Is there a wildcard value for vector values in r? For instance:> M <- *wildcard> (M==1)TRUE>(M=="peanut butter")TRUE>is.na(M)FALSE thanks, Francis -- Francis Smart (406) 223-8108 cell
Francis Smart <fsmart <at> gmail.com> writes:> Is there a wildcard value for vector values in r? > > For instance: > > > M <- *wildcard > > > (M==1) > TRUE > > >(M=="peanut butter") > TRUE > > >is.na(M) > FALSEIf grep on a vector does not help, maybe the following comes closer? Finding all variables rm(list=ls(all=TRUE)) a = 33 aa = 44 dd = 33 c = 3 names = "^a.*" Vars <- ls() r <- Vars[grep(names,Vars)] r # not really correct for names.* and Vars.* Dieter
I would be truly amazed if the answer were "yes". I find this the most fascinating question on R-help for a long time, maybe ever. Can you tell us what you have in mind and what your ultimate purpose is? Patrick Burns patrick at burns-stat.com +44 (0)20 8525 0696 http://www.burns-stat.com (home of "The R Inferno" and "A Guide for the Unwilling S User") Francis Smart wrote:> Is there a wildcard value for vector values in r? > > For instance: > > >> M <- *wildcard >> > > >> (M==1) >> > TRUE > > >> (M=="peanut butter") >> > TRUE > > >> is.na(M) >> > FALSE > > thanks, > Francis > >
Hi,
Since you insist, here is something that I think matches the
specifications :
wildcard <- function( ) structure( NULL, class = "wildcard" )
Ops.wildcard <- function (e1, e2){
if (nargs() == 1L)
return( e1 )
result <- switch(.Generic,
`<` = , `>` = , `==` = ,
`<=` = , `>=` = TRUE, `!=` = FALSE)
result
}
is.na.wildcard <- function( x ) FALSE
> w == 1
[1] TRUE
> w == "peanut butter"
[1] TRUE
> is.na( w )
[1] FALSE
> "peanut butter" == w
[1] TRUE
> w == w
[1] TRUE
> w != w
[1] FALSE
# Is negation of a wildcard also a wildcard, or should it be a bizarro
wildcard ?
> (!w) == 2
[1] TRUE
Not really sure how this could be useful though, and would also be
interested in Francis end game.
Romain
Patrick Burns wrote:> I would be truly amazed if the answer were "yes".
>
> I find this the most fascinating question on R-help
> for a long time, maybe ever. Can you tell us what
> you have in mind and what your ultimate purpose is?
>
> Patrick Burns
> patrick at burns-stat.com
> +44 (0)20 8525 0696
> http://www.burns-stat.com
> (home of "The R Inferno" and "A Guide for the Unwilling S
User")
>
> Francis Smart wrote:
>> Is there a wildcard value for vector values in r?
>>
>> For instance:
>>
>>
>>> M <- *wildcard
>>>
>>
>>
>>> (M==1)
>>>
>> TRUE
>>
>>
>>> (M=="peanut butter")
>>>
>> TRUE
>>
>>
>>> is.na(M)
>>>
>> FALSE
>>
>> thanks,
>> Francis
>>
>>
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.
>
>
>
--
Romain Francois
Independent R Consultant
+33(0) 6 28 91 30 30
http://romainfrancois.blog.free.fr
Sure thing. ?I realize that it is an unusual request and not the type of thing that I have seen used in any other language that I know of. So right now I am using some of the statistical functions of R to get some summary statistics and visual output from this historic data set. I have a lot functions that look something like this: summary(lm(SLV_DIE_PER[tontype==TONNAGE_TYPE]~SLV_PER_TON[tontype==TONNAGE_TYPE])) SLV_DIE_PER - being the percent of slaves that died between purchase and delivery SLV_PER_TON - being the number of slaves per standardized ton (ship capacity) tontype - being the type of ton that the ship capacity was recorded as. ?There are various factors mostly in the form of 1,2,3,4,5... representing Spanish Ton, British Ton, etc. Now I want to run a simple linear model and graphs and other things by specifying TONNAGE_TYPE=1 or 2 etc. ?Giving me a regression that is only using looking at a particular type of tonnage over that of another. All of that works fine. ?But, it gets a little ugly when I want to generalize the linear model to include all values irrespective of tontype. ?Of course I could duplicate and trim the statement as such: summary(lm(SLV_DIE_PER~SLV_PER_TON)) I am sure you can see how a wildcard could be more important given a series of similar expressions. ?Perhaps something that looks like this: summary(SLV_DIE_PER[(SLV_DIE_PER>=SLV_Min_Value)&(Nationality==Select_Nationality)&((SLV_PER_TON<=SLV_Max_Value))&(tontype==TONNAGE_TYPE)])) Well thanks for your interest. ?Any suggestions that can help clean up my code could be extremely helpful right now. Btw thanks Dieter for that hint. ?Not exactly what I was looking for but I am sure to use it in the future. Romain. Thanks for your code, though I don't see readily how to fit "w" into your functions. Perhaps you could add an additional line between: "is.na.wildcard <- function( x ) FALSE" and "> w == 1" Thanks! Francis> > On Wed, Apr 1, 2009 at 2:02 AM, Patrick Burns <pburns at pburns.seanet.com> wrote: >> I would be truly amazed if the answer were "yes". >> >> I find this the most fascinating question on R-help >> for a long time, maybe ever. ?Can you tell us what >> you have in mind and what your ultimate purpose is? >> >> Patrick Burns >> patrick at burns-stat.com >> +44 (0)20 8525 0696 >> http://www.burns-stat.com >> (home of "The R Inferno" and "A Guide for the Unwilling S User") >> >> Francis Smart wrote: >>> >>> Is there a wildcard value for vector values in r? >>> >>> For instance: >>> >>> >>>> >>>> M <- *wildcard >>>> >>> >>> >>>> >>>> (M==1) >>>> >>> >>> TRUE >>> >>> >>>> >>>> (M=="peanut butter") >>>> >>> >>> TRUE >>> >>> >>>> >>>> is.na(M) >>>> >>> >>> FALSE >>> >>> thanks, >>> Francis >>> >>> >> > > > > -- > Francis Smart > (406) 223-8108 cell >-- Francis Smart (406) 223-8108 cell