Interesting, right? The resulting data frame displays
NAs for missing records! This is because R does not know how to compare
NA with 500.
Obviously, missing values are problematic in analysis, so it's usually best to somehow remove them. Only then can we work on further analyzing the data. But if we can't use operators when one of the operands is
NA, how are we going to detect or display missing values? Well, as usual, there's a function for that!
is.na() function takes a single vector argument and returns a logical vector populated with
FALSE values. An element in the logical vector returned by
is.na() will only be
TRUE if the corresponding element in the original vector is
NA. It will be
FALSE otherwise. Here's an example of a vector with some missing values:
a <- c(2, 3, 4, 5, NA, NA)
is.na(a) will return the following:
 FALSE FALSE FALSE FALSE TRUE TRUE