Reshaping data

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?

Thanks,
Roland

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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?