Using apply to get group means

  x2 x1 x3.mean
1  1  A     1.5
2  1  B     2.0
3  1  C     3.5
4  2  A     4.0
5  2  B     5.5
6  2  C     6.0

Hi all,

I'm trying to improve my R skills and make my programming more  
efficient and succinct.  I can solve the following question, but  
wonder if there's a better way to do it:

I'm trying to calculate mean by several variables and then put this  
back into the original data set as a new variable.  For example, if  
I were measuring weight, I might want to have each individual's  
weight, and also the group mean by, say, race, sex, and geographic  
region.  The following code works:

x1<-rep(c("A","B","C"),3)
x2<-c(rep(1,3),rep(2,3),1,2,1)
x3<-c(1,2,3,4,5,6,2,6,4)
x<-as.data.frame(cbind(x1,x2,x3))
x3.mean<-rep(0,nrow(x))
for (i in 1:nrow(x)){

+   x3.mean[i]<-mean(as.numeric(x[,3][x[,1]==x[,1][i]&x[,2]==x[,2] 
[i]]))
+   }

cbind(x,x3.mean)

 x1 x2 x3 x3.mean
1  A  1  1     1.5
2  B  1  2     2.0
3  C  1  3     3.5
4  A  2  4     4.0
5  B  2  5     5.5
6  C  2  6     6.0
7  A  1  2     1.5
8  B  2  6     5.5
9  C  1  4     3.5

However, I'd love to be able to do this with "apply" rather than a  
for-loop.  Or is there a built-in function? Any suggestions?

Also, any way to avoid the hassles with having to convert to a data  
frame and then again to numeric when one variable is character?

Cheers,
Alan Cohen

Not exactly the output you asked for, but perhaps you can consider,

library(doBy)

summaryBy(x3~x2+x1,data=x,FUN=mean)

?x2 x1 x3.mean
1 ?1 ?A ? ? 1.5
2 ?1 ?B ? ? 2.0
3 ?1 ?C ? ? 3.5
4 ?2 ?A ? ? 4.0
5 ?2 ?B ? ? 5.5
6 ?2 ?C ? ? 6.0

the plyr package also provides similar functionality, as do the ?by, ?ave,
and ?tapply base functions.

Hi all,

I'm trying to improve my R skills and make my programming more efficient and succinct.  I can solve the following question, but wonder if there's a better way to do it:

I'm trying to calculate mean by several variables and then put this back into the original data set as a new variable.  For example, if I were measuring weight, I might want to have each individual's weight, and also the group mean by, say, race, sex, and geographic region.  The following code works:

  

x1<-rep(c("A","B","C"),3)
x2<-c(rep(1,3),rep(2,3),1,2,1)
x3<-c(1,2,3,4,5,6,2,6,4)
x<-as.data.frame(cbind(x1,x2,x3))
x3.mean<-rep(0,nrow(x))
for (i in 1:nrow(x)){
    

+   x3.mean[i]<-mean(as.numeric(x[,3][x[,1]==x[,1][i]&x[,2]==x[,2][i]]))
+   }                                      
  

cbind(x,x3.mean)
    

  x1 x2 x3 x3.mean
1  A  1  1     1.5
2  B  1  2     2.0
3  C  1  3     3.5
4  A  2  4     4.0
5  B  2  5     5.5
6  C  2  6     6.0
7  A  1  2     1.5
8  B  2  6     5.5
9  C  1  4     3.5

However, I'd love to be able to do this with "apply" rather than a for-loop.  Or is there a built-in function? Any suggestions?

Also, any way to avoid the hassles with having to convert to a data frame and then again to numeric when one variable is character?

Cheers,
Alan Cohen