On Fri, Jun 22, 2012 at 2:18 PM, John Kane <jrkrid...@inbox.com> wrote: > Hi and welcome to the R-help list. > > It would be much better for readers to get your data in a more easily used > format. > > There is a function called dput() that will output your data in a way that R > can read easily. > > We don't need to see all the data but perhaps hundred lines of it would be > nice. > > Try this where your file is called "mydata" > # just copy the line below and paste into R > head(mydata, 100)
I think you mean dput(head(mydata, 100)) OP: Once you put this up I'll give more reply, but for now I'd suggest you try to put your data in a proper time series class (zoo/xts if I might give a personal-ish plug) which will make all these calculations much easier. Best, Michael > > # Now copy the output and paste it into your wordprocess as a reply to the > list and we will have decent data to work with. > > John Kane > Kingston ON Canada > > >> -----Original Message----- >> From: mikeedinge...@gmail.com >> Sent: Fri, 22 Jun 2012 09:21:40 -0700 (PDT) >> To: r-help@r-project.org >> Subject: [R] Questions about doing analysis based on time >> >> >> I have a spreadsheet that I've read into R using read.csv. I've also >> attached it. It looks like this (except there are 1600+ entries): >> >>> Sunday >> SunDate SunTime SunScore >> 1 5/9/2010 0:00 0:00 127 >> 2 6/12/2011 0:00 0:00 125 >> 3 6/15/2008 0:04 0:04 98 >> 4 8/3/2008 0:07 0:07 118 >> 5 7/24/2011 0:07 0:07 122 >> 6 5/25/2008 0:09 0:09 104 >> 7 5/20/2012 0:11 0:11 124 >> 8 10/18/2009 0:12 0:12 121 >> 9 3/14/2010 0:12 0:12 117 >> 10 1/2/2011 0:12 0:12 131 >> >> SunDate and SunTime are both factors. In order to change the class to >> something I can work with, I use the following: >> >> Sunday$SunTime<-as.POSIXlt(SunTime,tz=””,”%H:%M”) >> Sunday$SunDate<-as.POSIXlt(SunDate,tz=””,”%m/%d/%Y %H:%M”) >> >> Now, the str(Sunday) command yields: >> >> 'data.frame': 1644 obs. of 3 variables: >> $ SunDate : POSIXlt, format: "2010-05-09 00:00:00" "2011-06-12 00:00:00" >> ... >> $ SunTime : POSIXlt, format: "2012-06-18 00:00:00" "2012-06-18 00:00:00" >> ... >> $ SunScore: int 127 125 98 118 122 104 124 121 117 131 ... >> >> I think all the elements in Sunday are correct for me to do what I want >> to >> do, but I don't know how to do them. >> >> 1. How can I get the mean score by hour? For example, I want the mean >> score > > >> of all the entries between 0:00 and 0:59, then 1:00 and 1:59, etc. >> 2. Is it possible for me to create a histogram by hour for each score >> over a >> certain point? For example, I want to make a histogram of all scores >> above >> 140 by the hour they occurred in. Is that possible? >> >> These last few might not be possibe (at least with R), but I'll ask >> anyway. >> I've got another data set similar to the one above, except it's got >> 12,000 >> entries over four years. If I do the same commands as above to turn Date >> and Time into POSIXlt, is it possible for me to do the following: >> >> 1. The data was recorded at irregular intervals, and the difference >> between >> recorded points can range from anywhere between 1 hour and up to 7. Is >> it >> possible, when data isn't recorded between two points, to insert the >> hours >> that are unrecorded along with the average of what that hour is. This is >> sort of a pre-requisite for the next two. >> 2. If one of the entries has a Score above a certain point, is it >> possible >> to determine how long it was above that point and determine the mean for >> all >> the instances this occurred. For example: >> 01/01/11 01:00 AM >> 101 >> 01/01/11 02:21 AM >> 142 >> 01/01/11 03:36 AM >> 156 >> 01/01/11 04:19 AM >> 130 >> 01/01/11 05:12 AM >> 146 >> 01/01/11 06:49 AM >> 116 >> 01/01/11 07:09 AM >> 111 >> There are two spans where it's above 140. The two and three o'clock >> hours, >> and the 5 o'clock hour. So the mean time would be 1.5 hours. Is it >> possible for R to do this over a much larger time period? >> >> 3. If a score reaches a certain point, is it possible for R to determine >> the average time between that and when the score reaches another point. >> For >> example: >> 01/01/11 01:01 AM >> 101 >> 01/01/11 02:21 AM >> 121 >> 01/01/11 03:14 AM >> 134 >> 01/01/11 04:11 AM >> 149 >> 01/01/11 05:05 AM >> 119 >> 01/01/11 06:14 AM >> 121 >> 01/01/11 07:19 AM >> 127 >> 01/01/11 08:45 AM >> 134 >> 01/01/11 09:11 AM >> 142 >> 01/01/11 10:10 AM >> 131 >> The score goes above 120 during the 2 AM hour and doesn't go above 140 >> until >> the 4 AM hour. Then it goes above 120 again in the 6 AM hour, but >> doesn't >> go above 140 until the 9 AM hour. So the average time to go from 120 to >> 140 >> is 2.5 hours. Can R does this over a much larger time frame? >> >> If anyone knows how to easily do any of these (particularly the first >> part), >> I'd greatly appreciate it. >> >> If some of these are possible, but aren't simple commands and require >> more >> in depth programming knowledge and time commitment, can someone at least >> tell me what sort of thing to look up? >> >> -- >> View this message in context: >> http://r.789695.n4.nabble.com/Questions-about-doing-analysis-based-on-time-tp4634230.html >> Sent from the R help mailing list archive at Nabble.com. >> >> ______________________________________________ > . > > ____________________________________________________________ > FREE 3D EARTH SCREENSAVER - Watch the Earth right on your desktop! > > ______________________________________________ > 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.
