PROC SQL: Tips and Translations for Data Step Users

By: Gail Jorgensen Susan Marcella

AGENDA

• SQL Syntax Review• Joins Translated• SQL Strengths & Uses

PROC SQL: Tips and Translations for Data Step UsersSyntax

Proc SQL; create table/view newdsname as select var1, var2, … varN

from dsname

where condition ;Quit;

PROC SQL: Tips and Translations for Data Step Users JOIN vs MERGE

Types of JOINs• Inner Join – selects only matching records

(same as: if ina and inb)

• Outer Join – selects some non-matching records– Left Join – selects all records from first table, only

matching records from second(same as: if ina)

– Right join – selects all records from second table, only matching records from first

(same as: if inb)

-- Full join – selects all records from both tables(same as having no if statement)

PROC SQL: Tips and Translations for Data Step UsersInner Join

proc sql; create table ds_c as select ds_a1.*, ds_b.* from ds_a1, ds_b where ds_a1.idfld = ds_b.idno;quit;

data c; merge ds_a1(in=ina) ds_b(in=inb rename=(idno=idfld)); by idfld; if ina and inb;run;

Dataset DS_A1 Dataset DS_BBidfld col2

1 M1 N

2 O3 P

4 Q5 R

idno col3 col41 X C2 X D2 Y F4 Z5 Z7 Z

idfld col2 idno col3 col41 M 1 X C1 N 1 X C2 O 2 X D2 O 2 Y F4 Q 4 Z5 R 5 Z

idfld col2 col3 col41 M X C1 N X C2 O X D2 O Y F4 Q Z5 R Z

PROC SQL: Tips and Translations for Data Step UsersLeft Join

idfld col2 col51 M A1 N D2 O3 P J4 Q K5 R N

proc sql; create table sql_left as select a.*, b.* from inf_a as a left join inf_b as b on a.idfld = b.idfld;quit;

data ds_left; merge inf_a(in=ina) inf_b(in=inb); by idfld; if ina ;run;

idfld col3 col41 X C2 X D2 Y F4 Z5 Z7 Z

Dataset inf_a Dataset inf_b

idfld col2 col5 col3 col41 N D X C

1 M A X C

2 O Y F

2 O X D

3 P J

4 Q K Z

5 R N Z

idfld col2 col5 col3 col41 N D X C1 M A X C2 O Y F2 O X D3 P J4 Q K Z5 R N Z

Dataset sql_left Dataset ds_left

PROC SQL: Tips and Translations for Data Step UsersRight Join

proc sql;

create table sql_right as

select a.*, b.*

from inf_a as a right join inf_b as b

on a.idfld = b.idfld;

quit;

data ds_right; merge inf_a(in=ina) inf_b(in=inb); by idfld; if inb;run;

idfld col2 col5 col3 col41 N D X C

1 M A X C

2 O Y F

2 O X D

4 Q K Z

5 R N Z

. Z

idfld col2 col5 col3 col41 M A X C

1 N D X C

2 O X D

2 O Y F

4 Q K Z

5 R N Z

7 Z

PROC SQL: Tips and Translations for Data Step Users Full Join

Obs name recd sent1 Amanda yes no

2 Gabi yes yes

3 Jan yes yes

4 Jim no yes

5 Pam no no

Obs name recd sent1 Alison yes yes

2 Jan yes yes

3 Pam no no

4 Tom yes yes

CList07CList08

proc sql;create table sql_clist asselect c7.name, c7.recd as recd07, c8.recd as recd08, c7.sent as sent07, c8.sent as sent08from clist07 as c7 full join clist08 as c8on c7.name=c8.name;quit;

proc sort data=clist07; by name; run;proc sort data=clist08; by name; run;data data_clist;merge clist07 clist08 (rename=(recd=recd08 sent=sent08));by name;run;

PROC SQL: Tips and Translations for Data Step Users Full Join (Con’t)

Obs Name recd07 recd08 sent07 sent081 yes yes

2 Amanda yes no

3 Gabi yes yes

4 Jan yes yes yes yes

5 Jim no yes

6 Pam no no no no

7 yes yes

Obs name recd sent recd08 sent081 Alison yes yes

2 Amanda yes no

3 Gabi yes yes

4 Jan yes yes yes yes

5 Jim no yes

6 Pam no no no no

7 Tom yes yes

Sql_CList Data_CList

PROC SQL: Tips and Translations for Data Step UsersHandling Duplicate Variable Names

