Ways to Create Variables

These are some of the most common ways that you can create variables in a DATA step:

In a DATA step, you can create a new variable and assign it a value by using it for the first time on the left side of an assignment statement. SAS determines the length of a variable from its first occurrence in the DATA step. The new variable gets the same type and length as the expression on the right side of the assignment statement.

When the type and length of a variable are not explicitly set, SAS gives the variable a default type and length, as shown in the examples in the following table.

If a variable appears for the first time on the right side of an assignment statement, SAS assumes that it is a numeric variable and that its value is missing. If no later statement gives it a value, SAS prints a note in the log that the variable is uninitialized.

When you read raw data in SAS by using an INPUT statement, you define variables based on positions in the raw data. You can use one of the following methods with the INPUT statement to provide information to SAS about how the raw data is organized:

See SAS Formats and Informats: Reference for more information about using each method.

The following example uses simple list input to create a SAS data set named GEMS and defines four variables based on the data provided:

data gems;
   input Name $ Color $ Carats Owner $;
   datalines;
emerald green 1 smith
sapphire blue 2 johnson
ruby red 1 clark
;

You can create a variable and specify its format or informat with a FORMAT or an INFORMAT statement. For example, the following FORMAT statement creates a variable named SALE_PRICE with a format of 6.2 in a new data set named SALES:

data sales;
   Sale_Price=49.99;  
   format Sale_Price 6.2;
run;

SAS creates a numeric variable with the name SALE_PRICE and a length of 8.

See SAS Formats and Informats: Reference for more information about using the FORMAT and INFORMAT statements.

You can use the LENGTH statement to create a variable and set the length of the variable, as in the following example:

data sales; 
   length Salesperson $20;
run; 

For character variables, you must use the longest possible value in the first statement that uses the variable, because you cannot change the length with a subsequent LENGTH statement within the same DATA step. The maximum length of any character variable in SAS is 32,767 bytes. For numeric variables, you can change the length of the variable by using a subsequent LENGTH statement.

When SAS assigns a value to a character variable, it pads the value with blanks or truncates the value on the right side, if necessary, to make it match the length of the target variable. Consider the following statements:

length address1 address2 address3 $ 200;
address3=address1||address2;

Because the length of ADDRESS3 is 200 bytes, only the first 200 bytes of the concatenation (the value of ADDRESS1) are assigned to ADDRESS3. You might be able to avoid this problem by using the TRIM function to remove trailing blanks from ADDRESS1 before performing the concatenation, as follows:

address3=trim(address1)||address2;

For more information, see LENGTH Statement in SAS Statements: Reference.

The ATTRIB statement enables you to specify one or more of the following variable attributes for an existing variable:

If the variable does not already exist, one or more of the FORMAT=, INFORMAT=, and LENGTH= attributes can be used to create a new variable. For example, the following DATA step creates a variable named FLAVOR in a data set named LOLLIPOPS:

data lollipops;
   Flavor="Cherry";
   attrib Flavor format=$10.;
run;

The IN= data set option creates a special Boolean variable that indicates whether the data set contributed data to the current observation. The variable has a value of 1 when true, and a value of 0 when false. You can use IN= on the SET, MERGE, and UPDATE statements in a DATA step.

The following example shows a merge of the OLD and NEW data sets where the IN= option is used to create a variable named X that indicates whether the NEW data set contributed data to the observation:

data master missing;
   merge old new(in=x);
   by id;
   if x=0 then output missing;
   else output master;
run;