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Introduction to SAS

Introduction to SAS. a programming environment and language for data manipulation and analysis. Files referenced here are available in the Green Lab at: P:briggspoec5317

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Introduction to SAS

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  1. Introduction to SAS a programming environment and language for data manipulation and analysis. Files referenced here are available in the Green Lab at: P:\briggs\poec5317 Single best book on SAS: Lora D. Delwiche and Susan Slaughter “The Little SAS Book: A Primer,” SAS Institute, 2nd edition, 1999

  2. First Example ProgramSample SAS program: sasex0.sas Output file (‘printout’) Program File *my first SAS program; data grocery; input product $ var1 var2; label var1='Number on Hand' var2='Number on Order'; lines; cheese 25 32 hotdogs 26 14 mustard 13 32 ;;;;;;;; run; proc print label; run; proc means; run; The SAS System 1 Number Number OBS PRODUCT on Hand on Order 1 cheese 25 32 2 hotdogs 26 14 3 mustard 13 32 The SAS System 19:13 Tuesday, July 16, 1996 2 Variable Label N Mean Std Dev Minimum Maximum ------------------------------------------------------------------------------------------------------- VAR1 Number on Hand 3 21.3333333 7.2341781 13.0000000 26.000000 VAR2 Number on Order 3 26.0000000 10.3923048 14.0000000 32.000000 -------------------------------------------------------------------------------------------------------

  3. SAS Log from First Sample Program: sasex0.log (with minor editing) 1 *my first SAS program; 3 data grocery; 4 input product $ var1 var2; 5 label var1='Number on Hand' 6 var2='Number on Order'; 7 lines; NOTE: The data set WORK.GROCERY has 3 observations and 3 variables. NOTE: DATA statement used: real time 0.148 seconds cpu time 0.070 seconds 11 ;;;;;;;; 12 run; 13 proc print label; run; NOTE: The PROCEDURE PRINT printed page 1. 14 proc means; run; NOTE: The PROCEDURE MEANS printed page 2.

  4. Alabama 1AL ESC 63 3894 3444 3267 Alaska 2AK PAC 94 402 304 228 Arizona 4AZ MTN 86 2718 1776 1306 Arkansas 5AR WSC 71 2286 1924 1787 California 6CA PAC 93 23668 19971 15735 Colorado 8CO MTN 84 2890 2211 1758 Connecticut 9CT NE 16 3108 3033 2536 Delaware 10DE SA 51 594 547 445 D of Columbia 11DC SA 53 638 757 764 Florida 12FL SA 59 9746 6797 4959 Georgia 13GA SA 58 5463 4587 3941 . . . Texas 48TX WSC 74 14229 11199 9582 Utah 49UT MTN 87 1461 1059 890 Vermont 50VT NE 13 511 444 389 Virginia 51VA SA 54 5347 4652 3970 Washington 53WA PAC 91 4132 3415 2859 West Virginia 54WV SA 55 1950 1745 1861 Wisconsin 55WI ENC 35 4706 4418 3952 Wyoming 56WY MTN 83 470 332 330 (51 lines of data) Data Documentation (state.dd): RECORD FORMAT SHEET: FILE: stpop.dat (PC) stpop.data (UNIX) Rec COLS Variable Type 1 1-17 Name of State Alpha 1 18-20 Federal Info. Processing code num 1 21-23 State postal code Alpha 1 24-27 Census Bureau Division Alpha 1 28-30 Census Bureau State code num 1 31-36 Population in 1980 1000 1 37-42 Population in 1970 1000 1 43-48 Population in 1960 1000 Second Sample ProgramHere is Data! How Get it into SAS? Data File (state.dat)

  5. *USE DATA STEP TO READ IN RAW DATA FROM AN O/S FILE AND CREATE A SAS DATA SET; DATA USPOP; *names the sasdata set to create; *read in data; INFILE 'p:\briggs\poec5317\state.dat'; INPUT STATE $ 1-17 FIPS 18-20 ST $ 21-23 DIV $ 24-27 CB 28-30 POP80 31-36 POP70 37-42 POP60 43-48; *create some new variables using assign statements; PPOP6070=(POP70-POP60)/POP60*100; PPOP7080=(POP80-POP70)/POP70*100; *label all variables; LABEL STATE='Name of State' FIPS='Federal Info. Processing Code' ST='State Postal Code' DIV='Census Bureau Division' CB='Census Bureau State Code' POP80='POPULATION in 1980' POP70='POPULATION in 1970' POP60='POPULATION in 1960' PPOP6070='% POP. Change 1960-1970' PPOP7080='% POP. Change 1970-1980'; RUN; *USE PROC STEPS TO ANALYSE THIS SAS DATA SET; *produce a simple print of the data; PROC PRINT DATA=USPOP; VARIABLES ST POP80 PPOP6070 PPOP7080 ; TITLE1 'US Demographic Change by State' ; TITLE2 '1960-1980'; RUN; *sort and print the data by geographic region; PROC SORT DATA=USPOP; BY CB; PROC PRINT DATA=USPOP(OBS=51) NOOBS LABEL; VARIABLES ST POP80 PPOP6070 PPOP7080; FORMAT PPOP6070 PPOP7080 5.1; FOOTNOTE 'STATES Are Ordered According to Census Bureau Division'; RUN; FOOTNOTE; *regression predicting growth in seventies from growth in sixties; PROC REG DATA=USPOP; MODEL PPOP7080=PPOP6070 /STB; TITLE 'Population Growth in the Seventies Predicted from Sixties; RUN; *produce descriptive statistics; PROC MEANS SUM MIN MAX; TITLE 'Population Statistics'; RUN; Second Sample Program (contd.)Example SAS Program for Reading Data File (sasex1.sas)

  6. 1 *USE DATA STEP TO READ IN RAW DATA FROM AN O/S FILE AND CREATE A SAS DATA SET; 2 options nocenter; 3 DATA USPOP; *names the sasdata set to create; 4 5 *read in data; 6 INFILE 'p:\briggs\poec5317\state.dat'; 7 INPUT STATE $ 1-17 FIPS 18-20 ST $ 21-23 8 DIV $ 24-27 CB 28-30 POP80 31-36 POP70 37-42 POP60 43-48; 9 10 *create some new variables using assign statements; 11 PPOP6070=(POP70-POP60)/POP60*100; 12 PPOP7080=(POP80-POP70)/POP70*100; 13 14 *label all variables; 15 LABEL STATE='NAME OF STATE' 16 FIPS='FEDERAL INFO. PROCESSING CODE' 17 ST='STATE POSTAL CODE' 18 DIV='CENSUS BUREAU DIVISION' 19 CB='CENSUS BUREAU STATE CODE' 20 POP80='POPULATION IN 1980' 21 POP70='POPULATION IN 1970' 22 POP60='POPULATION IN 1960' 23 PPOP6070='% POP. CHANGE 1960-1970' 24 PPOP7080='% POP. CHANGE 1970-1980'; 25 RUN; NOTE: The infile 'p:\briggs\poec5317\state.dat'; FILENAME='p:\briggs\poec5317\state.dat'; RECFM=V,LRECL=256 NOTE: 51 records were read from the infile The minimum record length was 80. The maximum record length was 80. NOTE: The data set WORK.USPOP has 51 observations and 10 variables. 28 *USE PROC STEPS TO ANALYSE THIS SAS DATA SET; 30 *produce a simple print of the data; 31 PROC PRINT DATA=USPOP; 32 VARIABLES ST POP80 PPOP6070 PPOP7080 ; 33 TITLE1 'US DEMOGRAPHIC CHANGE BY STATE' ; 34 TITLE2 '1960-1980'; 35 RUN; NOTE: The PROCEDURE PRINT used 0.98 seconds 37 *sort and print the data by geographic region; 38 PROC SORT DATA=USPOP; BY CB; NOTE: The data set WORK.USPOP has 51 observations and 10 variables. NOTE: The PROCEDURE SORT used 0.44 seconds. 39 PROC PRINT DATA=USPOP(OBS=51) NOOBS LABEL; 40 VARIABLES ST POP80 PPOP6070 PPOP7080; 41 FORMAT PPOP6070 PPOP7080 5.1; 42 FOOTNOTE 'STATES ARE ORDERED ACCORDING TO CENSUS BUREAU DIVISION'; 43 RUN; NOTE: The PROCEDURE PRINT used 0.27 seconds. 44 FOOTNOTE; 47 48 *regression to preditc growth in seventies form sixties; 49 PROC REG DATA=USPOP; 50 MODEL PPOP7080=PPOP6070 /STB; 51 TITLE 'Population Growth in the Seventies Predicted from Sixties'; 52 RUN; NOTE: 51 observations read. NOTE: 51 observations used in computations. 53 *produce descriptive statistics; NOTE: The PROCEDURE PLOT used 0.48 seconds. 54 PROC MEANS SUM MIN MAX; 55 TITLE 'Population Statistics'; 56 RUN; NOTE: The PROCEDURE MEANS used 0.55 seconds. Log from Second Sample Program: SASEX1.LOG

