R help - Jun 2006 - simplier way to import txt time-series data

Hello much more experienced R-users,

I have got a txt - file which contains data formated like this:

YYYY MM DD HH  data1  data2 ... data31
2002 12 01 01 0.002 0.003 ... 312.0

The single columns are divided by at least one space.

Is their an easy and fast way to make R understand that the first 4 
columns are year month day and hour  to recognize it as time series data.

The time series are not complete. Single hours could be missing.

Thanks a lot for answering my question. I just cannot believe that it is 
a big problem for R to handle this clean format while it even imports 
data from excel-files.

Greatings

Jan

Try this which reads in the data as a data frame and appends a
chron variable datetime:

Lines <- "YYYY MM DD HH  data1  data2
2002 12 01 01 0.002 0.003"

DF <- read.table(textConnection(Lines), header = TRUE)
library(chron)
DF$datetime <- with(DF, chron(paste(MM, DD, YYYY, sep = "/")) +
HH/24)
DF

On 6/7/06, Jan Schwanbeck <jansc at gmx.net>
wrote:
> Hello much more experienced R-users,
>
> I have got a txt - file which contains data formated like this:
>
> YYYY MM DD HH  data1  data2 ... data31
> 2002 12 01 01 0.002 0.003 ... 312.0
>
> The single columns are divided by at least one space.
>
> Is their an easy and fast way to make R understand that the first 4
> columns are year month day and hour  to recognize it as time series data.
>
> The time series are not complete. Single hours could be missing.
>
> Thanks a lot for answering my question. I just cannot believe that it is
> a big problem for R to handle this clean format while it even imports
> data from excel-files.
>
> Greatings
>
> Jan
>
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