IN08_05. Fun With Functions. Marje Fecht, Prowerk Consulting Ltd, Mississauga, ON Canada

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1 Fun With Functins Marje Fecht, Prwerk Cnsulting Ltd, Mississauga, ON Canada ABSTRACT Functins can be fun (and useful) if yu knw when, hw, and why t use them. Functins can be frustrating if yu d nt knw the tricks behind them. In this presentatin, we will explre the mst cmmnly used functins t streamline data prcessing and reduce yur prgramming effrt. Yu will learn hw t use summary functins, string functins, cnversin functins, and date functins. We will als explre sme f the 60 functins added t SAS 9. This presentatin will als help yu understand WHERE t use functins, since they are nt just fr the DATA Step. INTRODUCTION The SAS language is rich with functins that enable the savvy prgrammer t handle all f their data transfrmatin and manipulatin needs. Hwever, the wealth f functins des have implicatins: Hw d yu knw which functin t chse when s many are similar? Are there tricks fr using the functins? Shuld yu cnsider replacing ld cde with sme f the new SAS 9 functins? Where can functins be used in yur SAS cde? What is the difference between using Summary functins in the data step versus using Summary Prcedures? This Prceedings paper prvides an verview f the tpics that will be cvered in the presentatin. The detailed PwerPint is available at the presentatin, r frm the authr fllwing the cnference. A QUIZ Befre diving int the tpics, test yur knwledge! 1. What is the value f Q1? C = '' ; *** N blanks at all; Q1 = length( C ); 2. What is the value f Q2? C = ' ' ; *** ONE blank; Q2 = length( C ); 1

2 3. What is the value f Q3? IN08_05 C = 'eight ' ; Q3 = length( C ); 4. What is the value f Q4? m =. ; ** missing; y = 4 ; z = 0 ; ** zer; Q4 = m + y + z; 5. What is the value f Q5? m =. ; ** missing; y = 4 ; z = 0 ; ** zer; Q5 = mean(m -- z ); Hw sure are yu f yur answers? Have yu run int these questins befre? Less than 50% f the audience during my first tw presentatins (cnsisting f nvice, intermediate, and advanced SAS users) gt the crrect answers. The answers are: 1. Q1 = 1 2. Q2 = 1 (Length always returns 1 fr a blank string) 3. Q3 = 5 (Length returns the psitin f the right mst nn-blank character) 4. Q4 =. (numeric missing value) 5. Q5 =. (numeric missing value) SUMMARY FUNCTIONS Key features f mst SAS Summary functins include: ignre arguments cntaining missing data prcess data within an bservatin (rw) f data use the OF keywrd t specify ranges f variables. If yur gal is t summarize data within a clumn (variable), yu shuld cnsider SAS Summary Prcedures such as PROC MEANS r PROC SUMMARY. EXAMPLES The SUM functin prvides the ttal f all nn-missing arguments. m =. ; y = 4 ; z = 0 ; Q1 = sum(m, y, z ); Q2 = sum(f m -- z); 2

3 The abve prgram results in Q1 = 4 and Q2 = 4. Since the variable m cntains a missing value, it is ignred in the cmputatin. T sum an entire list f variables (where the variable rder is dictated by rder within the SAS data set), use the keywrd OF and a duble hyphen. If yu exclude the keywrd OF, SAS will subtract the value negative z frm the value f m and return the result. T determine the number f missing values that are excluded in a cmputatin, use the NMISS functin. m =. ; y = 4 ; z = 0 ; N = N(m, y, z); NMISS = NMISS(m, y, z); The abve prgram results in N = 2 (Number f nn missing values) and NMISS = 1 (number f missing values). TRICKS Listing all f the variables in a summary functin can be time cnsuming. If yu use sme tricks in naming yur variables, yu can use shrtcuts. Fr example, if yu want t ttal all f the variables beginning with the string amt, simply specify OF AMT: as the argument fr the summary functin. AmtGrc = 220 ; AmtCar = 180 ; AmtUtil = 270; Mnth = 12; MthlyAmt = Sum( f Amt:); put MthlyAmt = ; The abve prgram results in MthlyAmt = 670. STRING AND SEARCH FUNCTIONS The SAS Language has a full cmplement f character manipulatin functins, including functins t Search Substring Jin Cmpress and many thers.. COMBINING CHARACTER STRINGS If yu wrk with character data, yu prbably have t cmbine strings r extract strings. The cding can be cumbersme and there are many misunderstandings abut hw the functins wrk. EXAMPLE A standard example f string manipulatin invlves jining a first name, middle initial, and last name. Since all SAS variables are f fixed length, this results in extra blanks in the result by default. Thus, a standard slutin is: data cat; length fn mi ln $10; fn = 'Mary'; mi = ''; ln = 'Smith'; Name = trim(fn) ' ' trim(mi) ' ' ln; put name=; What wuld happen withut the trim functin? Since all SAS variables are f fixed length, Mary is actually stred in fn as Mary fllwed by 6 blanks. The result fr name is Mary Smith (there are tw blanks between Mary and Smith). Unfrtunately, if a persn had n recrded middle initial, the result wuld be 2 blank spaces between first and last names. When in dubt, use TRIMN t remve trailing blanks frm character expressins and return a null string if the expressin is missing. The abve example wuld be cded better as: 3

