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Rename Columns

In the Trifacta Application, you can rename individual columns through the column drop-down. Through transform steps, you can apply renaming to one or more columns.

Note

An imported dataset requires about 15 rows to properly infer column data types and the row, if any, to use for column headers.

Name Requirements

  • For best results, use alphanumeric characters and the underscore character (_) only.

  • Column names cannot begin with a space.

  • For more information, see Column Naming Requirements.

  • Rename Individual Columns

Rename a column through column menu

To rename a column, click the drop-down caret next to the column name. Click Rename.

Rename a column through suggestions

Steps:

  1. If your column already exists, click the name of the column.

  2. Click the Rename suggestion card.

  3. Click Modify.

  4. Replace the newColumnName value with your preferred column name.

Rename a column through transformation

You can use the following transformation to rename a single column through the Transform Builder. In this case, the Rename columns transformation is used to perform a manual rename of MySourceCol to MyNewCol.

Transformation Name

Rename columns

Parameter: Option

Manual rename

Parameter: Column

MySourceCol

Parameter: New name

MyNewCol

Rename a new column

Columns that are generated through transform steps are given a default name.

For the following types of transforms, however, you can specify the column name as part of the step:

  • derive

  • extractkv

  • merge

  • nest

When a transform is added to the recipe, an as: clause is automatically added to the transform step. You can modify your transform to change the value of the as: column. For example, the following transform generates a new column with the first word from the Name column. The as: value renames this generated column as FirstName:

Transformation Name

New formula

Parameter: Formula type

Single row formula

Parameter: Formula

FIND(Name,`{start} `,false,0)

Parameter: New name

FirstName

Auto-Generated Column Names

When your transforms generate new columns, names are automatically assigned to these columns based on the following pattern.

  1. If the transform includes a function reference, the function name is included in the new column. Example:

    Transformation Name

    New formula

    Parameter: Formula type

    Single row formula

    Parameter: Formula

    LEFT(city,3)

    New column name: left_city

  2. If the above step is applied again, a duplicate column is generated with the following name. Example:

    Transformation Name

    New formula

    Parameter: Formula type

    Single row formula

    Parameter: Formula

    LEFT(city,3)

    New column name: left_city1

  3. If the transform does not contain a function reference, the following convention is used:

    Transformation Name

    New formula

    Parameter: Formula type

    Single row formula

    Parameter: Formula

    'A'

    New column name: column1

    Transformation Name

    New formula

    Parameter: Formula type

    Single row formula

    Parameter: Formula

    'B'

    New column name: column2

Rename Multiple Columns

Dataprep by Trifacta enables to rename multiple columns using a single transformation. You can perform this batch renaming using one of the methods described in this section.

Note

OTE: In macros, Rename Columns transformations do not work. This is a known issue.

Tip

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

Steps:

  1. Open the Transform Builder to add a new step to your recipe.

  2. From the drop-down in the first textbox, select Rename columns.

  3. Select your method of renaming. See below.

  4. Select the column or columns to which to apply the rename.

    Tip

    To apply the renaming across all columns in the dataset, select All. This option is useful for pattern-based renames, such as adding a prefix or changing case.

  5. To add the step to your recipe, click Add.

Manual rename multiple columns

For each column that you select, you must add the new name just below the old one.

  • To add additional columns to the mapping, click Add.

  • To remove columns from the mapping, click Remove.

Add prefix

For the selected columns, you can apply a specific prefix value to the names.

Old Column Names

Prefix

New Column Names

column1
pre_
pre_column1
column2
pre_
pre_column2
column3
pre_
pre_column3

Transformation:

Transformation Name

Rename columns

Parameter: Option

Add prefix

Parameter: Column

column1,column2,column3

Parameter: Prefix

pre_

Add suffix

For the selected columns, you can apply a specific suffix value to the names. Example:

Old Column Names

Suffix

New Column Names

column1
_new
column1_new
column2
_new
column2_new
column3
_new
column3_new

Transformation:

Transformation Name

Rename columns

Parameter: Option

Add suffix

Parameter: Column

column1,column2,column3

Parameter: Suffix

_new

Apply rename to all columns

The following transformation performs the same rename as the previous one. Instead, it uses the All option to apply the rename across all columns of the dataset. If the number of columns changes in the future, then the rename is still applied across all of the columns in the dataset.

