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%Include: If you run a program containing the %INCLUDE statement, the SAS System executes any statements or data lines that you bring into the program. Statements are executed immediately. 

Syntax: 

Here,

• Source(s) specify the location of the information that you wish to access with the %INCLUDE statement.
• SOURCE2 causes the SAS log to show the source statements being used in your SAS program.
• S2=length specifies the length of the input record.
• Option-list specifies options that can be included in %INCLUDE.

%Eval: Integer arithmetic is used to evaluate arithmetic or logical expressions. %EVAL accepts only INTEGERS as operands in arithmetic expressions. Operands with floating-point values cannot be used in %EVAL arithmetic calculations. %SYSEVALF can be used in these cases.  

Syntax: %EVAL(arithmetic/logical-expression)

Example: 

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In SAS programming, USING an INFILE STATEMENT identifies an external file containing the data, WHEREAS using an INPUT statement describes the variables used. 

Syntax of INFILE: INFILE 'filename';

Syntax of INPUT: INPUT 'varname1' 'varname2';

Example:  

The PROC SORT command can be used to sort data in SAS. The command can be used for multiple VARIABLES within a program. It creates a new DATASET with sorting and keeps the original dataset unchanged. 

Syntax: 

Here, 

• Variable_name represents the column name on which sorting happens.
• Original represents the dataset name to be sorted.
• Sorted represents the dataset name after it is sorted.

PROC SORT in SAS enables the removal of duplicate values from a table primarily by utilizing TWO options: 

• NODUP
• NODUPKEY

NODUP VS NODUPKEY -

Below are two ways to delete duplicate values in SAS: 

• The use of nodups in the procedure:

The NODUPRECS (or NODUPREC or NODUP) option of PROC SORT identifies observations with identical values for all columns and REMOVES them from the output DATA set.

• The use of PROC SQL in the procedure:

PROC SQL can be used to remove duplicates. The DISTINCT keyword is used in the SELECT CLAUSE to ACCOUNT for duplicate observations.

Occasionally, multiple observations need to be CREATED from a single RECORD of raw data. In ORDER to specify how SAS will READ such a record, you can use the double trailing at-sign ( or "double trailing @").  By using a double trailing , SAS is told to "hold the line more strongly". A double trailing sign () directs SAS not to advance to another input record, but to hold the CURRENT input record for the next input statement. 

It is important to note that the single trailing @ does not hold an input record for subsequent Iterations of the data step. A trailing "@" indicates that an input record will only be held for this iteration of the data step (until the processing returns or gets back to the top of the data step), or that it will be passed to the next INPUT statement without a single trailing "@". 

The code below illustrates how to specify the number of iterations and SPECIFIC conditions within a single do loop. The ITERATIVE DO statement executes the DO loop until the Sum is greater than or EQUAL to 50000, or until the DO loop has executed 10 times, WHICHEVER comes first. 

TRANRWD, when APPLIED to a character string, replaces or eliminates all occurrences of a substring. By USING TRANWRD, you can scan for words (or patterns of characters) and replace them with a second word (or pattern of characters).  

Syntax:   

TRANWRD(source, target, replacement)  

Here,  

• The source is a character constant, VARIABLE, or expression you wish to translate.
• The target is an expression, constant, or variable searched in the source.
• Replacement specifies an expression, constant, or variable that will replace target.

Example:    
name : MRS. JOHNY Lever  
name=tranwrd(name, "Mrs.", "Ms.");   
Result : Ms. Johny Lever 

In a data STEP, SYMGET returns a macro VARIABLE's value. Conversely, the primary FUNCTION of SYMPUT is to STORE the value of the data set in a macro variable. 

Syntax of Symput: 

CALL SYMPUT(macro-variable, value);

Syntax of SYMGET: 

SYMGET(argument)

Example: In the following PROGRAM we have created a macro variable and then we have used the symput function to put the value where our key is 'avar' and then we have used the symget function to get the micro variable value.

proc MIXED data=SASHELP.IRIS plots=all; MODEL petallength= /; class species; run;

Basically, it is a SYNTAX error. In all cases, the MODEL STATEMENT MUST appear after the CLASS statement.

