Create column of data frames based on function - r

Question

I would like to use the map function with the tidyverse to create a column of data frames based on arguments from some, but not all, of the columns of the original data frame/tibble.
I would prefer to be able to use the map function so that I can replace this with future_map to utilize parallel computing.
With the exception of this solution not using map, this solution produces the correct end result (see also this question and answer: How to use rowwise to create a list column based on a function):
library(tidyverse)
library(purrr)
df <- data.frame(a= c(1,2,3), b=c(2,3,4), c=c(6,5,8))
fun <- function(q,y) {
r <- data.frame(col1 = c(q+y, q, q, y), col2 = c(q,q,q,y))
r
}
result1 <- df %>% rowwise(a) %>% mutate(list1 = list(fun(a, b)))
> result1
# A tibble: 3 × 4
# Rowwise: a
a b c list1
<dbl> <dbl> <dbl> <list>
1 1 2 6 <df [4 × 2]>
2 2 3 5 <df [4 × 2]>
3 3 4 8 <df [4 × 2]>
How can I instead do this with map? Here are three incorrect attempts:
Incorrect attempt 1:
wrong1 <- df %>% mutate(list1 = map(list(a,b), fun))
Incorrect attempt 2:
wrong2 <- df %>% mutate(list1 = map(c(a,b), fun))
Incorrect attempt 2:
wrong3 <- df %>% mutate(list1 = list(map(list(a,b), fun)))
The error I get is x argument "y" is missing, with no default. And I am not sure how to pass multiple arguments into a situation like this.
I would like a solution with multiple arguments, but if that is not possible, let's move to a function with one argument.
fun_one_arg <- function(q) {
r <- data.frame(col1 = c(q, q, q, q+q), col2 = c(3*q,q,q,q/2))
r
}
wrong4 <- df %>% mutate(list1 = map(a, fun_one_arg))
wrong5 <- df %>% mutate(list1 = list(map(a, fun_one_arg)))
These run, but the fourth columns are not data frames, as I would have expected.

Answer 1

We can use map2 as there are two arguments
library(dplyr)
df %>%
mutate(list1 = map2(a, b, fun)) %>%
as_tibble
# A tibble: 3 x 4
a b c list1
<dbl> <dbl> <dbl> <list>
1 1 2 6 <df [4 × 2]>
2 2 3 5 <df [4 × 2]>
3 3 4 8 <df [4 × 2]>
Or another option is pmap which can take more than 2 columns as well. The ..1, ..2 represents the columns in the same order
df %>%
mutate(list1 = pmap(across(c(a, b)), ~ fun(..1, ..2))) %>%
as_tibble