When discussing Vectorization or For Loops introduce apply functions

[victorfeagins]

In the R for Reproducible Scientific Analysis when discussing for loops or vectorization it might be important to let people know about the apply family of functions. For loops are generally slow in R and it might be handy to at least acknowledge the apply family of functions.

[bschiffthaler]

Apply functions do not vectorize. They are for-loops, sometimes called from C (lapply() and sapply()), in the case of apply, it's straight within R. From the source code of apply():

  if (length(d.call) < 2L) {
      if (length(dn.call))
          dimnames(newX) <- c(dn.call, list(NULL))
      for (i in 1L:d2) {
          tmp <- forceAndCall(1, FUN, newX[, i], ...)
          if (!is.null(tmp))
              ans[[i]] <- tmp
      }
  }
  else for (i in 1L:d2) {
      tmp <- forceAndCall(1, FUN, array(newX[, i], d.call,
          dn.call), ...)
      if (!is.null(tmp))
          ans[[i]] <- tmp
  }

The crucial bit is that they all are evaluating R code in the loop body, which is not really what is commonly meant by vectorization within R. Patrick Burns discusses this in his R Inferno, circle 4.