In case anyone wonders, this behavior is expected and consistent with
the note "the sum of an empty set is zero, by definition" in
help("sum"), i.e.> x <- numeric(0) > str(x) num(0) > sum(x) [1] 0 Analogously, prod(numeric(0)) gives 1.0. To OP, if you're in the end of the day is after the sample mean, note that mean() returns NaN in this case, e.g. > x <- rep(NA_real_, times=10) > mean(x, na.rm=TRUE) [1] NaN /Henrik On Mon, Jan 26, 2015 at 1:17 PM, Ista Zahn <istaz...@gmail.com> wrote: > Try with na.rm=TRUE. > On Jan 26, 2015 4:04 PM, "MacQueen, Don" <macque...@llnl.gov> wrote: > >> I'm a little puzzled by the assertion that the result is 0.0 when all the >> elements are NA: >> >> > sum(NA) >> [1] NA >> >> > sum(c(NA,NA)) >> [1] NA >> >> > sum(rep(NA, 10)) >> [1] NA >> >> > sum(as.numeric(letters[1:4])) >> [1] NA >> Warning message: >> NAs introduced by coercion >> >> >> Considering that the example snippet of code has several other aspects >> besides using sum(), among them subsetting rows of a data frame when there >> are apparently NAs in some its variables ... I wonder if the reason for >> the failure of that snippet has been misunderstood? >> >> >> -- >> Don MacQueen >> >> Lawrence Livermore National Laboratory >> 7000 East Ave., L-627 >> Livermore, CA 94550 >> 925-423-1062 >> >> >> >> >> >> On 1/25/15, 3:21 PM, "Allen Bingham" <aebingh...@gmail.com> wrote: >> >> >I understand that in order to get the sum function to ignore missing >> >values >> >I need to supply the argument na.rm=TRUE. However, when summing numeric >> >values in which ALL components are "NA" ... the result is 0.0 ... instead >> >of >> >(what I would get from SAS) of NA (or in the case of SAS "."). >> > >> >Accordingly, I've had to go to 'extreme' measures to get the sum function >> >to >> >result in NA if all arguments are missing (otherwise give me a sum of all >> >non-NA elements). >> > >> >So for example here's a snippet of code that ALMOST does what I want: >> > >> > >> >SumValue<-apply(subset(InputDataFrame,!is.na(Variable.1)|!is.na >> (Variable.2 >> >), >> >select=c(Variable.1,Variable.2)),1,sum,na.rm=TRUE) >> > >> >In reality this does NOT give me records with NA for SumValue ... but it >> >doesn't give me values for any records in which both Variable.1 and >> >Variable.2 are NA --- which is "good enough" for my purposes. >> > >> >I'm guessing with a little more work I could come up with a way to adapt >> >the >> >code above so that I could get it to work like SAS's sum function ... >> > >> >... but before I go that extra mile I thought I'd ask others if they know >> >of >> >functions in either base R ... or in a package that will better mimic the >> >SAS sum function. >> > >> >Any suggestions? >> > >> >Thanks. >> >______________________________________ >> >Allen Bingham >> >aebingh...@gmail.com >> > >> >______________________________________________ >> >R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >https://stat.ethz.ch/mailman/listinfo/r-help >> >PLEASE do read the posting guide >> >http://www.R-project.org/posting-guide.html >> >and provide commented, minimal, self-contained, reproducible code. >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
