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 from. Here is an example:
### BEGIN ###
func<-function(x){
m<-median(x$x)
if(m > 2 & m < x$y){
return(T)
}
return(F)
}
tmp<-data.frame(x=1:10,y=c(rep(34,3),rep(35,3),rep(34,4)),z=c(rep("a",3),rep("b",3),rep("c",4)))
res<-aggregate(tmp,list(z),func)
### END ###
The values in the example are trivial, but the problem is that only one column
is passed to my function at a time, so I can't determine how 'm'
relates to 'x$y'. Any tips/guidance is appreciated.
Mark T. W. Ebbert
Hi:
Try this:
library(plyr)
func <- function(x, y) {
m <- median(x)
if(m > 2 & m < mean(y)) ret <- TRUE else ret <- FALSE
ret
}
ddply(tmp, .(z), summarise, r = func(x, y))
z r
1 a FALSE
2 b TRUE
3 c TRUE
HTH,
Dennis
On Wed, Sep 15, 2010 at 2:45 PM, Mark Ebbert
<Mark.Ebbert@hci.utah.edu>wrote:
> Dear R gurus,
>
> I regularly come across a situation where I would like to apply a function
> to a subset of data in a dataframe, but I have not found an R function to
> facilitate exactly what I need. More specifically, I'd like my function
to
> have a context of where the data it's analyzing came from. Here is an
> example:
>
> ### BEGIN ###
> func<-function(x){
> m<-median(x$x)
> if(m > 2 & m < x$y){
> return(T)
> }
> return(F)
> }
>
>
>
tmp<-data.frame(x=1:10,y=c(rep(34,3),rep(35,3),rep(34,4)),z=c(rep("a",3),rep("b",3),rep("c",4)))
> res<-aggregate(tmp,list(z),func)
> ### END ###
>
> The values in the example are trivial, but the problem is that only one
> column is passed to my function at a time, so I can't determine how
'm'
> relates to 'x$y'. Any tips/guidance is appreciated.
>
> Mark T. W. Ebbert
> ______________________________________________
> R-help@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.
>
[[alternative HTML version deleted]]
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 have a context of where the data it's analyzing > came from. Here is an example: >> ### BEGIN ### > func<-function(x){ > m<-median(x$x)> if(m > 2 & m < x$y){ > return(T) > } > return(F) > } >The semantic question is what are you trying to test when you say "m < x$y" ? "m" is a scalar and x is a vector. By default only the first element of x$y will be compared (not actually callable in that manner.)> tmp<- > data.frame(x=1:10,y=c(rep(34,3),rep(35,3),rep(34,4)),z=c(rep("a", > 3),rep("b",3),rep("c",4))) > res<-aggregate(tmp,list(z),func)I see Dennis has tried to move you forward to the plyr strategy, but some of us are mired in the traditonal ways: ?split # returns a dataframe in segments defined by a factor > func<-function(x){ + m<-median(x["x"], na.rm=TRUE) + if(m > 2 && m < x["y"]){ + return(T) + } + return(F) + } > > tmp<- data.frame(x=1:10,y=c(rep(34,3),rep(35,3),rep(34,4)),z=c(rep("a", 3),rep("b",3),rep("c",4))) > res<-lapply(split(tmp,list(tmp$z)), func) > res $a [1] FALSE $b [1] TRUE $c [1] TRUE> ### END ### > > The values in the example are trivial, but the problem is that only > one column is passed to my function at a time, so I can't determine > how 'm' relates to 'x$y'. Any tips/guidance is appreciated.-- David Winsemius, MD West Hartford, CT
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
Abhijit
On 9/15/10 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
have a context of where the data it's analyzing came from. Here is an
example:
>
> ### BEGIN ###
> func<-function(x){
> m<-median(x$x)
> if(m> 2& m< x$y){
> return(T)
> }
> return(F)
> }
>
>
tmp<-data.frame(x=1:10,y=c(rep(34,3),rep(35,3),rep(34,4)),z=c(rep("a",3),rep("b",3),rep("c",4)))
> res<-aggregate(tmp,list(z),func)
> ### END ###
>
> The values in the example are trivial, but the problem is that only one
column is passed to my function at a time, so I can't determine how
'm' relates to 'x$y'. Any tips/guidance is appreciated.
>
> Mark T. W. Ebbert
> ______________________________________________
> 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.
--
Abhijit Dasgupta, PhD
Director and Principal Statistician
ARAASTAT
Ph: 301.385.3067
E: adasgupta at araastat.com
W: http://www.araastat.com