That is so simple, and works wonderfully! The best place to hide things is right in front of my face. thanks agian
stephen On Wed, Jun 25, 2008 at 10:24 PM, jim holtman <[EMAIL PROTECTED]> wrote: > Try this: > > y.ts <- ts(y, frequency=7) # make data weekly > aggregate(y.ts, FUN=mean) > > to get your 15 minute readings into a day, this should work: > > y.ts <- ts(y, frequency=96) > aggregate(y.ts, FUN=mean) > > This is fine as long as everything is evenly spaced. It might be > better if you had the time of the observation so that it would take > care of missing data when doing the aggregation. > > On Wed, Jun 25, 2008 at 9:57 PM, stephen sefick <[EMAIL PROTECTED]> wrote: > > #this is a daily series of precipitation data. I would like to condense > it > > into weekly means. How can I do this > > #as a side note I would like to do this same thing to two years worth of > > fifteen minute interval data and make it into > > #a series of daily averages (there are 96 readings per day) > > #is aggregate the right function? or... > > > > y <- c(1.23, 0, 0, 0, 0, 0, 0, 0, 0, 0.27, 0, 0.29, 0, 0, 0, 0.43, > > 0.2, 0, 0, 0.06, 0.05, 0.36, 0.06, 0, 0, 0, 0, 0.16, 0, 0, 0, > > 0.17, 0, 0.31, 0, 0, 0.01, 0, 0, 0, 0.19, 0, 0, 0, 0, 0, 0, 0.01, > > 0, 0.13, 0, 0.58, 0.07, 0, 1.48, 0.14, 0, 0, 0, 0, 0, 0, 0, 0, > > 0, 0, 0, 0.03, 0, 0, 0, 0.39, 0, 0, 0, 0, 0, 0.12, 2.79, 0, 0, > > 0, 0, 0, 0, 0.01, 0, 0, 0, 0.19, 0, 0, 0, 0, 0, 0, 0.89, 0, 0, > > 0, 0, 0, 0, 0, 0, 0, 0, 0.64, 0, 0, 0.31, 0, 0, 0, 0.31, 0, 0, > > 0, 0, 0, 0, 0, 0.08, 0.37, 0, 0.49, 0, 0, 0, 0, 0, 0, 0.49, 0, > > 0, 0, 0.15, 0, 0, 0, 0, 0, 0, 0.07, 0, 0, 0, 0, 0, 0, 0, 1.43, > > 0.02, 0, 0, 0, 0, 0, 0, 0, 0, 0.81, 1.9, 1.02, 0, 0, 0, 0, 0, > > 0, 0, 0, 0, 0, 0.35, 0.89, 0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0.22, > > 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0.21, 0.12, 0.58, > > 0, 0, 0, 0, 0.28, 0.09, 0, 0, 0, 0, 0.3, 0, 0, 0, 0, 0, 0.5, > > 0, 0.59, 0, 0, 0, 0.01, 0, 0, 0.04, 1.4, 0, 0.6, 0, 2.06, 0, > > 0, 0, 0, 0, 0.39, 0, 0, 0, 1.06, 0, 0.26, 0, 0.01, 0, 0, 0, 0, > > 0, 1.17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.18, 0, 0, 0, 0, 0, 0, > > 0, 0, 0, 0, 0, 0.02, 0, 0.05, 0, 0, 0.84, 0, 0, 0, 0, 0.04, 0.06, > > 0, 0, 0, 0, 0.46, 0, 0, 0, 0, 0.91, 0, 0, 0, 0, 0, 0, 0, 0, 0, > > 0, 0.32, 0, 0, 0, 0, 0, 0, 0, 1.29, 0.3, 0, 0, 0, 0.01, 0.61, > > 0.34, 0, 0, 0, 0, 0, 0, 0, 0.08, 0.1, 0, 0, 0, 0, 0, 0, 0, 0, > > 0, 0, 0, 0.02, 0, 0, 0, 0, 0, 0, 0, 0.28, 2.65, 0, 0, 2.21, 0, > > 0, 0, 0, 0.06, 0.12, 0.16, 0, 0, 0, 0.52, 0, 0.34, 0.18, 0, 0, > > 0, 0, 0, 0, 0, 0.03, 0.01, 0.28, 0, 0, 0.44, 0.75, 0, 0, 0, 0, > > 0, 0.33, 0, 0, 0, 1.28, 0.03, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 0, > > 0.69, 0, 0, 0, 0, 0, 0, 0, 0.57, 0, 0, 0, 0.24, 0, 0, 0) > > > > y.ts <- ts(y, frequency=30) > > aggregate(y.ts, nf=7, FUN=mean) > > > > -- > > Let's not spend our time and resources thinking about things that are so > > little or so large that all they really do for us is puff us up and make > us > > feel like gods. We are mammals, and have not exhausted the annoying > little > > problems of being mammals. > > > > -K. Mullis > > > > [[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. > > > > > > -- > Jim Holtman > Cincinnati, OH > +1 513 646 9390 > > What is the problem you are trying to solve? > -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis [[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.
