# How to use the floor() function in R?

In this tutorial, we will look at how to use the built-in floor() function in R with the help of some examples.

## What does the `floor()` function do in R?

You can use the built-in math function, floor() to get the largest integer smaller than or equal to a given number in R. Pass the number for which you want to get the floor as an argument to the `floor()` function. The following is the syntax –

`floor(x)`

If you pass an integer to the `floor()` function, you’ll get the same value as the output. Note that you can apply the `floor()` function to a numeric vector, array, matrix, and a dataframe as well.

## Examples

Let’s look at some examples of using the `floor()` function in R.

### Apply `floor()` function to a number

First, let’s look at some examples of using the `floor()` function on a positive real number.

```# floor for a positive real number
print(floor(3.2))
print(floor(3.4))
print(floor(3.7))```

Output:

``` 3
 3
 3```

You can see that we get the same output, 3 for the values, 3.2, 3.4, and 3.7. Notice that 3 is the largest integer that is smaller than or equal to the above values and thus we get 3 as the output for all the values in the above example.

Let’s now apply the floor function to negative real numbers.

```# floor for a negative real number
print(floor(-3.2))
print(floor(-3.4))
print(floor(-3.7))```

Output:

``` -4
 -4
 -4```

We get -4 as the result for the numbers, -3.2, -3.4, and -3.7. Here, -4 is the largest integer that is smaller than or equal to values passed.

### Apply `floor()` function to a numeric vector

You can similarly apply the `floor()` function to a numeric vector in R. If you apply the `floor()` function to a numeric vector, it will compute the floor for each value in the vector.

Let’s look at an example.

```# floor for a numeric vector
vec <- c(0, 1.3, -1.3, 2.5, 3.1)
print(floor(vec))```

Output:

`  0  1 -2  2  3`

You can see that we get the floor (or the floor value) for each element in the numeric vector.

You might also be interested in –

Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.

## Authors

• Piyush is a data scientist passionate about using data to understand things better and make informed decisions. In the past, he's worked as a Data Scientist for ZS and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.

• 