In this tutorial, we will look at how to count the number of distinct values in a vector in R with the help of some examples.

## How do you count unique values in a vector in R?

You can use a combination of the `length()`

and the `unique()`

function in R to count the number of distinct (or unique) values in a vector.

First, use the `unique()`

function to remove the duplicates and then apply the `length()`

function to get the unique value count inside the vector. The following is the syntax –

# count distinct values in vector vec length(unique(vec))

Note that the distinct value count from the above method is inclusive of `NA`

values (if any) inside the vector. See the examples below.

## Examples

Let’s now look at some examples of using the above method.

### Count of distinct values in a vector

Let’s create a vector of some numbers (and having some repeated values) and use a combination of the `length()`

and `unique()`

functions to get its distinct value count.

# create a vector vec <- c(1, 2, 3, 2, 3, 3) # count distinct values in vec print(length(unique(vec)))

Output:

[1] 3

We get 3 as the output since there are only three distinct values in the above vector – 1, 2, and 3.

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### Count of distinct values in a vector with NA values

What would happen if our vector contains some `NA`

values?

Let’s find out.

We’ll use the same vector from above with some additional `NA`

values and then apply the same method.

# create a vector vec <- c(1, 2, NA, 3, 2, 3, NA, 3) # count distinct values in vec print(length(unique(vec)))

Output:

[1] 4

Now, we get the unique value count as 4. This is because the `unique()`

function removes duplicates and not NA. Thus we get four unique values – 1, 2, `NA`

, and 3.

If you do not want to include `NA`

in the unique value count, you can remove `NA`

values from the vector before applying the above method.

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