I had trouble getting my output to look like yours until I realized
that you did not want "to sum up the weekly data to the monthly level"
but rather to sum up to the monthly *and* ID level.
> dftag<-aggregate(dft$y, list(ID=dft$ID, Month=as.yearmon(dft$time,
"%m/%d/%Y")), FUN=sum)
# in Month order rather than ID, Month order
> dftag[order(dftag$ID, dftag$Month), ]
ID Month x
3 1 Feb 2008 16
7 1 Sep 2008 8
1 2 Jan 2008 3
5 2 Mar 2008 13
6 2 Jun 2008 4
2 3 Jan 2008 11
4 3 Feb 2008 10
--
David Winsemius
On Jan 12, 2009, at 4:57 PM, liujb wrote:
Dear R users:
I have a data set that looks something like this:
ID time y
1 2/01/2008 4
1 2/09/2008 12
1 9/01/2008 8
2 1/06/2008 3
2 3/01/2008 4
2 3/09/2008 9
2 6/03/2008 4
3 1/02/2008 3
3 1/10/2008 8
3 2/02/2008 7
3 2/10/2008 3
I'd like to sum up the weekly data to the monthly level, so that it
looks
something like this:
ID time y
1 2/2008 16
1 9/2008 8
2 1/2008 3
2 3/2008 13
2 6/2008 4
3 1/2008 11
3 2/2008 10
What is the best way to do it?
Time must be character. How do I truncate a character so that I can
remove
the date and only keep the month and year?
Thank you very much in advance.
Julia
--
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