# [R] Reshaping data

Peter Dalgaard p.dalgaard at biostat.ku.dk
Thu Dec 8 10:34:00 CET 2005

```"Rau, Roland" <Rau at demogr.mpg.de> writes:

> Dear all,
>
> given I have data in a data.frame which indicate the number of people in
> a
> specific year at a specific age:
>
> n <- 10
> mydf <- data.frame(yr=sample(1:10, size=n, replace=FALSE),
>                    age=sample(1:12, size=n, replace=FALSE),
>                    no=sample(1:10, size=n, replace=FALSE))
>
> Now I would like to make a matrix with (in this simple example)
> 10 columns (for the years) and 12 rows (for the ages). In each cell,
> I would like to put the correct number of individuals.
>
> So far I was doing this as follows:
>
> mymatrix <- matrix(0, ncol=10, nrow=12)
> for (year in unique(mydf\$yr)) {
>   for (age in unique(mydf\$age)) {
>     if (length(mydf\$no[mydf\$yr==year & mydf\$age==age]) > 0) {
>       mymatrix[age,year] <- mydf\$no[mydf\$yr==year & mydf\$age==age]
>     } else {
>       mymatrix[age,year] <- 0
>     }
>   }
> }
>
> This is fairly fast in such a simple setting.
> But with more years and ages (and for roughly 300 datasets) this becomes
> pretty slow. And in addition, this is not really elegant R-code.
>
> Can somebody point me into the direction how I can do that in a more
> elegant
> way, possibly avoiding the loops?

This almost gets you there:

with(mydf, tapply(no,list(age,yr), sum))

except that it puts NA where you want 0, which you could fix with

m <- with(mydf, tapply(no,list(age,yr), sum))
m[is.na(m)] <- 0
m

Other options include matrix indexing:

with(mydf, {
M <- matrix(0,12,10)
M[cbind(age,yr)]<-no
})

or (tada...) the reshape() function, esp. if you want a data frame as
output.
--
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~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)                  FAX: (+45) 35327907

```