Combining (with SQL) HRP223 – 2013 October 30, 2013 Copyright © 1999-2013 Leland Stanford Junior University. All rights reserved. Warning: This presentation is protected by copyright law and international treaties. Unauthorized reproduction of this presentation, or any portion of it, may result in severe civil and criminal penalties and will be prosecuted to maximum extent possible under the law.

PROC SQL - Set Operators NO GUI (“noh gooey”) Outer Union Corresponding concatenates Unions unique rows from both queries Except rows that are part of first query Intersect rows common to both queries

outer union corresponding You can concatenate data files. I rarely use it. proc sql; create table isOuter as select dude from baseline outer union corresponding select dude from followup; quit;

union You can also concatenate data files and keep unique records: proc sql; create table isUnion as select dude from baseline union select dude from followup; quit;

except Say you needed everyone who did not come back. Start out with the baseline group and remove the people who came back. proc sql; select id from baseline except select id from followup; quit;

intersect Say you wanted to know who came back. In other words, what IDs are in both files? proc sql; select id from baseline intersect select id from followup; quit;

PROC SQL - Set Operators When you have tables (with more than one column) with the same structure, you can combine them with these set operators. Be extremely careful because SAS/SQL is forgiving about the structure of the tables and you may not notice problems in the data. For this to work as intended, the two tables must have the same variables, in the same order, and the variables must be of the same type (variables with the same name must both be character or both be numeric). Use the key word corresponding to have it match like-named variables.

corresponding The columns do not need to have matching names or even the same length and it will still operate on them. Use corresponding to help spot this problem. data fName; firstName = "Raymond"; run; data lName; lastName = "Balise"; proc sql; create table name as select firstName from fName union select lastName from lName ; quit; *create table name as union corresponding

Working with Repeated Keys A file tracking diagnoses or treatments will have multiple records for some people. If you want to count the number of records for a person, specify what variable(s) are used to group by. Count records in the group with count(*) or count not missing values with count(variableName) data dx; input id dxCode; datalines; 1 42 1 17 2 42 3 2 3 42 3 . 3 .A ; proc sql; create table counts as select id, count(*) as countRecords, count(dxCode) as countDx, count(distinct(dxCode)) as cntDistDx from dx group by id quit;

Notice count drops all flavors of missing data. Other Counts You can also count the type of not missing values with count(distinct(variableName)) Notice count drops all flavors of missing data.

If you have too much time on your hands If you have too much time on your hands ... you can use the GUI to sort the data and count by hand.

You can also use the GUI to do the counts