Try this: Lines <- '"Date (GMT)" "Open" "High" "Low" "Last" 17-03-2008 00:00:00 1,5764 1,5766 1,5747 1,5750 17-03-2008 00:05:00 1,5749 1,5750 1,5741 1,5744 17-03-2008 00:10:00 1,5745 1,5762 1,5741 1,5749' DF <- read.delim2(textConnection(Lines))
library(quantmod) z <- read.zoo(textConnection(Lines), # replace with "myfile.dat" header = TRUE, sep = "\t", dec = ",", format = "%d-%m-%Y %H:%M:%S", tz = "") q <- as.quantmod.OHLC(z, col.names = c("Open", "High", "Low", "Close")) chartSeries(q) Look at the zoo, quantmod and xts packages for more info. On Sat, Mar 22, 2008 at 6:19 AM, Thomas Steiner <[EMAIL PROTECTED]> wrote: > I want to create a open/high/low/last plot of intraday data. > I try to use the function plotOHLC from the tsteries package. I create > my own multiple time series and then try to plot it. > > raw Data Format (file eurusd2.csv): > "Date (GMT)" "Open" "High" "Low" "Last" > 17-03-2008 00:00:00 1,5764 1,5766 1,5747 1,5750 > 17-03-2008 00:05:00 1,5749 1,5750 1,5741 1,5744 > 17-03-2008 00:10:00 1,5745 1,5762 1,5741 1,5749 > > > library("tseries") > > raw=read.delim2("eurusd2.csv") > > date.d=strptime(raw$Date..GMT,"%d-%m-%Y %H:%M:%S") > > x=ts(data=c(raw$Open,raw$High,raw$Low,raw$Last),c="mts") > > plotOHLC(x) > Fehler in if ((!is.mts(x)) || (colnames(x)[1] != "Open") || > (colnames(x)[2] != : > Fehlender Wert, wo TRUE/FALSE nötig ist > > > > so there is a value missing where it expected a T/F... > > In Details of the help on the function plotOHLC it says: > The time scale of x must be in Julian dates (days since the origin). > > Perhaps anyone can provide help here? > Thanks, > Thomas > > ______________________________________________ > 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.