Hi, One possible way to get around it is using following idea : X1 <- rnorm(10) X2 <- rnorm(10)
Names <- c("X1","X2","X3") Names <- Names[Names %in% ls()] n <- length(Names) p <- 10 #length of each object output <- matrix(NA,ncol=n,nrow=p) for(i in 1:n){ output[,i] <- get(Names[i]) } output <- as.data.frame(output) names(output) <- Names You can also use an eval-parse construct like this : ## Alternative Names <- c("X1","X2","X3") Names <- Names[Names %in% ls()] Names <- paste(Names,collapse=",") expr = paste("output <- data.frame(",Names,")",sep="") eval(parse(text=expr)) Both are not really the most optimal solution, but do work. It would be better if you made a list or matrix beforehand and then save the results of the calculations in that list or matrix whenever the calculation turns out to give a result. Cheers Joris On Sat, Jun 5, 2010 at 1:23 AM, Scott Chamberlain <scham...@rice.edu> wrote: > Hello, I am trying to make a data frame from many elements after > running a function which creates many elements, some of which may not > end up being real elements due to errors or missing data. For example, > I have the following three elements p1s, p2s, and p3s. p9s did not > generate the same data as there was an error in the function for some > reason. I currently have to delete p9s from the data.frame() command > to get the data.frame to work. How can I make a data frame by somehow > ignoring elements (e.g., p9s) that do not exist, without having to > delete each missing element from data.frame()? The below is an example > of the code. > >> p1s > statistic parameter p.value > [1,] 3.606518 153 0.0004195377 >> p2s > statistic parameter p.value > [1,] -3.412436 8 0.009190015 >> p3s > statistic parameter p.value > [1,] 1.543685 599 0.1231928 > >> t(data.frame(t(p1s),t(p2s),t(p3s),t(p9s))) > Error in t(p9s) : object 'p9s' not found > > > Thanks, Scott Chamberlain > Rice University > Houston, TX > > ______________________________________________ > 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. > -- Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php ______________________________________________ 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.