# Average of Values in an R Vector

A vector is a one-dimensional data structure used to store data of the same type in R. Numeric vectors are commonly used to store a sequence of numbers. In this tutorial, we will look at how to get the average of values in an R vector with the help of some examples.

## How to get the average of values in a vector in R?

You can use the R `mean()` function to get the average of values in a vector. Pass the vector as an argument to the function. The following is the syntax –

```# average of values in a vector
mean(x, trim=0, na.rm=FALSE)```

The following are the arguments that you can give to the `mean()` function in R.

• x – The vector for which you want to compute the mean.
• trim – (Optional argument) Specifies the fraction of values to remove (or trim) from the start and the end of the vector before computing the mean. It is `0` by default.
• na.rm – (Optional argument) Indicates whether to remove missing values before computing the mean. It is `FALSE` by default.

The function returns the mean of values in the passed vector.

## Examples

Let’s look at some examples of using the above method to get the mean of values in a vector.

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### Average of values in a numeric vector

Let’s create a vector of numbers (and without any `NA` values) and apply the `mean()` function.

```# create a vector
vec <- c(1, 2, 3)
# mean of values in vector
mean(vec)```

Output:

`2`

We get the mean as 2, which is the correct mean of the values in the above vector, (1+2+3)/3=2.

What would happen if there are some `NA` present values in the vector?

Let’s find out.

First, we will create a vector with some `NA` values and then apply the `mean()` function without any additional arguments.

```# create a vector with NA values
vec <- c(1, 2, NA, 3, NA)
# mean of values in the vector
mean(vec)```

Output:

`<NA>`

You can see that we get `NA` as the output. This is because averaging anything with `NA` results in an `NA` in R.

### Average of values in a vector with `NA` values

You can pass `TRUE` to the `na.rm` parameter of the `mean()` function to exclude missing values when computing the average in a vector.

```# create a vector with NA values
vec <- c(1, 2, NA, 3, NA)
# mean of values in the vector
mean(vec, na.rm=TRUE)```

Output:

`2`

Now we get the average of the values in the above vector as 2.

### Trim vector before computing average

With the optional `trim` parameter in the `mean()` function, you can specify the fraction of values you want to trim (or exclude) from the start and the end of the vector before computing the mean. Let’s look at an example.

```# create a vector
vec <- c(1, 2, 3, 4, 5)
# mean of values in the vector
mean(vec, trim=0.2)```

Output:

`3`

Here, we get the mean of the values in the above vector after trimming the first and last 20% of the values. Since the vector is of length 5, trimming 20% means, we trim one value each from the start and the end. Thus, the average that we get in the output here is the average of the middle three values 2, 3, and 4 which is equal to 3.

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