R help - Jul 2011 - (unclassified?) Help Question

Dear List,

I'd appreciate you guidance for obtaining the desired result shown
below, by combining tapply(x, g, mean) and g in the example.

Basically, I'm trying to create a vector whose values are based on the
result from tapply(x, g, mean)  but that follow the pattern and length
given by the factor g. Of course I'm looking for a generic solution
(i.e, not something that just work for this particualr case).

set.seed(1)
f1 <- gl(2, 1, 10, labels=c("M", "F"))
f2 <- gl(2, 2, 10, labels=c("H", "L"))
x <- rnorm(10)
d <- data.frame(f1, f2, x)
g <- interaction(f1, f2)
tapply(x, g, mean)
>     M.H              F.H                 M.L        F.L
> 0.0929451 -0.3140711 -0.1740998  1.1668028
g
> [1] M.H F.H M.L F.L M.H F.H M.L F.L M.H F.H
> Levels: M.H F.H M.L F.L
Desired result:

x
> [1]  0.0929451 -0.3140711 -0.1740998  1.1668028  0.0929451 -0.3140711
-0.1740998
> [8]  1.1668028

Thanks for any help!
Lars.

On Jul 16, 2011, at 4:08 PM, Lars Bishop wrote:
> Dear List,
>
> I'd appreciate you guidance for obtaining the desired result shown
> below, by combining tapply(x, g, mean) and g in the example.
>
> Basically, I'm trying to create a vector whose values are based on the
> result from tapply(x, g, mean)  but that follow the pattern and length
> given by the factor g.
What does that mean? The length of g is 10 and there are 4 unique  
values. How are we supposed to get 8 categories?

 > length(g)
[1] 10
 > length(unique(g))
[1] 4

-- 
David.
> Of course I'm looking for a generic solution
> (i.e, not something that just work for this particualr case).
>
> set.seed(1)
> f1 <- gl(2, 1, 10, labels=c("M", "F"))
> f2 <- gl(2, 2, 10, labels=c("H", "L"))
> x <- rnorm(10)
> d <- data.frame(f1, f2, x)
> g <- interaction(f1, f2)
> tapply(x, g, mean)
>>    M.H              F.H                 M.L        F.L
>> 0.0929451 -0.3140711 -0.1740998  1.1668028
> g
>> [1] M.H F.H M.L F.L M.H F.H M.L F.L M.H F.H
>> Levels: M.H F.H M.L F.L
>
> Desired result:
>
> x
>> [1]  0.0929451 -0.3140711 -0.1740998  1.1668028  0.0929451  
>> -0.3140711 -0.1740998
>> [8]  1.1668028
>
>
> Thanks for any help!
> Lars.
>
> ______________________________________________
> 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 Winsemius, MD
West Hartford, CT

Is this what you want (using 'ave'):
> set.seed(1)
> f1 <- gl(2, 1, 10, labels=c("M", "F"))
> f2 <- gl(2, 2, 10, labels=c("H", "L"))
> x <- rnorm(10)
> d <- data.frame(f1, f2, x)
> g <- interaction(f1, f2)
> tapply(x, g, mean)
       M.H        F.H        M.L        F.L
 0.0929451 -0.3140711 -0.1740998  1.1668028
> g
 [1] M.H F.H M.L F.L M.H F.H M.L F.L M.H F.H
Levels: M.H F.H M.L F.L
> d
   f1 f2          x
1   M  H -0.6264538
2   F  H  0.1836433
3   M  L -0.8356286
4   F  L  1.5952808
5   M  H  0.3295078
6   F  H -0.8204684
7   M  L  0.4874291
8   F  L  0.7383247
9   M  H  0.5757814
10  F  H -0.3053884
> ave(d$x, d$f1, d$f2, FUN = mean)
 [1]  0.0929451 -0.3140711 -0.1740998  1.1668028  0.0929451 -0.3140711
-0.1740998  1.1668028  0.0929451
[10] -0.3140711
> d$result <- ave(d$x, d$f1, d$f2, FUN = mean)
> d
   f1 f2          x     result
1   M  H -0.6264538  0.0929451
2   F  H  0.1836433 -0.3140711
3   M  L -0.8356286 -0.1740998
4   F  L  1.5952808  1.1668028
5   M  H  0.3295078  0.0929451
6   F  H -0.8204684 -0.3140711
7   M  L  0.4874291 -0.1740998
8   F  L  0.7383247  1.1668028
9   M  H  0.5757814  0.0929451
10  F  H -0.3053884 -0.3140711
>

On Sat, Jul 16, 2011 at 4:08 PM, Lars Bishop <lars52r at gmail.com>
wrote:
> Dear List,
>
> I'd appreciate you guidance for obtaining the desired result shown
> below, by combining tapply(x, g, mean) and g in the example.
>
> Basically, I'm trying to create a vector whose values are based on the
> result from tapply(x, g, mean) ?but that follow the pattern and length
> given by the factor g. Of course I'm looking for a generic solution
> (i.e, not something that just work for this particualr case).
>
> set.seed(1)
> f1 <- gl(2, 1, 10, labels=c("M", "F"))
> f2 <- gl(2, 2, 10, labels=c("H", "L"))
> x <- rnorm(10)
> d <- data.frame(f1, f2, x)
> g <- interaction(f1, f2)
> tapply(x, g, mean)
>> ? ? M.H ? ? ? ? ? ? ?F.H ? ? ? ? ? ? ? ? M.L ? ? ? ?F.L
>> 0.0929451 -0.3140711 -0.1740998 ?1.1668028
> g
>> [1] M.H F.H M.L F.L M.H F.H M.L F.L M.H F.H
>> Levels: M.H F.H M.L F.L
>
> Desired result:
>
> x
>> [1] ?0.0929451 -0.3140711 -0.1740998 ?1.1668028 ?0.0929451 -0.3140711
-0.1740998
>> [8] ?1.1668028
>
>
> Thanks for any help!
> Lars.
>
> ______________________________________________
> 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.
>


-- 
Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?