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<title>Snipplr</title>
<link>http://snipplr.com/language/sas/tags/delete</link>
<description>Recent snippets posted on Snipplr.com</description>
<language>en-us</language>
<pubDate>Sat, 25 May 2013 00:05:12 GMT</pubDate>
<item>
<title>(SAS) How to delete previously assigned formats and informats of variables in the dataset - sarathannapareddy</title>
<link>http://snipplr.com/view/18187/how-to-delete-previously-assigned-formats-and-informats-of-variables-in-the-dataset/</link>
<description><![CDATA[ <p>How to delete previously assigned formats and informats completely from the SAS dataset:

PROC DATASETS lib=work;
MODIFY dsn;
FORMAT _all_;
INFORMAT _all_;
RUN; 
QUIT;</p> ]]></description>
<pubDate>Tue, 11 Aug 2009 16:26:20 GMT</pubDate>
<guid>http://snipplr.com/view/18187/how-to-delete-previously-assigned-formats-and-informats-of-variables-in-the-dataset/</guid>
</item>
<item>
<title>(SAS) Clean-up: Delete temporary Datasets in work directory - sarathannapareddy</title>
<link>http://snipplr.com/view/15923/cleanup-delete-temporary-datasets-in-work-directory/</link>
<description><![CDATA[ <p>It is better always to clean-up/empty the work directory before we run the next set of SAS code. This is VERY helpful in situations where the “working” files created tend to use up a large amount of memory, once the logic of the program has been checked, KILLing the working files will result in a more efficient program. Another important reason to issue the above statement at the end of a program is when programs are run in batch, this will clean up the working library to be sure any “old” files are not left around to be erroneously used1.</p> ]]></description>
<pubDate>Sun, 14 Jun 2009 12:28:58 GMT</pubDate>
<guid>http://snipplr.com/view/15923/cleanup-delete-temporary-datasets-in-work-directory/</guid>
</item>
<item>
<title>(SAS) Delete observations containing characters and keep numeric values only - webonomic</title>
<link>http://snipplr.com/view/11572/delete-observations-containing-characters-and-keep-numeric-values-only/</link>
<description><![CDATA[ <p>How to delete observations containing characters (e.g. 92z89 or abcd) and only keep the ones with numeric values.</p> ]]></description>
<pubDate>Tue, 27 Jan 2009 12:28:57 GMT</pubDate>
<guid>http://snipplr.com/view/11572/delete-observations-containing-characters-and-keep-numeric-values-only/</guid>
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