# R - Arrays

An array is created using the

**array()**function. It takes vectors as input and uses the values in the

**dim**parameter to create an array.

## Example

The following example creates an array of two 3x3 matrices each with 3 rows and 3 columns.# Create two vectors of different lengths. vector1 <- c(5,9,3) vector2 <- c(10,11,12,13,14,15) # Take these vectors as input to the array. result <- array(c(vector1,vector2),dim = c(3,3,2)) print(result)When we execute the above code, it produces the following result −

, , 1 [,1] [,2] [,3] [1,] 5 10 13 [2,] 9 11 14 [3,] 3 12 15 , , 2 [,1] [,2] [,3] [1,] 5 10 13 [2,] 9 11 14 [3,] 3 12 15

## Naming Columns and Rows

We can give names to the rows, columns and matrices in the array by using the**dimnames**parameter.

# Create two vectors of different lengths. vector1 <- c(5,9,3) vector2 <- c(10,11,12,13,14,15) column.names <- c("COL1","COL2","COL3") row.names <- c("ROW1","ROW2","ROW3") matrix.names <- c("Matrix1","Matrix2") # Take these vectors as input to the array. result <- array(c(vector1,vector2),dim = c(3,3,2),dimnames = list(row.names,column.names, matrix.names)) print(result)When we execute the above code, it produces the following result −

, , Matrix1 COL1 COL2 COL3 ROW1 5 10 13 ROW2 9 11 14 ROW3 3 12 15 , , Matrix2 COL1 COL2 COL3 ROW1 5 10 13 ROW2 9 11 14 ROW3 3 12 15

## Accessing Array Elements

# Create two vectors of different lengths. vector1 <- c(5,9,3) vector2 <- c(10,11,12,13,14,15) column.names <- c("COL1","COL2","COL3") row.names <- c("ROW1","ROW2","ROW3") matrix.names <- c("Matrix1","Matrix2") # Take these vectors as input to the array. result <- array(c(vector1,vector2),dim = c(3,3,2),dimnames = list(row.names, column.names, matrix.names)) # Print the third row of the second matrix of the array. print(result[3,,2]) # Print the element in the 1st row and 3rd column of the 1st matrix. print(result[1,3,1]) # Print the 2nd Matrix. print(result[,,2])When we execute the above code, it produces the following result −

COL1 COL2 COL3 3 12 15 [1] 13 COL1 COL2 COL3 ROW1 5 10 13 ROW2 9 11 14 ROW3 3 12 15

## Manipulating Array Elements

As array is made up matrices in multiple dimensions, the operations on elements of array are carried out by accessing elements of the matrices.# Create two vectors of different lengths. vector1 <- c(5,9,3) vector2 <- c(10,11,12,13,14,15) # Take these vectors as input to the array. array1 <- array(c(vector1,vector2),dim = c(3,3,2)) # Create two vectors of different lengths. vector3 <- c(9,1,0) vector4 <- c(6,0,11,3,14,1,2,6,9) array2 <- array(c(vector1,vector2),dim = c(3,3,2)) # create matrices from these arrays. matrix1 <- array1[,,2] matrix2 <- array2[,,2] # Add the matrices. result <- matrix1+matrix2 print(result)When we execute the above code, it produces the following result −

[,1] [,2] [,3] [1,] 10 20 26 [2,] 18 22 28 [3,] 6 24 30

## Calculations Across Array Elements

We can do calculations across the elements in an array using the**apply()**function.

### Syntax

apply(x, margin, fun)Following is the description of the parameters used −

**x**is an array.**margin**is the name of the data set used.**fun**is the function to be applied across the elements of the array.

### Example

We use the apply() function below to calculate the sum of the elements in the rows of an array across all the matrices.# Create two vectors of different lengths. vector1 <- c(5,9,3) vector2 <- c(10,11,12,13,14,15) # Take these vectors as input to the array. new.array <- array(c(vector1,vector2),dim = c(3,3,2)) print(new.array) # Use apply to calculate the sum of the rows across all the matrices. result <- apply(new.array, c(1), sum) print(result)When we execute the above code, it produces the following result −

, , 1 [,1] [,2] [,3] [1,] 5 10 13 [2,] 9 11 14 [3,] 3 12 15 , , 2 [,1] [,2] [,3] [1,] 5 10 13 [2,] 9 11 14 [3,] 3 12 15 [1] 56 68 60

*Table of contents:*1. R - Overview

2. R - Environment Setup

3. R - Basic Syntax

4. R - Data Types

5. R - Variables

6. R - Operators

7. R - Decision Making

8. R - Loops

9. R - Functions

10. R - Strings

11. R - Vectors

12. R - Matrices

13. R - Arrays

14. R - Factors

15. R - Data Frames

16. R - Packages

17. R - Data Reshaping

18. R - CSV Files

19. R - Excel Files

20. R - Binary Files

21. R - XML Files

22. R - JSON Files

23. R - Web Data

24. R - Database

25. R - Pie Charts

26. R - Bar Charts

27. R - Boxplots

28. R - Histograms

29. R - Line Graphs

30. R - Scatterplots

31. R - Mean, Median and Mode

32. R - Linear Regression

33. R - Multiple Regression

34. R - Logistic Regression

35. R - Normal Distribution

36. R - Binomial Distribution

37. R - Poisson Regression

38. R - Analysis of Covariance

39. R - Time Series Analysis

40. R - Nonlinear Least Square

41. R - Decision Tree

42. R - Random Forest

43. R - Survival Analysis

44. R - Chi Square Tests

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