How to find the column name with max value from a list in R

I have a data like this :

df <- data.frame(Product= paste0("AE", c(1:11)),
                 Condition=c("-","A","A","B","B","B","C","C","C","D","D"),
                 Score1=c(0.231,0.831,0.894,1e-05,1e-05,1e-05,0.874,0.785,0.879,1e-08,1e-08),
                 Score2=c(0.968,0.168,0.105,0.239,0.149,0.125,1e-05,1e-05,1e-05,0.159,0.105),
                 Score3=c(1e-07,1e-07,1e-07,1e-07,1e-07,1e-07,1e-05,1e-05,1e-05,0.855,0.827),
                 Score4=c(1e-07,1e-07,1e-07,1e-07,1e-07,1e-07,0.492,0.500,0.656,1e-08,1e-08))

after split(df, df$Condition) will like :

> split(df, df$Condition)
$`-`
  Product Condition Score1 Score2 Score3 Score4
1     AE1         -  0.231  0.968  1e-07  1e-07

$A
  Product Condition Score1 Score2 Score3 Score4
2     AE2         A  0.831  0.168  1e-07  1e-07
3     AE3         A  0.894  0.105  1e-07  1e-07

$B
  Product Condition Score1 Score2 Score3 Score4
4     AE4         B  1e-05  0.239  1e-07  1e-07
5     AE5         B  1e-05  0.149  1e-07  1e-07
6     AE6         B  1e-05  0.125  1e-07  1e-07

$C
  Product Condition Score1 Score2 Score3 Score4
7     AE7         C  0.874  1e-05  1e-05  0.492
8     AE8         C  0.785  1e-05  1e-05  0.500
9     AE9         C  0.879  1e-05  1e-05  0.656

$D
   Product Condition Score1 Score2 Score3 Score4
10    AE10         D  1e-08  0.159  0.855  1e-08
11    AE11         D  1e-08  0.105  0.827  1e-08

I want to get column with max value in each list,
like :
In $`-`　, $A and $Cis Score1,in $B is Score2,in $D is Score3.

I want get a table like

Condition    Column
        -    Score1
        A    Score1
        B    Score2
        C    Score1
        D    Score3

Any suggestion is helpful.Thank you.

In base R. using your split:

stack(lapply(split(df[-(1:2)], df[2]), \(x)names(x)[col(x)[which.max(unlist(x))]]))
  values ind
1 Score2   -
2 Score1   A
3 Score2   B
4 Score1   C
5 Score3   D

Note that there are better alternatives

An efficient way to get this is to tidyr::pivot_longer() so that you aggregate all the column data together and can easily take the top value in each Condition.

library(tidyverse)

df <- data.frame(Product= paste0("AE", c(1:11)),
                 Condition=c("-","A","A","B","B","B","C","C","C","D","D"),
                 Score1=c(0.231,0.831,0.894,1e-05,1e-05,1e-05,0.874,0.785,0.879,1e-08,1e-08),
                 Score2=c(0.968,0.168,0.105,0.239,0.149,0.125,1e-05,1e-05,1e-05,0.159,0.105),
                 Score3=c(1e-07,1e-07,1e-07,1e-07,1e-07,1e-07,1e-05,1e-05,1e-05,0.855,0.827),
                 Score4=c(1e-07,1e-07,1e-07,1e-07,1e-07,1e-07,0.492,0.500,0.656,1e-08,1e-08))


df |> 
  pivot_longer(starts_with("Score"), names_to = "Column") |> 
  group_by(Condition) |> 
  slice_max(order_by = value, n = 1) |> 
  select(Condition, Column)
#> # A tibble: 5 × 2
#> # Groups:   Condition [5]
#>   Condition Column
#>   <chr>     <chr> 
#> 1 -         Score2
#> 2 A         Score1
#> 3 B         Score2
#> 4 C         Score1
#> 5 D         Score3

^{Created on 2023-07-05 with reprex v2.0.2}