I like the zoo package, and there are several helpful examples.
library(zoo)

You can easily convert your data into a zoo object using
I was actually just doing this using this function:
LoadReturnData=function(x){
    ret = read.csv(x)
    ret = zoo(ret[ , -1], as.Date(ret[ , 1]))
    colnames(ret) = toupper(colnames(ret))
    return(ret)
}
fnd = LoadReturnData('/Data/SomeSpecialData.csv')

My data is already in weeks, and aggregating to months is easy using
as.yearmon

MonthIndex=as.yearmon(index(fnd))
aggregate(.~MonthIndex, data=fnd, sum)

If you have daily data and you need weeks, then you'll have to create a
vector to indicate the week, like the MonthIndex above.

e.g. for 365 days
WeekIndex = rep(1:53, each=7, length.out=365)

On Wed, Jan 12, 2011 at 2:20 PM, analyst41@hotmail.com <
analyst41@hotmail.com> wrote:

> I tried a date by date forecast of a time series and it seems to be
> too wild.  How can I aggregate the date into weeks or months as
> required?
>
> Thanks.
>
> The input looks like
>
> ID datadate("YYYY-MM-DD")  value_for_day
> --     -----                                -------
> --     ------                               --------
>
> and I want to be able to change it to
>
> ID dataweek value_for_week
>
> or
>
> ID datamonth value_ for_ month
>
> ______________________________________________
> 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.
>

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