To always select the variable from one dataset:– Drop unwanted version of variable

(PROC SQL permits all SAS dataset options)

– Select variable from specific table

To keep variable from both tables:– Rename the variable in one dataset

To select variable based on value:– Use CASE statement

PROC SQL: Tips and Translations for Data Step UsersCASE Statement

proc sql;create table NewCList asselect case when missing(c7.name) then c8.name

else c7.name end as name, c7.recd as recd07, c8.recd as recd08, c7.sent as sent07, c8.sent as sent08from clist07 as c7 full join clist08 as c8on c7.name=c8.name;quit;

proc sort data=clist07; by name; run;proc sort data=clist08; by name; run;data data_clist;merge clist07 clist08 (rename=(recd=recd08 sent=sent08));by name;run;

PROC SQL: Tips and Translations for Data Step UsersCASE Statement - Results

Obs name recd07 recd08 sent07 sent081 Alison yes yes

2 Amanda yes no

3 Gabi yes yes

4 Jan yes yes yes yes

5 Jim no yes

6 Pam no no no no

7 Tom yes yes

PROC SQL: Tips and Translations for Data Step UsersDown Calculations

PROC SORT data=shs.exposure; by subject_id; run;DATA counters(KEEP=TableName MAXOBS TOTOBS); SET shs.exposure END=LAST; BY subject_id;length TableName $ 50;RETAIN MAXOBS OBSCNTR TOTOBS 0;TableName=“exposure";TOTOBS+1;OBSCNTR+1;IF LAST.subject_id THEN DO; IF MAXOBS < OBSCNTR THEN MAXOBS=OBSCNTR; OBSCNTR=0;END;IF LAST THEN OUTPUT chemcnts;label maxobs='Maximum number of obs per person' totobs='Total Number obs in table';run;proc print data=counters;run;

Obs TableName MAXOBS TOTOBS

1 exposure 14 2124

PROC SQL: Tips and Translations for Data Step UsersDown Calculations

proc sql;create table sqlcounter asselect distinct subject_id, count(*) as subjcntfrom fshs.exposuregroup by subject_id;

select “exposure" as TableName, max(subjcnt) as MaxObs, sum(subjcnt) as TotObsfrom sqlcounter;quit;

TableName MaxObs TotObs

exposure 14 2124

Obs subject_id subjcnt

1 178 7

2 306 1

3 307 1

4 308 1

5 326 3

6 330 1

7 331 1

8 332 1

sqlcounter

PROC SQL: Tips and Translations for Data Step UsersCounts and Nesting Queries

proc sql;select distinct genre, count(*)from itunesgroup by genre;quit;

proc sql outobs=1;select (select count(*) from itunes) as TotalSongs, (select count(distinct genre) from itunes) as GenreCnt, (select count(distinct artist) from itunes) as ArtistCnt, (select count(distinct album) from itunes) as AlbumCntfrom itunes;quit;

Genre

Alternative 9

Bluegrass 43

Blues 14

Children's Music 62

Christian & Gospel 88

Classical 74

Country 77

Easy Listening 31

Electronic 1

Folk 16

General Folk 18

Gospel & Religious 40

Hip Hop/Rap 2

Holiday 13

Inspirational 70TotalSongs GenreCnt ArtistCnt AlbumCnt

802 23 160 100

PROC SQL: Tips and Translations for Data Step UserDictionaries

proc sql; create view detail as select * from dictionary.columns

; create view extern as select * from dictionary.members

; create view tbl as select * from dictionary.tables

; create view gotem as select trim(libname) as LibName, trim(memname) as TableName, trim(name) as ColName, label as ColLabel

from sashelp.vcolumn ;quit;

SAS

PROC SQL: Tips and Translations for Data Step UserDictionaries – Getting variable names

proc sql;

/* get names of all variables you want */

select name into :drinkvars separated by ', '

from dictionary.columns

where libname=‘AUG' and memname='DEMOG' and

lowcase(name) contains ‘ndrk';

/* use your newly created macro variable in your select statement */

create table drinks as

select &drinkvars

from aug.demog;

quit;

PROC SQL: Tips and Translations for Data Step UserDictionaries – Getting variable names

proc sql;/* add the table alias to the front of each variable name

as you create your macro variable */ select 'd.'||name into :aliasvars separated by ', 'from dictionary.columnswhere libname='AUG' and memname='DEMOG' and

lowcase(name) contains ('ndrk');

