R help - Jan 2008 - things that are difficult/impossible to do in SAS or SPSSbut simple in R

Good morning,

I use SAS and R/S-Plus as my primary tools so I have a lot of experience with
these programs.  By far and away, SAS is superior for handling the
"messy" datasets, but also the very large ones.  I work at times with
datasets in the hundreds of thousands (and on occasion, millions) of records. 
SAS, and especially PROC SQL, are invaluable for this.  But once I get to
datasets manageable for R/S-Plus, then I ship to these tools for the programming
and graphics.  This seems to work great.

Walt Paczkowski
Data Analytics Corp.


-----Original Message-----
>From: Rob Robinson <rob.robinson at bto.org>
>Sent: Jan 17, 2008 4:31 AM
>To: r-help at stat.math.ethz.ch
>Subject: Re: [R] things that are difficult/impossible to do in SAS or
SPSSbut simple in R
>
>
>I wonder if those who complain about SAS as a programming environment have
>discovered SAS/IML which provides a programming environment akin to Matlab
>which is more than capable (at least for those problems which can be treated
>with a matrix like approach). As someone who uses both SAS and R - graphical
>output is so much easier in R, but for handling large 'messy'
datasets SAS
>wins hands down...
>Cheers
>Rob
>
>*** Want to know about Britain's birds? Try  www.bto.org/birdfacts ***
>
>Dr Rob Robinson, Senior Population Biologist
>British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU
>Ph: +44 (0)1842 750050         E: rob.robinson at bto.org
>Fx: +44 (0)1842 750030         W: http://www.bto.org
>
>==== "How can anyone be enlightened, when truth is so poorly lit"
====>
>
>> -----Original Message-----
>> From: r-help-bounces at r-project.org 
>> [mailto:r-help-bounces at r-project.org] On Behalf Of Jeffrey J.
Hallman
>> Sent: 16 January 2008 22:38
>> To: r-help at stat.math.ethz.ch
>> Subject: Re: [R] things that are difficult/impossible to do 
>> in SAS or SPSSbut simple in R
>> 
>> SAS has no facilities for date arithmetic and no easy way to 
>> build it yourself.  In fact, that's the biggest problem with 
>> SAS: it stinks as a programming environment, so it's always 
>> much more difficult than it should be to do something new.  
>> As soon as you get away from the canned procs and have to 
>> write something of your own, SAS falls down.
>> 
>> I don't know enough about SPSS to comment.
>> --
>> Jeff
>> 
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide 
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>______________________________________________
>R-help at r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.

Walter Paczkowski wrote:
> Good morning,
> 
> I use SAS and R/S-Plus as my primary tools so I have a lot of experience
with these programs.  By far and away, SAS is superior for handling the
"messy" datasets, but also the very large ones.  I work at times with
datasets in the hundreds of thousands (and on occasion, millions) of records. 
SAS, and especially PROC SQL, are invaluable for this.  But once I get to
datasets manageable for R/S-Plus, then I ship to these tools for the programming
and graphics.  This seems to work great.
> 
> Walt Paczkowski
> Data Analytics Corp.
Previously I used SAS for 23 years and now R/S-Plus for 17.  SAS is 
effective for large datasets (in my work > 500,000 subjects) but except 
for that, R is far superior to SAS for data management and manipulation. 
  Just four of the reasons are that you can

- merge data frames multiple ways and compare the results
- deal with arrays (lists) of datasets using high-level operators
- easily do complex calculations on serial data such as find the highest 
blood pressure per subject that is measured before something else is 
measured
- sense the type of a variable (character, factor, date, discrete 
numeric, continuous numeric, etc.) while analyzing it, and tailor the 
analysis to the type of variable

http://biostat.mc.vanderbilt.edu/twiki/pub/Main/RS/sintro.pdf has a 
large section on data manipulation in S.

