Approaches to preserving object's attributes during extract/replace operations

Question

Recently I encountered the following problem in my R code. In a function, accepting a data frame as an argument, I needed to add (or replace, if it exists) a column with data calculated based on values of the data frame's original column. I wrote the code, but the testing revealed that data frame extract/replace operations, which I've used, resulted in a loss of the object's special (user-defined) attributes.

After realizing that and confirming that behavior by reading R documentation (http://stat.ethz.ch/R-manual/R-patched/library/base/html/Extract.html), I decided to solve the problem very simply - by saving the attributes before the extract/replace operations and restoring them thereafter:

myTransformationFunction <- function (data) {

  # save object's attributes
  attrs <- attributes(data)

  <data frame transformations; involves extract/replace operations on `data`>

  # restore the attributes
  attributes(data) <- attrs

  return (data)
}

This approach worked. However, accidentally, I ran across another piece of R documentation (http://stat.ethz.ch/R-manual/R-patched/library/base/html/Extract.data.frame.html), which offers IMHO an interesting (and, potentially, a more generic?) alternative approach to solving the same problem:

## keeping special attributes: use a class with a
## "as.data.frame" and "[" method:

as.data.frame.avector <- as.data.frame.vector

`[.avector` <- function(x,i,...) {
  r <- NextMethod("[")
  mostattributes(r) <- attributes(x)
  r
}

d <- data.frame(i = 0:7, f = gl(2,4),
                u = structure(11:18, unit = "kg", class = "avector"))
str(d[2:4, -1]) # 'u' keeps its "unit"

I would really appreciate if people here could help by:

1. Comparing the two above-mentioned approaches, if they are comparable (I realize that the second approach as defined is for data frames, but I suspect it can be generalized to any object);

2. Explaining the syntax and meaning in the function definition in the second approach, especially as.data.frame.avector, as well as what is the purpose of the line as.data.frame.avector <- as.data.frame.vector.

Answer 1

I'm answering my own question, since I have just found an SO question (How to delete a row from a data.frame without losing the attributes), answers to which cover most of my questions posed above. However, additional explanations (for R beginners) for the second approach would still be appreciated.

UPDATE:

Another solution to this problem has been proposed in an answer to the following SO question: indexing operation removes attributes. Personally, however, I better like the approach, based on creating a new class, as it's IMHO semantically cleaner.