aggredating date data

Von: analyst41 at hotmail.com <analyst41 at hotmail.com>
Betreff: [R] aggredating date data
An: r-help at r-project.org
Datum: Mittwoch, 12. Januar, 2011 20:20 Uhr
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

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)