Using apply to make an array out of each row of a dataframe in R?

I want to run mantelhaen.test in R which requires 2×2 contingency tables in 3D array form. These tables can be constructed by looping over each row of the dataframe, but I am trying to figure out if there is a vectorised way to do it – ie using apply(df[,c("col1","col2",etc), margin=1, array(x, c(2,2,11))) to make a 3D array for each row of the table (which would then be wrapped in mantelhaen.test).

I have previously got this to work using matrix() for fisher.test in R and Pandas, but in this case I am running into an issue where array() doesn’t seem to have any effect on the data. Here is a reproducible example:

df = data.frame(group1_variant_cases = c(2,1,3,0,0,2), group1_nonvariant_cases = c(100,92,33,40,21,87), 
                group1_variant_controls = c(1,2,1,0,2,1), group1_nonvariant_controls = c(45,61,70,71,31,55), 
                group2_variant_cases = c(0,2,1,0,1,0), group2_nonvariant_cases = c(201,99,213,52,178,98),
                group2_variant_controls = c(1,0,0,0,1,2), group2_nonvariant_controls = c(67,43,12,88,91,73)) 

apply(head(df,1), 1, function(x) array(x, c(2,2,2)))

Output:

      1
[1,]   2
[2,] 100
[3,]   1
[4,]  45
[5,]   0
[6,] 201
[7,]   1
[8,]  67

Any help appreciated!

>Solution :

With apply, there is simplify argument which is by default TRUE. Change it to FALSE and it works i.e. according to ?apply

If each call to FUN returns a vector of length n, and simplify is TRUE, then apply returns an array of dimension c(n, dim(X)[MARGIN]) if n > 1. If n equals 1, apply returns a vector if MARGIN has length 1 and an array of dimension dim(X)[MARGIN] otherwise.

apply(head(df,3), 1, function(x) array(x, c(2,2,2)), simplify = FALSE)

-output

$`1`
, , 1

     [,1] [,2]
[1,]    2    1
[2,]  100   45

, , 2

     [,1] [,2]
[1,]    0    1
[2,]  201   67


$`2`
, , 1

     [,1] [,2]
[1,]    1    2
[2,]   92   61

, , 2

     [,1] [,2]
[1,]    2    0
[2,]   99   43


$`3`
, , 1

     [,1] [,2]
[1,]    3    1
[2,]   33   70

, , 2

     [,1] [,2]
[1,]    1    0
[2,]  213   12