Faster ways to calculate frequencies and cast from long to wide

aggregate, plyr, r, reshape2

Solution

You don't need `ddply` for this. The `dcast` from `reshape2` is sufficient:

dat <- data.frame(
    id = c(rep(1, 4), 2),
    week = c(1:3, 1, 3)
)

library(reshape2)
dcast(dat, id~week, fun.aggregate=length)

  id 1 2 3
1  1 2 1 1
2  2 0 0 1

Edit : For a base R solution (other than `table` - as posted by Joshua Uhlrich), try `xtabs`:

xtabs(~id+week, data=dat)

   week
id  1 2 3
  1 2 1 1
  2 0 0 1

Problem

I am trying to obtain counts of each combination of levels of two variables, "week" and "id". I'd like the result to have "id" as rows, and "week" as columns, and the counts as the values. Example of what I've tried so far (tried a bunch of other things, including adding a dummy variable = 1 and then `fun.aggregate = sum` over that): ``` library(plyr) ddply(data, .(id), dcast, id ~ week, value_var = "id", fun.aggregate = length, fill = 0, .parallel = TRUE) ``` However, I must be doing something wrong because this function is not finishing. Is there a better way to do this? Input: ``` id week 1 1 1 2 1 3 1 1 2 3 ``` Output: ``` 1 2 3 1 2 1 1 2 0 0 1 ```

Original source