[R] Sum function and missing values --- need to mimic SAS sum function
aebingham2 at gmail.com
Mon Jan 26 22:56:14 CET 2015
Sven and John,
Thanks for your suggested code ... hits the mark! The code by John is what I need to be able to use in an apply function, but I really like the simplicity of Sven's suggestion.
Also thanks to all who replied --- really helped broaden my knowledge of R.
From: Sven E. Templer [mailto:sven.templer at gmail.com]
Sent: Monday, January 26, 2015 6:56 AM
To: Martin Maechler
Cc: Jim Lemon; r-help mailing list; Allen Bingham
Subject: Re: [R] Sum function and missing values --- need to mimic SAS sum function
you can also define 'na.rm' in sum() by 'NA state' of x (where x is your vector holding the data):
On 26 January 2015 at 13:45, Martin Maechler <maechler at lynne.stat.math.ethz.ch> wrote:
>>>>>> Jim Lemon <drjimlemon at gmail.com>
>>>>>> on Mon, 26 Jan 2015 11:21:03 +1100 writes:
> > Hi Allen, How about this:
> > sum_w_NA<-function(x) ifelse(all(is.na(x)),NA,sum(x,na.rm=TRUE))
> Excuse, Jim, but that's yet another "horrible misuse of ifelse()"
> John Fox's reply *did* contain the "proper" solution
> if (all(is.na(x))) NA else sum(x, na.rm=TRUE)
> The ifelse() function should never be used in such cases.
> Read more after googling
> "Do NOT use ifelse()"
> -- include the quotes in your search --
> or directly at
> Yes, this has been on R-help a month ago..
> > On Mon, Jan 26, 2015 at 10:21 AM, Allen Bingham
> > <aebingham2 at 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 aebingham2 at gmail.com
> >> ______________________________________________
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