1. Introduction to SAS Essentials Mastering SAS for Data Analytics
Alan Elliott and Wayne Woodward

2. Class 1, Session 2 Alan Elliott
Intro to SAS Chapter 2
Class 1, Session 2
Alan Elliott

3. LEARNING OBJECTIVES To enter data using freeform list input
To enter data using the compact method
To enter data using column input
To enter data using formatted input
To enter data using the INFILE technique
To enter multiple-line data

5. 2.1 Using SAS Data Steps
The DATA step is used to define a SAS data set, and to manipulate it and prepare it for analysis.
In the SAS language, the DATA statement signals the creation of a new data set. For example, a DATA statement in SAS code may look like this:
DATA MYDATA;

6. DATA Statement Signals the beginning of the DATA step.
Assigns a name (of your choice) to the data set created in the DATA Step. The general form of the DATA statement is:
DATA datasetname;

7. Temporary Data Set Names
The SAS “datasetname” in the DATA statement can have several forms:
The SAS datasetname can be a single name (used for temporary data sets, kept only during current SAS session). For example:
DATA EXAMPLE;
DATA OCT2007;

8. Permanent Data Set Names
Or, the SAS datasetname can be a two-part name. The two-part name tells SAS that this permanent data set will be stored on disk beyond the current SAS session in a SAS “library” indicated by the prefix name. For example:
DATA RESEARCH.JAN2016;
DATA CLASS.EX1;
DATA JONES.EXP1;

9. Windows Data Set Names
A SAS data set name can also refer directly to the Windows name of a file on your hard disk. For example:
DATA “C:\SASDATA\SOMEDATA”;
DATA “C:\MYFILES\DECEMBER\MEASLES”;
(note these refer to SAS data set files with .sas7bdat extensions – thus SOMEDATA.SAS7BDAT and MEASLES.SAS7BDAT)

10. Tasks done within the DATA Step
DATA datasetname;
<code that defines the variables in the data set>;
<code to enter data>;
<code to create new variables>;
<code to assign missing values>;
<code to output data>;
<code to assign labels to variables>;
<and other data tasks>;

11. 2.2 Understanding SAS data set structureID
SBP
DBP
GENDER
AGE WT
obs 1
001
120 80 M 15
115
obs 2
002
130 70 F 25
180
... .
obs 100
100
125 20
110
Columns are data variables (each named) and rows are subjects, observations, or records.

12. Columns and Rows
Each column represents a variable and is designated with a variable name (ID, SBP, etc.) Every SAS variable (column) must have a name, and the names must follow certain naming rules.
Each row, marked here as obs1, obs2, etc., indicate observations or records. An observation consists of data observed from one subject or entity.

13. 2.3 Rules for SAS variable names
must be 1‑32 characters long – but must not include any blanks.
must start with the letters A through Z or the _ (underscore). A name cannot include a blank.
may include numbers (but not as first character in name).
may include upper and lower case characters (variable names are case insensitive).
should be descriptive of the variable (optional but recommended).

14. Correct & Incorrect variable names
Correct SAS variable names are
GENDER AGE_IN_1999
AGEin _OUTCOME_HEIGHT_IN_CM
WT_IN_LBS
Incorrect SAS variable names are (WHY?)
AGE IN MeaslesCount
S S Number Question 5
WEIGHT IN KG AGE-In-2000

15. 2.4 Understanding SAS Variable Types
Numeric Variables (Default): A numeric variable is used to designate values that could be used in arithmetic calculations or are grouping codes for categorical variables.
For example, the variables SBP (systolic blood pressure), AGE, and WEIGHT are numeric. However, an ID number, phone number, or Social Security number should not be designated as a numeric variable. For one thing, you typically would not want to use them in a calculation.
Moreover, for ID numbers, if ID = were stored as a number, it would lose the zeros and become 12.

