Yes, there is an easy way. Create the regular time series you want by something like
x <- ts(0, start=c(2000,52), end=c(2003,9), frequency=52) and fill in the time points you have data for by xYear <- trunc(times(x)); xWeek <- cycle(x) attach(mydata) x[(xYear==year) & (xWeek==Week)] <- Count detach() Easy! On Fri, 14 Feb 2003, Schnitzler, Johannes wrote: > > I have several large data sets with counts per week. > > (Maximum week per year is 52. Counts from Week 53 > > are added to week 52.) > > > > A data set contains for example: > > > > Year Week Count > > 2000 52 2 > > 2001 1 5 > > 2001 2 7 > > 2001 5 4 > > 2001 7 2 > > ... ... ... > > ... ... ... > > > > Weeks with 0 counts are not listed in the data set. > > I want to perform time series analysis (frequency 52). > > > > > > Is there an easy way to expand the data set to: > > > > Year Week Count > > 2000 52 2 > > 2001 1 5 > > 2001 2 7 > > 2001 3 0 > > 2001 4 0 > > 2001 5 4 > > 2001 6 0 > > 2001 7 2 > > ... ... ... > > ... ... ... > > > > or is there already a function in "ts", which i have not found so far, > > to deal with this problem? > > > > > > Thank you very much. > > > > Johannes Schnitzler > > Germany Berlin > > > > > > > > ______________________________________________ > [EMAIL PROTECTED] mailing list > http://www.stat.math.ethz.ch/mailman/listinfo/r-help > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help
