Working with strings

Last updated: Feb 11, 2025

Working with strings (SPSS Modeler)

There are a number of operations available for strings.

Converting a string to uppercase or lowercase—uppertolower(CHAR).
Removing specified characters, such as `ID_` or `$`, from a string variable—stripchar(CHAR,STRING).
Determining the length (number of characters) for a string variable—length(STRING).
Checking the alphabetical ordering of string values—alphabefore(STRING1, STRING2).
Removing leading or trailing white space from values—trim(STRING), trim_start(STRING), or trimend(STRING).
Extract the first or last n characters from a string—startstring(LENGTH, STRING) or endstring(LENGTH, STRING). For example, suppose you have a field named item that combines a product name with a four-digit ID code (ACME CAMERA-D109). To create a new field that contains only the four-digit code, specify the following formula in a Derive node:
```
endstring(4, item)
```
Matching a specific pattern—STRING matches PATTERN. For example, to select persons with "market" anywhere in their job title, you could specify the following in a Select node:
```
job_title matches "*market*"
```
Replacing all instances of a substring within a string—replace(SUBSTRING, NEWSUBSTRING, STRING). For example, to replace all instances of an unsupported character, such as a vertical pipe ( | ), with a semicolon prior to text mining, use the replace function in a Filler node. Under Fill in fields in the node properties, select all fields where the character may occur. For the Replace condition, select Always, and specify the following condition under Replace with.
```
replace('|',';',@FIELD)
```
Deriving a flag field based on the presence of a specific substring. For example, you could use a string function in a Derive node to generate a separate flag field for each response with an expression such as:

hassubstring(museums,"museum_of_design")

See String functions for more information.

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