Frank
> 
> 
> -----Original Message-----
>> From: Rob Robinson <rob.robinson at bto.org>
>> Sent: Jan 17, 2008 4:31 AM
>> To: r-help at stat.math.ethz.ch
>> Subject: Re: [R] things that are difficult/impossible to do in SAS or
SPSSbut simple in R
>>
>>
>> I wonder if those who complain about SAS as a programming environment
have
>> discovered SAS/IML which provides a programming environment akin to
Matlab
>> which is more than capable (at least for those problems which can be
treated
>> with a matrix like approach). As someone who uses both SAS and R -
graphical
>> output is so much easier in R, but for handling large 'messy'
datasets SAS
>> wins hands down...
>> Cheers
>> Rob
>>
>> *** Want to know about Britain's birds? Try  www.bto.org/birdfacts
***
>>
>> Dr Rob Robinson, Senior Population Biologist
>> British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU
>> Ph: +44 (0)1842 750050         E: rob.robinson at bto.org
>> Fx: +44 (0)1842 750030         W: http://www.bto.org
>>
>> ==== "How can anyone be enlightened, when truth is so poorly
lit" ====>>
>>
>>> -----Original Message-----
>>> From: r-help-bounces at r-project.org 
>>> [mailto:r-help-bounces at r-project.org] On Behalf Of Jeffrey J.
Hallman
>>> Sent: 16 January 2008 22:38
>>> To: r-help at stat.math.ethz.ch
>>> Subject: Re: [R] things that are difficult/impossible to do 
>>> in SAS or SPSSbut simple in R
>>>
>>> SAS has no facilities for date arithmetic and no easy way to 
>>> build it yourself.  In fact, that's the biggest problem with 
>>> SAS: it stinks as a programming environment, so it's always 
>>> much more difficult than it should be to do something new.  
>>> As soon as you get away from the canned procs and have to 
>>> write something of your own, SAS falls down.
>>>
>>> I don't know enough about SPSS to comment.
>>> --
>>> Jeff

> Previously I used SAS for 23 years and now R/S-Plus for 17.  SAS is
> effective for large datasets (in my work > 500,000 subjects) but except
> for that, R is far superior to SAS for data management and manipulation.
>   Just four of the reasons are that you can
>
> - merge data frames multiple ways and compare the results
> - deal with arrays (lists) of datasets using high-level operators
> - easily do complex calculations on serial data such as find the highest
> blood pressure per subject that is measured before something else is
> measured
> - sense the type of a variable (character, factor, date, discrete
> numeric, continuous numeric, etc.) while analyzing it, and tailor the
> analysis to the type of variable
And one more:

 * you can trust that R will do the correct thing with missing values
(propagate them by default)

Hadley


-- 
http://had.co.nz/

The argument for SAS (and Stata) when working with large dataset comes 
up fairly often.  I have not had much experience in this area, but have 
been pleasantly surprised using R in combination with an SQL interface, 
in situations with modestly large, messy datasets.  I certainly would 
appreciate comments on the relative merits from anyone that has more 
experience in this area.

Paul Gilbert

Walter Paczkowski wrote:
> Good morning,
> 
> I use SAS and R/S-Plus as my primary tools so I have a lot of experience
with these programs.  By far and away, SAS is superior for handling the
"messy" datasets, but also the very large ones.  I work at times with
datasets in the hundreds of thousands (and on occasion, millions) of records. 
SAS, and especially PROC SQL, are invaluable for this.  But once I get to
datasets manageable for R/S-Plus, then I ship to these tools for the programming
and graphics.  This seems to work great.
> 
> Walt Paczkowski
> Data Analytics Corp.
> 
> 
> -----Original Message-----
> 
>>From: Rob Robinson <rob.robinson at bto.org>
>>Sent: Jan 17, 2008 4:31 AM
>>To: r-help at stat.math.ethz.ch
>>Subject: Re: [R] things that are difficult/impossible to do in SAS or
SPSSbut simple in R
>>
>>
>>I wonder if those who complain about SAS as a programming environment
have
>>discovered SAS/IML which provides a programming environment akin to
Matlab
>>which is more than capable (at least for those problems which can be
treated
>>with a matrix like approach). As someone who uses both SAS and R -
graphical
>>output is so much easier in R, but for handling large 'messy'
datasets SAS
>>wins hands down...
>>Cheers
>>Rob
>>
>>*** Want to know about Britain's birds? Try  www.bto.org/birdfacts
***
>>
>>Dr Rob Robinson, Senior Population Biologist
>>British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU
>>Ph: +44 (0)1842 750050         E: rob.robinson at bto.org
>>Fx: +44 (0)1842 750030         W: http://www.bto.org
>>
>>==== "How can anyone be enlightened, when truth is so poorly
lit" ====>>
>>
>>
>>>-----Original Message-----
>>>From: r-help-bounces at r-project.org 
>>>[mailto:r-help-bounces at r-project.org] On Behalf Of Jeffrey J.
Hallman
>>>Sent: 16 January 2008 22:38
>>>To: r-help at stat.math.ethz.ch
>>>Subject: Re: [R] things that are difficult/impossible to do 
>>>in SAS or SPSSbut simple in R
>>>
>>>SAS has no facilities for date arithmetic and no easy way to 
>>>build it yourself.  In fact, that's the biggest problem with 
>>>SAS: it stinks as a programming environment, so it's always 
>>>much more difficult than it should be to do something new.  
>>>As soon as you get away from the canned procs and have to 
>>>write something of your own, SAS falls down.
>>>
>>>I don't know enough about SPSS to comment.
>>>--
>>>Jeff
>>>
>>>______________________________________________
>>>R-help at r-project.org mailing list
>>>https://stat.ethz.ch/mailman/listinfo/r-help
>>>PLEASE do read the posting guide 
>>>http://www.R-project.org/posting-guide.html
>>>and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>______________________________________________
>>R-help at r-project.org mailing list
>>https://stat.ethz.ch/mailman/listinfo/r-help
>>PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>>and provide commented, minimal, self-contained, reproducible code.
> 
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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So how does SAS compare with one of the specialty languages such as perl.
I've found the combination of perl and R to work quite satisfactorily (as
long as I don't confuse the syntax and functions available in each.)

Clint

Clint Bowman			INTERNET:	clint at ecy.wa.gov
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On Thu, 17 Jan 2008, Walter Paczkowski wrote:
> Good morning,
>
> I use SAS and R/S-Plus as my primary tools so I have a lot of experience
with these programs.  By far and away, SAS is superior for handling the
"messy" datasets, but also the very large ones.  I work at times with
datasets in the hundreds of thousands (and on occasion, millions) of records. 
SAS, and especially PROC SQL, are invaluable for this.  But once I get to
datasets manageable for R/S-Plus, then I ship to these tools for the programming
and graphics.  This seems to work great.
>
> Walt Paczkowski
> Data Analytics Corp.
>
>
> -----Original Message-----
> >From: Rob Robinson <rob.robinson at bto.org>
> >Sent: Jan 17, 2008 4:31 AM
> >To: r-help at stat.math.ethz.ch
> >Subject: Re: [R] things that are difficult/impossible to do in SAS or
SPSSbut simple in R
> >
> >
> >I wonder if those who complain about SAS as a programming environment
have
> >discovered SAS/IML which provides a programming environment akin to
Matlab
> >which is more than capable (at least for those problems which can be
treated
> >with a matrix like approach). As someone who uses both SAS and R -
graphical
> >output is so much easier in R, but for handling large 'messy'
datasets SAS
> >wins hands down...
> >Cheers
> >Rob
> >
> >*** Want to know about Britain's birds? Try  www.bto.org/birdfacts
***
> >
> >Dr Rob Robinson, Senior Population Biologist
> >British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU
> >Ph: +44 (0)1842 750050         E: rob.robinson at bto.org
> >Fx: +44 (0)1842 750030         W: http://www.bto.org
> >
> >==== "How can anyone be enlightened, when truth is so poorly
lit" ====> >
> >
> >> -----Original Message-----
> >> From: r-help-bounces at r-project.org
> >> [mailto:r-help-bounces at r-project.org] On Behalf Of Jeffrey J.
Hallman
> >> Sent: 16 January 2008 22:38
> >> To: r-help at stat.math.ethz.ch
> >> Subject: Re: [R] things that are difficult/impossible to do
> >> in SAS or SPSSbut simple in R
> >>
> >> SAS has no facilities for date arithmetic and no easy way to
> >> build it yourself.  In fact, that's the biggest problem with
> >> SAS: it stinks as a programming environment, so it's always
> >> much more difficult than it should be to do something new.
> >> As soon as you get away from the canned procs and have to
> >> write something of your own, SAS falls down.
> >>
> >> I don't know enough about SPSS to comment.
> >> --
> >> Jeff
> >>
> >> ______________________________________________
> >> R-help at r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide
> >> http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >
> >______________________________________________
> >R-help at r-project.org mailing list
> >https://stat.ethz.ch/mailman/listinfo/r-help
> >PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> >and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>