# R – Count Distinct Values in a Vector

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.

📚 Data Science Programs By Skill Level

Introductory

Intermediate ⭐⭐⭐

🔎 Find Data Science Programs 👨‍💻 111,889 already enrolled

Disclaimer: Data Science Parichay is reader supported. When you purchase a course through a link on this site, we may earn a small commission at no additional cost to you. Earned commissions help support this website and its team of writers.

### 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.

You might also be interested in –