I use aggregate to generate a data frame with one row for each code,
In the following example, I find the means for each group in each field x,
and y, that have the same code value.
>test<-data.frame(code=c(1,1,2,2,3,2,1,3),x=1:8,y=log(1:8))
> test
code x y
1 1 1 0.0000000
2 1 2 0.6931472
3 2 3 1.0986123
4 2 4 1.3862944
5 3 5 1.6094379
6 2 6 1.7917595
7 1 7 1.9459101
8 3 8 2.0794415
> aggregate(test[,c("x","y"),],test$code,mean)
test.code x y
1 1 3.333333 0.8796858
2 2 4.333333 1.4255554
3 3 6.500000 1.8444397
> help(aggregate.data.frame)
For more information
You can also type aggregate.data.frame, to see the code Splus uses for this.
Tom Jagger
________________________________________
From: s-news-owner@lists.biostat.wustl.edu
[mailto:s-news-owner@lists.biostat.wustl.edu] On Behalf Of
Bill.Venables@csiro.au
Sent: Sunday, April 24, 2005 4:25 PM
To: andy_liaw@merck.com; mleeds@mlp.com; s-news@lists.biostat.wustl.edu
Subject: Re: [S] friend of mine's question
Another idea would be
coef(lm(cbind(price, volume, yield) ~ as.factor(code) - 1, mydat))
but this is limited to the special case of the mean. Andy's idea is easier
to generalize.
-----Original Message-----
From: s-news-owner@lists.biostat.wustl.edu
[mailto:s-news-owner@lists.biostat.wustl.edu] On Behalf Of Liaw, Andy
Sent: Monday, 25 April 2005 3:56 AM
To: 'Leeds, Mark'; s-news@lists.biostat.wustl.edu
Subject: Re: [S] friend of mine's question
One way or the other, the data need to be split into groups. Here's one
possible way:
sapply(split(mydata, mydata$code), colMeans)
Andy
-----Original Message-----
From: s-news-owner@lists.biostat.wustl.edu
[mailto:s-news-owner@lists.biostat.wustl.edu] On Behalf Of Leeds, Mark
Sent: Sunday, April 24, 2005 1:18 PM
To: s-news@lists.biostat.wustl.edu
Subject: [S] friend of mine's question
A friend of mine has a data set
With variables :
code price volume yield
where code is an integer and can take on
say 20 different values.
He wants the means of price, volume, yield
But within each code value.
Obviously, he can break it up by each code and then
take the means but he was hoping
there was a quicker
way to do this ? Thanks.
mark
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