SAS Certification Handout #9: Adv. Prog. Ch. 3-4

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1 SAS Certification Handout #9: Adv. Prog. Ch. 3-4 /************ Ch. 3 ********************/ /* First, make example data -- similar to Handout #8 */ libname cert 'C:/jrstevens/Teaching/SAS_Cert/AdvNotes'; /* In SAS Studio, after creating SAS_Cert folder with username jrstevens: libname cert '/home/jrstevens/sas_cert'; */ /* sales9 */ data cert.sales9; format LastName $9. Sales dollar8.; input LastName $ EmplID Division $ Sales; cards; Smith 315 A Nelson 333 A Uribe 612 C Larson 331 B Larsen 216 B Rasmussen 217 A Knecht 861 B D'Angelou 772 A Larson 331 C ; proc print data=cert.sales9; run; /* salary9 */ data cert.salary9; format Salary dollar8.; input ID Salary; cards; ; proc print data=cert.salary9; run; Obs LastName Sales EmplID Division 1 Smith $553, A 2 Nelson $555, A 3 Uribe $867, C 4 Larson $521, B 5 Larsen $123, B 6 Rasmussen $125, A 7 Knecht $983, B 8 D'Angelou $332, A 9 Larson $381, C Obs Salary ID 1 $54, $68, $89, $65, $62, $99, $123, $232, $34, $78,

2 /* Types of Horizontal Joins: Inner -- only rows in both tables; need WHERE or INNER JOIN... ON... */ Outer -- allow nonmatching rows from one or more tables; need [LEFT/RIGHT/FULL] JOIN... ON... /* All horizontal joins begin with a Cartesian product; here (9 rows in sales9)*(10 rows in salary9) --> 90 rows in Cartesian product */ select * from cert.sales9, cert.salary9; LastName Sales EmplID Division Salary ID Smith $553, A $54, Nelson $555, A $54, Uribe $867, C $54, Larson $521, B $54, Larsen $123, B $54, Rasmussen $125, A $54, Knecht $983, B $54, D'Angelou $332, A $54, Larson $381, C $54, D'Angelou $332, A $78, Larson $381, C $78, vs LastName Sales EmplID Division Salary ID Smith $553, A $65, Nelson $555, A $99, Uribe $867, C $34, Larson $521, B $62, Larsen $123, B $68, Rasmussen $125, A $89, Knecht $983, B $78, Larson $381, C $62, /* The 'optional' WHERE clause subsets */ select * from cert.sales9, cert.salary9 where sales9.emplid=salary9.id; 2

3 /* Can create table alias and use expressions in SELECT clause */ select CATX(":",s.division,s.EmplID) as DivID label='division:id', s.sales / y.salary as ratio label='sales per Salary Dollar' format=5.2 from cert.sales9 as s, cert.salary9 y /* table aliases */ where sales9.emplid=salary9.id order by DivID; Division:ID Sales per Salary Dollar A: A: A: B: B: B: C: C: /* LEFT/RIGHT/FULL joins -- see table on pp */ select * from cert.sales9 left join cert.salary9 on sales9.emplid=salary9.id; /* Compare to inner join using WHERE clause above */ LastName Sales EmplID Division Salary ID Larsen $123, B $68, Rasmussen $125, A $89, Smith $553, A $65, Larson $381, C $62, Larson $521, B $62, Nelson $555, A $99, Uribe $867, C $34, D'Angelou $332, A.. Knecht $983, B $78,

4 select * from cert.sales9 right join cert.salary9 on sales9.emplid=salary9.id; LastName Sales EmplID Division Salary ID.. $54, Larsen $123, B $68, Rasmussen $125, A $89, Smith $553, A $65, Larson $381, C $62, Larson $521, B $62, Nelson $555, A $99, $123, $232, Uribe $867, C $34, Knecht $983, B $78, select * from cert.sales9 full join cert.salary9 on sales9.emplid=salary9.id; LastName Sales EmplID Division Salary ID.. $54, Larsen $123, B $68, Rasmussen $125, A $89, Smith $553, A $65, Larson $381, C $62, Larson $521, B $62, Nelson $555, A $99, $123, $232, Uribe $867, C $34, D'Angelou $332, A.. Knecht $983, B $78,