Transformation:

Transformation Name

Rename columns

Parameter: Option

Add suffix

Parameter: Columns

All

Parameter: Suffix

_new

Convert to lowercase

For the selected columns, you can convert the columns names to lowercase. Example:

Old Column Names

New Column Names

Daily
daily
POS_Cost
pos_cost
Sales_Type
sales_type

Transformation:

Transformation Name

Rename columns

Parameter: Option

Convert to lowercase

Parameter: Column

Daily,POS_Cost,Sales_Type

For example, if the old column name is Sales_Type, then the new column name is renamed to sales_type.

Convert to UPPERCASE

For the selected columns, you can convert the columns names to uppercase. Example:

Old Column Names

New Column Names

Daily

DAILY

POS_Cost
POS_COST
Sales_Type
SALES_TYPE

Transformation:

Transformation Name

Rename columns

Parameter: Option

Convert to UPPERCASE

Parameter: Column

Daily,POS_Cost,Sales_Type

For example, if the old column name is Sales_Type, then the new column name is renamed to SALES_TYPE.

Keep from beginning (left)

For the selected columns, you can specify the number of characters to keep from the beginning (left) of the column names. Based on the number of characters you provide, the column name is updated. Example:

Old Column Names

Number of characters

New Column Names

Daily
3

Dai

POS_Cost
3
POS
Sales_Type
3
Sal

Transformation:

Transformation Name

Rename columns

Parameter: Option

Keep from beginning (left)

Parameter: Column

Daily,POS_Cost,Sales_Type

Parameter: Number of characters

3

For example, if the old column name is Sales_Type, then based on the number of characters to keep from the beginning (left) is 3, then new column name is renamed to Sal.

Keep from end (right)

For the selected columns, you can specify the number of characters to keep from end (right) of the column names. Based on the number of characters you provide, the column name is updated. Example:

Old Column Names

Number of characters

New Column Names

Daily
4

aily

POS_Cost
4
Cost
Sales_Type
4
Type

Transformation:

Transformation Name

Rename columns

Parameter: Option

Keep from beginning (right)

Parameter: Column

Daily,POS_Cost,Sales_Type

Parameter: Number of characters

4

For example, if the old column name is Sales_Type, then based on the number of characters to keep from the end (right) is 4, then new column name is renamed to Type.

Note

OTE: If the number of characters are more than the length of the column names, then the whole name of the column is retained.

Find and replace

You can apply literals, Wrangle , or regular expressions to match patterns of text in the source column names. These matching values can then be replaced by a fixed value.

Tip

The default behavior is to replace the first instance. Use the Match all occurrences checkbox to apply the pattern matching across all columns in your set.

For the selected columns, you can specify the number of characters to keep from end (right) of the column names. Based on the number of characters you provide, the column name is updated. Example:

Old Column Names

New Column Names

column1

Field1

column2

Field2

column3

Field3

Transformation:

Transformation Name

Rename columns

Parameter: Option

Find and replace

Parameter: Column

column1,column2,column3

Parameter: Find

'column'

Parameter: Replace with

'Field'

The above uses literal values for find and replace. For more information on pattern-based matching, see Text Matching.

Use row(s) as column names

When this method is applied, all of the values in the specified row or rows are used as the new names for each column.

Note

This method applies to all columns in the dataset.

Types:

Type

Description

Use a single row to rename columns

Specify the row number in the sample to use as the source for column names.

Note

Source row number information must be available. See below.

Use the first row in the sample to rename columns

Use the first row in the sample as the name for all columns.

Combine multiple rows to rename columns

Specify two or more rows to combine into column names. Details are below.

Note

Source row number information must be available. See below.

Source row number information:

Note

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

  • If a value is not applied for the source row number, the next row of data is used.

  • Source row numbers apply. Current row numbers may not be the same. In the data grid, mouse over the leftmost column to see available row information.

  • Each value in the row or combination of values across rows must be unique within the set of new column names.

  • The row is removed from its original position.

  • If the product is unable to find unique multi-row headers for the column, the first row of the header set is used.

Combine multiple rows

The following transformation renames the columns in the dataset based on the values in rows 3 and 4 of the data:

Transformation Name

Rename columns

Parameter: Option

Use row(s) as column names

Parameter: Type

Combine multiple rows to name columns

Parameter: Row Numbers - row A

3

Parameter: Row Numbers - row B

4

Parameter: Choose your separator

'_'

Parameter: Fill across?

Selected

In the above:

  • The separator is defined as an underscore character (_). This value can be empty.

  • When Fill across is selected, if any row value is empty, the last non-empty value for the row in a previous column is used as part of the column header.

In this section: