# How to Use the nrow() Function in R

The nrow() function in R is “used to get the rows for an object. The nrow() function can easily extract the number of rows in an object that can be a matrix, data frame, or even a dataset.

### Syntax

``nrow(data)``

### Parameters

The data is a required argument that can be vector, array, data frame, NULL, or matrix.

### Return value

It returns the number of rows of an input R object.

## Example 1: Counting the number of rows in the Data Frame

Create a data frame using the data.frame() function.

Use the nrow() function to count the number of rows in a data frame.

``````df <- data.frame(
students = c("Michael", "Taylor", "Selena"),
marks = c(90, 80, 75),
levels = c(10, 7, 8)
)

nrow(df)``````

Output

``[1] 3``

Our data frame has three rows and three columns, and we get the three rows using the nrow() function.

## Example 2: Counting the number of rows of the matrix in R

To count the number of rows of a matrix in R, use the nrow() function.

``````mat <- matrix(1:9, 3, 3)

print(mat)

cat("---Couting number of rows of a matrix---", "\n")

nrow(mat)``````

Output

``````     [,1]  [,2]  [,3]
[1,]   1     4     7
[2,]   2     5     8
[3,]   3     6     9

---Couting number of rows of a matrix---

[1] 3``````

You can see that the nrow() function returns three as output because the matrix has three rows.

## Example 3: Counting the number of rows of an array in R

Use the nrow() function to count the number of rows of an array in R.

``````arr <- array(1:12, dim = 4:3)

print(arr)

cat("---Counting number of rows using nrow() function---", "\n")

nrow(arr)``````

Output

``````     [,1] [,2] [,3]
[1,]   1   5    9
[2,]   2   6   10
[3,]   3   7   11
[4,]   4   8   12

---Counting number of rows using nrow() function---

[1] 4``````

You can see that the array has four rows and three columns, and its output is the same.

## Example 4: nrow() function with a condition in R

To use the nrow() function with a condition in R, use the subsetting.

The subsetting approach helps us filter some data based on the condition.

``````df <- data.frame(LETTERS, letters, position = 1:length(letters))

dfSubset <- df[6:10, ]

nrow(dfSubset)``````

Output

``[1] 5``

Let’s use the iris dataset and apply a condition while fetching the number of rows of the data frame.

``nrow(iris[iris\$Sepal.Length > 3, ])``

Output

``[1] 150``

You can see that the iris dataset has 150 rows whose Sepal.Length is greater than 3.