# Handle Missing Values in Vectors

Learn how to handle missing values in descriptive statistics using R.

## We'll cover the following

## Missing values

The artificial variable `v1`

doesn’t have any missing value (`v1 <- c(1, 2, 0, 2, 4, 5, 10, 1)`

). However, missing values are common in real-world data. What happens when missing values are present? This question is relevant both when we compute descriptive statistics for a vector and when we want to know how many missing or non-missing values are present in a vector.

Suppose we create a new variable called `v2`

, which is identical to `v1`

except that `v2`

has two missing values. In R, the default missing value is denoted by `NA`

. So, we replace two observations in `v1`

with `NA`

to generate `v2`

.

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