  7. US Demographic Change by State 1960-1980 OBS ST POP80 PPOP6070 PPOP7080 1 AL 3894 5.4178 13.0662 2 AK 402 33.3333 32.2368 3 AZ 2718 35.9877 53.0405 . . 51 WY 470 0.6061 41.5663 US Demographic Change by State 1960-1980 State % POP. % POP. Postal POPULATION Change Change Code in 1980 1960-1970 1970-1980 ME 1125 2.5 13.2 NH 921 21.6 24.8 VT 511 14.1 15.1 . . CA 23668 26.9 18.5 AK 402 33.3 32.2 HI 965 21.6 25.3 STATES are Ordered According to Census Bureau Division Population Growth in the Seventies Predicted from Sixties Model: MODEL1 Dependent Variable: PPOP7080 % POP. Change 1970-1980 Analysis of Variance Sum of Mean Source DF Squares Square F Value Prob>F Model 1 4600.88079 4600.88079 36.285 0.0001 Error 49 6213.20649 126.80013 C Total 50 10814.08729 Root MSE 11.26056 R-square 0.4255 Dep Mean 15.78436 Adj R-sq 0.4137 C.V. 71.33995 Parameter Estimates Parameter Standard T for H0: Standardized Variable DF Estimate Error Parameter=0 Prob > |T| Estimate INTERCEP 1 5.627559 2.30854548 2.438 0.0185 0.00000000 PPOP6070 1 0.756642 0.12561153 6.024 0.0001 0.65226722 Variable Variable DF Label INTERCEP 1 Intercept PPOP6070 1 % POP. Change 1960-1970 Example of Output from sasex1

  8. SAS programs constructed of: DATA steps which create SAS data sets PROC steps which analyze SAS data sets SAS statements begin anywhere on a line end with a semi-colon; extend to as many lines as needed can be stacked many to a line not case sensitive SAS names(for variables, datasets, etc) 8 characters or less start with alpha character no special characters except _ SAS variables: 2 types character (max. of 200 characters long) numeric(default 8 bytes long) Some of these rules for names and variables are less stringent in newer versions of SAS. The Rules of SAS Programming

  9. SAS Jobs raw data read by SAS DATA step creates SAS DATA SET analyzed by SAS PROC Step generates report/output etc. raw data Data State; input pop80 pop90; growth=pop90-pop80; State Proc MEANS; variables pop80 pop90; report/ output

  10. data may exist in one of two forms: as a raw data file, managed by the operating system (e.g Windows, or UNIX) as a SAS data set, managed by SAS SAS data sets are matrices (tables): variables occupy the columns each variable is identified by a name (e.g. Population) observations occupy the lines or rows (e.g. Texas) there is no limit to the number of observations SAS always processes just one observation at a time An entry (matrix element) in this table is called a data value. Once data are in a SAS data set, only the meaning of the variable names needs to be remembered--all physical details of the raw data file can be forgotten. proc contents; proc print; Raw Data & SAS Data Sets SAS data set descriptors data set name variable attributes: name, type, length, format informat, label. history: source statements used to create the data set report data Jane F 11 57.3 83 John M 12 59.0 99.5 . . . Alice F 13 56.5 84.0 obs1 obs2 obs3 . . . obs19 report Name Gender Age Height Weight variables in columns SAS Procedures can only process SAS data sets. A data step is used to read raw data into a SAS data set.

