Rename Transform

Note

Transforms are a part of the underlying language, which is not directly accessible to users. This content is maintained for reference purposes only. For more information on the user-accessible equivalent to transforms, see Transformation Reference.

Renames one or more columns based on specified names, patterns, row values, or prefixes and suffixes. You can also rename to uppercase or lowercase values.

Note

Column names are case-insensitive and cannot begin with whitespace.

Tip

To prevent potential issues with downstream systems, you should limit your column lengths to no more than 128 characters.

Other ways to rename:

It's easier to rename columns through the user interface.
- To rename a single column, double-click the column name or selectRename...from the column drop-down in the Transformer Page.
- To rename multiple columns, you can select values in the Column Browser and perform batch renames.
Transforms that generate new columns might support theasparameter, which enables specifying the name of the new column. Using the as parameter avoids the extra step of adding a rename transform after column generation.
- See Derive Transform.
- See Extractkv Transform.
- See Extractlist Transform.
- See Merge Transform.
- See Nest Transform.

Basic Usage

Rename a single column manually:

rename mapping: [oldName,'NewName']

Output: Renames the column OldName to NewName.

Rename multiple columns:

This transform supports multiple methods for renaming two or more columns in a single step. See below for examples.

Syntax and Parameters

rename: type: renameType col: column_ref [mapping: [column1,'newColumn1Name'], [column2,'newColumn2Name']] [prefix: 'strPrefix'][suffix: 'strSuffix'] [keepIndex: NumOfChars][on: `patternOrLiteral`] [with: 'replacementString'] [method: strMethodType] [sourcerownumber: intRowNum] [sourcerownumbers: strCommaList]

Token	Required?	Data Type	Description
rename	Y	transform	Name of the transform
type	Y	string	Enum of supported renaming types. For more information, see "type" below.
col	Y	string	Name of column or columns to rename
prefix	N	string	(type=prefix) Prefix to prepend to the column name
suffix	N	string	(type=suffix) Suffix to append to the column name
keepIndex	N	integer	(type=keepLeft or type=keepRight) Number of characters on the left or right side of the column to retain
mapping	N	array	(type=manual) Array containing mappings from old column name and new column name
on	N	string	(type=findAndReplace) Pattern or string literal for which to search each column name
with	N	string	(type=findAndReplace) Replacement value for found pattern or string literal in column names
method	N	string	(type=header) Enum of supported methods for renaming headers based on row numbers. See "method" below.
sourcerownumber	N	integer	(type=header,method=index) Row number from the source data to use as the new names for the selected columns
sourcerownumbers	N	string	(type=header,method=multi) Comma-separated list of row numbers from the source data to use as the new names for the selected columns
separator	N	string	(type=header,method=multi) String to separate row values when multiple rows are used to define column headers.
filltype	N	boolean	(type=header,method=multi) When `true`, empty row values are replaced with the nearest row value to the left in the replacement column header.
sanitize	N	boolean	When `true`, column names are sanitized after they have been renamed.

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

type

Type of column rename to perform. Options:

Type	Description	Other required parameters
manual	Manual rename of one or more columns.	`mapping` - array specifies one or more manual column renames.
prefix	Rename column by adding a prefix to it.	`prefix` - string value with which to prepend the column name.
suffix	Rename column by adding a suffix to it.	`suffix`- string value with which to append the column name.
findAndReplace	Rename the column using find and replace.	`on` - value to find in column names `with` - value to replace found value in column names.
keepLeft	Keep the leftmost characters in the column name	`keepIndex` - number of characters on the left side of the column name to keep
keepRight	Keep the right characters in the column name	`keepIndex`- number of characters on the right side of the column name to keep
upper	Rename column to use all uppercase characters.	None.
lower	Rename column to use all lowercase characters.	None.
header	Rename column based on a row number	`method` - enum defining the method of rename of the column headers. Additional parameters are required depending on the `method` value. See below.

Usage Notes:

Required?	Data Type
Yes	Enum of supported String values.

col

Identifies the column or columns to which to apply the transform.

Tip

The col parameter must be specified for all types. You can use the * wildcard to apply to all columns.

Usage Notes:

Required?	Data Type
Yes	Comma-separated list of column names (String values)

mapping

An array describing the old names and new names for each column to rename.

Example:

Old column name	New column name
column1	FirstName
column2	LastName
column3	Phone

Transform step:

rename mapping: [column1,'FirstName'],[column2,'LastName'],[column3,'Phone']

Usage Notes:

Required?	Data Type
No	Array

prefix

For batch rename using prefixes, this parameter specifies the string value with which to precede each of the column names.

Usage Notes:

Required?	Data Type
No	String

suffix

For batch rename using suffixes, this parameter specifies the string value with which to append each of the column names.

Usage Notes:

Required?	Data Type
No	String

For batch rename using find and replace, this parameter specifies the pattern or string literal to use to match values.

Replacement values are specified with the with parameter.

Usage Notes:

Required?	Data Type
No	String (pattern or literal)

with

For batch rename using find and replace, this parameter specifies the literal string values with which to replace the found pattern.

Find patterns and values are specified with the on parameter.

