[R] Loading Intraday Time Series Data

[John Kane]

Hi Steve,

I "think" what you want to do is get a unique time-date from the first two columns.  

Try something like this: (changing the file name obviously.
mydate should give you a time and date format that you can add to the existing data.frame.



mydata <- read.table("C:/rdata/dates.junk.csv", header=TRUE, sep=",",
     colClasses=c("character","character", "numeric" , "numeric",
       "numeric", "numeric", "numeric", "numeric"))


 df1 <- paste(mydata[,1], "", mydata[,2]) 
 
 
mydates <- strptime(df1, "%d/%m/%Y %H%M")


--- On Sun, 5/16/10, Steve Johns <steve.johns at verizon.net> wrote:

> From: Steve Johns <steve.johns at verizon.net>
> Subject: [R] Loading Intraday Time Series Data
> To: r-help at r-project.org
> Received: Sunday, May 16, 2010, 7:22 AM
> Hi,
> 
> I am trying to load a data file that looks like this:
> 
> |Date,Time,Open,High,Low,Close,Up,Down
> 05/02/2001,0030,421.20,421.20,421.20,421.20,11,0
> 05/02/2001,0130,421.20,421.40,421.20,421.40,7,0
> 05/02/2001,0200,421.30,421.30,421.30,421.30,0,5
> 05/02/2001,0230,421.60,421.60,421.50,421.50,26,1|
> etc.
> 
> into an R timeseries or ts object.
> 
> The key point is that both the date and time need to become
> part of the index.
> 
> With zoo, this line will load the data:
> 
> z <- read.zoo("foo_hs.csv", format = "%m/%d/%Y",
> sep=",", header = TRUE )
> 
> but the Time does not become part of the index this
> way.  This means the index is non-unique, and that is
> not the goal.
> 
> Could someone kindly show me a way, using R itself, to deal
> with the separate Date and Time columns so as to properly
> combine them into the index for the timeseries?
> 
> Thanks!
> 
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