Introduction to SAS System Where Expressions

Introduction to Where ExpressionsMark Tabladillo, Ph.D.

Software Developer, MarkTab ConsultingAssociate Faculty University of PhoenixAssociate Faculty, University of Phoenix

January 30, 2007

IntroductionIntroduction

• WHERE expressions allow for processingWHERE expressions allow for processing subsets of observations

• WHERE expressions can be used in theWHERE expressions can be used in the DATA step or with PROC (procedure) statements

• This presentation will contain a series of features and examples of the WHERE pexpression

• We end with some intensive macros

WHERE-expression ProcessingWHERE expression Processing

• Enables us to conditionally select a subsetEnables us to conditionally select a subset of observations, so that SAS processes only the observations that meet a set ofonly the observations that meet a set of specified conditions.

http://support.sas.com/onlinedoc/913/getDoc/en/lrcon.hlp/a000999253.htm

Work Sales DatasetWork.Sales Datasetdata work.sales (drop=i randomState);

length state $2 sales 8 randomState 3;length state $2 sales 8 randomState 3;do i = 1 to 2500;

randomState = round(rand('gaussian',3,1)+0.5);if randomState in (1,2,3,4,5) then do;( )

select(randomState);when(1) state='TN';when(2) state='AL';when(3) state='GA';when(3) state= GA ;when(4) state='FL';when(5) state='MS';

end;sales = int(rand('gaussian',1000000,500000));output work.sales;

end;end;end;run;

Data Set Option or StatementData Set Option or Statementdata work.highSales;

set work.sales (where=(sales>1500000));run;

data work highSales;data work.highSales;set work.sales;where sales>1500000;run;

proc means data=work.sales;where sales>1500000;run;;

Data Set Option or StatementData Set Option or Statementdata work.lowSales;

set work.sales (where=(sales<0));run;

data work lowSales;data work.lowSales;set work.sales;where sales<0;run;

proc means data=work.sales (where=(sales<0));run;

Multiple ComparisonsMultiple Comparisonsdata work.highFloridaSales;

set work.sales (where=(sales>1500000 and state = 'FL'));run;

data work highFloridaSales;data work.highFloridaSales;set work.sales;where sales>1500000 and state = 'FL';run;

proc freq data=work.sales;tables state;where sales>1500000 and state = 'FL';;run;

SAS FunctionsSAS Functionsdata work.highFloridaSales;

set work.sales (where=(sales>1500000 and substr(state,1,1) = 'F'));run;

data work highFloridaSales;data work.highFloridaSales;set work.sales;where sales>1500000 and substr(state,1,1) = 'F';run;

proc means data=work.sales;where sales>1500000 and substr(state,1,1) = 'F';run;;

Comparison OperatorsComparison OperatorsPriority Order of

EvaluationSymbols Mnemonic

EquivalentEvaluation EquivalentGroup I right to left **

++-

ˆ ¬ ~ NOT>< MIN<> MAX




EquivalentEvaluation EquivalentGroup II left to right *

//Group

IIIleft to right +

-Group

IVleft to right || ¦¦ !!

IV




EquivalentEvaluation EquivalentGroup

Vleft to right < LT

<= LE= EQ

¬= NE>= GE> GT

IN




EquivalentEvaluation EquivalentGroup

VIleft to right & AND

Group VII

left to right | ¦ ! OR


Comparison OperatorsComparison Operatorsdata work.extremeNonGeorgia;

set work.sales (where=((sales<0 | sales>1500000) and state in ('TN','AL','FL','MS')));

run;

data work.extremeNonGeorgia;set work.sales;where (sales<0 | sales>1500000) and state in ('TN','AL','FL','MS');run;

data work.extremeNonGeorgia;set work.sales;;where ^ (0 <= sales <= 1500000) & state ne 'GA';run;


“Between And”Between Anddata work.boundedNonGeorgia;

set work.sales (where=((sales between 1000000 and 1500000) & state in ('TN','AL','FL','MS')));

run;

data work.boundedNonGeorgia;set work.sales;where (sales between 1000000 and 1500000) &

t t i ('TN' 'AL' 'FL' 'MS')state in ('TN','AL','FL','MS');run;


Contains ?Contains ?data work.LStates;

set work.sales (where=(state contains 'L'));run;

data work LStates;data work.LStates;set work.sales;where state contains 'L';run;

data work.LStates;set work.sales;where state ? 'L';;run;


Is Null/Is MissingIs Null/Is Missingdata work.nullStates;

set work.sales (where=(state is null));run;

data work.missingStates;set work.sales (where=(state is missing));se o sa es ( e e (s a e s ss g));run;

data work.nullSales;set work sales;set work.sales;where sales is missing;run;

data work.nonNullSales;set work.sales;where sales is not missing;run;run;