  11. *my program; OPTIONS nocenter linesize=80; DATA sasdata1; INFILE ‘c:\rawdata’; INPUT var1 var2; …. RUN; DATA sasdata2; ….. RUN; DATA sasdata; MERGE sasdata1 sasdata2; … RUN; PROC first; …. RUN; PROC second; RUN; comment statement--not part of PROC or DATA step establishes options--not part of PROC or DATA step start data step & name sas data set being created location of raw data file identify variables within raw data set other data step statements end first data step start second data step end second data step start third data step combine first and second data sets into ‘master’ set end third data step begin first PROC step to analyze data end first PROC step begin second PROC step for more analysis end second PROC step Example Structure of a SAS Program data step data step data step proc step

  12. From another SAS data set the first observation is selected from the source data set it is processed through all statements in the data step ( up to the run;) it is output to the data set(s) being created the second observation from the source is selected, etc. From a raw data file the first n logical records (based on the INPUT statement) are selected from the source they are processed through all statements in the data step they are output to the data set(s) being created, usually as one observation the next n logical records from the source are selected, etc. How SAS data sets are named: temporary v. permanent • Temporary (duration of program execution only) • --single level name: datasetname e.g. USPOP • Permanent (saved to disk) • --double level name: libraryname.datasetname e.g. POPDATA.USPOP How SAS data sets are built: one observation at a time

  13. Once a SAS data set has been saved permanently (by using a two level name) it can be recalled for use in PROCS, or for further modification *recall and use in a PROC; LIBNAME POPDATA 'c:\sasdata\usstate\'; PROC MEANS DATA=POPDATA.USPOP; RUN; *recall and further modify (transform) the data set temporarily; LIBNAME POPDATA 'c:\sasdata\usstate\'; DATA USPOP; SET POPDATA.USPOP; lines of code RUN; *recall, modify and save new version permanently; LIBNAME POPDATA 'c:\sasdata\usstate\'; DATA POPDATA.USPOPV2 SET POPDATA.USPOP; lines of code RUN; Using Permanent SAS data sets If the POPDATA library has been defined in SAS Explorer, the LIBNAME statement may be omitted. For SAS V7, the folder ‘c:\sasadata\usstate\’ contains a file called USPOP.SAS7BDAT The same name (USPOP) could be used for the new version (called USPOPV2). This is dangerous, but may be necessary if disk space is short.

  14. * read in some data from an O/S file and create a temporary SAS data set called USPOP; *illustrates use of: --fixed field format --multiple lines of input per observation; DATA USPOP; INFILE ‘p:\appsdata\briggs\poec5317\state2.dat’; INPUT STATE $ 1-17 FIPS 18-20 ST $ 21-23 DIV $ 24-27 CB 28-30 POP80 31-36 POP70 37-42 POP60 43-48 #2 UNEMP80 3.1 AGE2040 5.1 @10 INC80 6.0; /* describes the data in the file*/ RUN; *it is good practice to print some of the data read and check it; PROC PRINT DATA=USPOP(OBS=5); /* prints first five observations.*/ TITLE 'Check of Data Read In'; * read additional data into a second SAS data set called POP85; *illustrates use of: --free-field format --identification of O/S file on the INFILE statement; --FILENAME statement to assign an ‘alias’ to a file /*equates ‘nickname’ (in1) with real file name*/ FILENAME in1 'p:\appsdata\briggs\poec5317\stpop85.dat'; DATA POP85; INFILE in1; /*uses nickname to identify the data file */ INPUT POP85 POP82 FIPS; DROP POP82; RUN; /************************************************ With free field format , variables don’t necessarily occupy the same column position (field) on each line. This can be convenient but also dangerous since a single error (e.g. missing space or data value) can result in ALL subsequent data being read incorrect. *************************************************/ Third Example SAS Program: sasex2A.sas (1 of 3)

