Convert Mixed-Length named List to data.frame

Question

I have a list of the following format:

[[1]]
[[1]]$a
[1] 1

[[1]]$b
[1] 3

[[1]]$c
[1] 5

[[2]]       
[[2]]$c
[1] 2

[[2]]$a
[1] 3

There i

Answer 1

Well, I gave my first thought a try and the performance wasn't as bad as I was afraid of, but I'm sure there's still room for improvement (especially in the waster matrix -> data.frame conversion).

convertList <- function(myList, ids){
    #this computes a list of the numerical index for each value to handle the missing/
    # improperly ordered list elements. So it will have a list in which each element 
    # associated with A has a value of 1, B ->2, and C -> 3. So a row containing
    # A=_, C=_, B=_ would have a value of `1,3,2`
    idInd <- lapply(myList, function(x){match(names(x), ids)})

    # Calculate the row indices if I were to unlist myList. So if there were two elements
    # in the first row, 3 in the third, and 1 in the fourth, you'd see: 1, 1, 2, 2, 2, 3
    rowInd <- inverse.rle(list(values=1:length(myList), lengths=sapply(myList, length)))

    #Unlist the first list created to just be a numerical matrix
    idInd <- unlist(idInd)

    #create a grid of addresses. The first column is the row address, the second is the col
    address <- cbind(rowInd, idInd)

    #have to use a matrix because you can't assign a data.frame 
    # using an addressing table like we have above
    mat <- matrix(ncol=length(ids), nrow=length(myList))

    # assign the values to the addresses in the matrix
    mat[address] <- unlist(myList)

    # convert to data.frame
    df <- as.data.frame(mat)
    colnames(df) <- ids

    df
}   
myList <- createList(50000)
ids <- letters[1:3]

system.time(df <- convertList(myList, ids))

It's taking about 0.29 seconds to convert the 50,000 rows on my laptop (Windows 7, Intel i7 M620 @ 2.67 GHz, 4GB RAM).

Still very much interested in other answers!