16. Character (Text, String) Variables
Character (Text, String) Variables: Character variables are used for values that are not used in arithmetic calculations.
For example, a variable that uses M and F as codes for gender would be a character variable. For character variables, case matters, because to the computer a lowercase f is a different character from an uppercase F. It is important to note that a character variable may contain numerical digits.
As mentioned previously, a Social Security number (e.g., ) or an ID number (e.g., ) should be designated as a character variable because their values should never be used in mathematical calculations.
When designating a character variable in SAS, you must indicate to SAS that it is of character type. This is shown in upcoming examples.

17. Date Variables
Date Variables: A date value may be entered into SAS using a variety of formats, such as 10/15/09, 01/05/2010, JAN052010, and so on. As you will see in upcoming examples, dates are handled in SAS using format specifications that tell SAS how to read or display the date values. For more information about dates in SAS, see Appendix B.
Technically, dates are integers. We’ll learn more about dates, and how to manipulate them, later.

18. 2.5 Methods of reading data into SAS
Reading data using freeform list input
Reading data using the compact method
Reading data using column input
Reading data using formatted input.

19. Freeform Data Entry Open the file DFREEFORM.SAS DATA MYDATA;
The INPUT statement defines the variables (some character, designated by $ after name.)
Open the file DFREEFORM.SAS
DATA MYDATA;
INPUT ID $ SBP DBP GENDER $ AGE WT;
DATALINES; M F M F
F ; ;
PROC PRINT;
RUN;
DATALINE indicates that data are listed next.
The data must match the INPUT statement – the same number of values per line, separated with blanks.
DATA ends with a semicolon.

20. Data set created from code
Obs ID
SBP
DBP
GENDER
AGE WT 1
001
120 80 M 15
115 2
002
130 70 F 25
180 3
003
140
100 89
170 4
004 20
150 5
125
110

21. Advantages of freeform list input
Easy, very little to specify.
No rigid column positions which makes data entry easy.
If you have a data set where the data are separated by blanks, this is the quickest way to get your data into SAS.

22. Restrictions for freeform list input
Every variable on each data line must be in the order specified by the INPUT statement.
Fields must be separated by at least one blank.
Blank spaces representing missing variables are not allowed. Having a blank space in the data causes values to be out of sync. If there are missing values in the data, a dot (.) should be placed in the position of that variable in the data line. For example, a data line with AGE missing might read:
F . 150
No embedded blanks are allowed within the data value for a character field, like MR ED.
A character field has a default maximum length of 8 characters in freeform input.

23. Compact Data Format
The symbol in the INPUT statement tells SAS to allow multiple rows of data on each line. You must be careful that the data matches the input definition.
DATA WEIGHT; INPUT TREATMENT LOSS DATALINES; ; PROC PRINT; RUN;

24. Hands-On Example p 27
1. Open the program file DFREEFORM.SAS. (The code was shown above.) Run the program. 2. Observe that the output listing (shown here) illustrates the same information as in Table 2.4. Etc…

25. Column Input (This is DCOLUMN.SAS) DATA MYDATA;
INPUT ID $ 1-3 SBP 4-6 DBP 7-9
GENDER $ 10 AGE WT 13-15;
DATALINES;
M15115
F25180
M89170
F30150
F20110 ;
RUN;
Note how data are in specific columns. In the INPUT statement, the columns are specified by the ranges following a variable name.
INPUT variable startcol‑endcol ...;

26. Advantages of column input
Data fields can be defined and read in any order in the INPUT statement and unneeded columns of data can be skipped.
Blanks are not needed to separate fields.
Character values can range from 1 to 200 characters. For example:
INPUT DIAGNOSE $ 1‑200;
For character data values, embedded blanks are no problem, e.g., John Smith
Input only the variables you need -- skip the rest. This is handy when your data set (perhaps downloaded from a large database) contains variables you’re not interested in using. Only read the variables you need.

27. Rules and restrictions for column Input
Data values must be in fixed column positions.
Blank fields are read as missing.
Character fields are read right justified in the field.
Column input has more specifications than list input. You must specify the column ranges for each variable.