  15. *We now combine together our two data sets into a single ‘research’ data set; PROC SORT DATA=POP85;BY FIPS; DATA USPOP; MERGE POP85 USPOP; BY FIPS; RUN; /******************************************** MERGE allows us to combine observation in one data set(s) with those in another. The data sets are placed ‘side-by-side.’ Observations are matched based upon common values on a BY variable. Note that: --BY variable must exist with same name in both data sets. --Both data sets must be sorted by the BY variable. *********************************************/ /******************************************** If no BY variable is available, the two data sets will be placed 'side-by-side' with observations matched only by sequential order. Dangerous! If they are not in the exact same order, or if an observation is missing from one data set, there will be a mismatch from that point onwards and no erroror warning message will be issued. *********************************************/ Example SAS Program Set: sasex2A.sas(2 of 3)

  16. *we now save our final research data set permanently on disk; *be sure that the subdirectory (folder) specified in the LIBNAME statement exists on your file system before running program; LIBNAME POPDATA 'c:\sasdata\usstate\'; *specifies the subdirectory to use to save the SAS data sets; DATA POPDATA.USPOP; *note two level name; SET USPOP; *identifies source SAS data set; KEEP STATE FIPS ST DIV REG POP85 POP90 POP80 POP70 POP60; * selects variables for inclusion; LABEL STATE='Name of State' FIPS='Federal Information Processing code' ST='State postal code' DIV='Census Bureau Division' REG='Census Bureau Region' POP90='Population in 1990' POP80='Population in 1980' POP70='Population in 1970' POP60='Population in 1960'; RUN; /***************************************** SAS data sets with a 'two level' name (POPDATA.USPOP) are saved permanently after the job runs. The 'first level' (POPDATA in this example) is a SAS alias (often referred to as a SAS library) which identifies, via a LIBNAME command, the sub-directory in which the SAS data set will be stored. The SAS data set is written to that subdirectory with the 'second level' name as the filename, and an extension of ".sd2" in SAS/PC (or ‘.ssd001’ in UNIX) (that is, in the example, 'uspop.sd2' or 'uspop.ssd01'.); ‘Single level’ SAS data sets are internally given a first level name by SAS of WORK. (e.g. WORK.USPOP). They exist only for the duration of the job. A SET statement is used to identify the source SAS data set. We are ‘setting’ WORK.USPOP into the data step to be saved as POPDATA.USPOP, if you like. ***********************************************/ /********************************************** The above two steps could have been accomplished together: LIBNAME POPDATA 'c:\sasdata\usstate\’ DATA POPDATA.USPOP; MERGE POP85 USPOP; BY FIPS; *other lines of code beginning with KEEP...; RUN; **************************************************/ Example SAS Program Set: sasex2A.sas (3 of 3)

  17. Alabama 1AL ESC 63 3894 3444 3267 410 271 -233 178 75 294 16347 Alaska 2AK PAC 94 402 304 228 60 63 16 36 97 374 28395 Arizona 4AZ MTN 86 2718 1776 1306 243 231 228 712 62 305 19017 Arkansas 5AR WSC 71 2286 1924 1787 208 131 -71 232 69 279 14641 California 6CA PAC 93 23668 19971 15735 2123 1620 2113 2078 65 335 21537 Colorado 8CO MTN 84 2890 2211 1758 238 233 213 446 50 358 21279 Connecticut 9CT NE 16 3108 3033 2536 282 128 214 52 47 306 23149 . . . Wisconsin 55WI ENC 35 4706 4418 3952 461 274 4 14 66 299 20915 Wyoming 56WY MTN 83 470 332 330 42 42 -39 96 41 350 22430 RECORD FORMAT SHEET: File:state2.dat (PC) or state2.data (UNIX) Rec COLS Variable Type/Format 1 1-17 Name of State Alpha 1 18-20 Federal Info. Processing code num 1 21-23 State postal code Alpha 1 24-27 Census Bureau Division Alpha 1 28-30 Census Bureau State code num 1 31-36 Population in 1980 1000 1 37-42 Population in 1970 1000 1 43-48 Population in 1960 1000 1 50-54 Natural increase 1960-1970 1000 1 55-59 Natural increase 1970-1980 1000 1 60-64 Net migration 1960-1970 1000 1 65-69 Net migration 1970-1980 1000 2 1- 3 Percent Unemployed, 1980 .1 2 4- 8 Percent Aged 20 thru 39 .1 2 9-15 Median Family Income, 1980 num raw data data documentation STPOP2.DAT and STPOP2.DD printout of SAS Data set Check of Data Read In 11:19 Monday, July 15, 1996 36 OBS STATE FIPS ST DIV CB POP80 POP70 POP60 UNEMP80 AGE2040 INC80 1 Alabama 1 AL ESC 63 3894 3444 3267 7.5 29.4 16347 2 Alaska 2 AK PAC 94 402 304 228 9.7 37.4 28395 3 Arizona 4 AZ MTN 86 2718 1776 1306 6.2 30.5 19017 4 Arkansas 5 AR WSC 71 2286 1924 1787 6.9 27.9 14641 5 California 6 CA PAC 93 23668 19971 15735 6.5 33.5 21537

