David W and all, Thank you very much for your help.
Here is the final output that I want in the form of data frame. The data frame should contain x, group and group_ mean in the following way x group group mean 46 1 42.3 125 2 89.6 36 1 42.3 193 3 235.25 209 3 235.25 78 2 89.6 66 2 89.6 242 3 235.25 297 3 235.25 45 1 42.3 Thanks a lot On Tue, Apr 3, 2012 at 9:51 AM, David Winsemius <dwinsem...@comcast.net>wrote: > > On Apr 3, 2012, at 9:32 AM, R. Michael Weylandt wrote: > > Use cut2 as I suggested and David demonstrated. >> > > Agree that Hmisc::cut2 is extremely handy and I also like that fact that > the closed ends of intervals are on the left side (which is not the same > behavior as cut()), which has the otehr effect of setting include.lowest = > TRUE which is not the default for cut() either (to my continued amazement). > > But let me add the method I use when doing it "by hand": > > cut(x, quantile(x, prob=seq(0, 1, length=ngrps+1)), include.lowest=TRUE) > > -- > David. > > > > >> Michael >> >> On Tue, Apr 3, 2012 at 9:31 AM, Val <valkr...@gmail.com> wrote: >> >>> Thank you all (David, Michael, Giovanni) for your prompt response. >>> >>> First there was a typo error for the group mean it was 89.6 not 87. >>> >>> For a small data set and few groupings I can use prob=c(0, .333, .66 >>> ,1) to >>> group in to three groups in this case. However, if I want to extend the >>> number of groupings say 10 or 15 then do I have to figure it out the >>> split(x, cut(x, quantile(x, prob=c(0, .333, .66 ,1)) >>> >>> Is there a short cut for that? >>> >>> >>> Thanks >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> On Tue, Apr 3, 2012 at 9:13 AM, R. Michael Weylandt >>> <michael.weyla...@gmail.com> wrote: >>> >>>> >>>> Ignoring the fact your desired answers are wrong, I'd split the >>>> separating part and the group means parts into three steps: >>>> >>>> i) quantile() can help you get the split points, >>>> ii) findInterval() can assign each y to a group >>>> iii) then ave() or tapply() will do group-wise means >>>> >>>> Something like: >>>> >>>> y <- c(36, 45, 46, 66, 78, 125, 193, 209, 242, 297) # You need a "c" >>>> here. >>>> ave(y, findInterval(y, quantile(y, c(0.33, 0.66)))) >>>> tapply(y, findInterval(y, quantile(y, c(0.33, 0.66))), mean) >>>> >>>> You could also use cut2 from the Hmisc package to combine findInterval >>>> and quantile into a single step. >>>> >>>> Depending on your desired output. >>>> >>>> Hope that helps, >>>> Michael >>>> >>>> On Tue, Apr 3, 2012 at 8:47 AM, Val <valkr...@gmail.com> wrote: >>>> >>>>> Hi all, >>>>> >>>>> Assume that I have the following 10 data points. >>>>> x=c( 46, 125 , 36 ,193, 209, 78, 66, 242 , 297 , 45) >>>>> >>>>> sort x and get the following >>>>> y= (36 , 45 , 46, 66, 78, 125,193, 209, 242, 297) >>>>> >>>>> I want to group the sorted data point (y) into equal number of >>>>> observation per group. In this case there will be three groups. The >>>>> first >>>>> two groups will have three observation and the third will have four >>>>> observations >>>>> >>>>> group 1 = 34, 45, 46 >>>>> group 2 = 66, 78, 125 >>>>> group 3 = 193, 209, 242,297 >>>>> >>>>> Finally I want to calculate the group mean >>>>> >>>>> group 1 = 42 >>>>> group 2 = 87 >>>>> group 3 = 234 >>>>> >>>>> Can anyone help me out? >>>>> >>>>> In SAS I used to do it using proc rank. >>>>> >>>>> thanks in advance >>>>> >>>>> Val >>>>> >>>>> [[alternative HTML version deleted]] >>>>> >>>> >>>> >>>>> ______________________________**________________ >>>>> R-help@r-project.org mailing list >>>>> https://stat.ethz.ch/mailman/**listinfo/r-help<https://stat.ethz.ch/mailman/listinfo/r-help> >>>>> PLEASE do read the posting guide >>>>> http://www.R-project.org/**posting-guide.html<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<https://stat.ethz.ch/mailman/listinfo/r-help> >> PLEASE do read the posting guide http://www.R-project.org/** >> posting-guide.html <http://www.R-project.org/posting-guide.html> >> and provide commented, minimal, self-contained, reproducible code. >> > > David Winsemius, MD > West Hartford, CT > > [[alternative HTML version deleted]] ______________________________________________ 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.
