Question

I need to do some analysis on vehicles that are identified by their ID. The results of this analysis will include some numeric, factor, and logical information. All the data used in the analysis is in one data frame, so that the function goes like this:

Results <- by(Data, Data$ID, Function)

Where Function is designed to give output like this:

Function <- function(DF) {
                          ## Do stuff...
                          return(c(23.2, as.factor("SuperFast"), TRUE))
                         }

What’s been great about this approach so far is that in addition to being quite fast (taking ~1 min where a for loop took hours), it’s easy to put in data.frame format by:

as.data.frame(do.call("rbind", Results))

But of course, c in Function and "rbind" in do.call coerce everything into the same object type. To resolve this, I’ve been making Function spit out a character vector (like as.character(23.2, "SuperFast", TRUE) and then changing object types manually at the end.

Is there (1) a way to return something that can be a row in a dataframe that has different object types or (2) a better method than using by and c (for rows)?

Just for kicks, here’s something that can be used for Data:

Data <- data.frame(ID=c(1,2,2,3))

Answer 1

Just return a data frame instead of a vector from your function:

Function <- function(DF) {
    ## Do stuff...
    return(data.frame(a = 23.2,b = as.factor("SuperFast"),c = TRUE))
}

As an aside, the only thing coercing everything to the same data type was c. rbind has a data frame method that will (mostly) preserve types, assuming all the data frames you pass to it line up.