Overview

This sample shows how to use the complev function to compare and find strings that are similar, but not an exact match. This is sometimes called a "fuzzy merge". SAS provides several string comparison functions, including

• compare
• soundex
• compged
• complev
• spedis

For the compged, complev and spedis functions, the programmer needs to determine what is an acceptable cost or distance between the strings to determine they are a possible match. See the documentation for more information.

Additional Documentation

Documentation for BASE SAS Functions

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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 data set of valid magazine names.*/
data mags;
input title $char30.;
datalines;
Science 
Discover
Nature Today
Journal of Medicine
Outside
;
run;

/*Create data set of articles with magazine name.  Some of the magazine names are not quite correct.*/
data articles;
infile datalines dlm=',';
input magtitle :$30. article :$30.;
datalines;
Science, Bears
Sciene, Cats
Sciences, Dogs
Discovery, Stars
Discover, Planets
Outdoors, Hiking
;

/*Generate two output data sets: MATCH if the magazine names are an exact match and */
/*CLOSE if the distance between the magazine names is within the value we have set.*/

/*First, we read in all the correct magazine titles from the MAGS data set into an array.*/
/*Then we read through each observation in the data set ARTICLES.  If the magazine names*/
/*are an exact match, we output to MATCH and stop checking for a magazine.  If COMPLEV returns*/
/*a distance of less than or equal to 5 (chosen arbitrarily to get matches we consider*/
/*"close enough"), then the observation is written to the CLOSE data set.*/

data match (keep = magtitle article) 
close (keep=distance magtitle possible_mag article);
array mags[5] $20 _temporary_;
do until (done);
	set mags end=done;
	count+1;
	mags[count] = title;
end;

do until (checkdone);
	set articles end=checkdone;
	do i = 1 to dim(mags);
		distance = complev(magtitle, mags[i],'iln');
		if distance=0 then do;
			output match;
			leave;
		end;
		else if distance <= 5 then do;
			possible_mag = mags[i];
			output close;
		end;
	end;
end;
stop;
run;

          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.
        

Data set MATCH:

                                   Obs    magtitle    article

                                    1     Science     Bears
                                    2     Discover    Planets


Data set CLOSE:
                                                                 possible_
                      Obs    magtitle     article    distance       mag

                       1     Sciene       Cats           1       Science
                       2     Sciences     Dogs           1       Science
                       3     Discovery    Stars          1       Discover
                       4     Outdoors     Hiking         5       Outside