SAS Certification Handout #7: Ch

Transcription

1 SAS Certification Handout #7: Ch /************ Ch. 19 ********************/ /* Consider a mailing list example, partial from Kansas City Royals Kauffman Stadium One Royal Way Kansas City MO Phone: (816) San Franciso Giants AT&T Park 24 Willie Mays Plaza San Francisco CA Phone: (415) New York Yankees Yankee Stadium One East 161st Street Bronx NY Phone: (718) */ /* NOTE: All of these observations have the same number of records (lines) in the data file (5), in a structured order */ filename mlb "C:\jrstevens\Teaching\SAS_Cert\Notes\a7_mlb.txt" * filename mlb "/home/jrstevens/sas_cert/a7_mlb.txt" /* / sequential line pointer like a line break, moving input pointer to next line (record) */ infile mlb input CityName & $13. Name & $8. / Stadium & $16. / Address & $21. / City & $13. State $2. Zip AreaCode Phone $8. proc print data=a7 Obs CityName Name Stadium Address City State Zip AreaCode Phone 1 Kansas City Royals Kauffman Stadium One Royal Way Kansas City MO San Franciso Giants AT&T Park 24 Willie Mays Plaza San Francisco CA New York Yankees Yankee Stadium One East 161st Street Bronx NY

2 /* multiple INPUT statements work sequentially, applied to records in order */ infile mlb input CityName & $13. Name & $8. input Stadium & $16. input Address & $21. input City & $13. State $2. Zip AreaCode Phone $8. proc print data=a7 Obs CityName Name Stadium Address City State Zip AreaCode Phone 1 Kansas City Royals Kauffman Stadium One Royal Way Kansas City MO San Franciso Giants AT&T Park 24 Willie Mays Plaza San Francisco CA New York Yankees Yankee Stadium One East 161st Street Bronx NY /* # non-sequential line pointer can be used to read in multiple records to a single observation, reading records in any order, and even skipping some lines altogether */ infile mlb input #1 CityName & $13. Name & $8. Phone $8. #2 Stadium & $16. AreaCode 3. #4 City & $13. State $2. Zip proc print data=a7 Obs CityName Name Phone Stadium AreaCode City State Zip 1 Kansas City Royals Kauffman Stadium 816 Kansas City MO San Franciso Giants AT&T Park 415 San Francisco CA New York Yankees Yankee Stadium 718 Bronx NY 10451

3 /************ Ch. 20 ********************/ /* Consider a 'repeated measures' data set, where each subject was measured multiple times */ /* An inefficient data storage: */ input subject score cards proc print data=a7 Obs subject score /* More efficient to have more than one observation in each line (i.e., in each record). Use to hold input pointer on currect record across multiple iterations of the DATA step use this for "repeating blocks" of data */ input subject cards Obs subject score proc print data=a

4 /* Same data, but with just one record per subject. Here, if there are the same number of repeating fields for each subject, and OUTPUT. holds input pointer on current record for the current iteration of the DATA step only. */ input /* Get subject value, and stay on same line. */ input /* Get score from next field. */ output /* Write current PDV to data set. */ cards Obs subject score proc print data=a /* Wait... need to execute OUTPUT for each repeating field in the record p. 625 shows how could do this without DO loop, too */ input do rep = 1 to 3 input output end cards proc print data=a7 Obs subject rep score /* Now, what if have different number of repeating fields for some subjects -- like in an incomplete repeated measures study? First, try OUTPUT input do rep = 1 to 3 /* problem here: not 3 reps for all subjects */ input output end Obs subject rep score cards proc print data=a

5 /* With varying number of repeating fields, need combination of MISSOVER and DO WHILE(... NE.) But: MISSOVER doesn't work with CARDS statement, so must use INFILE */ filename fields "C:/jrstevens/Teaching/SAS_Cert/Notes/a7_varying.txt" * filename fields "/home/jrstevens/sas_cert/a7_varying.txt" infile fields missover /* p. 544: MISSOVER prevents SAS from going to the next record to read a variable value if, when using list input, it does not find values in the current record for all of the INPUT statement variables. So even though we don't have 'missing' values at the end of any datafile row, we do want to keep SAS from trying to get the next data value from the next row, until we are done reading observations from the current row. */ input subject /* MUST have this line to get started. */ rep = 0 /* Will be reset at every iteration of DATA step (each record) */ do while(score ne.) rep+1 output /* Writes current PDV to data set. */ input /* Gets value from next field */ /* (in the current record only, */ /* thanks to MISSOVER). */ end Obs subject score rep proc print data=a /* NOTE: Pages 630 & 636 demonstrate that _N_ in the PDV tracks the number of iterations through the DATA step, NOT the number of observations created to that point. */

6 /************ Ch. 21 ********************/ /* Sometimes a data file is organized into header records (lines) and detail records (lines), where all detail records follow corresponding header records, with possibly multiple detail records for each header record. Such files are called hierarchical (due to this nesting of detail records inside header records). */ /* Example: header record is company (C) detail record is founder (F), with variables lastname firstname networth */ /* Create one observation per detail record */ retain company /* keep value across DATA step iterations */ input type if type="c" then company $10. if type="f" /* recall default THEN is KEEP this subsets the data */ input lastname $ firstname $ networth cards C Microsoft Obs company type lastname firstname networth F Gates Bill 81.1e9 F Allen Paul 17e9 1 Microsoft F Gates Bill C Apple 2 Microsoft F Allen Paul F Jobs Steve 8.3e9 F Wayne Ronald. 3 Apple F Jobs Steve F Wozniak Steve 150e6 4 Apple F Wayne Ronald. proc print data=a7 5 Apple F Wozniak Steve /* What if that last IF statement included a subsequent THEN? */ retain company input type if type="c" then company $10. if type="f" then input lastname $ Obs company type lastname firstname networth firstname $ networth 1 Microsoft C. cards C Microsoft 2 Microsoft F Gates Bill F Gates Bill 81.1e9 F Allen Paul 17e9 3 Microsoft F Allen Paul C Apple F Jobs Steve 8.3e9 F Wayne Ronald. F Wozniak Steve 150e6 4 Apple 5 Apple 6 Apple C F F Jobs Wayne Steve Ronald proc print data=a7 7 Apple F Wozniak Steve /* remember DATA step is executed for each record! */

7 /* Same data, but now create one observation per header record (here, calculate total networth of founders within each company). For this, we need to use the END= option of the INFILE statement, so we can't use CARDS */ filename money "C:/jrstevens/Teaching/SAS_Cert/Notes/a7_company.txt" * filename money "/home/jrstevens/sas_cert/a7_company.txt" /* MISSOVER needed here to handle. for networth at end of 6th record. PAD needed to handle different ending columns for company in 1st and 4th records */ data a7 (keep = company total) infile money end=last missover pad retain company /* Keep value across DATA step iterations. */ input type /* Keep input pointer on current record. */ if type="c" then do if _n_ > 1 then output /* OUTPUT means write current PDV to data set */ total=0 input company $10. /* Input pointer was still where we left it. */ end else if type="f" then do input lastname $ firstname $ networth total+networth end if last then output /* Recall last = 0 for all but final obs, where it is 1 */ proc print data=a7 label format total dollar16. label total = 'Total Net Worth of Founders' company = 'Name of Company' Obs Name of Company Total Net Worth of Founders 1 Microsoft $98,100,000,000 2 Apple $8,450,000,000