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STARTSWITH Function

Returns true if the leftmost set of characters of a column of values matches a pattern. The source value can be any data type, and the pattern can be a Wrangle , regular expression, or a string.

  • The STARTSWITH function is ideal for matching based on patterns for any data type. If you need to match strings using a fixed number of characters, you should use the LEFT function instead. See LEFT Function.

  • See ENDSWITH Function.

Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

Basic Usage

String literal example:

startswith(FullName,'Mr.')

Output: Returns true if the first three letters of the FullName column value are "Mr.".

Wrangle example:

startswith(CustId,`{alpha-numeric}{6}`)

Output: Returns true if the CustId column begins with a six-digit alpha-numeric sequence. Otherwise, the value is set to false.

Regular expression example:

if(startswith(phone,/^(\+0?1\s)?\(?\d{3}\)?[\s.-]\d{3}[\s.-]\d{4}$/),'phone - ok','phone - error')

Output: Returns phone - ok if the value of the phone column begins with a value that matches a 10-digit U.S. phone number. Otherwise, the output value is set to phone - error.

Syntax and Arguments

startswith(column_any,pattern[,ignore_case])

Argument

Required?

Data Type

Description

column_any

Y

any

Name of the column to be applied to the function

pattern

Y

string

Pattern or literal expressed as a string describing the pattern to which to match.

ignore_case

N

string

Whentrue, matching is case-insensitive. Default isfalse.

For more information on syntax standards, see Language Documentation Syntax Notes.

column_any

Name of the column to be searched.

  • Multiple columns and wildcards are not supported.

Usage Notes:

Required?

Data Type

Example Value

Yes

Column reference

myColumn

pattern

Wrangle , regular expression, or string literal to locate in the values in the specified column.

Usage Notes:

Required?

Data Type

Example Value

Yes

String

`{zip}`

ignore_case

When true, matches are case-insensitive. Default is false.

Nota

This argument is not required. By default, matches are case-sensitive.

Usage Notes:

Required?

Data Type

Example Value

No

String value

'false'

Examples

Dica

For additional examples, see Common Tasks.

Example - STARTSWITH and ENDSWITH Functions

This example demonstrates functions that can be used to evaluate the beginning and end of values of any type using patterns.

Functions:

Item

Description

STARTSWITH Function

Returns true if the leftmost set of characters of a column of values matches a pattern. The source value can be any data type, and the pattern can be a Wrangle , regular expression, or a string.

ENDSWITH Function

Returnstrueifthe rightmost set of characters of a column of values matches a pattern. The source value can be any data type, and the pattern can be a Wrangle , regular expression, or a string.

Source:

The following inventory report indicates available quantities of product by product name. You need to verify that the product names are valid according to the following rules:

  • A product name must begin with a three-digit numeric brand identifier, followed by a dash.

  • A product name must end with a dash, followed by a six-digit numeric SKU.

Source data looks like the following, with the Validation column having no values in it.

InvDate

ProductName

Qty

Validation

04/21/2017

412-Widgets-012345

23

04/21/2017

04-Fidgets-120341

66

04/21/2017

204-Midgets-4421

31

04/21/2017

593-Gidgets-402012

24

Transformation:

In this case, you must evaluate the ProductName column for two conditions. These conditional functions are the following:

IF(STARTSWITH(ProductName, `#{3}-`), 'Ok', 'Bad ProductName-Brand')
IF(ENDSWITH(ProductName, `-#{6}`), 'Ok', 'Bad ProductName-SKU')

One approach is to create two new test columns and then edit the column based on the evaluation of these two columns. However, using the following, you can compress the evaluation into a single step without creating the intermediate columns:

Transformation Name

Edit column with formula

Parameter: Columns

Status

Parameter: Formula

IF(STARTSWITH(ProductName, `#{3}-`), IF(ENDSWITH(ProductName, `-#{6}`), 'Ok', 'Bad ProductName-SKU'), 'Bad ProductName-Brand')

Results:

InvDate

ProductName

Qty

Validation

04/21/2017

412-Widgets-012345

23

Ok

04/21/2017

04-Fidgets-120341

66

Bad ProductName-Brand

04/21/2017

204-Midgets-4421

31

Bad ProductName-SKU

04/21/2017

593-Gidgets-402012

24

Ok