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Rename Transform

注意

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.

注意

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

提示

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.

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.

提示

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

on

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.

注意

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.

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.

注意

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.

注意

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

提示

For additional examples, see Common Tasks.

Rename a column

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

提示

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

本节内容如下: