[R] "Copy-pastable" output of 1000 plus variables

[BR_email]

David:
Sorry, of course I will show you the code:
Copy-Pasteable
PROC CONTENTS data=IN
out = vars (keep = name type) noprint;
run;
PROC SQL noprint;
select name into :varlist_is_here separated by ’ ’ from vars;
quit;
%put _global_ ;

Bruce Ratner, Ph.D.
The Significant Statistician™
(516) 791-3544
Statistical Predictive Analtyics -- www.DMSTAT1.com
Machine-Learning Data Mining and Modeling -- www.GenIQ.net
  

David Winsemius wrote:
> I don't have a lot of interest in trying to replicate operations in SAS.
>
> If you don't exhibit the willingness to show code in R then ... best of luck. But do read the Posting Guide to at least understand the local expectations.
>
> Good luck;
> David
>
> Sent from my iPhone
>
>> On Apr 23, 2017, at 5:26 PM, David L Carlson <dcarlson at tamu.edu> wrote:
>>
>> This might work for you:
>>
>> cols <- LETTERS # actually this will be cols <- colnames(df) in your example
>> # Create a data frame to select columns
>> choose <- data.frame(cols, select=0, stringsAsFactors=FALSE)
>> # Run the editor and replace 0 with 1 in the select column
>> # for each variable you wish to include
>> fix(choose)
>> # Your list of variables will be the vector mycols
>> mycols <- choose$cols[choose$select==1]
>>
>>
>> David L. Carlson
>> Department of Anthropology
>> Texas A&M University
>>
>> -----Original Message-----
>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of BR_email
>> Sent: Sunday, April 23, 2017 3:47 PM
>> To: Jeff Newmiller <jdnewmil at dcn.davis.ca.us>; r-help at r-project.org
>> Subject: Re: [R] "Copy-pastable" output of 1000 plus variables
>>
>> Jeff:
>> Thanks, Please see my reply to David.
>> Bruce
>>
>> Bruce Ratner, Ph.D.
>> The Significant Statistician™
>> (516) 791-3544
>> Statistical Predictive Analtyics -- www.DMSTAT1.com
>> Machine-Learning Data Mining and Modeling -- www.GenIQ.net
>>
>>
>> Jeff Newmiller wrote:
>>> Coming from an Excel background, copying and pasting seems attractive, but it does not create a reproducible record of what you did so it becomes quite tiring and frustrating after some time has passed and you return to your analysis.
>>>
>>> Nitpick: you put the setdiff function in the row selection position, an error I am sure Hadley did not recommend.
>>>
>>> Since R is programmable, there are far more ways to select columns than just setdiff. Since your description of desired features is vague, you are unlikely to get the answer you would really like from your email. Some possibilities to think about:
>>>
>>> a) use regular expressions and grep or grepl to select by similar character patterns. E.g. all columns including the the substring "value" or "key": grep( "key|value", names( dta ). Possible to specify very complex selection patterns, but there are whole books on regular expressions, so you can't expect to learn all about them on this R-specific mailing list.
>>>
>>> b) use a separate csv file with a column listing each column name, and then one column for each subset you want to define, using TRUE/FALSE values to include or not include the column name identified. E.g.
>>>
>>> # typically easier to manage in an external data f
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