Use arrays and iterative DO loops to determine whether there are missing values across an observation. Delete the observation when a missing value is found.

Please click on the Full Code and Output tabs to see the sample and the output.

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These sample files and code examples are provided by SAS Institute Inc. "as is" without warranty of any kind, either express or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Recipients acknowledge and agree that SAS Institute shall not be liable for any damages whatsoever arising out of their use of this material. In addition, SAS Institute will provide no support for the materials contained herein.

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/* Create sample data */

data testdata;                  
input ch1 $ ch2 $ num1 num2 num3;      
datalines;                      
aaa bbb 1 2 3             
. bbb 1 1 1               
. . . . .             
aaa bbb 1 1 1            
aaa bbb 1 . 2               
aaa . 1 1 .             
;    
run;

data nomiss;                    
set testdata;   

/* Use the reserved word _NUMERIC_ to load all numeric variables  */
/* into the NUM array.  Use the reserved word _CHARACTER_ to      */ 
/* to load all character variables into the CHR array.            */

array chr(*) _character_;      
array num(*) _numeric_;    

/* Check for missing values and delete when found. */ 

do i = 1 to dim(chr);          
 if missing(chr(i)) then delete;    
end;                            
do j = 1 to dim(num);           
 if missing(num(j)) then delete;       
end;                               
drop i j;  
run;
 
proc print;                     
run;                         

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These sample files and code examples are provided by SAS Institute Inc. "as is" without warranty of any kind, either express or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Recipients acknowledge and agree that SAS Institute shall not be liable for any damages whatsoever arising out of their use of this material. In addition, SAS Institute will provide no support for the materials contained herein.

Obs    ch1    ch2    num1    num2    num3

 1     aaa    bbb      1       2       3
 2     aaa    bbb      1       1       1

This sample shows how to delete observations from a data set when at least one variable value across the observation is missing.

Type:

Sample

Date Modified:	2011-02-08 10:18:03
Date Created:	2011-02-03 09:07:24

Operating System and Release Information

Product Family	Product	Host	SAS Release
			Starting	Ending
SAS System	Base SAS	z/OS
		Z64
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		Microsoft® Windows® for 64-Bit Itanium-based Systems
		Microsoft Windows Server 2003 Datacenter 64-bit Edition
		Microsoft Windows Server 2003 Enterprise 64-bit Edition
		Microsoft Windows XP 64-bit Edition
		Microsoft® Windows® for x64
		OS/2
		Microsoft Windows 95/98
		Microsoft Windows 2000 Advanced Server
		Microsoft Windows 2000 Datacenter Server
		Microsoft Windows 2000 Server
		Microsoft Windows 2000 Professional
		Microsoft Windows NT Workstation
		Microsoft Windows Server 2003 Datacenter Edition
		Microsoft Windows Server 2003 Enterprise Edition
		Microsoft Windows Server 2003 Standard Edition
		Microsoft Windows Server 2003 for x64
		Microsoft Windows Server 2008
		Microsoft Windows Server 2008 for x64
		Microsoft Windows XP Professional
		Windows 7 Enterprise 32 bit
		Windows 7 Enterprise x64
		Windows 7 Home Premium 32 bit
		Windows 7 Home Premium x64
		Windows 7 Professional 32 bit
		Windows 7 Professional x64
		Windows 7 Ultimate 32 bit
		Windows 7 Ultimate x64
		Windows Millennium Edition (Me)
		Windows Vista
		Windows Vista for x64
		64-bit Enabled AIX
		64-bit Enabled HP-UX
		64-bit Enabled Solaris
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		AIX
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		IRIX
		Linux
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		Tru64 UNIX