Look at the zoo and quantmod packages. On Sat, May 10, 2008 at 12:51 AM, falcon <[EMAIL PROTECTED]> wrote: > > I am new to R and am trying to solve the following problem: > > I have a data file containing tick-by-tick, millisecond level prices for > some stocks. I have another file or two containing orders and trades, > again, with millisecond time-stamps. Both of these files are irregularly > spaced and the time stamps are in an iso format (<date> > <time>.<millisecond>) > > I would like to create a price chart, and overlay on it the times and prices > at which orders were sent out and trades were received. > > My purpose is basically to visualize the data to help me pinpoint problems > and visually describe a day's trading activity. I am not (yet) interested > in any detailed statistical analysis. > > >From what I have read, the basic time series (ts) object is not appropriate > since it is only for regularly spaced time series. The few examples I have > seen for the 'its' package, generate an artificial time series, rather than > reading from a file, extracting out relevant columns (say a time stamp > column and a price column) and converting that to the right time series > object (including taking care of time stamp formats). > > Any idea how I can approach this problem? > > Thanks > Falcon > -- > View this message in context: > http://www.nabble.com/irregular-time-series-and-multiple%2C-overlaid-plots-tp17159961p17159961.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. >
______________________________________________ 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.