Searching for greater/less than values with NAs

Question

I have a dataframe for which I've calculated and added a difftime column:

    name   amount   1st_date   2nd_date  days_out
    JEAN  318.5 1971-02-16 1972-11-27  650 days
 GREGORY 1518.5       <NA>       <NA>   NA days
    JOHN  318.5       <NA>       <NA>   NA days
  EDWARD  318.5       <NA>       <NA>   NA days
  WALTER  518.5 1971-07-06 1975-03-14 1347 days
   BARRY 1518.5 1971-11-09 1972-02-09   92 days
   LARRY  518.5 1971-09-08 1972-02-09  154 days
   HARRY  318.5 1971-09-16 1972-02-09  146 days
   GARRY 1018.5 1971-10-26 1972-02-09  106 days

I want to break it out and take subtotals where days_out is 0-60, 61-90, 91-120, 121-180.

For some reason I can't even reliably write bracket notation. I would expect

members[members$days_out<=120, ] to show just Barry and Garry, but I get a whole lot of lines like:

NA.1095     <NA>     NA       <NA>       <NA>  NA days
NA.1096     <NA>     NA       <NA>       <NA>  NA days
NA.1097     <NA>     NA       <NA>       <NA>  NA days

Those don't exist in the original data. There's no one without a name. What am I doing wrong here?

Answer 1

This is standard behavior for < and other relational operators: when asked to evaluate whether NA is less than (or greater than, or equal to, or ...) some other number, they return NA, rather than TRUE or FALSE.

Here's an example that should make clear what is going on and point to a simple fix.

x <- c(1, 2, NA, 4, 5)
x[x < 3]
# [1]  1  2 NA
x[x < 3 & !is.na(x)]
# [1] 1 2

---

To see why all of those rows indexed by NA's have row.names like NA.1095, NA.1096, and so on, try this:

data.frame(a=1:2, b=1:2)[rep(NA, 5),]
#       a  b
# NA   NA NA
# NA.1 NA NA
# NA.2 NA NA
# NA.3 NA NA
# NA.4 NA NA