{"id":75387,"date":"2020-01-11T15:27:16","date_gmt":"2020-01-11T09:57:16","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=75387"},"modified":"2020-01-11T15:27:16","modified_gmt":"2020-01-11T09:57:16","slug":"r-arrays","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/r-arrays\/","title":{"rendered":"R Arrays – A Comprehensive Guide to Array with Examples"},"content":{"rendered":"

This TechVidvan tutorial is designed to help R programming beginner to get a clear understanding of how to easily work with R arrays.\u00a0<\/strong><\/p>\n

Arrays are multi-dimensional<\/strong> data structures in R. This means that they can have any number of dimensions. They are vectors with two or more dimensions to them. Matrices are a special case of 2-D arrays.<\/p>\n

In this tutorial, we will explore the concept of arrays in R programming. We will learn to create arrays, name rows, columns, and other dimensions. We will then look at accessing their elements and modifying them.<\/p>\n

Finally, we will look at how different operations on arrays work in the R programming language.<\/p>\n

So, are you excited?<\/p>\n

What are arrays in R?<\/h2>\n

R arrays are data objects that store data in more than two dimensions. Arrays are homogeneous<\/strong> in nature. This means that they can store values of a single basic data type only.<\/strong> They store the data in the form of layered matrices<\/strong>. Let us take a look at different ways of creating an array.<\/p>\n

But before learning how to create an array in R, first look at the syntax of the array function.<\/p>\n

