[R] MySQL + R as a Replacement for SAS Proc SQL + Various Stat Procs

[Wensui Liu]

Hi, there,
it seems size of your data is very manageable in R.
i've been using proc sql in SAS a lot and found sqldf package is very
similar to proc sql. check it out.
one more thought. instead of using R as scripting lang. to process
data, it might be worthy to take a look at python.

On Jan 18, 2008 11:10 PM,  <JWilliamson at lecg.com> wrote:
>
> For cost reasons, I'd like to replace SAS on my PC under Win XP Pro.
>
> Nearly all my work involves medium-size datasets (100k-10M) records which I
> cleanup, relate, fliter and get into shape for analysis using SAS/SQL
> followed by standard statistical procedures, e.g. regression using SAS proc
> reg.
>
> It seems to me that this type of analysis could be done in MySQL followed
> by R, but I'd like some advice about the best way to pass datasets from
> MySQL to R.  I understand there are various connectivity packages
> avaialble, RODBC and RMySQL, but I'd appreciate some advice about where to
> dig in first.
>
> I'd like to avoid additional syntax in my SQL code -- so it seems better
> not to coat SQL queries in R wrappers and pass them to MySQL -- probably
> better for my way of working to finish all the SQL work and pass a clean
> table ready to analyze to R.
>
> One of the great advantages for me using SAS is that I can beat the data
> into shape using proc SQL and then call proc STAT_OF_THE_DAY all in the
> same batch file with no plumbing, data conversion or additional
> machination.
>
> But if I could do this in MySQL + R, well in a few years I'd have the down
> payment for an Audi TT instead of having given it to SAS Institute.
>
> If someone found a practical way to make this work -- pls let me know.  And
> thanks in advance.
>
> Jack Williamson
> LECG
> 2049 Century Park East, Suite 2300
> Los Angeles CA 90067
> 323-683-5004
> jwilliamson at lecg.com
>
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>



-- 
===============================
WenSui Liu
Statistical Project Manager
ChoicePoint Precision Marketing
(http://spaces.msn.com/statcompute/blog)