What are D and M? 'Index' here could be a number or a name.
In either case, df[[D]] would be the equivalent of df$D.
However, your computation does not need a loop at all, let alone two.
Try something like
tmp <- with(df, paste(D, m))
dates <- unique(tmp)
On Wed, 21 Feb 2007, Alp ATICI wrote:
> I have a data frame called df which has about 100 columns but thousands of
> rows. I set D the index of df$D and M to be the index of df$M.
> When I run the following loop as it is vs. df[,D] and df[,M] replaced with
> df$D and df$M there is a real big time difference in completion (with the
> latter being significantly faster). Is there an easy reason why and how I
> could speed up access?
>
> for (m in 1:12) {
> for (d in 1:31) {
> filter1<-((df[,D]==d) & (df[,M]==m))
> if(sum(filter1)>0) {
> ctr<-ctr+1
> dates[ctr]<-paste(as.character(d),as.character(m))
> }
> }
> }
>
> Thanks...
>
> [[alternative HTML version deleted]]
>
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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