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
Perhaps you can do this: cbind(df, sapply(rbind(c(NA, NA),log(df)), diff)) On 10/01/2008, Vishal Belsare <shoot.spam at gmail.com> 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 at 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-Paran?-Brasil 25? 25' 40" S 49? 16' 22" O
Maybe: cbind(df,rbind(NA,apply(log(df),2,diff))) Bart Vishal Belsare 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 at 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. > >-- View this message in context: http://www.nabble.com/diff-in-a-dataframe-tp14728790p14731043.html Sent from the R help mailing list archive at Nabble.com.
So, what's the easiest way to add a column to a dataframe? Just do it. Here is a really simple example to illustrate:> foo <- data.frame(x=1:4,y=2:5) > foox y 1 1 2 2 2 3 3 3 4 4 4 5> foo$z <- c(NA,diff(foo$x)) > foox y z 1 1 2 NA 2 2 3 1 3 3 4 1 4 4 5 1 Solutions using apply and sapply are overly complicated for what you requested. If you had to do this for many, many columns a looping solution would be worth it, but for just two columns, it's not. -Don At 12:46 PM +0530 1/10/08, Vishal Belsare 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 at 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.-- -------------------------------------- Don MacQueen Environmental Protection Department Lawrence Livermore National Laboratory Livermore, CA, USA 925-423-1062
Hello Vishal Maybe this is what you want? x<-c(0.34,0.36,3) y<-c(0.56,0.76,4) a<-data.frame(x,y)>ax y 1 0.34 0.56 2 0.36 0.76 3 3.00 4.00 a$diff<-(log(a$x)) a$diff2<-(log(a$y))>ax y diff diff2 1 0.34 0.56 -1.078810 -0.5798185 2 0.36 0.76 -1.021651 -0.2744368 3 3.00 4.00 1.098612 1.3862944 and if you wnat to coerce the first row to a whatever value just type a[1,]<-NA Cheers A ----- Messaggio originale ----- Da: Vishal Belsare <shoot.spam@gmail.com> A: r-help@r-project.org Inviato: Mercoledì 9 gennaio 2008, 23:16:38 Oggetto: [R] diff in a dataframe 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. ___________________________________ ttp://it.docs.yahoo.com/nowyoucan.html [[alternative HTML version deleted]]
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 <shoot.spam at gmail.com> 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 at 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. >