1. SAS Workshop SAS Data Management Hun Myoung Park, Ph.D.
University Information Technology Services
Center for Statistical and Mathematical Computing
Saturday, September 22, 2018
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2. Outline INPUT Statement: Input Styles INFILE Statement
SAS Data Management
September 22, 2018
Outline
INPUT Statement: Input Styles
INFILE Statement
PROC IMPORT/EXPORT
Data Manipulation
IF…ELSE & DO…END Clauses
Recode Variables
LABEL and RENAME Variables
Select Observations & Variables
Working with Data Sets
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3. SAS DATA SOURCES University Information Technology Services
SAS Data Management
September 22, 2018
SAS DATA SOURCES
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Center for Statistical and Mathematical Computing

4. DATA STEP DATA steps read and manipulate data.
SAS Data Management
September 22, 2018
DATA STEP
DATA steps read and manipulate data.
INPUT tells how SAS reads data.
DATALINES indicates data items to be read begin from the next line.
INFILE reads data from an external file.
LIBNAME sm ‘c:\temp\sas’;
DATA sm.grade0;
INPUT name $ id stat math;
DATALINES;
John …
RUN;
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5. INPUT STATEMENT There are six input styles.
SAS Data Management
September 22, 2018
INPUT STATEMENT
There are six input styles.
List INPUT: simply list variable names
Modified list INPUT: for ill-organized data
Column INPUT: location of data items
Formatted INPUT: format of data items
Named INPUT: variable=data
Mixed INPUT: combine input styles
SAS recognizes styles automatically.
List (previous slide), column, and formatted INPUT are commonly used.
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6. COLUMN INPUT Specify column locations of data items
SAS Data Management
September 22, 2018
COLUMN INPUT
Specify column locations of data items
$ follows a character variable name
Data should be aligned correctly
Some data may be skipped (id below)
DATA sm.grade1;
INPUT name $ 1-6 stat math 15-17;
DATALINES;
John
Rachel …
RUN;
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7. FORMATTED INPUT Specify formats of data items.
SAS Data Management
September 22, 2018
FORMATTED INPUT
Specify formats of data items.
Data should be aligned correctly.
$6. means a string 6 characters long.
3.0 or 3. means a 3 digit number without a decimal point.
DATA sm.grade2;
INPUT name $6. id 5. male 3. stat 3.0;
DATALINES;
John
Rachel …
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8. COLUMN CONTROLS @n moves the input pointer to the nth column.
SAS Data Management
September 22, 2018
COLUMN CONTROLS
@n moves the input pointer to the nth column.
+n shifts the input pointer by n column to the right.
You may skip some variables (e.g., id)
INPUT name $6. +5 stat math 3.;
DATALINES;
John
Rachel …
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9. LINE CONTROLS @ and @@ trailing hold input records
SAS Data Management
September 22, 2018
LINE CONTROLS
@ and trailing hold input records
INPUT name $ stat math
DATALINES;
John Ron
#n moves the input pointer to nth line, / moves the input pointer to the next line INPUT name $6. #2 stat 3. / math 3.;
John 89 95
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Center for Statistical and Mathematical Computing

10. SAS Data Management
September 22, 2018
USING INFORMAT
INFORMAT defines a format of data entry and FORMAT for data output
COMMA and PERCENT
INPUT income COMMA9. saving PERCENT3.;
DATALINES;
170,200 89%
92,540 95%
MMDDYY and DOLLAR
INPUT dates MMDDYY10. sales DOLLAR12.0;
10/01/ $343,750
10/05/2009 $9,784,650
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11. SAS Data Management
September 22, 2018
INFILE STATEMENT 1
INFILE specifies an external data file that is created in advance.
INFILE ‘c:\temp\sas\grade2.txt’;
INPUT name $6. id 5. stat math (3.);
If the data file contains missing values, add the MISSOVER option to INFILE.
The MISSOVER option treats all remaining variables without values as missing values.
INFILE ‘c:\temp\sas\grade2.txt’ MISSOVER;
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Center for Statistical and Mathematical Computing

12. SAS Data Management
September 22, 2018
INFILE STATEMENT 2
Alternatively, use FILENAME to make an alias of an external file.
Like LIBNAME, FILENAME makes it easy to referring a file name especially when the name and path are long.
FILENAME gFile ‘c:\temp\grade2.txt’;
DATA sm.grade2;
INFILE gFile MISSOVER;
INPUT name $6. id 5. stat math (3.);
RUN;
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Center for Statistical and Mathematical Computing

