Thanks Pascal! It certainly helps! 2014-09-29 17:10 GMT+08:00 Pascal Oettli <kri...@ymail.com>:
> Hi Miao, > > You certainly will find useful answers here : > http://cran.r-project.org/web/views/TimeSeries.html > > Regards, > Pascal Oettli > > On Mon, Sep 29, 2014 at 6:05 PM, jpm miao <miao...@gmail.com> wrote: > > Hi, > > > > I've not used R for about one year and don't know well about the > updates > > on the time series-related package. > > > > My primary job is to do economic/financial time series data analysis - > > annual, monthly, daily, etc. I usually read data by the package > > "XLConnect", which can read xls or xlsx files directly. It's excellent. > > However I can't find a package to manipulate time series data. For > example, > > I just want to do an easy manipulation , e.g, to label the dates of the > > data from , say, 1991M10 to 2014M07, and then extract part of the data, > > say, 2005M01 to 2010M12 and do analysis. Is there any package work well > for > > my purpose? > > > > I sometimes need to aggregate monthly data to quarterly data and I find > > "aggregate" function helpful. > > > > In the past I used packages xts, zoo and don't find it really user > > friendly. Maybe I haven't mastered it; maybe there're some updates > (which I > > don't know) now. Could someone recommend a package or provide an example > > (or just the document, I can read it) for my purpose? > > > > Attached is an exemplary data set I talked about. > > > > Thanks, > > > > Miao > > > > ______________________________________________ > > 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. > > > > > > -- > Pascal Oettli > Project Scientist > JAMSTEC > Yokohama, Japan > [[alternative HTML version deleted]] ______________________________________________ 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.