Will this do it for you: > Bill <- 1:100 # test data > # partition > Bill.p <- split(Bill, rep(1:10, each=10)) > Bill.p $`1` [1] 1 2 3 4 5 6 7 8 9 10 $`2` [1] 11 12 13 14 15 16 17 18 19 20 $`3` [1] 21 22 23 24 25 26 27 28 29 30 $`4` [1] 31 32 33 34 35 36 37 38 39 40 $`5` [1] 41 42 43 44 45 46 47 48 49 50 $`6` [1] 51 52 53 54 55 56 57 58 59 60 $`7` [1] 61 62 63 64 65 66 67 68 69 70 $`8` [1] 71 72 73 74 75 76 77 78 79 80 $`9` [1] 81 82 83 84 85 86 87 88 89 90 $`10` [1] 91 92 93 94 95 96 97 98 99 100 > sapply(Bill.p, mean) 1 2 3 4 5 6 7 8 9 10 5.5 15.5 25.5 35.5 45.5 55.5 65.5 75.5 85.5 95.5 > >
On Tue, Jun 3, 2008 at 8:35 PM, William Pepe <[EMAIL PROTECTED]> wrote: > > I have a data set(Bill) of with 1 variable (var1), with 100 obs that are in > ascending order. I want to sample every 10 observations and save them in 10 > different groups such as > > Group1 is obs 1-10 > Group 2 is obs-11-20 > > and so on. > > First step is to subset them into the 10 groups, then calculate the mean of > var1 for each of the 10 groups. Any help would be appreciated. Thanks. > > _________________________________________________________________ > > > sh_skydrive_062008 > [[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<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 you are trying to solve? [[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.
