[R] using ddply but preserving some of the outside data

[jebyrnes]

OK, I see how this would work for a rolling mean with continuous
observations.  However, my actual problem is a bit more complex.  I have a
number of observations, not necessarily evenly spaced.  So, the data I'm
working with looks somewhat more like what this would produce

set.seed(2003)
sites<-c("a", "b", "c")
dates<-round(runif(20,0,50))

a.df<-expand.grid(sites=sites, dates=dates)
a.df$value<-runif(30,0,100)
a.df<-as.data.frame(a.df)

And, rather than getting a rolling daily average, let's say I want an
average from any sample points from the previous 20 days.

#now, I want to get the average of the 
mean2<-function(df, date){
	sub.df<-subset(df, df$dates-date<20 &
				df$dates-date>-20 )
	return(mean(df$value))
	}

Would the rollmean approach still work here? 


Gabor Grothendieck wrote:
> 
> In particular, try this:
> 
>> library(zoo)
>> a.wide <- reshape(a.df, dir = "wide", timevar = "dates", idvar = "sites")
>> rollmean(as.zoo(t(a.wide[,-1])), 2)
> 
> 1 56.855685 58.62981 95.14842
> 2 58.049821 58.81659 78.70020
> 3 11.199634 89.91179 76.22853
> 4  1.152741 43.63333 93.03040
> 
> 
> 
> 

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