Convert an Object into a Matrix in R Programming – as.matrix() Function

In R Programming Language as. matrix() function is used to convert an object into a Matrix.

Syntax: as.matrix(x)

Parameters:

• x: Object to be converted

 as.matrix() Function in R Example

Example 1: Convert vector to the matrix using as.matrix()

R

# R program to convert an object to matrix

# Creating a vector
x <- c(1:9)

# Calling as.matrix() Function
as.matrix(x)

Output:

      [, 1]
 [1, ]    1
 [2, ]    2
 [3, ]    3
 [4, ]    4
 [5, ]    5
 [6, ]    6
 [7, ]    7
 [8, ]    8
 [9, ]    9

Example 2: Convert Dataframe to the matrix using as.matrix()

R

# R program to convert an object to matrix

# Calling pre-defined data set
BOD

# Calling as.matrix() Function
as.matrix(BOD)

Output:

  Time demand
1    1    8.3
2    2   10.3
3    3   19.0
4    4   16.0
5    5   15.6
6    7   19.8
     Time demand
[1, ]    1    8.3
[2, ]    2   10.3
[3, ]    3   19.0
[4, ]    4   16.0
[5, ]    5   15.6
[6, ]    7   19.8

Example 3: Convert a Sparse Matrix to a Dense Matrix using as.matrix()

R

library(Matrix)

# Create a sparse matrix
sparse_mat <- Matrix(c(0, 0, 0, 0, 0, 0, 1, 2, 0), nrow = 3, ncol = 3)
sparse_mat
# Convert to a dense matrix
dense_mat <- as.matrix(sparse_mat)
dense_mat

Output:

3 x 3 sparse Matrix of class "dtCMatrix"
          
[1,] . . 1
[2,] . . 2
[3,] . . .

     [,1] [,2] [,3]
[1,]    0    0    1
[2,]    0    0    2
[3,]    0    0    0

Example 4: Convert a SpatialPointsDataFrame to a Matrix using as.matrix()

R

library(sp)

# Create a SpatialPointsDataFrame
coordinates <- cbind(c(1, 2, 3), c(4, 5, 6))
sdf <- SpatialPointsDataFrame(coords = coordinates, data = data.frame(ID = 1:3))
sdf
# Convert to a matrix of coordinates
coord_matrix <- as.matrix(coordinates)
coord_matrix

Output:

  coordinates ID
1      (1, 4)  1
2      (2, 5)  2
3      (3, 6)  3

     [,1] [,2]
[1,]    1    4
[2,]    2    5
[3,]    3    6

These examples show the flexibility of the as.matrix() function in handling different types of objects and conversions in R Programming Language. Depending on our data and requirements, we may need to tailor the conversion process accordingly.