**We have launched a free Basic Kubernetes Course**. Click here to enrol now! Kubernetes is a container orchestration platform used by enterprises worldwide and Kubernetes developers are in high demand!

# Data Structures – Matrix and Array in R

In the previous tutorial we saw atomic vectors and list. In this tutorial we look at Matrix and Array in R.

### Array

An array is a vector with additional attributes

`dim`

which stores the dimension of the array and

`dimnames`

which stores the names of the dimensions. Here’s an example:

> array(1:8,dim=c(2,2,2)) , , 1 [,1] [,2] [1,] 1 3 [2,] 2 4 , , 2 [,1] [,2] [1,] 5 7 [2,] 6 8

This creates a 2,2,2 array. You can check if an object is an array by using the

`is.array()`

function

> x=array(1:8,dim=c(2,2,2)) > is.array(x) [1] TRUE

The array has an attribute called dim.

> attributes(x) $dim [1] 2 2 2

You can also get the dimensions using the

`dim`

function

> dim(x) [1] 2 2 2

we can assign names to the dimensions. In the example below we create a list with dimnames. The length of each element in the list should correspond to the dimension.

> x=array(1:8,dim=c(2,2,2),dimnames=list(c('a','b'),c('e','f'),c('g','h'))) > x , , g e f a 1 3 b 2 4 , , h e f a 5 7 b 6 8

### Matrix

A matrix is an 2 dimensional array. Lets create one

> a=matrix(1:8,nrow=2,ncol=4) > a [,1] [,2] [,3] [,4] [1,] 1 3 5 7 [2,] 2 4 6 8

The data is filled column first. nrow specifies number of rows and ncol specifies number of columns. To fill in rows first use the ‘byrow’ specifier

> a=matrix(1:8,nrow=2,ncol=4,byrow=TRUE) > a [,1] [,2] [,3] [,4] [1,] 1 2 3 4 [2,] 5 6 7 8

An element of a matrix can be accessed by specifying ‘row,column’

> a[2,3] [1] 7

This retrieves the element at row 2 and column 3. You can also specify a single index

> a[1] [1] 1 > a[2] [1] 5

This accesses the elements in column first order. To select a complete row or complete column

# get first row > a[1,] [1] 1 2 3 4 # get first column > a[,1] [1] 1 5

Multiple rows or columns can also be accessed

> a[,c(1,2)] [,1] [,2] [1,] 1 2 [2,] 5 6 > a[,1:3] [,1] [,2] [,3] [1,] 1 2 3 [2,] 5 6 7

You can assign names to the rows and columns. The names can be used to access the elements

> dimnames(a)=list(c("a","b"),c("c","d","e","f")) > a c d e f a 1 2 3 4 b 5 6 7 8 > a["a","e"] [1] 3

You can check if an object is a matrix by using

`is.matrix()`

. Length of a matrix is given by

`length()`

. To find the number of rows and number of columns use the

`nrow()`

and

`ncol()`

functions respectively. To get all the dimensions use the

`dim()`

function.

> a=matrix(1:8,nrow=2,ncol=4,byrow=TRUE) > length(a) [1] 8 > dim(a) [1] 2 4 > nrow(a) [1] 2 > ncol(a) [1] 4

To get all the names of the rows use the

`rownames`

function and to get all the column names use the

`colnames`

function.

> a=matrix(1:8,nrow=2,ncol=4,byrow=TRUE) > dimnames(a)=list(c("a","b"),c("c","d","e","f")) > rownames(a) [1] "a" "b" > colnames(a) [1] "c" "d" "e" "f"

We can combine two matrices row wise using

`rbind()`

and columnwise using

`cbind()`

. we Will explore this function in details in the subsequent tutorials, but for now, lets look at one example

# create two matrices with dimensions 2x2 > a=matrix(1:4,ncol=2,nrow=2) > a [,1] [,2] [1,] 1 3 [2,] 2 4 > b=matrix(5:8,ncol=2,nrow=2) > b [,1] [,2] [1,] 5 7 [2,] 6 8 # cbind combines the matrices by columns. #think of it as putting the matrix on the side of the other matrix. > cbind(a,b) [,1] [,2] [,3] [,4] [1,] 1 3 5 7 [2,] 2 4 6 8 #rbind combines the matrices by rows. #Think of it as putting the matrix on the bottom of the other matrix. > rbind(a,b) [,1] [,2] [1,] 1 3 [2,] 2 4 [3,] 5 7 [4,] 6 8

We can convert the matrix back to a vector by using the c() function

> c(a) [1] 1 2 3 4 #as.vector also works > as.vector(a) [1] 1 2 3 4

A list can also be converted to a matrix.

> l = list("a",c(1,2),TRUE,"b") > matrix(l,nrow=2,ncol=2) [,1] [,2] [1,] "a" TRUE [2,] Numeric,2 "b" # we create a 2x2 matrix. > m=matrix(l,nrow=2,ncol=2) # the 2,1 element is a vector > m[2,1] [[1]] [1] 1 2

So far we have been using cases where we provide all elements while creating a matrix. Lets look at two examples, where we provide less elements than is required by the ncol and nrow specification.

# 6 elements and nrow*ncol = 6. all good. > a=matrix(1:6,nrow=3,ncol=2) > a [,1] [,2] [1,] 1 4 [2,] 2 5 [3,] 3 6 #3 elements and nrow*ncol = 6. # R recycles elements since number of elements is a multiple or #sub-multiple of number or rows. > a=matrix(1:3,nrow=3,ncol=2) > a [,1] [,2] [1,] 1 1 [2,] 2 2 [3,] 3 3 # 4 elements and nrow*ncol = 6. Not good. > a=matrix(1:4,nrow=3,ncol=2) Warning message: In matrix(1:4, nrow = 3, ncol = 2) : data length [4] is not a sub-multiple or multiple of the number of rows [3]