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Re: st: R Array [was: Mata for data management]


From   "Gabi Huiber" <ghuiber@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: R Array [was: Mata for data management]
Date   Fri, 1 Feb 2008 10:59:36 -0500

I can't think of any example, but up until last year I have been using
only Stata for all my data analysis needs, so I am biased. I can only
speculate that arrays accommodate a style of programming that's more
mainstream. I base this on a very brief tinkering experience. Last
summer I picked up R and PHP. Then I took an online class on C++
through my local community college. I didn't know much about computer
programming, so I didn't know what to expect, but I found all kinds of
common traits between these languages and they all had arrays; so I
just figured that arrays must be a general language construct because
R, PHP and C++ are not designed to do the same thing. So, once I got
to use arrays I liked them. If Stata offered them I could use them
here too, but I don't really miss them, if that's what you're getting
at. I have been using Stata for so long that its ways feel natural to
me.

Gabi

On Feb 1, 2008 10:02 AM, Scott Merryman <scott.merryman@gmail.com> wrote:
> Thanks.
>
> I guess, more concretely, what can be done (or preformed more
> efficiently) with an R array that cannot be done with Stata (-foreach-
> or -forv-)?
>
> Scott
>
>
> On Jan 31, 2008 9:44 PM, Gabi Huiber <ghuiber@gmail.com> wrote:
> > Oops. Thank you, Scott.
> >
> > An array is a general data object. It's a a vector when indexed by one
> > subscript, a matrix when indexed by two subscripts, or it can be
> > indexed by more than two subscripts. It can take numeric and character
> > elements. You can think of a numeric array A(i,j,k) as a list of i
> > matrices of (j,k) size. The ability to take non-numeric elements is
> > useless in statistics, but it's helpful in general data management.
> >
> > In Stata or SAS we think of data sets as tables with as many columns
> > as variables and as many rows as the largest number of non-missing
> > observations. This works for statistical analysis. General-purpose
> > programming languages (judging by the two I dabble in) seem to want
> > you to think of your data in terms of data objects -- scalars,
> > vectors, matrices, lists, etc. R is a statistical analysis programming
> > environment, but it stayed close to this general-purpose way of
> > dealing with data; maybe because its underlying language, S, was
> > invented by a computer scientist?
> >
> > Gabi
> >
> >
> > On Jan 31, 2008 10:14 PM, Scott Merryman <scott.merryman@gmail.com> wrote:
> > > On Jan 31, 2008 8:48 PM, Gabi Huiber <ghuiber@gmail.com> wrote:
> > > > I'm trying to cheat and speed things up a bit when dealing with a
> > > > bunch of files with names such as fileYYYYMMDD.dta. I could collect
> > > > the numeric part of the names in a column vector that starts with the
> > > > initial values a=J({potential number of files}, 1,0). But there is a
> > > > fair chance that my YYYYMMDD succession has gaps, so at the end of the
> > > > process this column vector will have some zeroes.
> > > >
> > > > I would like to do this:
> > > >
> > > > mata
> > > > a=sort(a,1)
> > > >
> > > > Then drop all the zero elements of a, and end up with a shorter
> > > > vector. But I can't find anything like "drop rows" in the Mata book or
> > > > Google. Any ideas?
> > >
> > > -select()- ?
> > >
> > > mata
> > > A = (1,2,3,4,0,5,6,0,0,7)
> > > A2 = select(A, A:>0)
> > > A2
> > > end
> > >
> > >
> > > > Generally, some R-like way to deal with arrays would be nice to have
> > > > in Mata or Stata.
> > >
> > > How do R arrays work?
> > >
> > > Scott
> > >
> >
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