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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 Pattern , regular expression, or a string.- The
STARTSWITHfunction 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 theLEFTfunction 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.".
Pattern 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 | When true, matching is case-insensitive. Default is false. |
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
Pattern , 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.
NOTE: This argument is not required. By default, matches are case-sensitive.
Usage Notes:
| Required? | Data Type | Example Value |
|---|---|---|
| No | String value | 'false'
|
Tip: For additional examples, see Common Tasks.
Examples
Example - STARTSWITH and ENDSWITH Functions
STARTSWITH- check start of values in a specified column against a specific pattern or literal. See STARTSWITH Function.ENDSWITH- check end of values in a specified column against a specific pattern or literal. See ENDSWITH Function.
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 |
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