data.frame to array (2 columns)

Question

i'd like to know how to transform a data.frame into an array in R. therefor my data.frame consists of 16 columns and >100 rows. every row stands for one individual (snail). i did put 8 landmarks on each snail. so now i've got 16 coordinates/individual. no i want to transform the data.fram into an array, where each individual gets its own matrix and all individuals are put together in one (big) array.

my data looks like this: 6 individuals with 8 landmarks aka 16 coordinates (X&Y)

     X1.Lms    Y1.Lms    X2.Lms    Y2.Lms    X3.Lms    Y3.Lms    X4.Lms    Y4.Lms    X5.Lms    Y5.Lms   X6.Lms    Y6.Lms    X7.Lms    Y7.Lms X8.Lms Y8.Lms
1 132500000 132500000 114500000 132000000 150100000 121500000  97600000 123500000 164700000 107800000 77600000 110400000 181600000  81700000     NA     NA
2 135700000 150900000 114100000 152000000 147500000 142500000  96900000 143800000 161900000 128600000 78300000 131200000 178000000 100500000     NA     NA
3 134100000 136900000 113700000 135400000 148700000 129900000  99600000 127800000 164700000 115900000 76600000 115100000 183600000  87600000     NA     NA
4 137400000 147100000 119500000 145600000 149500000 143000000 102400000 136800000 169400000 128200000 84000000 123400000 186700000 106000000     NA     NA
5 141300000 144200000 115800000 141300000 154000000 135800000 103900000 132700000 171300000 122400000 83600000 120800000        NA        NA     NA     NA
6 136300000 153700000 118100000 150200000 151700000 146900000 105500000 143700000 168400000 135200000 83600000 132000000 188900000 111600000     NA     NA

you can get this table into R by entering:

sample <- structure(list(X1.Lms = c(132500000L, 135700000L, 134100000L, 137400000L, 141300000L, 136300000L), Y1.Lms = c(132500000L, 150900000L, 136900000L, 147100000L, 144200000L, 153700000L), X2.Lms = c(114500000L, 114100000L, 113700000L, 119500000L, 115800000L, 118100000L), Y2.Lms = c(132000000L, 152000000L, 135400000L, 145600000L, 141300000L, 150200000L), X3.Lms = c(150100000L, 147500000L, 148700000L, 149500000L, 154000000L, 151700000L), Y3.Lms = c(121500000L, 142500000L, 129900000L, 143000000L, 135800000L, 146900000L ), X4.Lms = c(97600000L, 96900000L, 99600000L, 102400000L, 103900000L, 105500000L), Y4.Lms = c(123500000L, 143800000L, 127800000L, 136800000L, 132700000L, 143700000L), X5.Lms = c(164700000L, 161900000L, 164700000L, 169400000L, 171300000L, 168400000L ), Y5.Lms = c(107800000L, 128600000L, 115900000L, 128200000L, 122400000L, 135200000L), X6.Lms = c(77600000L, 78300000L, 76600000L, 84000000L, 83600000L, 83600000L), Y6.Lms = c(110400000L, 131200000L, 115100000L, 123400000L, 120800000L, 132000000L ), X7.Lms = c(181600000L, 178000000L, 183600000L, 186700000L, NA, 188900000L), Y7.Lms = c(81700000L, 100500000L, 87600000L, 106000000L, NA, 111600000L), X8.Lms = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_), Y8.Lms = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_ )), .Names = c("X1.Lms", "Y1.Lms", "X2.Lms", "Y2.Lms", "X3.Lms", "Y3.Lms", "X4.Lms", "Y4.Lms", "X5.Lms", "Y5.Lms", "X6.Lms", "Y6.Lms", "X7.Lms", "Y7.Lms", "X8.Lms", "Y8.Lms"), row.names = c(NA, 6L ), class = "data.frame")

alternatively i've put the code on pastebin.

the result should look like the sample data of gorilla females in the "shapes" package, where every coordinate (X1.S & Y1.S) is a matrix on its own. i guess the dimensions have to be (8 x 2 x n). n is the number of rows in the original data.frame.

install.packages("shapes")
library(shapes)
data(gorf.dat)
gorf.dat

the data is organized as an array with the dimensions (8 x 2 x n)

, , 1

       [,1] [,2]
 [1,]    5  193
 [2,]   53  -27
 [3,]    0    0
 [4,]    0   33
 [5,]   -2  105
 [6,]   18  176
 [7,]   72  114
 [8,]   92   38

, , 2

        [,1] [,2]
  [1,]   51  191
  [2,]   55  -31
  [3,]    0    0
  [4,]    0   33
  [5,]   25  106
  [6,]   56  171
  [7,]   98  105
  [8,]   99   15

, , 3

      [,1] [,2]
[1,]   36  187
[2,]   59  -31
[3,]    0    0
[4,]    0   36
[5,]   12  102
[6,]   38  171
[7,]   91  103
[8,]  100   19

and so on....

i've tried with x <- as.array(sample, dim=...) but i'm not able to find a solution so far. i guess i have to try something similar thant the transpose function in ms excel.

greetings, luke

--- EDIT ---

you're answers helped a lot, but i guess you've got me wrong. the first individual has got 8 Landmarks with 16 coordinates (X1, Y1, X2, Y2, X3, Y3....). so to be absolutely clear on my desired results :)... what i have in mind should look more like this:

, , 1
      [,1]       [,2]
 132500000  132500000
 114500000  132000000
 150100000  121500000
  97600000  123500000
 164700000  107800000
  77600000  110400000
 181600000   81700000
        NA         NA


, , 2
        [,1]       [,2]
   135700000  150900000
   114100000  152000000
   147500000  142500000
   969000000  143800000
   161900000  128600000
    78300000  131200000 
   178000000  100500000
          NA         NA

the first row (aka first case) has 8 Landmarks with 16 coordinates. all of them should be stored in a matrix. after that i want to combine all cases (>100) into an array where each individual has its own matrix.

thanks for the quick response guys!!!

Answer 1

Try this:

nlandmarks = 8; nind = nrow(sample)
array(t(sample[,c(1:nlandmarks*2 -1, 1:nlandmarks * 2)]), 
  dim = c(nlandmarks, 2, nind))

Answer 2

Revised to handle new data structure:

sdat <- apply(sample, 1,matrix, ncol=2, byrow=TRUE ) #unfolds the interleaved columns
dim(sdat) <- c(8,2,6)  # expands 16 x 6 into one X column and one Y column per slice
#-----------------
> sdat[, , 1:2]
, , 1

          [,1]      [,2]
[1,] 132500000 132500000
[2,] 114500000 132000000
[3,] 150100000 121500000
[4,]  97600000 123500000
[5,] 164700000 107800000
[6,]  77600000 110400000
[7,] 181600000  81700000
[8,]        NA        NA

, , 2

          [,1]      [,2]
[1,] 135700000 150900000
[2,] 114100000 152000000
[3,] 147500000 142500000
[4,]  96900000 143800000
[5,] 161900000 128600000
[6,]  78300000 131200000
[7,] 178000000 100500000
[8,]        NA        NA


    .... remaining 4 slices omitted