Represent this as a time series. Using
the zoo package:
> library(zoo)
> z <- zoo(cbind(price_g = c(0.34, 0.36), price_s = c(0.56, 0.76)),
> as.Date(c("2000-01-01", "2000-01-05")))
> diff(log(z))
price_g price_s
2000-01-05 0.05715841 0.3053816
> diff(log(z), na.pad = TRUE)
price_g price_s
2000-01-01 NA NA
2000-01-05 0.05715841 0.3053816
See the two zoo vignettes:
vignette("zoo")
vignette("zoo-quickref")
On Jan 10, 2008 2:16 AM, Vishal Belsare <[EMAIL PROTECTED]> 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
>
> ______________________________________________
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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