Perhaps you can do this:
cbind(df, sapply(rbind(c(NA, NA),log(df)), diff))
On 10/01/2008, Vishal Belsare <
shoot.spam@...> wrote:
> I have a dataframe say:
>
> date price_g price_s
> 0.34 0.56
> 0.36 0.76
> . .
> . .
> . .
>
> and so on. say, 1000 rows.
>
> Is it possible to add two columns to this dataframe, by computing say
> diff(log(price_g) and diff(log(price_s)) ?
>
> The elements in the first row of these columns cannot be computed, but
> can I coerce this to happen and assign a missing value there? It would
> be really great if I could do that, because in this case I don't have
> to re-index my transformed series to the dates again in a new
> dataframe.
>
> Thanks in anticipation.
>
>
> Vishal Belsare
>
> ______________________________________________
>
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>
--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
______________________________________________
R-help@... mailing list
https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide
http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.