  18. 1165 1139 23 1156 998 948 33 977 535 520 50 530 5823 5746 25 5798 967 953 44 962 3175 3128 9 3154 17762 17575 36 17735 7568 7430 34 7515 11864 11883 42 11901 10745 10777 39 10752 5500 5484 18 5498 11538 11481 17 11511 9085 9118 26 9075 4775 4747 55 4766 4190 4133 27 4162 . . . 26358 24786 6 25622 522 446 2 500 1051 998 15 1039 Documentation for file: stpop85.dat Observations: States of the US Variables: Population, 7/1/1985 Population, 7/1/1982 FIPS code Population, 7/1/84 Free field format--variables separated by spaces STPOP85.DAT and STPOP85.dd(data and data documentation files) Data Data documentation

  19. 1 *read in some data from an O/S file 2 & create a temporary SAS data set called USPOP; 3 4 DATA USPOP; 5 INFILE 'p:\appsdata\briggs\poec5317\state2.dat'; 6 INPUT STATE $ 1-17 FIPS 18-20 ST $ 21-23 DIV $ 24-27 CB 28-30 POP80 31-36 POP70 37-42 POP60 43-48 7 #2 UNEMP80 3.1 AGE2040 5.1 @10 INC80 6.0; 8 /* describes the data in the file*/ 9 RUN; NOTE: The infile 'f:\public\poec5317\state2.dat' is: FILENAME=f:\public\poec5317\state2.dat, RECFM=V,LRECL=256 NOTE: 102 records were read from the infile 'p:\appsdata\briggs\poec5317\state2.dat'. The minimum record length was 80. The maximum record length was 80. NOTE: The data set WORK.USPOP has 51 observations and 11 variables. NOTE: The DATA statement used 2.08 seconds. 10 11 *it is good practice to print some of the data read and check it; 12 PROC PRINT DATA=USPOP(OBS=5); /* prints first five observations.*/ 13 TITLE 'Check of Data Read In'; 15 *read additional data into a second SAS data set called POP85; 16 17 FILENAME in1 'p:\appsdata\briggs\poec5317\stpop85.dat'; *assigns 'nickname' (in1) to file; 18 DATA POP85; 19 INFILE in1; 20 INPUT POP85 POP82 FIPS; 21 DROP POP82; 22 RUN; NOTE: The infile IN1 is: FILENAME=p:\appsdata\briggs\poec5317\stpop85.dat, RECFM=V,LRECL=256 NOTE: 51 records were read from the infile IN1. The minimum record length was 17. The maximum record length was 30. NOTE: The data set WORK.POP85 has 51 observations and 2 variables. NOTE: The DATA statement used 0.77 seconds. 23 24 sasex2A.log (1 of 2)

