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elwayfan446
Barite | Level 11

Hello,

 

I have recently been researching ways to come up with some basic statistics for the variable data in my datasets.  I found code that works well for me in THIS article by Rick Wicklin using proc iml.  I had some questions about his code but he is referring questions to this forum.  I want to take the following code that he used as an example in the blog and modify it to only pull back the variables I need.  Currently, it pulls back the statistics for all variables in the dataset.  I also am confused on how I would then export this to a dataset.  Could someone point me in the right direction on both of these questions?

 

proc iml;
use work.datagapanalysis;
read all var _NUM_ into x[colname=nNames]; 
n = countn(x,"col");
nmiss = countmiss(x,"col");
 
read all var _CHAR_ into x[colname=cNames]; 
close work.datagapanalysis;
c = countn(x,"col");
cmiss = countmiss(x,"col");
 
/* combine results for num and char into a single table */
Names = cNames || nNames;
rNames = {"    Missing", "Not Missing"};
cnt = (cmiss // c) || (nmiss // n);
print cnt[r=rNames c=Names label=""];
2 REPLIES 2
Rick_SAS
SAS Super FREQ

Instead of 

read all var _NUM_ into x[colname=nNames];

use

nNames = {"var1" "var2" "var3"};
read all var nNames into x;

 Similarly, use

cNames = {"othervar1" "othervar2"};
read all var cNames into x;

 After you have formed the 'cnt' matrix, use the techniques in the article http://blogs.sas.com/content/iml/2011/04/18/writing-data-from-a-matrix-to-a-sas-data-set.html"Writing data from a matrix to a SAS data set."

elwayfan446
Barite | Level 11

Thank you Rick.  I will give this a try!

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