On 10 Dec 2008, at 17:25, hadley wickham wrote:
On Wed, Dec 10, 2008 at 11:02 AM, baptiste auguie
<[EMAIL PROTECTED]> wrote:
Dear list,
I have a data.frame with x, y values and a 3-level factor "group",
say. I
want to create a new column in this data.frame with the values of y
scaled
to 1 by group. Perhaps the example below describes it best:
x <- seq(0, 10, len=100)
my.df <- data.frame(x = rep(x, 3), y=c(3*sin(x), 2*cos(x),
cos(2*x)), #
note how the y values have a different maximum depending on the
group
group = factor(rep(c("sin", "cos", "cos2"), each=100)))
library(reshape)
df.melt <- melt(my.df, id=c("x","group")) # make a long format
df.melt <- df.melt[ order(df.melt$group) ,] # order the data.frame
by the
group factor
df.melt$norm <- do.call(c, tapply(df.melt$value, df.melt$group,
function(.v) {.v / max(.v)})) # calculate the normalised value per
group and
assign it to a new column
library(lattice)
xyplot(norm + value ~ x,groups=group, data=df.melt, auto.key=T) #
check
that it worked
This procedure works, but it feels like I'm reinventing the wheel
using
hammer and saw. I tried to use aggregate, by, ddply (plyr package),
but I
coudn't find anything straight-forward.
It's pretty easy with ddply:
df.melt <- ddply(df.melt, .(group), transform, norm = y / max(y))
Hadley
--
http://had.co.nz/
Very nice indeed! My test failed as I somehow misunderstood the syntax
and didn't think of applying transform().
Many thanks too,
baptiste
______________________________________________
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.
