You were very close. This will work:   data testpalmbeach17; set finalsii.palmbeachfinal17; exmpt_04_num = input(exmpt_04, best12.); drop exmpt_04; rename exmpt_04_num=exmpt_04; run; ... View more

Better sort the data and use first./last. to separate between the duplicates and the last one, for examle:   proc sort data=have; by parcel_d sale_mo /* month ? */ sale_prc; run; data ones dups; set have; by parcel_d sale_mo sale_prc; if last.sale_prc then output ones; else output dups; run; ... View more

You could try regular expressions   data foo; infile datalines delimiter=','; informat raw $varying1024.; input raw $; datalines; 3991 3rd ST ; run; proc sql; select prxchange('s/(\d+)(?: )(\w+)/$1/', -1, raw) as house_number ,prxchange('s/(\d+)(?: )(\w+)/$2/', -1, raw) as street from foo; quit; ... View more

This often better done in data profiling tools like Dataflux.   I have worked on address standardization but mostly through the hand written code. I used to do this on basis of business rules defined by stakeholders(regularly new rules were defined, say once in couple of months), it solved most of our problems but  was not enough ( this is what I strongly believe).    When I was in this project they allow me to use Dataflux, because I was told that running Dataflux on large datasets will take lot of time. I was using datasets close to 200 million records and was using explicit SQL pass through.   Below is paper on Dataflux, which you might find interesting   http://www2.sas.com/proceedings/sugi30/102-30.pdf ... View more

How are you importing your CSVs? Please post your code if you are using something like PROC IMPORT. ... View more

You could probably do an array. Not sure it's less code in the end, but easier to manage perhaps?   array min_pay(20:26) (50000 55000 60000 70000 ... 120000); array max_pay(20:26) (70000 75000 .. 200000); grade = input(compress(paygrade, ,'kd'), 8.); minimum = min_pay(grade); maximum = max_pay(grade); ... View more