28. How SAS interprets column data
INPUT GENDER $ 1‑3; M
M ---> All read as M

29. Numbers in Columns INPUT X 1‑6; 1 2 3 4 5 6 7 READ AS 2 3 0 230
READ AS
E E1 or 23

30. Hands-On Exercise p 31 (DCOLUMN.SAS)
DATA MYDATA; INPUT ID $ 1-3 SBP 4-6 DBP 7-9 GENDER $ 10 AGE WT 13-15; DATALINES; M F M F F20110 ; RUN; PROC PRINT DATA=MYDATA;

31. Reading Data Using Formatted Input
DATA MYDATA;
variable1 variable2 format. ...;
Example:
DATA MYDATA
SBP DBP GENDER $1. @8 WT OWE COMMA9.;
   
Note the difference in the INPUT statement.

32. Three Components In Formatted Input
@1 SBP 3.
is the starting column “pointer” means start in column 1.
The variable name.
The “informat” defines what kind of data to input. In this case “3.” indicates an integer with at most 3 digits.

33. Input Formats Table 2.6, p 33 Informat Meaning 5.
Five columns of data as numeric data.
$5.
Character variable with width 5, removing leading blanks.
$CHAR5.
Character variable with width 5, preserving leading blanks.
COMMA7.
Seven columns of numeric data and strips out any commas or dollar signs (i.e., $40,000 is read as 40000).
COMMA10.2
Reads 10 columns of numeric data with 2 decimal places (strips commas and dollar signs.) $19, is read as
MMDDYY8.
Date as 01/12/16. (Watch out for Y2K issue.)
MMDDYY10.
Date as 04/07/2016
DATE7.
Date as 20JUL16
DATE9.
Date as 12JAN2016. (No Y2K issue.)

34. Informats & Formats In SAS
INFORMATS are used to read data into a SAS data set
FORMATS are used to specify how to output (write) data values
Most Format specifications (such as MMDDYY10.) can be used as EITHER an informat or a format.

35. More about formats
Formats must end with a dot (.) or a dot followed by a number
5. : A number up to five digits, no decimals, so could take on values from to
5.2 : A number up to five digits, and up to 2 decimals – so could take on values from to 99.99
$5. : A character value of up to five digits, such as ABCDE, abcde, or (*&6%

36. Advantages & restrictions for using formatted input
Advantages and restrictions are similar to those for column input.
The primary difference is the ability to read in data using INFORMAT specifications.
Is particularly handy for reading dates and dollar values.
Restrictions are similar to those for column input.

37. Hands-On Exercise, p 36 (DINFORMAT.SAS)
DATA MYDATA;
SBP DBP
GENDER WT OWE COMMA9.;
DATALINES;
120 80M115 $5,431.00
130 70F180 $12,122
140100M
120 80F150 4,523.2
125 80F110 $ ;
PROC PRINT DATA=MYDATA;
RUN;

38. Some Common Output Formats
Compare these to the INPUT formats listed earlier.

39. Using the SAS INFORMAT Statement
There is a SAS statement named INFORMAT that you could use in the freeform data entry case. For example, (see p 37)
DATA PEOPLE;
INFORMAT LASTNAME FIRSTNAME $12. AGE 3. SCORE 4.2;
INPUT LASTNAME FIRSTNAME AGE SCORE;
DATALINES;
Lincoln George
Ryan Lacy ;
PROC PRINT DATA=PEOPLE;
RUN;
In this case, the INFORMAT statement can specify that a freeform text value is longer than the default eight characters.

40. Reading External Data Using INFILE
Suppose you have text data in a file in this format
101 A
102 A
104 B
110 A
How can you read this data into SAS?

41. INFILE Statement
INSTEAD of the DATALINES statement (followed by data), you use the INFILE Statement:
DATA MYDATA;
INFILE 'C:\SASDATA\EXAMPLE.DAT';
INPUT ID $ 1-3 GP $ 5 AGE 6-9
TIME TIME TIME ;
RUN;
PROC MEANS;
INFILE replaces DATALINES, and defines where the data are located on disk.
NOTE: There is no DATALINES statement. This is where the DATA step ends and the PROC step begins.

