How to create a new dataset of rows which contain NA in a specific column?

Question

Here is a simplified version of my dataset:

myDF <- tibble(city = rep(c("London", "Madrid", "Paris"), each = 3),
               date = rep(c("Day1", "Day2", "Day3"), times = 3),
               visits = c(20, 32, NA, NA, 28, 26, 25, NA, 21))

# A tibble: 9 x 3
  city   date  visits
  <chr>  <chr>  <dbl>
1 London Day1      20
2 London Day2      32
3 London Day3      NA
4 Madrid Day1      NA
5 Madrid Day2      28
6 Madrid Day3      26
7 Paris  Day1      25
8 Paris  Day2      NA
9 Paris  Day3      21

I know I can find the index for each row which has NA in the "visits" column with the following:

which(is.na(myDF$visits))
# console output: 3, 4, 8

But if the above code returns hundreds of index values, how can I create a new dataset which only contains the rows that appear in the console output?

If there is alternative code that can be used please mention.

Any help is much appreciated :)