[R] R: Tools for thinking about data analysis and graphics

Jeffrey Spies jspies at virginia.edu
Thu Oct 7 06:04:15 CEST 2010


Hi, Michael,

When I teach/preach on R, I emphasize the language's focus on data,
both in its objects and operations. It might seems basic, but it's
fundamental to most of the features you and others have mentioned. As
a statistical programming language, what we intend to do with R is
often very naturally accomplished using vector operations on tabular
data, where columns represent variables of the same data type and rows
represent observations of these variables for a given member of the
dataset.  Fortunately, these are core components of R.  For instance,
we can easily perform complex selections of variables and/or members,
which, more often than not, serve as input to or power the functions
that generate the statistics and graphics we care about.
Unfortunately, vector operations seem to be difficult for people to
learn how to use properly, and there are penalties for not using them,
but as they say: no pain, no gain. :)

If you'd be willing to share the materials you create for your talk,
I'd be interested in seeing them.

Cheers,

Jeff.

On Wed, Oct 6, 2010 at 5:05 PM, Michael Friendly <friendly at yorku.ca> wrote:
>  I'm giving a talk about some aspects of language and conceptual tools for
> thinking about how
> to solve problems in several programming languages for statistical computing
> and graphics. I'm particularly
> interested in language features that relate to:
>
> o expressive power: ease of translating what you want to do into the results
> you want
> o elegance: how well does the code provide a simple human-readable
> description of what is done?
> o extensibility: ease of generalizing a method to wider scope
> o learnability: your learning curve (rate, asymptote)
>
> For R, some things to cite are (a) data and function objects, (b)
> object-oriented methods (S3 & S4); (c) function mapping over data with
> *apply methods and plyr.
>
> What other language features of R should be on this list?  I would welcome
> suggestions (and brief illustrative examples).
>
> -Michael
>
>
> --
> Michael Friendly     Email: friendly AT yorku DOT ca
> Professor, Psychology Dept.
> York University      Voice: 416 736-5115 x66249 Fax: 416 736-5814
> 4700 Keele Street    Web:   http://www.datavis.ca
> Toronto, ONT  M3J 1P3 CANADA
>
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