try this:
> x.1 <- data.frame(income=runif(100)*10000,
educ=sample(c('hs','col','none'),100,T))
> x.1
income educ
1 5930.30882 col
2 5528.83222 hs
3 5967.04041 hs
4 3926.30682 hs
5 2603.75924 none
...........
> x.2 <- tapply(x.1$income, x.1$educ, mean)
> x.2
col hs none
5575.310 4994.921 5481.962
> x.1$median <- x.2[x.1$educ]
> x.1
income educ median
1 5930.30882 col 5575.310
2 5528.83222 hs 4994.921
3 5967.04041 hs 4994.921
4 3926.30682 hs 4994.921
5 2603.75924 none 5481.962
6 7398.83325 col 5575.310
7 265.06895 hs 4994.921
.........
>
Jim
__________________________________________________________
James Holtman "What is the problem you are trying to solve?"
Executive Technical Consultant -- Convergys Labs
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"Dimitri Joe"
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.br> cc:
Sent by: Subject: [R] vectorization
[EMAIL PROTECTED]
ath.ethz.ch
06/17/2005 14:00
Hi there,
I have a data frame (mydata) with 1 numeric variable (income) and 1 factor
(education). I want a new column in this data with the median income for
each education level. A obviously inneficient way to do this is
for ( k in 1: nrow(mydata) ) {
l <- mydata$education[k]
mydata$md[k] <- median(mydata$income[mydata$education==l],na.rm=T)
}
Since mydata has nearly 30.000 rows, this will be done not untill the end
of this month. I thus need some help for vectorizing this, please.
Thanks,
Dimitri
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