dim() in R

dim() function is used to get the dimension of a matrix, array, data frame, or vector. It is a part of the base R package. This guide explains how to use the dim() in R.

Syntax

dim(x)

Arguments

• x = a vector, matrix, array, or data frame

Using dim() to get the dimension of a Vector

A vector is a one-dimensional data structure. To get the dimension of a vector, you need to specify the vector as an argument to the dim() function. It will always return NULL.

Example

#creating a vector
x <- 1:3
#printing vector
x
#getting the dimension of a vector
dim(x)

Output

[1] 1 2 3
NULL

Using dim() to get the dimension of a Matrix

A matrix is a two-dimensional array. To get the dimension of a matrix, you need to specify the matrix as an argument to the dim() function. It will return a vector of two integers that indicate the number of rows and columns in the matrix.

Example

#creating a matrix
y <- matrix(1:9, nrow=3, ncol=3)
#printing matrix
y
#getting the dimension of a matrix
dim(y)

Output

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

[1] 3 3

Using dim() to get the dimension of an Array

An array is a three-dimensional data structure. To get the dimension of an array, you need to specify the array as an argument to the dim() function. It will return a vector of three integers that indicate the size of the array.

Example

#creating an array
a <- array(1:8, c(2, 2, 2))
#printing array
a
#getting the dimension of the array
dim(a)

Output

, , 1
[,1] [,2]
[1,] 1 3
[2,] 2 4

, , 2
[,1] [,2]
[1,] 5 7
[2,] 6 8

[1] 2 2 2

Using dim() to get the dimension of a Data Frame

A data frame is a two-dimensional data structure. To get the dimension of a data frame, you need to specify the data frame as an argument to the dim() function. It will return a vector of two integers that indicate the number of rows and columns in the data frame.

Example

#creating a data frame
df <- data.frame(x=1:3, y=4:6)
#printing data frame
df
#getting the dimension of the data frame
dim(df)

Output

x y
1 1 4
2 2 5
3 3 6

[1] 3 2

Here, 3 indicates the number of rows in the data frame, and 2 indicates the number of columns.