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

I want to run mantelhaen.test in R which requires 2x2 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!

CodePudding user response：

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