Finding unique combinations by row using tidyverse

[turkjr19]

Hi,
I have a data frame with hundreds of rows and 4 columns. I re-created a small sample. I'm looking to get all the unique combinations per row into a data frame of two columns as shown in df_want

Thank you in advance

library(tidyverse)

# data
df <- tibble(
  p1 = c("A", "D"),
  p2 = c("B", "E"),
  p3 = c("C", "F"),
  p4 = c("D", "A")
)

# unique combinations of df by row
df_want <- tibble(
  player = c("A", "A", "A",
             "B", "B", "C",
             "D", "D", "D",
             "E", "E", "F"),
  partner = c("B", "C", "D",
             "C", "D", "D",
             "E", "F", "A",
             "F", "A", "A")
)

[FJCC]

I expect there is a more elegant way to do this.

library(tidyverse)
#> Warning: package 'tibble' was built under R version 4.1.2
df <- tibble(
  p1 = c("A", "D"),
  p2 = c("B", "E"),
  p3 = c("C", "F"),
  p4 = c("D", "A")
)
df
#> # A tibble: 2 x 4
#>   p1    p2    p3    p4   
#>   <chr> <chr> <chr> <chr>
#> 1 A     B     C     D    
#> 2 D     E     F     A

dflong <- df |> mutate(ROW=row_number()) |> 
  pivot_longer(cols = -ROW) |> select(-name)
dflong
#> # A tibble: 8 x 2
#>     ROW value
#>   <int> <chr>
#> 1     1 A    
#> 2     1 B    
#> 3     1 C    
#> 4     1 D    
#> 5     2 D    
#> 6     2 E    
#> 7     2 F    
#> 8     2 A
Nested <- dflong |> group_by(ROW) |>  nest()  

CombFunc <- function(DF) {
  tmp <- combn(DF$value,2)
  tmp <- t(tmp)
  tmp <- as.data.frame(tmp)
  colnames(tmp) <- c("player","partner")
  return(tmp)
}

Combin <- mutate(Nested, Comb= lapply(data, CombFunc))
UNNESTED <- unnest(Combin,cols = Comb) |> ungroup()
df_wanted <- select(UNNESTED, player,partner)         
df_wanted
#> # A tibble: 12 x 2
#>    player partner
#>    <chr>  <chr>  
#>  1 A      B      
#>  2 A      C      
#>  3 A      D      
#>  4 B      C      
#>  5 B      D      
#>  6 C      D      
#>  7 D      E      
#>  8 D      F      
#>  9 D      A      
#> 10 E      F      
#> 11 E      A      
#> 12 F      A

^{Created on 2022-02-22 by the reprex package (v2.0.1)}

[turkjr19]

Thank you. Appreciate the support.