LikeLikedata work.likeL;

set work sales (where=(state like '%L'));set work.sales (where=(state like '%L'));run;

data work.likeL;set work.sales (where=(state like "%L"));run;

data work likeL;data work.likeL;set work.sales (where=(state like "%%L"));run;

data work.notLikeG;set work.sales;where state not like 'G_';run;run;


Sounds Like (Soundex)Sounds Like (Soundex)data work.soundsLikeFill;

set work.sales (where=(state =* 'fill'));run;

data work notSoundsLikeTin;data work.notSoundsLikeTin;set work.sales;where state not =* 'tin';run;


“Same And”Same Anddata work.boundedNonGeorgia;

set work.sales (where=((sales between 1000000 and 1500000) & state in ('TN','AL','FL','MS')));

run;

data work.boundedNonGeorgia;set work.sales;where (sales between 1000000 and 1500000);

h d t t i ('TN' 'AL' 'FL' 'MS')where same and state in ('TN','AL','FL','MS');run;

data work.boundedNonGeorgia;g ;set work.sales;where same and (sales between 1000000 and 1500000); where same and state in ('TN','AL','FL','MS');run;run;


WHERE vs Subsetting IFWHERE vs. Subsetting IFTask Method

Make the selection in a procedure without using a WHERE expressionMake the selection in a procedure without using a preceding DATA step

WHERE expression

Take advantage of the efficiency available with an indexed data set

WHERE expression

Use one of a group of special operators, such as BETWEEN-AND, CONTAINS, IS MISSING or IS NULL, LIKE, SAME-AND, and Sounds-Like

WHERE expression

B th l ti thi th th i bl l b tti IFBase the selection on anything other than a variable value that already exists in a SAS data set. For example, you can select a value that is read from raw data, or a value that is calculated or assigned during the course f th DATA t

subsetting IF

of the DATA stepMake the selection at some point during a DATA step

rather than at the beginningsubsetting IF

Execute the selection conditionally subsetting IFExecute the selection conditionally subsetting IF


Intensive Dataset GenerationIntensive Dataset Generation%macro OurCentury();%local year interest;y ;%do year = 2001 %to 2100;

%let interest = %sysfunc(compound(1,.,0.05,%eval(&year.-2001)));data work.sales&year. (drop=i randomState index=(state sales));

length state $2 stateName $20 sales 8 randomState 3;g ;do i = 1 to 2500;

randomState = round(56*rand('uniform')+0.5);if randomState <= 56 and randomState not in (3,7,14,43,52) then do;

state = fipstate(randomState);p ( )stateName = fipnameL(randomState);sales = int(rand('gaussian',1000000*&interest.,500000*&interest.));output work.sales&year.;

end;end;run;

%end;%mend OurCentury;y%OurCentury;

Year/State DatasetsYear/State Datasets%macro SalesByYearState();%local year stateCode state;%do year = 2001 %to 2100;

%do stateCode = 1 %to 56;%if &stateCode ne 3 & &stateCode ne 7 & &stateCode ne 14 &%if &stateCode. ne 3 & &stateCode. ne 7 & &stateCode. ne 14 &

&stateCode. ne 43 & &stateCode. ne 52 %then %do;%let state = %sysfunc(fipstate(&stateCode.));data work.sales&year.&state.;

t k l &set work.sales&year.;where state = "&state.";run;

%end;;%end;

%end;%mend SalesByYearState;%SalesByYearState;%SalesByYearState;

Year/State High Sales DatasetsYear/State High Sales Datasets%macro HighSalesByYearState();%local year stateCode state interest keepDataset;%do year = 2001 %to 2100;

%let interest = %sysfunc(compound(1,.,0.05,%eval(&year.-2001)));%do stateCode = 1 %to 56;

%if &stateCode. ne 3 & &stateCode. ne 7 & &stateCode. ne 14 & &stateCode. ne 43 &&stateCode. ne 52 %then %do;&stateCode. ne 52 %then %do;%let state = %sysfunc(fipstate(&stateCode.));%let keepDataset = 0;data work.sales&year.&state.high;

set work.sales&year.;h t t "& t t " d l > 2000000*&i t twhere state = "&state." and sales > 2000000*&interest.;

call symput('keepDataset',left('1'));run;

%if not(&keepDataset.) %then %do;proc datasets lib=work nolist;p

delete sales&year.&state.high;run; quit;

%end;%end;

%end;%end;%end;%mend HighSalesByYearState;%HighSalesByYearState;

ConclusionConclusion

• The WHERE expression allows forThe WHERE expression allows for efficient observation processing in the DATA step and the PROC statementsDATA step and the PROC statements

• The SAS System Documentation provides specific details on the syntaxspecific details on the syntax

• Using macros increases the processing f WHERE ipower of WHERE expressions

Contact InformationContact Information

• Mark TabladilloMark TabladilloMarkTab Consultinghttp://www marktab com/http://www.marktab.com/

Technology

Introduction to SAS System Where Expressions