If that is the situation then plot(tt) in your post could not have been what you wanted in any case, e.g. plot(10:20)
On Sat, Jun 20, 2009 at 11:49 AM, Thomas Levine<thomas.lev...@gmail.com> wrote: > This produces the x-axis is the index, and the y-axis is time. It has all of > the time information on the same axis, allowing me to plot cumulative > occurrences by time (my original plan) if the times are sorted, which they > should be. > > I think I'll end up using some variant of plot(tt,seq_along(tt)), putting > the time axis along the bottom. > > Thanks > > Tom > > On Sat, Jun 20, 2009 at 11:15 AM, Gabor Grothendieck > <ggrothendi...@gmail.com> wrote: >> >> Try this: >> >> plot(seq_along(tt), tt) >> >> >> On Sat, Jun 20, 2009 at 10:55 AM, Thomas Levine<thomas.lev...@gmail.com> >> wrote: >> > Here's what I get >> >> head(tt) >> > [1] "2008-02-20 03:09:51 EST" "2008-02-20 12:12:57 EST" >> > [3] "2008-03-05 09:11:28 EST" "2008-03-05 17:59:40 EST" >> > [5] "2008-03-09 09:00:09 EDT" "2008-03-29 15:57:16 EDT" >> > >> > But I can't figure out how to plot this now. plot(tt) does not appear to >> > be >> > univariate. I get the same plot with plot(as.Date(tt)), which would make >> > sense if time is used because of the range of the dates and the >> > insignificance of the times of day. >> >> head(as.Date(tt)) >> > [1] "2008-02-20" "2008-02-20" "2008-03-05" "2008-03-05" "2008-03-09" >> > [6] "2008-03-29" >> > >> > plot(tt) and plot(as.Date(tt)) give something like year as a function of >> > the >> > rest of the date. Here they are >> > >> > >> > Here are the addresses >> > http://thomaslevine.org/time/tt.png >> > http://thomaslevine.org/time/as.Date.tt.png >> > >> > Tom >> > >> > On Fri, Jun 19, 2009 at 6:21 PM, Gabor Grothendieck >> > <ggrothendi...@gmail.com> wrote: >> >> >> >> Try this: >> >> >> >> >> >> Lines <- "Sun, 14 Jun 2009 07:33:00 -0700 >> >> Sun, 14 Jun 2009 08:35:10 -0700 >> >> Sun, 14 Jun 2009 21:26:34 -0700 >> >> Mon, 15 Jun 2009 19:47:47 -0700 >> >> Wed, 17 Jun 2009 21:50:41 -0700" >> >> >> >> # L <- readLines("myfile.txt") >> >> L <- readLines(textConnection(Lines)) >> >> tt <- as.POSIXct(L, format = "%a, %d %b %Y %H:%M:%S") >> >> >> >> >> >> >> >> On Fri, Jun 19, 2009 at 6:06 PM, Thomas Levine<thomas.lev...@gmail.com> >> >> wrote: >> >> > I am analysing occurrences of a phenomenon by time, and each of these >> >> > timestamps taken from email headers represents one occurrence. (The >> >> > last >> >> > number is the time zone.) I can easily change the format. >> >> > >> >> > Sun, 14 Jun 2009 07:33:00 -0700 >> >> > Sun, 14 Jun 2009 08:35:10 -0700 >> >> > Sun, 14 Jun 2009 21:26:34 -0700 >> >> > Mon, 15 Jun 2009 19:47:47 -0700 >> >> > Wed, 17 Jun 2009 21:50:41 -0700 >> >> > >> >> > I've found documentation for a plethora of ways of importing time >> >> > data, >> >> > but >> >> > I can't decide how to approach it. Any ideas on what may be the >> >> > cleanest >> >> > way? The only special concern is that I'll want to plot these data by >> >> > date >> >> > and time, meaning that I would rather not bin all of the occurrences >> >> > from >> >> > one day. >> >> > >> >> > The time zone isn't important as these are all local times; the time >> >> > zone >> >> > only changes as a function of daylight savings time, so I probably >> >> > shouldn't >> >> > use it at all. >> >> > >> >> > Tom >> >> > >> >> > [[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. >> >> > >> > >> > > > ______________________________________________ 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.
