Hi Johannes ,
Try this:
var1 <- rep(c("a","b"),c(100,100))
var2 <- runif(200,1,50)
df.test <- data.frame(var1,var2)
fn <- function(x){
x <- x$var2
x1 <- sort(x)
x2 <- seq(length(x))
x3 <- x2/max(x2)
df <- data.frame(x1,x2,x3)
df
}
require(plyr)
ddply(df.test,.(var1),fn)
I think it should do what you've asked.
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On Sat, May 5, 2012 at 12:51 PM, Johannes Radinger <jradin...@gmx.at> wrote:
> Hi,
>
> I am really confused how ddply work, so maybe you can help me.
>
> I created a function that sorts a vector etc.
>
> fn <- function(x){
> x1 <- sort(x)
> x2 <- seq(length(x))
> x3 <- x2/max(x2)
> df <- data.frame(x1,x2,x3)
> df
> }
>
> Probably this is not the best form of the function, but at least it
> produces what I want (data to plot a cumulative count curve).
> This function works on a single vector but I have a melted dataframe like:
>
> var1 <- rep(c("a","b"),c(100,100))
> var2 <- runif(200,1,50)
> df.test <- data.frame(var1,var2)
>
> ..and I want to apply that function on var2 but splitted by the variable
> var1. I think this might be a case for ddply...
>
> anything like: ddply(df.test,.(var1),fn(var2))...
> maybe someone know how to do that (modifying my function and applying it
> on a splitted dataframe).
>
> Best regards,
>
> Johannes
>
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>
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