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, analys...@hotmail.com <
analys...@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
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> 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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