42. DATALINES vs INFILE
When data are in the program code: Use DATALINES statement
When data are read from external source: Use INFILE statement.
ALSO NOTE: Do not confuse INFILE with the INPUT statement.

43. Hands-On Example p 38 (DINFILE1.SAS)
DATA MYDATA;
INFILE 'C:\SASDATA\EXAMPLE.TXT';
INPUT ID $ 1-3 GP $ 5 AGE 6-9
TIME TIME TIME ;
PROC MEANS DATA=MYDATA;
RUN;
RESULTS

44. 2.6 Going Deeper – More Techniques
Reading Multiple Records per Observation
If your data for each record extends multiple lines: You can use more than one INPUT statement
INPUT ID $ SEX $ AGE WT;
INPUT SBP DBP BLDCHL;
INPUT OBS1 OBS2 OBS3;
Or you can read the data using the / (advance) indicator:
INPUT ID $ SEX $ AGE WT/ SBP DBP BLDCHL/ OBS1 OBS2 OBS3;

45. Hands-On Example p 40. (DMULTILINE.SAS)
DATA MYDATA;
INPUT ID $ SEX $ AGE WT/ SBP DBP BLDCHL/
OBS1 OBS2 OBS3;
DATALINES;
10011 M
10012 F
10013 M ;
PROC PRINT DATA=MYDATA;
RUN;
RESULTS

46. Input Pointer Controls

47. Using Advanced INFILE Options
DLM: This option allows you to define a delimiter to be something other than a blank. For example, if data are separated by commas, include the option DLM = ‘,’ in the INFILE statement.
FIRSTOBS= n :Tells SAS on what line you want it to start reading your raw data file. This is handy if your data file contains one or more header lines or if you want to skip the first portion of the data lines.
OBS= n :Indicates which line in your raw data file should be treated as the last record to be read by SAS.
See Table 2.13 p 41 for more options

48. Hands-On Example, p 42 (DINFILE2.SAS)
DATA MYDATA;
INFILE 'C:\SASDATA\EXAMPLE.CSV' DLM=', '
FIRSTOBS=2 OBS=26;
INPUT GROUP $ AGE TIME1 TIME2 TIME3 Time4 SOCIO;
PROC MEANS;
RUN;

49. Hands On Exercise DINFILE3.SAS p 43
Note strange delimiter
Open the program file DINFILE3.SAS.
DATA PLACES;
INFILE DATALINES DLMSTR='!∼!';
INPUT CITY $ STATE $ ZIP;
DATALINES;
DALLAS!∼!TEXAS!∼!75208
LIHUE!∼!HI!∼!96766
MALIBU!∼!CA!∼!90265 ;
PROC PRINT;
Etc…

50. Input a data set where there are blanks
This is a ruler.

51. Do Hands On Example p 44 (DINFILE4.SAS)
Note TRUNCOVER
DATA TEST;
INFILE "C:\SASDATA\DINFILEDAT.TXT" TRUNCOVER;
INPUT LAST $1-21 FIRST $ 22-30
ID $ ROLE $ 37-44;
RUN;
PROC PRINT DATA=TEST;RUN;

52. Summary
One of the most powerful features of SAS, and a reason it is used in many research and corporate environments, is that it is very adaptable for reading in data from a number of sources. This chapter showed only the tip of the iceberg. More information about getting data into SAS is provided in the following chapter. For more advanced techniques, see the SAS documentation.

53. These slides are based on the book:
Introduction to SAS Essentials Mastering SAS for Data Analytics, 2nd Edition
By Alan C, Elliott and Wayne A. Woodward
Paperback: 512 pages
Publisher: Wiley; 2 edition (August 3, 2015)
Language: English
ISBN-10:  X
ISBN-13: 
These slides are provided for you to use to teach SAS using this book. Feel free to modify them for your own needs. Please send comments about errors in the slides (or suggestions for improvements) to Thanks.