I wrote a dirty hack last time I faced this problem, I'll be curious to see what is the proper way of dealing with the scoping and evaluation rules.

library(datasets)

myfunction<-function(table, extraction)  {
    table2<-subset(table,extraction)
return(table2)
}


condition1 <- quote(iris$Species=="setosa") # I'm not sure how to evaluate within the environment, perhaps you could use with(table, subset(table, extraction) ) in your function condition2 <- bquote(.(condition1) & iris$Sepal.Width < 3.5) # say, if you want to concatenate several conditions together

myfunction(iris, extraction= eval(condition1))
myfunction(iris, extraction= eval(condition2))


Best wishes,

baptiste



On 17 Dec 2008, at 19:07, GOUACHE David wrote:

Hello R-helpers,

I'm writing a long function in which I manipulate a certain number of datasets. I want the arguments of said function to allow me to adapt the way I do this. Among other things, I want my function to have an argument which I will pass on to subset() somewhere inside my function. Here is a quick and simplified example with the iris dataset.

myfunction<-function(table, extraction)  {
    table2<-subset(table, extraction)
return(table2) }

myfunction(iris, extraction= Species=="setosa")


############## end

What I would like is for this function to return exactly the same thing as :
subset(iris, Species=="setosa")


Thanks for your help.

Regards,

David Gouache

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_____________________________

Baptiste AuguiƩ

School of Physics
University of Exeter
Stocker Road,
Exeter, Devon,
EX4 4QL, UK

Phone: +44 1392 264187

http://newton.ex.ac.uk/research/emag

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