If I understand your intent, I believe you can get what you want much faster (no interpreted loops and linear times) by looking at this slightly differently.
First of all, the choice of columns is unimportant, as indexing can be used to create a data frame containing only the columns of interest. So I think you can abstract your request to: group the rows of a data frame so that all rows in a group "match." Now the problem here is exactly what you mean by "match." If the data are numeric, finite precision arithmetic requires one to ask whether you mean **exactly equal** or just equal within a tolerance. I shall assume the former, but the latter is often what one wants. It is a little more difficult to handle, but one way to do it with the present approach is to first round to a few digits that represent the tolerance and then proceed with the rounded values. As always (and as recommended by the posting guide !) a small reproducible example is helpful: ## Create a data frame with groups of identical rows. z <- data.frame(matrix(rnorm(60),ncol=3))[sample(20,50,repl=TRUE),] ## now create a factor column of "id's" in which identical columns ## have identical id's (a hash) id <- factor(do.call(paste,c(z,sep="+"))) ## The levels of the factors now "index" groups of rows that "match" ## They can be easily accessed in a variety of way, e.g. as.numeric(id) ## gives all rows of each group of matching rows ## the same integer index. etc. This all requires only linear time. Hope this helps -- or my apologies if I have misinterpreted what was requested. Bert Gunter Genentech Nonclinical Biostatistics -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Dimitris Rizopoulos Sent: Thursday, October 08, 2009 6:28 AM To: joris meys Cc: r-help@r-project.org; Rama Ramakrishnan Subject: Re: [R] Need a vectorized way to avoid two nested FOR loops Another approach is: n <- 20 set.seed(2) x <- as.data.frame(matrix(sample(1:2, n*6, TRUE), nrow = n)) x.col <- c(1, 3, 5) values <- do.call(paste, c(x[x.col], sep = "\r")) out <- lapply(seq_along(ind), function (i) { ind <- which(values == values[i]) ind[!ind %in% i] }) out Best, Dimitris joris meys wrote: > Neat piece of code, Jim, but it still uses a nested loop. If you order > the matrix first, you only need one passage through the whole matrix > to find the information you need. > > Off course I don't take into account the ordering. If the ordering > algorithm doesn't work in linear time, then it doesn't really matter I > guess. The limiting step would become the ordering algorithm. > > Kind regards > Joris > > > > On Thu, Oct 8, 2009 at 2:24 PM, jim holtman <jholt...@gmail.com> wrote: >> I answered the wrong question. Here is the code to find all the >> matches for each row: >> >> n <- 20 >> set.seed(2) >> # create test dataframe >> x <- as.data.frame(matrix(sample(1:2,n*6, TRUE), nrow=n)) >> x >> x.col <- c(1,3,5) >> >> # match against all the other rows >> x.match1 <- apply(x[, x.col], 1, function(a){ >> .mat <- which(apply(x[, x.col], 1, function(z){ >> all(a == z) >> })) >> }) >> >> # remove matches to itself >> x.match2 <- lapply(seq(length(x.match1)), function(z){ >> x.match1[[z]][!(x.match1[[z]] %in% z)] >> }) >> # x.match2 contains which rows indices match >> >> >> >> >> >> >> >> >> >> >> On Wed, Oct 7, 2009 at 3:52 PM, Rama Ramakrishnan <r...@alum.mit.edu> wrote: >>> Hi Friends, >>> >>> I have a data frame d. Let vars be the column indices for a subset of the >>> columns in d (e.g., vars <- c(1,3,4,8)) >>> >>> For each row r in d, I want to collect all the other rows in d that match >>> the values in row r for just the columns in vars. >>> >>> The naive way to do this is to have a for loop stepping through each row in >>> d, and within the loop have another loop going through all the rows again, >>> checking for equality. This is quadratic in the number of rows and takes way >>> too long. Is there a better, "vectorized" way to do this? >>> >>> Thanks in advance! >>> >>> Rama Ramakrishnan >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> >> >> -- >> Jim Holtman >> Cincinnati, OH >> +1 513 646 9390 >> >> What is the problem that you are trying to solve? >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Dimitris Rizopoulos Assistant Professor Department of Biostatistics Erasmus University Medical Center Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands Tel: +31/(0)10/7043478 Fax: +31/(0)10/7043014 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