Usage Notes:

Required?	Data Type
No	String (pattern or literal)

keepIndex

For batch rename using keep-left or keep-right, this parameter specifies the number of characters on the left or right side of the column name to retain as the new column name.

Note

This value must be an integer greater than 0. If this value results in multiple columns having the same new name, you must specify a greater value to create unique names or use a different rename method.

Usage Notes:

Required?	Data Type
No	Integer

method

Type of row-based column rename to perform. Options:

Type	Description	Other required parameters
index	Rename based on a single row number.	`sourcerownumber` - source row number values to use as new column headers.
filter	Use the values in the first row in the current sample to use as the new column names.	None.
multi	Rename column by adding a suffix to it.	`sourcerownumbers`- comma-separated list of values for the source row numbers to use as new column headers. Other parameters are applicable. See below.

Type

Description

Other required parameters

index

Rename based on a single row number.

sourcerownumber - source row number values to use as new column headers.

filter

Use the values in the first row in the current sample to use as the new column names.

None.

multi

Rename column by adding a suffix to it.

sourcerownumbers- comma-separated list of values for the source row numbers to use as new column headers.

Other parameters are applicable. See below.

Usage Notes:

Required?	Data Type
No	Enum of supported row-based rename types (String).

sourcerownumber

The row number from the original source data which contains the values to use to rename all columns in the dataset. The row is removed from its original position.

Note

If source row number information is no longer available, this method cannot be used for column rename.

Usage Notes:

Required?	Data Type
No	Integer (Positive value)

sourcerownumbers

A comma-separated list of the row numbers from the original source data containing the values to use to rename all columns in the dataset. These rows are removed from its original position.

Note

If source row number information is no longer available, this method cannot be used for column rename.

Usage Notes:

Required?	Data Type
No	Comma-separated list of row numbers (String)

separator

String value to separate row value entries in the column header when multiple rows are used to rename columns. This value is not required.

Usage Notes:

Required?	Data Type
No	String

filltype

When set to true, empty values encountered in row values used to rename the column header are replaced using the nearest non-empty column value to the left. Default is false.

Usage Notes:

Required?	Data Type
No	Boolean

sanitize

When set to true, new column headers are sanitized to remove special characters. Default is false.

Usage Notes:

Required?	Data Type
No	Boolean

Examples

Tip

For additional examples, see Common Tasks.

Rename a column

In the following dataset, the length columns do not include any units of measure.

Tip

For downstream consumption, any column that contains a measure should include the units of measure in the column name. Avoid including units of measure in cell values, which forces the column to be retyped as String type.

Source:

Object	LengthX	LengthY	LengthZ
ObjA	10	20	30
ObjB	3	4	5
ObjC	6	9	12

Transformation:

Perhaps you know the units are centimeters. You can rename using the following:

Transformation Name	`Rename columns`
Parameter: Option	Manual rename
Parameter: Column	LengthX
Parameter: New column name	'LengthX_cm'

Now, you want to convert the units of measure to inches. You can use the New Formula transformation to convert values and generate a new column name:

Transformation Name	`New formula`
Parameter: Formula type	Single row formula
Parameter: Formula	(LengthX_cm * 0.393701)
Parameter: New column name	'LengthX_in'

You might want to reformat the generated values using transformations like the following, which rounds the results to two decimal points:

Transformation Name	`Edit column with formula`
Parameter: Columns	LengthX_in
Parameter: Formula	numformat(LengthX_in, '##.00')

Repeat the above steps for the other length columns.

Results:

Object	LengthX_cm	LengthY_cm	LengthZ_cm	LengthX_in	LengthY_in	LengthZ_in
ObjA	10	20	30	3.94	7.87	11.81
ObjB	3	4	5	1.18	1.57	1.97
ObjC	6	9	12	2.36	3.54	4.72

You can delete the original columns if needed.

Rename multiple columns

Source:

column1	column2	column3	column4	column5
data1	data2	data3	data4	data5

Transformation:

Add prefix:

Transformation Name	`Rename columns`
Parameter: Option	Add prefix
Parameter: Columns	column1,column2,column3,column4,column5
Parameter: Prefix	'new_'

new_column1	new_column2	new_column3	new_column4	new_column5
data1	data2	data3	data4	data5

Add suffix:

Transformation Name	`Rename columns`
Parameter: Option	Add suffix
Parameter: Columns	new_column1,new_column2,new_column3,new_column4,new_column5
Parameter: Suffix	'a'

new_column1a	new_column2a	new_column3a	new_column4a	new_column5a
data1	data2	data3	data4	data5

Convert to UPPERCASE:

Transformation Name	`Rename columns`
Parameter: Option	Convert to UPPERCASE
Parameter: Columns	Column1,Column2,Column3,Column4,Column5

COLUMN1	COLUMN2	COLUMN3	COLUMN4	COLUMN5
data1	data2	data3	data4	data5

Find and replace:

Transformation Name	`Rename columns`
Parameter: Option	Find and replace
Parameter: Columns	new_column1,new_column2,new_column3,new_column4,new_column5
Parameter: Find	'_column'
Parameter: Replace	'_field'

new_field1	new_field2	new_field3	new_field4	new_field5
data1	data2	data3	data4	data5

In this section:

Rename Transform

Basic Usage

Syntax and Parameters

Examples

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