[R] R-question

Greg Snow Greg.Snow at intermountainmail.org
Wed Sep 13 18:52:00 CEST 2006


I don't believe that doing a direct SQL query on a native R object is currently possible, others have pointed out ways to do some of the things you would want SQL for using built-in R commands.

If you really want to use SQL you could transfer the data frames you want to use to database tables, then query those and return the result.  You may want to look at the RSQLite and SQLiteDF packages that would help with these steps without requiring any database setup outside of R.

It probably not be too much work to write a function that would take an SQL query as a string and a list of data frames as arguments, copy the data frames to SQLite tables (SQLiteDF function sql.data.frame does this), then submit the query on those data frames (using RSQLite package) and return the result.

Hope this helps, 


-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at intermountainmail.org
(801) 408-8111
 

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Thorsten Muehge
Sent: Wednesday, September 13, 2006 4:18 AM
To: r-help at stat.math.ethz.ch
Subject: [R] R-question



Hello Colleagues,
I programmed in SAS for 3 years and would like to switch to a not so costly software product.

Hence I started to evaluate R, and my first test look promising.

However I have some question:

1. Is it possible to query R files by SQL internally on data frames (not on a database) and how is the syntax (I have the RODBC package installed).

I would like to extract year, Quarter, week, from a date column in a data frame (see attachment). After this I want to attach the column to the original data frame.

How do I do this in R?

Dr .Th.Mühge,

PMP®
Procurement Technology Center
IBM Deutschland GmbH, Hechtsheimer Str.2, D-55131 Mainz
Phone: xx49-(0)6131-84-2416
Mobile: xx49-(0)15117457978
e-mail: muehge at de.ibm.com
(See attached file: Debug1.csv)



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