Language Reference

REPLACE Statement

replaces values in observations and updates observations

REPLACE <range> <VAR operand> <WHERE(expression)>;

The inputs to the REPLACE statement are as follows:

range

specifies a range of observations.

operand

selects a set of variables.

expression

is evaluated for being true or false.

The REPLACE statement replaces the values of observations in a SAS data set with current values of IML matrices with the same name. Use the range, VAR, and WHERE arguments to limit replacement to specific variables and observations. Replacement matrices should be the same type as the data set variables. The REPLACE statement uses matrix elements in row order replacing the value in the th observation with the th matrix element. If there are more observations in range than matrix elements, the REPLACE statement continues to use the last matrix element.

For example, the following statements cause all occurrences of ILL to be replaced by IL for the variable STATE:

  
    state="IL"; 
    replace all var{state} where(state="ILL");
 

You can specify a range of observations with a keyword or by record number using the POINT option. You can use any of the following keywords to specify a range:

ALL

all observations

CURRENT

the current observation

NEXT <number>

the next observation or the next number of observations

AFTER

all observations after the current one

POINT operand

observations by number, where operand can be one of the following:

Operand	Example
a single record number	point 5
a literal giving several	point {2 5 10}
record numbers
the name of a matrix	point p
containing record numbers
an expression in parentheses	point (p+1)

If the current data set has an index in use, the POINT option is invalid.

You can specify a set of variables to use with the VAR clause. The variables argument can have the following values:

• a literal containing variable names
• the name of a matrix containing variable names
• an expression in parentheses yielding variable names
• one of the keywords described in the following list:

  _ALL_

  for all variables
  
  

  _CHAR_

  for all character variables
  
  

  _NUM_

  for all numeric variables

The following examples demonstrate each possible way you can use the VAR clause.

  
    var {time1 time5 time9}; /* a literal giving the variables */ 
    var time;                /* a matrix containing the names  */ 
    var('time1':'time9');    /* an expression                  */ 
    var _all_;               /* a keyword                      */
 

The WHERE clause conditionally selects observations, within the range specification, according to conditions given in the clause. The general form of the WHERE clause is

WHERE( variable comparison-op operand)

In the preceding statement,

variable

is a variable in the SAS data set.

comparison-op

is any one of the following comparison operators:

<

less than

<=

less than or equal to

=

equal to

>

greater than

>=

greater than or equal to

^=

not equal to

?

contains a given string

^?

does not contain a given string

=:

begins with a given string

=*

sounds like or is spelled like a given string

operand

is a literal value, a matrix name, or an expression in parentheses.

WHERE comparison arguments can be matrices. For the following operators, the WHERE clause succeeds if all the elements in the matrix satisfy the condition:

^=   ^?   <   <=   >   >=

For the following operators, the WHERE clause succeeds if any of the elements in the matrix satisfy the condition:

=   ?   =:   =*

Logical expressions can be specified within the WHERE clause by using the AND (&) and OR (|) operators. The general form is

	clause&clause	(for an AND clause)
	clause|clause	(for an OR clause)

where clause can be a comparison, a parenthesized clause, or a logical expression clause that is evaluated by using operator precedence.

Note: The expression on the left-hand side refers to values of the data set variables, and the expression on the right-hand side refers to matrix values.

The following statement replaces all variables in the current observation:

  
    replace;