Array function syntax<\/h3>\n

The syntax of the array()<\/code><\/strong>function is as follows:<\/p>\n

Array_name = array(data,dim = c(row_size,column_size,matrices), dimnames = list(row_names,column_names,matrices_names))<\/pre>\n
Where data<\/code><\/strong> is a vector that provides the values to fill the array,<\/p>\n
dim<\/code><\/strong> is a vector that tells the dimensions of the array,<\/p>\n
row_size<\/code><\/strong> is the number of rows in the array,<\/p>\n
column_size<\/code><\/strong> is the number of columns in the array,<\/p>\n
matrices<\/code><\/strong> denotes the number of matrices in the array,<\/p>\n
dimnames<\/code><\/strong> is a list of names for the dimensions of the array,<\/p>\n
row_names<\/code><\/strong> is a vector with the names for all the rows,<\/p>\n
column_names<\/code><\/strong> is a vector with the names for all the columns,<\/p>\n
matrices_names<\/code><\/strong> is a vector with the names for all the matrices in the array.<\/p>\n
Creating R arrays<\/h3>\n
There are many ways to create R arrays. We can use the array()<\/code><\/strong> function to create an array.<\/p>\n
For example:<\/p>\n
Code:<\/strong><\/p>\n
> arr1 <- array(c(1:18),dim=c(2,3,3))\n> arr1<\/pre>\n
Output:<\/strong><\/p>\n
\"creating<\/a><\/strong><\/p>\n
We can also create an array by changing the dimensions<\/strong> of a vector. For example:<\/p>\n
Code:<\/strong><\/p>\n
> vec_to_arr <- c(1,2,3,4,5,6,7,8)\n> dim(vec_to_arr) <- c(2,2,2)\n> vec_to_arr<\/pre>\n
Output:<\/strong><\/p>\n
\"creating<\/a><\/strong><\/p>\n
Naming the dimensions of R arrays<\/h3>\n
We can name the rows, columns, and matrices of an array during its creation by using the dimnames<\/code><\/strong> attribute of the array()<\/code><\/strong> function. For example:<\/p>\n
Code:<\/strong><\/p>\n
> rnames <- c(\"r1\",\"r2\",\"r3\")\n> cnames <- c(\"c1\",\"c2\",\"c3\")\n> mnames <- c(\"m1\",\"m2\",\"m3\")\n> named_array <- array(c(1:27),dim=c(3,3,3),dimnames= list(rnames,cnames,mnames))\n> named_array<\/pre>\n
Output:<\/strong><\/p>\n
\"naming<\/a><\/strong><\/p>\n
We can use the dimnames()<\/code><\/strong>function to name the dimensions and to change their names after an array\u2019s creation. For example:<\/p>\n
Code:<\/strong><\/p>\n
> named_array2 <- array(c(1:18),c(3,3,2))\n> mnames2 <- c(\"m1\",\"m2\")\n> dimnames(named_array2) <- list(rnames,cnames,mnames2)\n> named_array2<\/pre>\n
Output:<\/strong><\/p>\n
\"naming<\/a><\/strong><\/h3>\n
Indexing R array<\/h3>\n
We can access the elements of an array by using the square brackets<\/strong> to denote an index. We can use four types of indices for this, which are positive integers, negative integers, logical values or characters.<\/p>\n
Using positive integers<\/h4>\n
Code:<\/strong><\/p>\n
> named_array[2,1,3] #second row, first column and third matrix of named_array<\/pre>\n
Code:<\/strong><\/p>\n
> named_array[c(1,2),c(2,3),c(1,2)] #first and second row, second and third column of first and second matrices<\/pre>\n
Output:<\/strong><\/p>\n
\"positive<\/a><\/strong>Using negative integers<\/h4>\n
Code:<\/strong><\/p>\n
> named_array[-1,-3,-2] #remove first row, third column and second matrix of named_array<\/pre>\n
Output:<\/strong><\/p>\n
\"negative<\/a><\/strong>Using logical vectors<\/h4>\n
Code:<\/strong><\/p>\n
> named_array[c(T,F,T),c(F,T,T),c(T,T,F)] #first and third row, second and third column of first and second matrix of named_array<\/pre>\n
Output:<\/strong><\/p>\n
\"logical<\/a><\/strong><\/p>\n
Logical index vectors recycle, in case they are shorter than the array dimensions. For example:<\/p>\n
Code:<\/strong><\/p>\n
>named_array[c(T,F),c(F,T),c(T,T,F),drop=FALSE]<\/pre>\n
Output:<\/strong><\/p>\n
\"logical<\/a><\/strong><\/p>\n
Note:<\/strong> If we select a single entry of any dimension of an array, the result will be a matrix. To avoid that, we use drop=FALSE<\/code><\/strong> argument.<\/p>\n
Using character vectors<\/h4>\n
Code:<\/strong><\/p>\n
> named_array[c(\"r1\",\"r3\"),c(\"c2\",\"c3\"),c(\"m1\",\"m2\")]<\/pre>\n
Output:<\/strong><\/p>\n
\"character<\/a><\/p>\n
Modifying R array<\/h3>\n
We can use the indexing techniques to access elements or parts of an array. Then we can use re-assignment<\/strong> to change their values. For example:<\/p>\n
Code:<\/strong><\/p>\n
> named_array[1,,1] <- c(4,4,4)\n> named_array<\/pre>\n
Output:<\/strong><\/p>\n
\"modifying<\/a><\/strong><\/p>\n
We can also use the dim()<\/code><\/strong> function to change the dimensions of an array. For example:<\/p>\n
Code:<\/strong><\/p>\n
> dim(arr1) <- c(3,3,2)\n> arr1<\/pre>\n
Output:<\/strong><\/p>\n
\"modify<\/a><\/strong><\/h3>\n
R Array arithmetic<\/h3>\n
In R<\/a>, the basic operations of addition, subtraction, multiplication, and division work element-wise. We need to ensure that the arrays are of the proper size and valid according to matrix arithmetic.<\/p>\n
For example, the number of rows of the first matrix and the number of columns of the second matrix should be the same for multiplication.<\/p>\n
1. Addition<\/h4>\n
Code:<\/strong><\/p>\n
> test_arr1 <- array(c(1:8),c(2,2,2))\n> test_arr2 <- array(c(9:16),c(2,2,2))\n> arr_add <- test_arr1+test_arr2\n> arr_add<\/pre>\n
Output:<\/strong><\/p>\n
\"R<\/a><\/strong><\/p>\n
2. Subtraction<\/h4>\n
Code:<\/strong><\/p>\n
> arr_sub <- test_arr2-test_arr1\n> arr_sub<\/pre>\n
Output:<\/strong><\/p>\n
\"R<\/a><\/strong>3. Multiplication<\/h4>\n
Code:<\/strong><\/p>\n
> arr_mul <- test_arr1*test_arr2\n> arr_mul<\/pre>\n
Output:<\/strong><\/p>\n
\"R<\/a><\/strong>4. Division<\/h4>\n
Code:<\/strong><\/p>\n
> arr_div <- test_arr2\/test_arr1\n> arr_div<\/pre>\n
Output:<\/strong><\/p>\n
\"R<\/a><\/strong><\/p>\n
5. Power operator<\/h4>\n
The power operator^<\/code><\/strong>works on R arrays in the same fashion that is element-wise.<\/p>\n
Code:<\/strong><\/p>\n
> arr_pow <- test_arr1^2\n> arr_pow<\/pre>\n
Output:<\/strong><\/p>\n
\"power<\/a><\/strong><\/p>\n
6. The apply() Function<\/h4>\n
We can also perform operations on array elements with the apply()<\/code><\/strong> function. The apply function performs a given function on all columns or all rows of an array or matrix.<\/p>\n
For example, the following code gives the sums of all the columns of test_arr1<\/code><\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
> test_arr1<\/pre>\n
Code:<\/strong><\/p>\n
> col_sum <- apply(test_arr1,2,sum)\n> col_sum<\/pre>\n
Output:<\/strong><\/p>\n
\"apply()<\/a><\/strong>Summary<\/h2>\n
In this tutorial, we learned about the arrays in R programming. We learned about their creation, modification, and manipulation. We saw how to access their elements. Finally, we looked at a few basic mathematical operations on arrays.<\/p>\n
R Arrays are special vectors with multiple dimensions to them. They store multidimensional rectangular data.<\/p>\n
Now you must be realizing how important R vector is, take a tour to R vectors<\/a> <\/strong>and master the concept.<\/p>\n
The above article should give you a clear understanding of arrays in the R programming language.<\/p>\n
Confusion in R array examples? Ask TechVidvan in the comment section.<\/p>\n
Keep learning!!<\/p>\n","protected":false},"excerpt":{"rendered":"
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