R help - Dec 2008 - tapply within a data.frame: a simpler alternative?

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.

I'll appreciate any input,

Baptiste





_____________________________

Baptiste Augui?

School of Physics
University of Exeter
Stocker Road,
Exeter, Devon,
EX4 4QL, UK

Phone: +44 1392 264187

http://newton.ex.ac.uk/research/emag

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 Augui?
> 
> School of Physics
> University of Exeter
> Stocker Road,
> Exeter, Devon,
> EX4 4QL, UK
> 
> Phone: +44 1392 264187
> 
> http://newton.ex.ac.uk/research/emag
> 
> ______________________________________________
> 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.
-- 
Chuck Cleland, Ph.D.
NDRI, Inc. (www.ndri.org)
71 West 23rd Street, 8th floor
New York, NY 10010
tel: (212) 845-4495 (Tu, Th)
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fax: (917) 438-0894

On Wed, Dec 10, 2008 at 11:02 AM, baptiste auguie <ba208 at exeter.ac.uk>
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/

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.
> 
> I'll appreciate any input,
You (as many before you) have overlooked the ave() function, which can
replace the ordering as well the do.call(c,tapply(....))

Also, I fail to see what good the melt()ing is for:
> dim(my.df)
[1] 300   3
> dim(melt(my.df, id=c("x","group")) )
[1] 300   4

And the extra column is just "y"


my.df <- transform(my.df, norm=ave(y, group,
   function(.v) {.v / max(.v)}))
xyplot(norm + y ~ x,groups=group,  data=my.df, auto.key=T)

-- 
   O__  ---- Peter Dalgaard             ?ster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark      Ph:  (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)              FAX: (+45) 35327907

You might take a look at the transformBy function in the doBy package

For example, 
new.df=transformBy(~group,data=my.df, new=y/max(y))

David Freedman


baptiste auguie-2 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.
> 
> I'll appreciate any input,
> 
> Baptiste
> 
> 
> 
> 
> 
> _____________________________
> 
> Baptiste Augui?
> 
> School of Physics
> University of Exeter
> Stocker Road,
> Exeter, Devon,
> EX4 4QL, UK
> 
> Phone: +44 1392 264187
> 
> http://newton.ex.ac.uk/research/emag
> 
> ______________________________________________
> 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.
> 
> 

-----
David Freedman
Atlanta
-- 
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