On Apr 3, 2012, at 10:11 AM, Val wrote: > 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
I you want group means in a vector the same length as x then instead of using tapply as done in earlier solutions you should use `ave`. -- DW > > 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 > 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. > > David Winsemius, MD > West Hartford, CT > > 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.
