Try this:
x
Datetime Temp
1 01/01/07 00:01 11.5
2 01/01/07 00:16 11.6
y
Datetime Temp
1 01/01/07 00:01 10
2 01/01/07 00:16 3
merge(x, y, by="Datetime")
Datetime Temp.x Temp.y
1 01/01/07 00:01 11.5 10
2 01/01/07 00:16 11.6 3
On 22/02/2008, stephen sefick <[EMAIL PROTECTED]> wrote:
> I have two dataframes in R that were tab seperated .txt files
>
> y<-read.table("foo.txt", header=T)
> x<-read.table("foo.txt", header=T)
>
> these are set up like this:
>
> Datetime Temp
> 01/01/07 00:01 11.5
> 01/01/07 00:16 11.6
>
> etc etc to 66000 rows in y and 33000 rows in x
>
> The two files overlap with the same data for a period of time but
> contain different values outside of these. Is there a way to merge
> these two data sets based on the shared date time column into one
> large dataset of ~90,000 lines. I want to eventually make this into a
> time series with frequency= 1/15.
>
> Thanks
>
> Stephen
> --
> Let's not spend our time and resources thinking about things that are
> so little or so large that all they really do for us is puff us up and
> make us feel like gods. We are mammals, and have not exhausted the
> annoying little problems of being mammals.
>
> -K. Mullis
>
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> and provide commented, minimal, self-contained, reproducible code.
>
--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
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