Resources for optimizing code
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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