Special operators (%in%, %*%) in R Programming

Introduction

Special operators help you do common tasks easily, like checking if something is in a list or multiplying matrices.

When you want to check if values exist inside a group of values.

When you need to multiply two matrices together.

When filtering data based on membership in a set.

When performing mathematical operations on tables of numbers.

When working with data frames and you want to find matching elements.

Syntax

R Programming

x %in% y
x %*% y

%in% checks if elements of x are found in y and returns TRUE or FALSE.

%*% performs matrix multiplication between x and y.

Examples

Checks which numbers in the first list are also in the second list.

R Programming

c(1, 2, 3) %in% c(2, 3, 4)

Multiplies two 2x2 matrices together.

R Programming

matrix(c(1, 2, 3, 4), nrow=2) %*% matrix(c(5, 6, 7, 8), nrow=2)

Checks if the word "apple" is in the list of fruits.

R Programming

"apple" %in% c("banana", "apple", "cherry")

Sample Program

This program checks which numbers in values are also in check using %in%. Then it multiplies two matrices using %*% and prints both results.

R Programming

values <- c(10, 20, 30, 40)
check <- c(20, 50)
result_in <- values %in% check

mat1 <- matrix(c(1, 2, 3, 4), nrow=2)
mat2 <- matrix(c(5, 6, 7, 8), nrow=2)
result_mult <- mat1 %*% mat2

print(result_in)
print(result_mult)

Important Notes

%in% returns a logical vector showing TRUE or FALSE for each element.

%*% requires the number of columns in the first matrix to match the number of rows in the second matrix.

These operators make code easier to read and write for common tasks.

Summary

%in% checks membership of elements in a vector or list.

%*% performs matrix multiplication.

Both are special operators that simplify common operations in R.

Practice

1. What does the %in% operator do in R?

easy

A. Calculates the sum of two vectors

B. Performs element-wise multiplication of two vectors

C. Performs matrix multiplication

D. Checks if elements of one vector are present in another vector

Solution

1. Step 1: Understand the purpose of %in%

   The %in% operator is used to check membership, meaning it tests if elements of one vector exist in another.

2. Step 2: Compare with other operations

   Other options describe arithmetic or matrix operations, which are not the function of %in%.

3. Final Answer:

   Checks if elements of one vector are present in another vector -> Option D

4. Quick Check:

   %in% = membership check [OK]

Hint: Remember: %in% means 'is in' for membership [OK]

Common Mistakes:

• Confusing %in% with arithmetic operators
• Thinking %in% does matrix multiplication
• Assuming %in% returns numeric results

2. Which of the following is the correct syntax for matrix multiplication in R?

easy

A. A * B

B. A %*% B

C. A %in% B

D. A + B

Solution

1. Step 1: Identify matrix multiplication operator

   In R, matrix multiplication is done using %*%, so A %*% B is correct syntax.

2. Step 2: Differentiate from other operators

   * is element-wise multiplication, %in% is membership, and + is addition.

3. Final Answer:

   A %*% B -> Option B

4. Quick Check:

   Matrix multiply = %*% [OK]

Hint: Use %*% for matrix multiply, * for element-wise [OK]

Common Mistakes:

• Using * instead of %*% for matrix multiplication
• Confusing %in% with multiplication
• Using + for multiplication

3. What is the output of the following R code?

x <- c(3, 1, 5)
y <- c(3, 4, 5, 6)
x %in% y

medium

A. [TRUE, FALSE, TRUE]

B. [FALSE, TRUE, FALSE]

C. [TRUE, TRUE, TRUE]

D. [FALSE, FALSE, FALSE]

Solution

1. Step 1: Check each element of x in y

   3 is in y, so TRUE; 1 is not in y, so FALSE; 5 is in y, TRUE.

2. Step 2: Form the logical vector

   The result is [TRUE, FALSE, TRUE].

3. Final Answer:

   [TRUE, FALSE, TRUE] -> Option A

4. Quick Check:

   %in% returns logical vector [OK]

Hint: Check each element presence one by one [OK]

Common Mistakes:

• Mixing order of TRUE/FALSE in output
• Assuming %in% returns indices
• Confusing %in% with element-wise comparison

4. Identify the error in the following R code:

A <- matrix(c(1,2,3,4), nrow=2)
B <- matrix(c(5,6,7,8), nrow=2)
C <- A *%* B

medium

A. Matrices A and B have incompatible dimensions

B. Missing library for matrix multiplication

C. Incorrect operator *%* used for matrix multiplication

D. Matrix A is not defined properly

Solution

1. Step 1: Check operator syntax

   The operator *%* is invalid in R; correct operator is %*%.

2. Step 2: Verify matrix dimensions and definitions

   Both matrices are 2x2, so dimensions are compatible and matrices are defined correctly.

3. Final Answer:

   Incorrect operator *%* used for matrix multiplication -> Option C

4. Quick Check:

   Matrix multiply operator is %*% [OK]

Hint: Use %*% exactly for matrix multiplication [OK]

Common Mistakes:

• Typing operators in wrong order
• Assuming *%* is valid
• Confusing element-wise * with matrix multiply

5. Given two matrices:

M1 <- matrix(c(1, 0, 2, 3), nrow=2)
M2 <- matrix(c(4, 1, 0, 2), nrow=2)

Which R expression correctly computes the matrix product and then checks if the number 5 is in the resulting matrix?

hard

A. 5 %in% (M1 %*% M2)

B. M1 *%*% M2 %in% 5

C. M1 %in% 5 %*% M2

D. M1 %*% M2 == 5

Solution

1. Step 1: Perform matrix multiplication correctly

   Use %*% to multiply M1 and M2: M1 %*% M2.

2. Step 2: Check membership of 5 in the product matrix

   Use %in% to check if 5 is present in the resulting matrix: 5 %in% (M1 %*% M2).

3. Final Answer:

   5 %in% (M1 %*% M2) -> Option A

4. Quick Check:

   Matrix multiply then membership check = 5 %in% (M1 %*% M2) [OK]

Hint: Chain %*% then %in% with parentheses [OK]

Common Mistakes:

• Using wrong operator order
• Typing *%*% instead of %*%
• Using == instead of %in% for membership