Thanks everyone for the responses. They were all helpful!
On Sep 15, 2010, at 5:22 PM, Abhijit Dasgupta, PhD wrote:
I would approach this slightly differently. I would make func a
function of x and y.
func - function(x,y){
m - median(x)
return(m 2 m y)
}
Now generate tmp
Dear R gurus,
I regularly come across a situation where I would like to apply a function to a
subset of data in a dataframe, but I have not found an R function to facilitate
exactly what I need. More specifically, I'd like my function to have a context
of where the data it's analyzing came
Hi:
Try this:
library(plyr)
func - function(x, y) {
m - median(x)
if(m 2 m mean(y)) ret - TRUE else ret - FALSE
ret
}
ddply(tmp, .(z), summarise, r = func(x, y))
z r
1 a FALSE
2 b TRUE
3 c TRUE
HTH,
Dennis
On Wed, Sep 15, 2010 at 2:45 PM, Mark Ebbert
On Sep 15, 2010, at 5:45 PM, Mark Ebbert wrote:
Dear R gurus,
I regularly come across a situation where I would like to apply a
function to a subset of data in a dataframe, but I have not found an
R function to facilitate exactly what I need. More specifically, I'd
like my function to
I would approach this slightly differently. I would make func a
function of x and y.
func - function(x,y){
m - median(x)
return(m 2 m y)
}
Now generate tmp just as you have. then:
require(plyr)
res - daply(tmp, .(z), summarise, res=func(x,y))
I believe this does the trick
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