R: split data frame rows by space, remove common elements, put unequal length columns in new df

Question

Suppose, I have df with two rows of strings that I need to split by space, unlist, then find anti-intersection and reuse in a list. I can do it brute force by working with each row individually. Problem is that there can be more than 2 rows etc. My working solution thus far is below, but there must be a simpler way of not accessing each line. Thanks!!

    df = structure(list(A = structure(1:2, .Label = c("R1", "R2"), class = "factor"), 
                        B = c("a b c d e f g o l", 
                              "b h i j k l m n o p q"
                        )), .Names = c("A", "B"), row.names = c(NA, -2L), class = "data.frame")

    dat1 = unlist(strsplit(df[1,2]," "))
    dat2 = unlist(strsplit(df[2,2]," "))

    f <- function (...) 
    {
      aux <- list(...)
      ind <- rep(1:length(aux), sapply(aux, length))
      x <- unlist(aux)
      boo <- !(duplicated(x) | duplicated(x, fromLast = T))
      split(x[boo], ind[boo])
    }

    excl = (f(dat1, dat2))
L <- list(excl[[1]],excl[[2]])

cfun <- function(L) {
  pad.na <- function(x,len) {
    c(x,rep("",len-length(x)))
  }
  maxlen <- max(sapply(L,length))
  print(maxlen)
  do.call(data.frame,lapply(L,pad.na,len=maxlen))
}

a = cfun(L)

What I had:

    A   B
1   Food    a b c d e f g
2   HABA    b h i j k l m n o p q

What I got:

    c..a....c....d....e....f....g.......... c..h....i....j....k....m....n....p....q..
1   a   h
2   c   i
3   d   j
4   e   k
5   f   m
6   g   n
7       p
8       q

Edit: The goal is to eliminate common elements from all columns. I.e. if "4" is present in row 1 and seen anywhere else - remove. New test set:

df1 = structure(list(A = structure(1:3, .Label = c("R1", "R2", "R3"
), class = "factor"), B = c("1 4 78 5 4 6 7 0", "2 3 76 8 2 1 8 0", 
"4 7 1 2")), .Names = c("A", "B"), row.names = c(NA, -3L), class = "data.frame")

Current output from suggested code:

    a   b   c
1   4   2   4
2   78  3   7
3   5   76  2
4   4   8   NA
5   6   2   NA
6   7   8   NA
7   0   0   NA

2, 4, and 7 should not be there as they are seen in more than 1 column. Bottom line - output should consist of unique numbers/elements only in any columns. Thanks!!