The na_example vector represents a series of counts. You can quickly examine the object using:

library(dslabs)
data("na_example")  
str(na_example)
#>  int [1:1000] 2 1 3 2 1 3 1 4 3 2 ...

Or have a look at the first 50 values with:

head(na_example, n = 50)
#>  [1]  2  1  3  2  1  3  1  4  3  2  2 NA  2  2  1  4 NA  1  1  2  1  2  2  1  2  5 NA  2  2  3  1  2  4  1  1  1  4  5  2  3  4  1  2  4  1  1  2  1  5 NA

We observe that not all the values in the vector contain an integer number, some of them are missing values, denoted by NA in R.

When we compute the average with the function mean, we obtain an NA result as well:

mean(na_example)
#> [1] NA

The mean function requires input without missing values. We will tackle this in the next exercise, first we want to find out how many missing values we have.

The is.na function returns a logical vector that tells us which entries are NA. Assign this logical vector to an object called ind and determine how many NAs does na_example have. Store your anwser in na_count.

Hint: you can use the sum function to count the number of occurences of TRUE in a logical vector. The TRUE values will be counted as 1 and the FALSE values as 0.