R help - Oct 2010 - Force evaluation of variable when calling partialPlot

Dear R Users,

I'm using the randomForest package and would like to generate partial
dependence plots, one after another, for a variety of variables:

m <- randomForest( s, ... )
varnames <- c( "var1", "var2", "var3",
"var4" )   # var1..4 are all in
data frame s
for( v in varnames ) {
   partialPlot( x=m, pred.data=s, x.var=v )
}

...but this doesn't work, with partialPlot complaining that it can't
find the variable "v". I think I need to force the evaluation of the
loop variable v so that partialPlot sees the correct variable names,
but am stumped after trying eval and similar functions. Any
suggestions on how to do this? Googling has not turned up anything
very useful.

Thanks,
Ben

The plot titles aren't pretty, but the following works for me:

R> library(randomForest)
randomForest 4.5-37
Type rfNews() to see new features/changes/bug fixes.
R> set.seed(1004)
R> iris.rf <- randomForest(iris[-5], iris[[5]], ntree=1001)
R> par(mfrow=c(2,2))
R> for (i in 1:4) partialPlot(iris.rf, iris, names(iris)[i])

Andy

From: Ben Bond-Lamberty
> 
> Dear R Users,
> 
> I'm using the randomForest package and would like to generate partial
> dependence plots, one after another, for a variety of variables:
> 
> m <- randomForest( s, ... )
> varnames <- c( "var1", "var2", "var3",
"var4" )   # var1..4 are all in
> data frame s
> for( v in varnames ) {
>    partialPlot( x=m, pred.data=s, x.var=v )
> }
> 
> ...but this doesn't work, with partialPlot complaining that it
can't
> find the variable "v". I think I need to force the evaluation of
the
> loop variable v so that partialPlot sees the correct variable names,
> but am stumped after trying eval and similar functions. Any
> suggestions on how to do this? Googling has not turned up anything
> very useful.
> 
> Thanks,
> Ben
> 
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