Sum function and missing values --- need to mimic SAS sum function
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. Allen -----Original Message----- 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): sum(x, na.rm=!all(is.na(x)))
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
http://stat.ethz.ch/pipermail/r-help/2014-December/424367.html
Yes, this has been on R-help a month ago..
Martin
> 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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> ______________________________________________
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______________________________________________ R-help at 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.