Partition matrix into N equally-sized chunks with R

Question

How can I partition a matrix or dataframe into N equally-sized chunks with R? I want to cut the matrix or dataframe horizontally.

For example, given:

r = 8
c = 10
number_of_chunks = 4
data = matrix(seq(r*c), nrow = r, ncol=c)
>>> data

     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    1    9   17   25   33   41   49   57   65    73
[2,]    2   10   18   26   34   42   50   58   66    74
[3,]    3   11   19   27   35   43   51   59   67    75
[4,]    4   12   20   28   36   44   52   60   68    76
[5,]    5   13   21   29   37   45   53   61   69    77
[6,]    6   14   22   30   38   46   54   62   70    78
[7,]    7   15   23   31   39   47   55   63   71    79
[8,]    8   16   24   32   40   48   56   64   72    80

I would like to have to cut data into a list of 4 elements:

Element 1:

     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    1    9   17   25   33   41   49   57   65    73
[2,]    2   10   18   26   34   42   50   58   66    74

Element 2:

     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[3,]    3   11   19   27   35   43   51   59   67    75
[4,]    4   12   20   28   36   44   52   60   68    76

Element 3:

     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[5,]    5   13   21   29   37   45   53   61   69    77
[6,]    6   14   22   30   38   46   54   62   70    78

Element 4:

     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[7,]    7   15   23   31   39   47   55   63   71    79
[8,]    8   16   24   32   40   48   56   64   72    80

With numpy in python, I can use numpy.array_split.

Answer 1

Here's an attempt in base R. Calculate "pretty" cut values for the sequence of rows using pretty. Categorized the sequence of row numbers with cut and return a list of the the sequence split at the cut values with split. Finally, run through a list of the split row values using lapply extract the matrix subsets with [.

lapply(split(seq_len(nrow(data)),
             cut(seq_len(nrow(data)), pretty(seq_len(nrow(data)), number_of_chunks))),
       function(x) data[x, ])
$`(0,2]`
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    1    9   17   25   33   41   49   57   65    73
[2,]    2   10   18   26   34   42   50   58   66    74

$`(2,4]`
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    3   11   19   27   35   43   51   59   67    75
[2,]    4   12   20   28   36   44   52   60   68    76

$`(4,6]`
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    5   13   21   29   37   45   53   61   69    77
[2,]    6   14   22   30   38   46   54   62   70    78

$`(6,8]`
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    7   15   23   31   39   47   55   63   71    79
[2,]    8   16   24   32   40   48   56   64   72    80

Roll this into a function:

array_split <- function(data, number_of_chunks) {
  rowIdx <- seq_len(nrow(data))    
  lapply(split(rowIdx, cut(rowIdx, pretty(rowIdx, number_of_chunks))), function(x) data[x, ])
}

Then, you can use

array_split(data=data, number_of_chunks=number_of_chunks)

to return the same result as above.

---

A nice simplification suggested by @user20650 is

split.data.frame(data,
                 cut(seq_len(nrow(data)), pretty(seq_len(nrow(data)), number_of_chunks)))

A surprise to me, split.data.frame returns a list of matrices when its first argument is a matrix.

Answer 2

number_of_chunks = 4
lapply(seq(1, NROW(data), ceiling(NROW(data)/number_of_chunks)),
       function(i) data[i:min(i + ceiling(NROW(data)/number_of_chunks) - 1, NROW(data)),])

OR

lapply(split(data, rep(1:number_of_chunks, each = NROW(data)/number_of_chunks)),
       function(a) matrix(a, ncol = NCOL(data)))