Learning the R way – A Wish

Dear Patrick--
After the official Core Team's R manuals and the individual function
help pages, I have found "The R Inferno" to be the single most useful
piece of documentation when I have gotten stuck with a R problems. It is
the only introduction that seems to be aware of the ambiguities present
in the official documentation and of some of the ways one can get stuck
in traps of misunderstanding. Plus, it is enjoyably witty.

When I first started using it, I found it ranged from very useful to
pretty frustrating. I did not always understand what the examples you
presented were trying to say. It is still true that I occasionally wish
for a little more discursive explanatory style, but as time goes by I

find that I am increasingly likely to get the point just from the example.

Many thanks, Andrew


On Tue, Mar 5, 2013 at 1:46 AM, Patrick Burns <pburns at pburns.seanet.com
<mailto:pburns at pburns.seanet.com>> wrote:

    Andrew,

    That sounds like a sensible document you propose.
    Perhaps I'll do a few blog posts along that vein -- thanks.

    I presume you know of 'The R Inferno', which does
    a little of what you want.

    Pat



    On 04/03/2013 23:42, andrewH wrote:

        There is something that I wish I had that I think would help me
        a lot to be a
        better R programmer, that I think would probably help many
        others as well.
        I put the wish out there in the hopes that someone might think
        it was worth
        doing at some point.

        I wish I had the code of some substantial, widely used package ?
        lm, say ?
        heavily annotated and explained at roughly the level of R
        knowledge of
        someone who has completed an intro statistics course using R and
        picked up
        some R along the way.  The idea is that you would say what the
        various
        blocks of code are doing, why the authors chose to do it this
        way rather
        than some other way, point out coding techniques that save time
        or memory or
        prevent errors relative to alternatives, and generally, to
        explain what it
        does and point out and explain as many of the smarter features
        as possible.
        Ideally, this would include a description at least at the
        conceptual level
        if not at the code level of the major C functions that the
        package calls, so
        that you understand at least what is happening at that level, if
        not the
        nitty-gritty details of coding.

        I imagine this as a piece of annotated code, but maybe it could
        be a video
        of someone, or some couple of people, scrolling through the code
        and talking
        about it. Or maybe something more like a wiki page, with various
        people
        contributing explanations for different lines, sections, and
        practices.

        I am learning R on my own from books and the internet, and I
        think I would
        learn a lot from a chatty line-by-line description of some
        substantial block
        of code by someone who really knows what he or she is doing ?
        perhaps with a
        little feedback from some people who are new about where they
        get lost in
        the description.

        There are a couple of particular things that I personally would
        hope to get
        out of this.  First, there are lots of instances of good coding
        practice
        that I think most people pick up from other programmers or by having
        individual bits of code explained to them that are pretty hard
        to get from
        books and help files.  I think this might be a good way to get
        at them.

        Second, there are a whole bunch of functions in R that I call
        meta-programming functions ? don?t know if they have a more
        proper name.
        These are things that are intended primarily to act on R
        language objects or
        to control how R objects are evaluated. They include functions
        like call,
        match.call, parse and deparse, deparen, get, envir, substitute,
        eval, etc.
        Although I have read the individual documentation for many of
        these command,
        and even used most of them, I don?t think I have any fluency
        with them, or
        understand well how and when to code with them.  I think reading a
        good-sized hunk of code that uses these functions to do a lot of
        things that
        packages often need to do in the best-practice or standard R
        way, together
        with comments that describe and explain them would help a lot
        with that.
        (There is a good smaller-scale example of this in Friedrich Leisch?s
        tutorial on creating R packages).

        These are things I think I probably share with many others. I
        actually have
        an ulterior motive for suggesting lm in particular that is more
        peculiar to
        me, though not unique I am sure. I would like to understand how
        formulas
        work well enough to use them in my own functions. I do not think
        there is
        any way to get that from the help documentation. I have been
        working on a
        piece of code that I suspect is reinventing, but in an awkward
        and kludgey
        way, a piece of the functionality of formulas. So far as I have
        been able to
        gather, the only place they are really explained in detail is in
        chapters 2
        & 3 of the White Book, ?Statistical Models in S?. Unfortunately,
        I do not
        have ready access to a major research library and I have way,
        way outspent
        my book budget. Someday I?ll probably buy a copy, but for the
        time being, I
        am stuck without it. So it would be great to have a piece of
        code that uses
        them explained in detail.

        Warmest regards to all,  andrewH




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