  20. *Now combine together our two data sets into a single ‘research’ data set; 25 26 *First, add the new data in the POP85 data set to the original USPOP; 27 28 PROC SORT DATA=POP85; BY FIPS; NOTE: The data set WORK.POP85 has 51 observations and 2 variables. NOTE: The PROCEDURE SORT used 0.5 seconds. 29 DATA USPOP; 30 MERGE POP85 USPOP; 31 BY FIPS; 32 RUN; NOTE: The data set WORK.USPOP has 51 observations and 12 variables. NOTE: The DATA statement used 0.7 seconds. 34 *now save the sas data set permanently; 35 36 LIBNAME POPDATA 'c:\sasdata\usstate\'; NOTE: Libref POPDATA was successfully assigned as follows: Engine: V611 Physical Name: C:\SASDATA\USSTATE 37 *specifies the subdirectory to use to save the SAS data sets; 38 DATA POPDATA.USPOP; *note two level name; 39 SET USPOP; *identifies source SAS data set; 40 KEEP STATE FIPS ST DIV POP85 POP80 POP70 POP60; * selects variables for inclusion; 41 LABEL STATE='Name of State' 42 FIPS='Federal Information Processing code' 43 ST='State postal code' 44 DIV='Census Bureau Division' 45 POP80='Population in 1980' 46 POP70='Population in 1970' 47 POP60='Population in 1960'; 48 RUN; NOTE: The data set POPDATA.USPOP has 51 observations and 8 variables. NOTE: The DATA statement used 0.77 seconds. sasex2A.log (2 of 2)

  21. The source of information for creating a SAS data set may be: data typed into the program file (‘in-stream’ data) use LINES & INPUT an Operating System (OS) raw data (flat) file on disk use INFILE & INPUT statements optionally FILENAME also a previous SAS data set created in the program use SET or MERGE a SAS data set saved on disk use two-level name with SET or MERGE LIBNAME to identify subdirectory Data newsas; input var1 var2; lines; raw data here SAS Action Overview:Sources of Info. (‘data’) for a SAS Data Set Data newsas; infile ‘c:\rawdata’; input var1 var2; Data newsas; set oldsas; Data newsas; merge oldsasA oldsasB; more info next page LIBNAME saslib ‘c:\sasdata\’; Data newsas; set saslib.oldsas;

  22. New SAS data set(s) can be created from existing SAS data set(s) by: transfering and reshaping using SET changing variables with KEEP, DROP and ASSIGN (# obs =) changing observations with IF, DELETE, OUTPUT (# obs <) merging with MERGE or UPDATE ('side by side') (# obs =) with BY statement (matched) without BY statement (unmatched) concatenating 2 or more with SET ('one after the other') (# obs >) sorting observations with PROC SORT (# obs =) integrating/combining observations with PROC SUMMARY (# obs <) Note: more than one data set can be created within one data step data sets can also be created by PROC steps. 1980 TX LA OK NM SAS Action Overview:Transforming SAS data sets Reshaping Data version2; SET version1; Data p8090; MERGE p80 p90; 1990 TX LA OK NM TX LA OK NM Merge TX LA cnty 1 cnty2 Concatenate Data Two; SET TX LA; cnty 1 cnty2 cnty 1 cnty2 cnty 1 cnty2 States NE MW S W Regions NE MW S W Summary

  23. To an O/S data file: ‘Flat files’ can be created from SAS data sets by using: FILE ('reverse' of INFILE) to identify the file optionally FILENAME also PUT ('reverse' of INPUT) to create the format of the file For printing: Many SAS procedures produce ‘printout.’ that is, they write information to the SAS Output window (or the file .lst in UNIX) in a format suitable for printing Use standard print commnds to get a paper copy (e.g. File /Print pull down menu on PC) PROC PRINT is no different from other PROCS as regards printing better name might be PROC DATASHOW Data _null_; set oldsas; file ‘c:\rawdata’; if _n_=1 then put‘var1, var2,var3’; put var1‘,’ var2‘,’ var3’,’; *creates file for export to spreadsheet; SAS Action Overview:Outputting Information

  24. Steps in debugging a program ASSUME THAT THE PROGRAM HAS NOT WORKED CORRECTLY! • correct all syntax problems (ERROR messages) • establish reason for all WARNING messages • check that every data set has the correct number of obs. and vars • are values on all variables reasonable • check against hard copy/data read in • no 500 kid families • run test data and hand-check calculations for at least three observations • first, last, one-in-between • be sure sample data includes missing values!

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