The **dist() function in R** is used to find the distance between the rows of a matrix. If you are not familiar with this function, then please check out our instructions below, we will discuss its syntax, application, and how to use it in your R program.

**Dist() function in R**

**What does the dist() function do in R?**

“Dist” stands for distance. So basically, the **dist()** function will calculate the distance of the rows of a data matrix. It can measure six different types of distances: Euclidean, Maximum, Canberra, Manhattan, Binary, and Minkowski.

**Syntax**:

`dist(matrix, method)`

**Parameter**s:

**matrix**: the matrix/data frame.**method**: the types of distance you want to calculate. It is one of these six: Euclidean, Maximum, Canberra, Manhattan, Binary, and Minkowski.

**How to use dist() in R**?

There are six distance modes that the **dist()** function offers.

**Euclidean distance**: The distance between two points or two vectors. Calculated by this formula:

Let’s say we have this matrix:

vector1 <- c(12, 34, 13, 49, 67, 25, 63) vector2 <- c(68, 91, 43, 16, 27, 32, 11) vector3 <- c(18, 21, 75, 24, 92, 13, 62) data <- rbind(vector1, vector2, vector3) data

```
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
vector1 12 34 13 49 67 25 63
vector2 68 91 43 16 27 32 11
vector3 18 21 75 24 92 13 62
```

Now to calculate the Euclidean distance between the vectors in this matrix, do as follow:

dist(data, method = "euclidean")

**Output:**

```
vector1 vector2
vector2 112.81401
vector3 73.78347 125.19984
```

As you can see, the results are well-demonstrated and easy to follow. For example, the Euclidean distance between `vector_1`

and `vector_2`

is` 112.81401`

.

If we have 4 vectors like this:

vector1 <- c(12, 34, 13, 49, 67, 25, 63) vector2 <- c(68, 91, 43, 16, 27, 32, 11) vector3 <- c(18, 21, 75, 24, 92, 13, 62) vector4 <- c(20, 32, 19, 51, 60, 42, 38) data <- rbind(vector1, vector2, vector3, vector4) dist(data, method = "euclidean")

We would get:

```
vector1 vector2 vector3
vector2 112.81401
vector3 73.78347 125.19984
vector4 32.72614 97.48846 80.19352
```

The 5 other methods (Maximum, Canberra, Manhattan, Binary, and Minkowski) are used just the same way. Simply change the method to whatever mode you want to use. For example, if you want to calculate the Canberra distance:

vector1 <- c(12, 34, 13, 49, 67, 25, 63) vector2 <- c(68, 91, 43, 16, 27, 32, 11) vector3 <- c(18, 21, 75, 24, 92, 13, 62) data <- rbind(vector1, vector2, vector3) dist(data, method = "canberra")

**Output**:

```
vector1 vector2
vector2 3.450448
vector3 1.964397 3.344653
```

You can search the internet for the definition of each type of distance or check out this link for more information.

**Summary**

In this tutorial, we have shown you the **dist() function in R** and how to use it in your program. The dist() function helps us calculate six types of distances between vectors in a matrix.

**Maybe you are interested**:

- The replace() function in R: How to use replace function in R?
- Head function in R: How to use head() in R
- pt() function in R: How to use the pt function in R

Hello. My name is Khanh Hai Ngo. I graduated in Information Technology at VinUni. My advanced programming languages include C, C++, Python, Java, JavaScript, TypeScript, and R, which I would like to share with you. You will benefit from my content.

**Name of the university: **VinUni

**Major**: EE

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