In this guide, we will share with you how to get the intersection of two objects in R by the `intersect()`

function. The` intersect `

in R is used with two common mode objects. Let’s learn more about it with the explanation and examples below.

**What does the intersect do in R?**

The `intersect()`

function in R is used to get the intersection of two common mode objects. Because of the function of the `intersect()`

in R, it is created by many packages such as: ‘dplyr’, ‘lubridate’, ‘base R’, and ‘generics’. For your demand, this function can be used in some different ways, but the main function of it is to get the intersection of the elements of two objects. Let’s take a look at the syntax of this function.

**Syntax**:

`intersect(data1, data2)`

**Parameters**:

**data1:**The data of the first object.**data2:**The data of the second object.

After learning the usage and the syntax of the `intersect()`

function, we will show you how to use this function with some examples in the next title below.

**How to use the intersect in R**?

The `intersect()`

function is used with almost all objects in R such as: the vector, the array, the data frame, … In this title, we will show you how to use the `intersect()`

function with the vector and the data frame.

**Use the **`intersect()`

function with the vector

`intersect()`

function with the vectorWe can use the `intersect()`

function to get the common elements of two vectors in R.

Look at the example below:

vec1 <- c(1, 2, 3, 4, 5) vec2 <- c(3, 4, 5, 6, 7, 8) # Get the common values of two vectors intersect(vec1, vec2)

**Output**

`[1] 3 4 5`

**Use the **`intersect()`

function with the data frame

`intersect()`

function with the data frameWe can use the `intersect()`

function to get the common elements of two data frames in R.

To that, you can not use the `intersect()`

function in the ‘base R’ package, you should use the `intersect()`

function in the` 'dplyr' `

instead.

Look at the example below:

# Create the first data frame df1 <- data.frame( Customers = c("Alex", "Peter", "Linda", "John", "Puth"), Height = c(180, 190, 185, 199, 200) ) df1

**Output**

```
Customers Height
1 Alex 180
2 Peter 190
3 Linda 185
4 John 199
5 Puth 200
```

Create another data frame.

# Create the second data frame df2 <- data.frame( Customers = c("Florentino", "Peter", "Linda", "John", "Tulen"), Height = c(180, 190, 185, 199, 201) ) df2

**Output**

```
Customers Height
1 Florentino 180
2 Peter 190
3 Linda 185
4 John 199
5 Tulen 201
```

Let’s get the common rows of two data frames you have created by the intersect() function in the ‘dplyr’ package.

df1 <- data.frame( Customers = c("Alex", "Peter", "Linda", "John", "Puth"), Height = c(180, 190, 185, 199, 200) ) df2 <- data.frame( Customers = c("Florentino", "Peter", "Linda", "John", "Tulen"), Height = c(180, 190, 185, 199, 201) ) # Get the common rows of two data frames df <- dplyr::intersect(df1, df2) df

**Output**

```
Customers Height
1 Peter 190
2 Linda 185
3 John 199
```

You can learn how to merge two data frames by row names in R here.

**Summary**

You have learned about the usage, the syntax, and how to use the `intersect`

in R. The `intersect()`

function is built in some packages in R. You can use the `intersect()`

function in different ways with the different packages to accommodate your demand. We hope this tutorial is helpful to you. Thanks!

**Maybe you are interested**:

- The abline() function in r
- drop() Function In R: Removes Redundant Dimension
- The first() function in R

My name is Thomas Valen. As a software developer, I am well-versed in programming languages. Don’t worry if you’re having trouble with the C, C++, Java, Python, JavaScript, or R programming languages. I’m here to assist you!

**Name of the university:** PTIT

**Major**: IT

**Programming Languages**: C, C++, Java, Python, JavaScript, R