As others have pointed out its close to XML but not quite there; however, you could use strapply in gsubfn to extract the data. It pulls out the data matching the regular expression giving vector, vec, consisting of: date price date price ... Pulling out even and odd elements separately and converting them to Date and numeric, respectively, gives the resulting data.frame.
See http://gsubfn.googlecode.com for more on the gsubfn package and the three zoo vignettes in the zoo package for more on it. Lines <- '- <Temp diffgr:id="Temp14" msdata:rowOrder="13"> <Date>2005-01-17T00:00:00+05:30</Date> <SecurityID>10149</SecurityID> <PriceClose>1288.40002</PriceClose> </Temp> - <Temp diffgr:id="Temp15" msdata:rowOrder="14"> <Date>2005-01-18T00:00:00+05:30</Date> <SecurityID>10149</SecurityID> <PriceClose>1291.69995</PriceClose> </Temp> - <Temp diffgr:id="Temp16" msdata:rowOrder="15"> <Date>2005-01-19T00:00:00+05:30</Date> <SecurityID>10149</SecurityID> <PriceClose>1288.19995</PriceClose> </Temp>' library(gsubfn) vec <- strapply(Lines, "....-..-..|[0-9]+[.][0-9]+")[[1]] ix <- seq_along(vec) %% 2 == 1 DF <- data.frame(date = as.Date(vec[ix]), price = as.numeric(vec[!ix])) # or, instead of the last line, you could convert it to a zoo object so # that its in a more convenient form for time series manipulation: library(zoo) z <- zoo(as.numeric(vec[!ix]), as.Date(vec[ix])) On Wed, Nov 5, 2008 at 1:22 AM, RON70 <[EMAIL PROTECTED]> wrote: > > Hi everyone, > > I have this kind of raw dataset : > > - <Temp diffgr:id="Temp14" msdata:rowOrder="13"> > <Date>2005-01-17T00:00:00+05:30</Date> > <SecurityID>10149</SecurityID> > <PriceClose>1288.40002</PriceClose> > </Temp> > - <Temp diffgr:id="Temp15" msdata:rowOrder="14"> > <Date>2005-01-18T00:00:00+05:30</Date> > <SecurityID>10149</SecurityID> > <PriceClose>1291.69995</PriceClose> > </Temp> > - <Temp diffgr:id="Temp16" msdata:rowOrder="15"> > <Date>2005-01-19T00:00:00+05:30</Date> > <SecurityID>10149</SecurityID> > <PriceClose>1288.19995</PriceClose> > </Temp> > > I was looking for some R procedure to extract data from this, that should be > in following format : > > 2005-01-17 1288.40002 > 2005-01-18 1291.69995 > 2005-01-19 1288.19995 > > Can R help me to do this? > > -- > View this message in context: > http://www.nabble.com/How-to-extract-following-data-tp20336690p20336690.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.