SAS Procedures: They PROCESS data in SAS data SETS to create statistics, tables, reports, charts, and plots, as well as to perform other analyses and operations on the data. All types of statistical analysis can be performed using SAS procedures. Execution of a procedure is TRIGGERED by the keyword PROC, which starts the step. Here are some SAS PROCs: 

• PROC SORT
• PROC MEAN
• PROC SQL
• PROC COMPARE
• PROC REPORT
• PROC FREQ, etc.

SAS Functions: There are many built-in functions in SAS that aid in the analysis and processing of data. You USE them in DATA statements. Different functions take different numbers of ARGUMENTS. Here is a list of SAS functions: 

• SCAN()
• NPUT()
• SUBSTR()
• COUNTC()
• COMPRESS(), etc.

Proc SUMMARY and Proc MEANS are essentially the same methods for CALCULATING descriptive statistics, such as mean, count, sum, median, etc. Also, it is capable of calculating several other metrics such as percentiles, quartiles, variances, standard deviations, and t-tests. N, MIN, MAX, MEAN, and STD DEV are the default statistics produced by PROC MEANS.  

• They differ mainly in the output TYPE they PRODUCE by default. Unlike PROC SUMMARY, PROC MEANS by default prints output in the LISTING window or other open destination. When the print option is included in the Proc SUMMARY statement, the results will be printed to the output window.
• By default, PROC MEANS takes into account all of the numerical variables in the STATISTICAL analysis. PROC SUMMARY, on the other hand, takes into account all of the variables described in the VAR statement in the statistical analysis.

There are a number of SAS System options that users can USE to troubleshoot macro problems and issues. Macro-option results are automatically shown in the SAS Log.  

• MEMRPT: Displays memory usage statistics in the SAS logs.
• MERROR: SAS will issue a warning if we attempt to invoke a macro that SAS does not recognize. Whenever there is a misspelling or if a macro is not defined, warning messages are displayed.
• MLOGIC: SAS PRINTS details about the macro EXECUTION in its log. In short, it identifies and displays micro logic.
• MPRINT: When you execute a macro CODE, SAS doesn't show it in the LOG file, but when you use the MPRINT option it displays all the SAS statements of the resolved macro code. With the MPRINT option, one statement per LINE is printed along with the corrected macro code.
• SYMBOLGEN: It prints a message in the LOG file about how a macro variable is resolved. Specifically, a message is printed in the LOG whenever a macro variable is resolved.

%LET: %Let is GENERALLY used to create MICRO variables and assign values to them. You can define it inside or OUTSIDE a macro. 

Syntax: %LET macro-variable-name = value;

Any number, text or date can be entered in the Value field, depending on what the program requires.  

How to use the Micro Variable?

Whenever referencing macro variables, an AMPERSAND (&) is used followed by the macro variable name as shown below: 

& <Macro variable Name>

Macro Parameters: Macros have variables called parameters whose values you set when you invoke the macro. The parameters are added to a macro by naming them in parenthesis in %macro.

Syntax: 

How to call a Macro?

To call/use micro variables, we use % followed by the macro variable name and then pass parameters.
%macro_name(par1,par2,....parn);

The FOLLOWING are some WAYS to create macro variables: 

• %LET
• %Global
• Call Symput
• Proc SQL into clause
• Macro Parameters

Macro is a group of SAS statements (program) that automates repetitive tasks. With SAS's Macros feature, we can avoid repeating SECTIONS of code and use them again and again when needed without having to type them again and it increases readability also. Automation makes your work faster because you don't have to write the same lines of code every day. %MACRO and %MEND are the start and end statements of a macro program. These can be reused multiple times. The SAS program declares them at the beginning and then calls them out during the body of the program when needed.

Macro variables contain a VALUE that will be used over and over again by SAS PROGRAMS. With a maximum of 65534 characters, macro variables are one of SAS's most powerful tools. They can be either global or local in scope. The % Local macro variable is a variable that can be defined and accessed inside macro programs only. The %Global macro variable is defined in OPEN code (outside of the macro program) and can be accessed from any SAS program running in the SAS environment. 

Syntax: The local variables are declared in the following syntax. 

In the following program, we have created the Macro variable in which we pass the parameters comma-separated and then we have written the Macro statement followed by the %MEND statement. After that, we have called the macro program by passing the parameters.