13. SAS Data Management
September 22, 2018
INFILE STATEMENT 3
DLM specifies a delimiter. More than one delimiter can be used. e.g., *iu*
DSD (Delimiter Sensitive Data) assumes a comma delimiter and is needed for missing values
INFILE DATALINES DLM=’,’ DSD;
INPUT name $ id stat math;
DATALINES;
John,10091,89,95
Rachel,10100,,99 …
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14. SAS Data Management
September 22, 2018
READ ODD STRINGS
What if a string variable is long and/or contain commas? Use ampersand (&)
INFILE DATALINES DLM=‘,’ DSD;
INPUT name : $20. title & $100.;
DATALINES;
Lindblom,”Still Muddling, Not Yet Through”
Park, “Reading “”Small is Beautiful”””
How to read quotation marks in a string? Use tilde(~)
INPUT name : $20 title ~ $100.;
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Center for Statistical and Mathematical Computing

15. SAS Data Management
September 22, 2018
READ THROUGH NETWORK
SAS can read external data files through TCP/IP (http and ftp)
FILENAME masil URL '
DATA sm.grade2;
INFILE masil FIRSTOBS=1; INPUT name $6. id 5. stat math (3.);
URL denotes HTTP (protocol)
FIRSTOBS=1 tells SAS to read observations from the 1st row
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16. VIEW A DATA SET PROC CONTENTS displays data structures of a data set.
SAS Data Management
September 22, 2018
VIEW A DATA SET
PROC CONTENTS displays data structures of a data set.
PROC CONTENTS DATA=sm.grade2; RUN;
PROC MEANS displays summary statistics of a data set.
PROC MEANS DATA=sm.grade2; RUN;
PROC PRINT displays values of variables in a data set.
PROC PRINT DATA=sm.grade2;
VAR stat math;
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17. SAS Data Management
September 22, 2018
PROC IMPORT 1
PROC IMPORT reads external files such as CSV, Excel, dBase, and Access.
FILENAME airline URL '
PROC IMPORT DATAFILE=‘airline’ OUT=sm.airline DBMS=CSV;
GETNAMES=YES;
DATAROW=2;
DBMS specifies the format of the file.
IMPORT Wizard is more user-friendly in MS- Windows. Click File->Import Data.
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18. PROC IMPORT 2 An example of reading an Excel file.
SAS Data Management
September 22, 2018
PROC IMPORT 2
An example of reading an Excel file.
PROC IMPORT DATAFILE="c:\airline.xls“
OUT=sm.airline2 DBMS=EXCEL2000;
SHEET=“sheet1";
GETNAMES=YES;
SHEET specifies a worksheet with a range of data to be read in an Excel file.
SHEET=“sheet1$A1:G91";
GETNAMES=YES reads variable names from the file.
CAUTION: Excel 2007 file should be saved as 2003 format for SAS 9.13.
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Center for Statistical and Mathematical Computing

19. SAS Data Management
September 22, 2018
PROC EXPORT
Export to a CSV file. DATA specifies a data set to be exported.
PROC EXPORT
DATA=sm.airline OUTFILE="c:\temp\airline.csv“
DBMS=CSV REPLACE;
Export to an Excel file. REPLACE overwrites the existing data set.
DATA=sm.ariline OUTFILE="c:\temp\airline2.xls“
DBMS=EXCEL2000 REPLACE;
RUN;
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20. DATA MANIPULATION Data sets are manipulated in DATA steps
SAS Data Management
September 22, 2018
DATA MANIPULATION
Data sets are manipulated in DATA steps
SET statement loads existing SAS data sets
DATA sm.grade7;
SET sm.grade2;
sum1 = stat+math;
sum2 = SUM(stat, math);
mean1 = (stat+math)/2;
mean2 = MEAN(stat, math);
RUN;
The result is stored into grade7 without changing anything in grade2
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Center for Statistical and Mathematical Computing

