[R] Loading intraday data with zoo

[arun]

Hi,
You may need to add "dec=","" in the read.csv.
dat1<- read.table(text="
Time;Mid
31/01/2013 00:00;1,35679
31/01/2013 00:01;1,35678
31/01/2013 00:02;1,356785
31/01/2013 00:03;1,35689
31/01/2013 00:04;1,3569
31/01/2013 00:05;1,3569
31/01/2013 00:06;1,356885
31/01/2013 00:07;1,35691
31/01/2013 00:08;1,357 
",sep=";",dec=",",header=TRUE,stringsAsFactors=FALSE)

f1 <- function(...) as.POSIXct(paste(...), format = "%d/%m/%Y %H:%M") 
library(zoo)
 b <- read.zoo(dat1, index = 1, FUN  = f1) 

library(xts)
dat2<- xts(b)
 dat2
#                           x
#2013-01-31 00:00:00 1.356790
#2013-01-31 00:01:00 1.356780
#2013-01-31 00:02:00 1.356785
#2013-01-31 00:03:00 1.356890
#2013-01-31 00:04:00 1.356900
#2013-01-31 00:05:00 1.356900
#2013-01-31 00:06:00 1.356885
#2013-01-31 00:07:00 1.356910
#2013-01-31 00:08:00 1.357000
 plot(dat2)
A.K.



>Hi all, 
>
>I would like to do some time series analysis on intraday data. 
>Therefore, I try to read some data with zoo and then convert them a xts-object. 
>
>The data are like: 
>Time;Mid 
>31/01/2013 00:00;1,35679 
>31/01/2013 00:01;1,35678 
>31/01/2013 00:02;1,356785 
>31/01/2013 00:03;1,35689 
>31/01/2013 00:04;1,3569 
>31/01/2013 00:05;1,3569 
>31/01/2013 00:06;1,356885 
>31/01/2013 00:07;1,35691 
>31/01/2013 00:08;1,357 
>
>My r-code is 
>df<-read.csv("file.csv", header=TRUE, sep=";") 
>f1 <- function(...) as.POSIXct(paste(...), format = "%d/%m/%Y %H:%M") 
 >b <- read.zoo(df, index = 1, sep=";", header = TRUE, FUN  = f1) 
>data<-xts(b) 
>plot(data) 
>
>The following error occurs: 
>Error in plot.window(...) : need finite 'ylim' values 
>In addition: Warning messages: 
>1: In as.double.xts(y) : NAs introduced by coercion 
>2: In min(x) : no non-missing arguments to min; returning Inf 
>3: In max(x) : no non-missing arguments to max; returning -Inf 
>
>I think the problem is that the index does not recognize the 
"%d/%m/%Y %H:%M" format, but I do not know how to handle this problem. 
>Does anyone know a solution to my problem? 
Thank you a lot! 
Michi 
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