[R] tapply within a data.frame: a simpler alternative?

Chuck Cleland ccleland at optonline.net
Wed Dec 10 18:20:21 CET 2008


On 12/10/2008 12:02 PM, baptiste auguie 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.

with(my.df, ave(y, group, FUN = function(x){x/max(x)}))

?ave

> I'll appreciate any input,
> 
> Baptiste
> _____________________________
> 
> Baptiste Auguié
> 
> School of Physics
> University of Exeter
> Stocker Road,
> Exeter, Devon,
> EX4 4QL, UK
> 
> Phone: +44 1392 264187
> 
> http://newton.ex.ac.uk/research/emag
> 
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-- 
Chuck Cleland, Ph.D.
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