[R] Sum function and missing values --- need to mimic SAS sum function

[Allen Bingham]

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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