Question

I do not use that many functions but when I do I tend to use an anon function and some form of apply . I now however am trying to write a function that works over items in a list.

There are two lists that each have many items (by item I mean e.g. mylist1[1]). All items are dataframes. I want to take the first dataframe from mylist1 and the first dataframe from mylist2 and run a bunch of functions over the columns in those dataframes. Then take the 2nd mylist1 item and the 2nd mylist2 item and so on…

Below is the sort of thing I am used to writing but clearly does not work in this case with two lists. Can anyone help me out with a fast way to figure out how I should approach this using something other than sapply method that seems to be causing the main problem.

a <- c(1:10)
b <- c(1:10)
z <- c(rep("x", 5), rep("y", 5))
df <- data.frame(cbind(a, b, z))
mylist1 <- split(df, z)
mylist2 <- split(df, z)

myfunction <- function(x, y) 
{

    a <- as.data.frame(x[1])
    b <- as.data.frame(y[1])
    meana <- mean(a[1])
    meanb <- mean(b[1])
    model <- lm(a[1]~b[1])
    return(c(model$coefficients[2], meana, meanb))
}

result <- sapply(mylist1, mylist2, myfunction)

I also just thought do people think it would be better to subset by z rather than split and do the function that way?

Answer 1

You are describing exactly the use case for mapply.

result <- mapply(myfunction,x=mylist,y=mylist2)

Unfortunately your example doesn’t seem to enjoy being passed two data.frames (x, y ‘s first elements are both data.frames, which x[1] and y[1] would seem to contradict).