[R] Resources for optimizing code

[Roger Bivand]

On Fri, 5 Nov 2004, Janet Elise Rosenbaum wrote:

> 
> I want to eliminate certain observations in a large dataframe (21000x100).
> I have written code which does this using a binary vector (0=delete obs,
> 1=keep), but it uses for loops, and so it's slow and in the extreme it 
> causes R to hang for indefinite time periods.
> 
> I'm looking for one of two things:
> 1.  A document which discusses how to avoid for loops and situations in
> which it's impossible to avoid for loops.
> 
> or
> 
> 2.  A function which can do the above better than mine.  

?subset
newdata <- subset(DATAFRAME, asst==1)

which will work whether DATAFRAME is a matrix or data.frame (two different 
classes).

> 
> My code is pasted below.
> 
> Thanks so much,
> 
> Janet 
> 
> # asst is a binary vector of length= nrow(DATAFRAME).  
> # 1= observations you want to keep.  0= observation to get rid of.
> 
> remove.xtra.f <-function(asst, DATAFRAME) {
> 	n<-sum(asst, na.rm=T)
> 	newdata<-matrix(nrow=n, ncol=ncol(DATAFRAME))
> 	j<-1
> 	for(i in 1:length(data)) {
> 		if (asst[i]==1) {
> 			newdata[j,]<-DATAFRAME[i,]
> 			j<-j+1
> 		}
> 	}
> 	newdata.f<-as.data.frame(newdata)
> 	names(newdata.f)<-names(DATAFRAME)
> 	return(newdata.f)
> }
> --  
> Janet Rosenbaum                                 jerosenb at fas.harvard.edu
> PhD Candidate in Health Policy, Harvard GSAS
> Harvard Injury Control Research Center, Harvard School of Public Health
> 
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-- 
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Breiviksveien 40, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93
e-mail: Roger.Bivand at nhh.no