On Fri, Nov 21, 2008 at 5:50 AM, Gerit Offermann <[EMAIL PROTECTED]> wrote: > Dear list, > > thanks to your help I managed to find means of analysing my data. > > However, the whole data set contains 264 variables. Of which some are > factors, others are not. The factors tend to be grouped, e.g. > data$f1304 to data$f1484 and data$f3204 to data$5408. > > But there are other types of variables in the data set as well, > e.g. data$f1504. > > Not every spot is taken, i.e data$f1345 to data$1399 might not exist > in the data set.
We can compute on the names like this (using the builtin anscombe data set to get just columns y1, x1, x2, x3, x4). Try this: # display anscombe data set anscombe # names.x are names that start with x names.x <- grep("^x", names(anscombe), value = TRUE) anscombe[, c("y1", names.x)] > > The solution "summaryBy" works for cross analysis, of which there is > a handful. So I am not worried here. > > The solution from Jorge is fine. > However, I am trying to get my head around how to efficiently > reduce my data set to the dependet variable and the factors such that > the solution is applicable. > > Having to type each variable into > my.reduced.data <- cbind(my.data$f1001, my.data$1002, my.data$1003... > is an obvious option, but does not seem to be the most efficient one. > > Are there better ways to go about? > > Thanks, > Gerit > -- > Sensationsangebot nur bis 30.11: GMX FreeDSL - Telefonanschluss + DSL > für nur 16,37 Euro/mtl.!* http://dsl.gmx.de/?ac=OM.AD.PD003K11308T4569a > > ______________________________________________ > 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.