/* do your merge or whatever using the macro variable you just created */ create table newtable as select &aliasvars, c.expcategoryfrom aug.demog as d left join aug.exposure as c on d.jcml_id=c.jcml_id;

quit;

PROC SQL: Tips and Translations for Data Step UserViews

• Views are ‘virtual tables’• Created with CREATE VIEW statement• Can be used as if they are normal physical tables• Enhance security

– can construct a view of only fields and rows that user is allowed to view• Enhance ease-of-use

– Can combine rows and columns from multiple tables into a single view• Facilitate data integrity

– Can have several views on the same table, but only have to update the base table– Users always see up-to-date data

proc sql; create view aug.testview as select d.subject_id, d.case_id, d.age, e.job_num, e.exposure_element from aug.demog as d, aug.exposure as e where d.subject_id=e.subject_id;quit;

PROC SQL: Tips and Translations for Data Step Users Creating Data Source Indicators

Obs famid name inc1 2 Art 22000

2 1 Bill 30000

3 3 Paul 25000

4 4 Karl 95000

dads Obs famid faminc96 faminc97 faminc981 3 75000 76000 77000

2 1 40000 40500 41000

3 2 45000 45400 45800

4 5 55000 65000 70000

5 6 22000 24000 28000

faminc

proc sql; create table sql_fj as select *, (dads.famid=faminc.famid) as indic, (dads.famid ~=.) as dadind, (faminc.famid ~=.) as famind, coalesce(dads.famid, faminc.famid) as fid from dads full join faminc on dads.famid=faminc.famid; quit;

proc sort data=dads out=sorted_dads; by famid; run; proc sort data=faminc out=sorted_faminc; by famid; run; data ds_fj; merge sorted_dads(in=in1) sorted_faminc(in=in2); by famid; if in1 and in2 then indic=1; else indic=0; dadind=in1; famind=in2; fid=famid; run;

PROC SQL: Tips and Translations for Data Step UsersFull Join - cont

Obs famid name inc faminc96 faminc97 faminc98 indic dadind famind fid1 1 Bill 30000 40000 40500 41000 1 1 1 1

2 2 Art 22000 45000 45400 45800 1 1 1 2

3 3 Paul 25000 75000 76000 77000 1 1 1 3

4 4 Karl 95000 . . . 0 1 0 4

5 . . 55000 65000 70000 0 0 1 5

6 . . 22000 24000 28000 0 0 1 6

Obs famid name inc faminc96 faminc97 faminc98 indic dadind famind fid1 1 Bill 30000 40000 40500 41000 1 1 1 1

2 2 Art 22000 45000 45400 45800 1 1 1 2

3 3 Paul 25000 75000 76000 77000 1 1 1 3

4 4 Karl 95000 . . . 0 1 0 4

5 5 . 55000 65000 70000 0 0 1 5

6 6 . 22000 24000 28000 0 0 1 6

Sql_fj

Ds_fj

PROC SQL: Tips and Translations for Data Step UsersAdditional Uses

proc sql;title 'Bad Control Matches';select c.subject_id, c.casenum, c.gender, age as CntlAge label='CntlAge', (select age from cases where subject_id=c.casenum) as CaseAge, abs(cntlage-calculated caseage) as AgeDifffrom controls as c left join demog as don c.subject_id=d.subject_idwhere (not within5 and not within10);quit;

Scenario:

For a case/control study, verify that all controls have age within 5 to 10 years of the related case age.

PROC SQL: Tips and Translations for Data Step UserMerging Multiple Tables

proc sql; create table sql_c3 as select a.name, b.class, case when missing(c.grade1) then "missing 1“ when missing(c.grade2) then "missing 2“ when missing(c.grade3) then "missing 3“ when missing(c.grade4) then "missing 4"

else "none missing“ end as miss_grade from indat_a as a, indat_b as b, indat_c as c where c.classid=b.classid and c.perid=a.perid;quit;

Obs name class miss_grade1 Mary Art none missing

2 Olive Art none missing

3 Quincy Art none missing

4 Nat Art none missing

5 Pat Art none missing

6 Quincy Music missing 4

7 Richard Music none missing

8 Mary Math none missing

9 Nat Math none missing

10 Olive Math none missing

11 Pat Math none missing

12 Quincy Math missing 2

13 Richard Math none missing

14 Mary English none missing

15 Nat English none missing

16 Olive English none missing

17 Pat English none missing

18 Quincy English none missing

19 Richard English none missing

SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration.