Perhaps you can do this: cbind(df, sapply(rbind(c(NA, NA),log(df)), diff))
On 10/01/2008, 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 > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Henrique Dallazuanna Curitiba-Paraná-Brasil 25° 25' 40" S 49° 16' 22" O ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