4 data cat; length fn mi ln $10; fn = 'Mary'; mi = ''; ln = 'Smith'; Name = trimn(fn) trimn(' ' mi ) ' ' ln; put name=; SAS 9 FUNCTIONS Prir t SAS 9, yu prbably used cmplex sequences f functins r steps t accmplish standard tasks. When yu cncatenated 2 character strings, yu likely had t left justify, trim, and include an extra blank t get the prper result. If yu needed t determine the secnd highest value in a list f variables fr each bservatin, yu likely used quite a few cmparative statements r maybe even used a PROC. Mre than 60 analytic and data manipulatin functins were added t SAS 9. Many functins were added t reduce cde cmplexity. Additinally, the lgic behind sme functins was revised t imprve perfrmance (LENGTH and TRIM functins). REDUCE CODE COMPLEXI TY Several character functins were added t reduce the cmplexity f cmmn tasks. Fr example, the CATX functin prvides a straightfrward slutin t jining 2 strings s the result remves leading and trailing blanks and includes a designated character as a separatr. Versin 8 Slutin: Cmbine = trim(left(char1)) ' ' left(char2); SAS 9 Slutin: Cmbine = CATX(' ', Char1, Char2); If yu used repetitive INDEX and SUBSTR functins t determine hw many times a wrd ccurs in a character string, that task can be accmplished mre easily in Versin 9. The COUNT functin determines the number f times argument 2 ccurs in argument 1. SUBSTR has always been an effective functin fr extracting (r replacing) a prtin f a character string. Tw variatins f SUBSTR are available in SAS 9: CHAR - t extract a single character frm a text string JustOne = CHAR(String, 5); FIRST t grab just the first character frm a text string Initial = FIRST(name); If yu need t strip bth leading and trailing blanks frm a string, yu can skip using the LEFT and TRIM functins and just use the new STRIP functin. COMPUTING STATISTICS OR QUANTITIES If yu wrk frequently with Medians r Percentiles, yu can nw btain thse quantities in the DATA step. The MEDIAN functin determines the median f nn-missing values. The PCTL functin accepts a percentage fr argument 1 t specify the percentile f interest. The functin then cmputes the percentile fr the list f values. If yu need t find the secnd largest value in a list f values, r perhaps the third smallest value, the LARGEST and SMALLEST functins are available. In additin t supplying a list f values, yu supply which placement yu are lking fr. ThirdLargest = LARGEST(3, a, b, c, d, e, f); 4

5 WHERE TO USE FUNCTIONS D yu typically create a subset f yur data befre prcessing the data in a PROC? If yu answered YES, yu may be reading yur data twice unnecessarily. Mst functins can be used in a WHERE statement which means a lt f prcessing can ccur in PROCs. Suppse yu want t lk at all July sales. Instead f a tw-step subset print prcess, yu can handle the subsetting in the same step as the print. prc print data=sashelp.retail; where mnth(date) = 7; title 'Sandal Sales in July'; If the abve example were handled as a DATA step t subset, fllwed by a PROC step t Print, the data wuld have been prcessed twice. If yu wrk with large vlumes f data, the savings in resurces wuld be cnsiderable. CONCLUSION Befre yu write messy cde t slve yur data transfrmatin/manipulatin needs, review the existing functins. Yu may be able t slve mst tasks in ne line rather than many, which will als make yur cde easier t understand (and thus easier t inherit ). REFERENCES The SAS nline dcumentatin prvides bth syntax and examples fr all f the available functins. CONTACT INFORMATION Yur cmments and questins are valued and encuraged. Cntact the authr at: Marje Fecht Prwerk Cnsulting marje.fecht@prwerk.cm Web: SAS and all ther SAS Institute Inc. prduct r service names are registered trademarks r trademarks f SAS Institute Inc. in the USA and ther cuntries. indicates USA registratin. Other brand and prduct names are trademarks f their respective cmpanies. 5