21. IF…THEN CLAUSE IF… THEN IF… THEN… ELSE IF… THEN… ELSE IF…
SAS Data Management
September 22, 2018
IF…THEN CLAUSE
IF… THEN
IF mean1 GT 90 THEN DELETE;
IF sum1 >= 98 THEN grade=‘A+’;
IF (stat>90 AND math>90) THEN grade=‘A’;
IF… THEN… ELSE
IF mean2 >= 98 THEN grade=‘A+’;
ELSE grade=‘A’;
IF… THEN… ELSE IF…
ELSE IF mean2>=92 THEN grade=‘A’;
ELSE IF mean2>=88 THEN grade=‘A-’;
ELSE grade=‘B’;
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22. DO LOOP DO…TO… END DO num= 4, 6, 9, 10; …; END;
SAS Data Management
September 22, 2018
DO LOOP
DO…TO… END
DO i=1 TO 100 BY 1;
random=RANNOR( );
OUTPUT sm.randomtest;
END;
DO num= 4, 6, 9, 10; …; END;
DO str=‘Mon’, ‘Tue’, ‘Wed’; …; END;
DO WHILE (n<=10); …; END;
DO OVER for an array variable
DO OVER arr; …; END;
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Center for Statistical and Mathematical Computing

23. SAS Data Management
September 22, 2018
IF & DO… END
This combination executes a list of statements in a block. Imagine { and } in C and most computer languages.
IF mean2 GT 90 THEN DO; …;
END;
ELSE DO;
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24. SAS Data Management
September 22, 2018
INPUT & DO… END
This combination enables you to read experiment data in an easy manner.
INPUT drug $
DO level=‘High’, ‘Medium’, ‘Low’;
INPUT symptom
OUTPUT;
END;
DATALINES;
Drug
Drug
Drug
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25. RECODE VARIABLES 1 Use operators and functions
SAS Data Management
September 22, 2018
RECODE VARIABLES 1
Use operators and functions
DATA sm.grade8;
SET sm.grade2;
random=RANNOR( );
id=_N_; /* serial observation number */
IF… THEN and Special Usage
IF age <= 20 THEN age2=0;
ELSE IF age<=30 THEN age2=1;
ELSE IF age<=40 THEN age2=2;
ELSE age2=3;
Age2 = (age>20)+(age>30)+(age>40);
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26. SAS Data Management
September 22, 2018
RECODE VARIABLES 2
ARRAY links between variables and corresponding arrays (temporary vars.)
Suppose trust has 1 through 5 and needs reverse recoding.
ARRAY arr trust;
DO OVER arr;
arr=6-arr;
END;
ARRAY arr(5) q1-q5;
DO i=1 TO 5;
arr(i)=6-arr(i);
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27. SAS Data Management
September 22, 2018
MULTIPLE RESPONSE
Suppose respondents are asked to choose three items and their choices are stored in the wide form from c1, c2, c3, respectively.
For frequency analysis, data need to be rearranged in to the long form using OUTPUT.
DATA sm.patient2;
SET sm.patient;
choice=c1; OUTPUT;
choice=c2; OUTPUT;
choice=c3; OUTPUT;
RUN;
The number of observations becomes N*3 .
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Center for Statistical and Mathematical Computing