5 /* COALESCE -- to force overlay of common columns from two tables (only matters when have some non-matching rows) */ select coalesce(s.emplid, y.id) as newid, LastName, sales, salary from cert.sales9 as s full join cert.salary9 as y on s.emplid=y.id; /* p. 110 table summarizes how SQL queries Are more flexible than DATA step match-merging: (1) don't need sorted/indexed data sets; (2) don't need same-named columns; (3) can join with other than equal (=) comparison -- e.g., could use WHERE s.emplid > y.id (if it made sense) */ newid LastName Sales Salary 125. $54, Larsen $123,513 $68, Rasmussen $125,321 $89, Smith $553,312 $65, Larson $381,592 $62, Larson $521,592 $62, Nelson $555,827 $99, $123, $232, Uribe $867,159 $34, D'Angelou $332, Knecht $983,152 $78,912 /* (pp ) in-line view: a temporary (or virtual) table produced by a nested query inside FROM clause */ select ilv.divid, ss.lastname, ilv.ratio from cert.sales9 as ss, ( select CATX(":",s.division,s.EmplID) as DivID label='division:id', s.sales / y.salary as ratio label='sales per Salary Dollar' format=5.2, s.emplid from cert.sales9 as s, cert.salary9 as y where sales9.emplid=salary9.id and Division='A' ) as ilv where ilv.emplid=ss.emplid; Division:ID LastName Sales per Salary Dollar A:315 Smith 8.48 A:333 Nelson 5.59 A:217 Rasmussen 1.40 /* p. 118 multi-way and reflexive join example shows efficiency of SQL queries over traditional SAS programming */ 5

6 /************ Ch. 4 ********************/ /* First, make example data; three medical clinics, sometimes patients visit all three clinics in a single day; A=low level, B=mid-level, C=critical care level*/ libname cert 'C:/jrstevens/Teaching/SAS_Cert/AdvNotes'; /* Visits to Clinic A */ data cert.a9; input patient date date7. heartrate; format date date7.; cards; May09 78 Obs patient May May May Apr Jun Jun Jun Jul09 87 ; proc print data=cert.a9; run; date heartrate MAY APR JUL09 87 /* Visits to Clinic B */ data cert.b9; input patient date date7. weight heartrate; format date date7.; cards; May Obs patient Jun Jun Jul Jul ; proc print data=cert.b9; run; date weight heartrate MAY JUN JUN JUL JUL /* Visits to Clinic C */ data cert.c9; input patient date date7. heartrate; format date date7.; cards; May09 87 Obs patient Jul09 99 ; proc print data=cert.c9; run; date heartrate MAY JUL

7 /* Ch. 4 key points: */ (p. 136) good visualization of vertical combination methods; EXCEPT, INTERSECT, UNION are true vertical combinations without regard to column names (so order of columns matters!); only OUTER UNION does not overlay columns (true concatenation). (p ) order of set operations is determined by parentheses; otherwise, INTERSECT before all others ALL - don't restrict to unique rows CORR - use (and overlay) same-named columns 7

8 /* (p. 140) EXCEPT */ except select * from cert.b9; /* (p. 142) EXCEPT ALL */ except all select * from cert.b9; heartrate APR JUL MAY heartrate APR JUL MAY /* (p ) EXCEPT CORR */ except corr select * from cert.b9; APR JUL MAY09 99 /* (p ) EXCEPT ALL CORR */ except all corr select * from cert.b9; /* NOTE that matching rows in second table only count once */ APR JUL MAY

9 /* (p. 147) INTERSECT */ intersect select * from cert.b9; /* (p ) INTERSECT ALL */ intersect all select * from cert.b9; /* (p ) INTERSECT CORR */ intersect corr select * from cert.b9; NOTE: No rows were selected. NOTE: No rows were selected. /* (p ) INTERSECT ALL CORR */ intersect corr all select * from cert.b9; /* NOTE that matching rows in second table only count once */ /* (p. 152) UNION */ union select * from cert.b9; heartrate APR JUN JUN JUL JUL MAY MAY JUL

10 /* (p. 153) UNION ALL */ union all select * from cert.b9; /* (p. 154) UNION CORR */ union corr select * from cert.b9; APR JUL JUL MAY JUL09 87 /* (p. 155) UNION ALL CORR */ union all corr select * from cert.b9; heartrate MAY APR JUL MAY JUN JUN JUL JUL MAY APR JUL JUL JUL

11 /* (p. 160) OUTER UNION [keeps all rows] */ outer union select * from cert.b9; patient date weight heartrate MAY APR JUL MAY JUN JUN JUL JUL /* (p. 161) OUTER UNION CORR [keeps all rows but overlays same-named columns] */ outer union corr select * from cert.b9; /* Combination: find patients who visited A and B, but not C, on the same day, regardless of whether they had the same measurements taken */ (select patient, date from cert.a9 intersect select patient, date from cert.b9) except select patient, date from cert.c9; patient date JUN09 weight MAY APR JUL JUL JUL