R Operators

When working with data in R, operators are essential tools that help you perform calculations, compare values, and manipulate data. Just like symbols like +, –, or = in math, R uses a variety of operators to handle tasks such as arithmetic operations, logical checks, and assignments.

Understanding R operators is crucial for writing clear and efficient code, whether you’re analyzing data, building models, or just getting started with R programming. In this blog, we’ll explore the different types of R operators, how they work, and how you can use them in real-world examples.

Let’s dive in and make R operators simple and easy to understand!

Table of Contents

• • R Operators
    • Arithmetic Operators
    • Assignment Operators
    • Logical Operators
    • Relational Operators
    • Miscellaneous Operators
  • Conclusion

R Operators

An Operator is a symbol that tells to perform different operations between operands. R programming is very rich in built-in operators.

R has the following data operators:

• Arithmetic Operators
• Assignment Operators
• Logical Operators
• Relational Operators
• Miscellaneous Operators

Let us discuss the types of operators in detail.

1. Arithmetic Operators

These operators perform basic arithmetic operations like addition, subtraction, multiplication, division, exponent, modulus, etc.

Let us see what these operators do.

For example, take two variables:

For example:-

x <- 10
y <- 5

These operators can also be used to carry out mathematical operations on vectors.

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For creating vectors, we use the c() function.

In the case of vectors, all these operations are done in an element-by-element fashion.

Example Usage

x <- c(9, 9, 9)
y <- c(1, 1, 1)
print(x + y)

Output:

[1] 10 10 10

Let us see how you can use these arithmetic operators in R programming.

1. Addition

a <- c(8,4.2,7)

b <- c(2, 4, 3)

print(a+b)

Output:

[1] 10.0  8.2 10.0

2. Subtraction

a <- c(4,7.8,7)

b <- c(6, 4, 2)

print(a-b)

Output:

[1] -2.0  3.8  5.0

3. Multiplication

a <- c(4,6.2,7)

b <- c(8, 2, 6)

print(a*b)

Output:

[1] 32.0 12.4 42.0

4. Division

a <- c(6,5.5,8)

b <- c(12, 2, 4)

print(a/b)

Output:

[1] 0.50 2.75 2.00

5. Exponent

a <- c(3,5.5,4)

b <- c(2, 4, 3)

print(a^b)

Output:

[1]   9.0000 915.0625  64.0000

6. Modulus

a <- c(3,7.5,8)

b <- c(6, 4, 4)

print(a%%b)

Output:

[1] 3.0 3.5 0.0

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2. Assignment Operators

The use of these operators is to assign values to the variables. There are two kinds of assignments, leftwards assignment, and rightwards assignment.
Operators ‘<-‘ and  ‘=’ are used to assign values to any variable.
x<- 3 or x = 3 (Leftwards Assignment)
3 -> x or x = 3 (Rightwards Assignment)

3. Logical Operators

These operators are used to perform Boolean operations like AND, OR, NOT, etc. on variables.
Different logical operators are as follows:

ZEROS are taken as FALSE and NON-ZERO numbers are taken as TRUE.
For example:

x <- c(FALSE, TRUE, 3, 0)
y <- c(FALSE, TRUE, FALSE, TRUE)
!x                  # NOT operation
x & y             # AND operation

Output:

[1] TRUE FALSE FALSE TRUE
[1] FALSE TRUE FALSE FALSE

Example 2:

x && y
x || y

Output

[1] FALSE
[1] FALSE

4. Relational Operators

These operators are used to compare two values or variables. To find if one is smaller, greater, equal, not equal, and other similar operations these operators are used. The output of a
A relational operator is always a Logical value, that is either TRUE or FALSE.
For example:-
x <- 10
y <- 5

5. Miscellaneous Operators

These R programming operators are used for special cases and are not for general mathematical or logical computation.
colon operator – It is used to generate a series of numbers in sequence for a vector.
For example:

Create an array:

x <- 0:9
print(x)

Output

[1] 0 1 2 3 4 5 6 7 8 9

Check using %in% operator for elements

v1 <- 5
t <- 0:9
print(v1 %in% t)

Output

[1] TRUE

%* %: This operator multiplies a matrix with its transpose.
For example:

M = matrix(c(1, 2, 3, 4), nrow = 2, ncol = 2, byrow = TRUE)
T = M %*% t(M)
print(T)

Output

      [,1]  [,2]
[1,]  5    11
[2,] 11    25

Conclusion

In this tutorial, we learned about the different R programming operators and how to use these operators to perform various arithmetic and logical manipulations in R. This knowledge is fundamental for anyone pursuing Data Science online training, as it enables you to efficiently analyze and manipulate data using R. Understanding operators like arithmetic, comparison, and logical operators will help you perform key tasks such as data transformation, statistical analysis, and model evaluation.

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