28. RENAME VARIABLES Use the DATA statement in DATA Step.
SAS Data Management
September 22, 2018
RENAME VARIABLES
Use the DATA statement in DATA Step.
“old variable= new variable”
DATA sm.grade9( RENAME=(sum1=total1) );
SET sm.grade7; …
RUN;
Use the RENAME statement in a DATA step. “old variable= new variable”
DATA sm.grade10;
RENAME sum2=total2 mean2=average2;
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29. LABEL VARIABLES Variable labels
SAS Data Management
September 22, 2018
LABEL VARIABLES
Variable labels
SET sm.grade2;
LABEL stat=‘Statistics’ math=‘Math’;
Value labels using PROC FORMAT. PROC FORMAT;
VALUE yes_L 1=‘Yes’ 0=‘No’;
VALUE $male_L ‘M’=‘Male’ ‘F’=‘Female’;
A period in label name ($male_L.) may not be omitted in a FORMAT statement.
DATA sm.survey2;
SET sm.survey1;
FORMAT trust yes_L. male $male_L.;
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30. SELECT OBSERVATIONS Use the IF clause
SAS Data Management
September 22, 2018
SELECT OBSERVATIONS
Use the IF clause
Keep only obs that meet the condition
IF mean2 >= 90;
IF (stat GE 80 OR math GE 80);
Delete obs that meet the condition
IF mean2 LT 80 THEN DELETE;
IF (stat<80 AND math <80) THEN DELETE;
WHERE in DATA/PROC uses a subset of a data set w/o changing the data set
WHERE mean2 GE 90;
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31. SAS Data Management
September 22, 2018
SELECT VARIABLES
Use either KEEP or DROP statement; You may not use both in a DATA step.
DATA sm.grade15;
SET sm.grade7;
DROP sum1 mean1;
RUN;
In a DATA statement. Do not omit =.
DATA sm.grade16 (KEEP=sum2 mean2);
SET grade7;
DATA sm.grade17 (DROP=sum1 mean1);
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32. APPEND DATA SETS Use SET with a list of data sets to be appended.
SAS Data Management
September 22, 2018
APPEND DATA SETS
Use SET with a list of data sets to be appended.
DATA sm.grade20;
SET sm.grade12 sm.grade13;
You may use PROC APPEND or PROC DATASETS when the master data set is huge.
PROC APPEND BASE=sm.grade12 DATA=sm.grade13;
RUN;
BASE= specifies a master data set and DATA= a data set to be appended.
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33. SPLIT DATA SETS Use DATA statement. Do not omit = after DROP and KEEP.
SAS Data Management
September 22, 2018
SPLIT DATA SETS
Use DATA statement. Do not omit = after DROP and KEEP.
DATA sm.grade21 (DROP=math)
sm.grade22(DROP=stat);
SET sm.grade2; …
Use OUTPUT statement in IF… THEN… ELSE clause.
DATA …
SET sm.grade7;
IF mean2 GT 90 THEN OUTPUT sm.gradeHigh;
ELSE OUTPUT sm.gradeLow;
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Center for Statistical and Mathematical Computing

34. SAS Data Management
September 22, 2018
SORT DATA SETS
Sort data sets before using BY in a DATA/PROC step (e.g., match merge)
PROC SORT DATA=sm.grade21 OUT=grade23;
BY id;
PROC SORT by default sorts in a ascending order. For a descending order, add DESCENDING before the variable name
PROC SORT DATA=sm.grade22 OUT=sm.grade24;
BY id DESCENDING mean2;
RUN;
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35. MERGE DATA SETS Simple merge using MERGE.
SAS Data Management
September 22, 2018
MERGE DATA SETS
Simple merge using MERGE.
DATA sm.grade25;
MERGE sm.grade21 sm.grade24;
Match merge using MERGE and BY.
DATA sm.grade26;
MERGE sm.grade23 sm.grade24;
BY id; …
Be careful when data structure is different across data sets to be merged.
Can be used for updating data sets.
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36. SAS Data Management
September 22, 2018
UPDATE DATA SETS
UPDATE updates a data set using a transaction data set.
Data sets need to be sorted in advance.
DATA sm.surveyNew;
UPDATE sm.survey08 sm.survey10 UPDATEMODE=MISSINGCHECK;
BY id;
MISSINGCHECK prevents missing in the transaction file from replacing values in a master file.
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37. SAS Data Management
September 22, 2018
GET AGGREGATE DATA
PROC MEANS generates aggregate statistics into a data set.
PROC MEANS DATA=sm.airline;
VAR cost output;
CLASS airline;
OUTPUT OUT=sm.air_mean1 MEAN=costM outputM;
Variables costM and outputM are stored into a new data set air_mean1.
You may specify other statistics as well.
PROC MEANS DATA=sm.airline N SUM MEAN VAR;
VAR cost output fuel load;
OUTPUT OUT=sm.air_mean2;
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38. PROC DATASETS Display data sets in the library of interest.
SAS Data Management
September 22, 2018
PROC DATASETS
Display data sets in the library of interest.
PROC DATASETS LIBRARY=sm;
RUN;
The procedure can also manage (e.g., copy, rename, repair, delete) SAS files.
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39. SAS Data Management
September 22, 2018
RESOURCES
Burlew, Michele M Reading External Data Files Using SAS: Examples Handbook. Cary, NC: SAS Institute.
Long, J. Scott The Workflow of Data Analysis Using Stata. College Station, TX: Stata Press.
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Center for Statistical and Mathematical Computing