There are many ways to select unique or distinct rows from a dataframe, one of which is using dplyr distinct in R. This article will share the syntax, parameters, and usage of the **distinct() function in R**.

**What is the dplyr distinct in R**?

The dplyr package provides the distinct() function. It selects distinct or unique rows from the dataframe.

**Syntax:**

`distinct(data frame, ..., .keep_all)`

**Parameters:**

**data frame:**a data frame.**…:**Optional rows to use when determining distinct.**.keep_all:**Default is FALSE. If TRUE, keep all variables in the dataframe.

**How to use the distinct() function in R**?

You can use the distinct() function to get distinct rows of all columns or selected columns in the dataframe. You can also set the value of the **.keep_all** parameter to TRUE to keep all variables in the dataframe.

We built a simple data frame for the height and weight of some students. In it, some of the height and weight values are repeated.

**Example:**

# Create a data frame student <- data.frame( name = c( "Avram", "Rebecca", "Hansen", "Alana", "Kelly", "Dudley", "Brenna", "Tyrone", "Oliver", "Laura" ), height = c(164, 172, 173, 164, 172, 163, 175, 156, 173, 164), weight = c(55, 66, 67, 48, 79, 57, 66, 55, 71, 48) ) print(student)

**Output:**

```
name height weight
1 Avram 164 55
2 Rebecca 172 66
3 Hansen 173 67
4 Alana 164 48
5 Kelly 172 79
6 Dudley 163 57
7 Brenna 175 66
8 Tyrone 156 55
9 Oliver 173 71
10 Laura 164 48
```

**Get distinct rows of selected columns**

You can do distinct on the selected** **column by setting the second parameter ‘…’ to the variable name that you want to use to perform distinctly.

**Example:**

student <- data.frame( name = c( "Avram", "Rebecca", "Hansen", "Alana", "Kelly", "Dudley", "Brenna", "Tyrone", "Oliver", "Laura" ), height = c(164, 172, 173, 164, 172, 163, 175, 156, 173, 164), weight = c(55, 66, 67, 48, 79, 57, 66, 55, 71, 48) ) library(dplyr) # Distinct with the 'height' column student1 <- distinct(student, height) cat("Distinct with the 'height' column\n") print(student1) # Distinct with the 'weight' column student2 <- distinct(student, weight) cat("\nDistinct with the 'weight' column\n") print(student2)

**Output:**

```
Distinct with the 'height' column
height
1 164
2 172
3 173
4 163
5 175
6 156
Distinct with the 'weight' column
weight
1 55
2 66
3 67
4 48
5 79
6 57
7 71
```

**Keep all variables in the data frame**

The **‘.keep_all**‘ parameter is set to FALSE by default. You can choose to keep all other variables by setting ‘.keep_all’ to TRUE.

**Example:**

student <- data.frame( name = c( "Avram", "Rebecca", "Hansen", "Alana", "Kelly", "Dudley", "Brenna", "Tyrone", "Oliver", "Laura" ), height = c(164, 172, 173, 164, 172, 163, 175, 156, 173, 164), weight = c(55, 66, 67, 48, 79, 57, 66, 55, 71, 48) ) library(dplyr) # Choose to keep all other variables when doing distinct with the 'height' column student1 <- distinct(student, height, .keep_all = TRUE) cat("Distinct with the 'height' column\n") print(student1) # Choose to keep all other variables when doing distinct with the 'weight' column student2 <- distinct(student, weight, .keep_all = TRUE) cat("\nDistinct with the 'weight' column\n") print(student2)

**Output:**

```
Distinct with the 'height' column
name height weight
1 Avram 164 55
2 Rebecca 172 66
3 Hansen 173 67
4 Dudley 163 57
5 Brenna 175 66
6 Tyrone 156 55
Distinct with the 'weight' column
name height weight
1 Avram 164 55
2 Rebecca 172 66
3 Hansen 173 67
4 Alana 164 48
5 Kelly 172 79
6 Dudley 163 57
7 Oliver 173 71
```

**Summary**

We learned about the **distinct() function in R** and how to use it on variables. We recommend using the distinct() function in R with the** .keep_all** parameter set to TRUE for the most intuitive results. Thank you for reading.

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Hello, my name’s Bruce Warren. You can call me Bruce. I’m interested in programming languages, so I am here to share my knowledge of programming languages with you, especially knowledge of C, C++, Java, JS, PHP.

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