dplyr

df %>%
  group_by(group)%>%
  summarise(across(x, f))%>%
  unpack(x)
#> # A tibble: 3 × 3
#>   group   min   max
#>   <chr> <int> <int>
#> 1 a         6     9
#> 2 b         7    12
#> 3 c         6    10

Note that if you do not want to unpack, you could use the `do` function after the `group_by`. ie `df %>%group_by(group)%>%do(f(.$x))` — Onyambu, Feb 10 '23 at 17:06

S-SHAAF · Answer 2 · 2023-02-10T18:04:38.497

0

set.seed(1)

df <- dplyr::tibble(group = rep(letters[1:3], each = 3),
                    x = rpois(9, 10))

function

g <- function(x){
      data.frame(min = min(x), max = max(x))
    }

calling g:

df %>%
  group_by(group) %>%
  summarise(across(x, g,  .unpack = TRUE))

edited Feb 10 '23 at 18:04

answered Feb 10 '23 at 16:38

S-SHAAF

1,863
2
5
14

1

OP was asking for a solution where the output of the function is a vector. Did you not just replace the input function (range -> min & max)? – Jakob Gepp Feb 10 '23 at 16:41
The question is how to get the output with a shorter script! - reshaping a wide format – S-SHAAF Feb 10 '23 at 16:53
2

The main question is: "I am trying to assign the vector output (i.e. greater than length 1) of a function to multiple columns in a single operation (or at least as concisely as possible)." not to shorten this one example. – Jakob Gepp Feb 10 '23 at 16:56
edited!, still not clear why creating function if it was already exist in the tidyverse. BTW, thanks a lot for your notice. – S-SHAAF Feb 10 '23 at 18:05

score 0 · Accepted Answer · answered Feb 13 '23 at 15:53

Based on onyambu's answer, I build a small generic function for this. There probably will be some edge cases, where this will not work.

out2col <- function(x, fun, out_names = c(), add_args = list()) {
    tmp <- do.call(what = fun, args = c(list(x), add_args))
    out <- data.frame(t(tmp))
    if (length(out_names) != 0) {
      if (length(tmp) != length(out_names)) {
        stop("provided names did not match the number of outputs")
      }
      out <- setNames(object = out, nm = out_names)
    } 
    return(out)
}

Examples without any additional parameters:

df %>%
  summarise(across(x, out2col, .unpack = TRUE, fun = range),
        .by=group)

Output:

# A tibble: 3 × 3
  group  x_X1  x_X2
  <chr> <int> <int>
1 a         7    10
2 b        11    14
3 c         9    14

Examples with additional parameters:

df %>%
  summarise(across(x, out2col, .unpack = TRUE, fun = quantile,
                   out_names = c("min", "max", "Q25"),
                   add_args = list(probs = c(0, 1, 0.25))
                   ),
            .by=group)

Output:

# A tibble: 3 × 4
  group x_min x_max x_Q25
  <chr> <dbl> <dbl> <dbl>
1 a         7    10   7.5
2 b        11    14  11.5
3 c         9    14  10

Concisely assign vector output of a function to multiple variables in dplyr

3 Answers3