R Language Subsetting Matrices
Example
For each dimension of an object, the [ operator takes one argument. Vectors have one dimension and take one argument. Matrices and data frames have two dimensions and take two arguments, given as [i, j] where i is the row and j is the column. Indexing starts at 1.
## a sample matrix
mat <- matrix(1:6, nrow = 2, dimnames = list(c("row1", "row2"), c("col1", "col2", "col3")))
mat
# col1 col2 col3
# row1 1 3 5
# row2 2 4 6
mat[i,j] is the element in the i-th row, j-th column of the matrix mat. For example, an i value of 2 and a j value of 1 gives the number in the second row and the first column of the matrix. Omitting i or j returns all values in that dimension.
mat[ , 3]
## row1 row2
## 5 6
mat[1, ]
# col1 col2 col3
# 1 3 5
When the matrix has row or column names (not required), these can be used for subsetting:
mat[ , 'col1']
# row1 row2
# 1 2
By default, the result of a subset will be simplified if possible. If the subset only has one dimension, as in the examples above, the result will be a one-dimensional vector rather than a two-dimensional matrix. This default can be overriden with the drop = FALSE argument to [:
## This selects the first row as a vector
class(mat[1, ])
# [1] "integer"
## Whereas this selects the first row as a 1x3 matrix:
class(mat[1, , drop = F])
# [1] "matrix"
Of course, dimensions cannot be dropped if the selection itself has two dimensions:
mat[1:2, 2:3] ## A 2x2 matrix
# col2 col3
# row1 3 5
# row2 4 6
Selecting individual matrix entries by their positions
It is also possible to use a Nx2 matrix to select N individual elements from a matrix (like how a coordinate system works). If you wanted to extract, in a vector, the entries of a matrix in the (1st row, 1st column), (1st row, 3rd column), (2nd row, 3rd column), (2nd row, 1st column) this can be done easily by creating a index matrix with those coordinates and using that to subset the matrix:
mat
# col1 col2 col3
# row1 1 3 5
# row2 2 4 6
ind = rbind(c(1, 1), c(1, 3), c(2, 3), c(2, 1))
ind
# [,1] [,2]
# [1,] 1 1
# [2,] 1 3
# [3,] 2 3
# [4,] 2 1
mat[ind]
# [1] 1 5 6 2
In the above example, the 1st column of the ind matrix refers to rows in mat, the 2nd column of ind refers to columns in mat.
