setheader

Rename the columns in your data extract.

This guide explains how to configure the setheader instruction. To learn about another instruction, go back to the Available custom script instructions overview.

Introduction

Use the setheader instruction to change the names of the columns in a data extract. You must provide a name for each column in the data extract, even if you do not wish to rename the column. Any column that does not have a name provided is removed from the data extract. See the example below.

Creating a custom script transformation using the setheader instruction

To create and configure a custom script using the setheader instruction, follow these steps:

  1. Create a custom script transformation.

  2. In the Instructions step, select the setheader instruction.

  3. To configure the custom script instruction, fill in the following fields. Required fields are marked with an asterisk (*).

Header*

Click and enter the new names for the columns. Enter the names in the order in which they are to be applied to the columns. If you do not want to change the name of a column, enter its current name. To make sure no columns are removed, enter a name for each column in the data extract.

Subtable

Enter the name for a subtable that you want to use within this custom script.

A subtable is a temporary table that only exists for this custom script. You can apply additional instructions within the same custom script to the subtable. However, the subtable cannot be used in any other custom scripts.

If a subtable does not exist for the current custom script, the transformation is applied to the data extract, and the enriched data is output into the subtable. If the subtable already exists for the custom script, the subtable is used as the input for the transformation and optionally as the output.

Example

Transformation configuration

In this example, we want to change the name of the first two columns in our data extract, and leave the third column the same. To do this, we need to enter names for all three columns - we simply enter the current name of the third column so that it is not deleted from the data extract.

Field*

Campaign Name

Advert Type

Clicks

Data table before transformation

Campaign

Ad Group

Clicks

Brand

media

7

Branding

ecommerce

3

Dashboard

brand awareness

18

Brand

Ecommerce

4

Dashboard

media|social

5

Branding

media

11

Data table after transformation

Campaign Name

Advert Type

Clicks

Brand

media

7

Branding

ecommerce

3

Dashboard

brand awareness

18

Brand

Ecommerce

4

Dashboard

media|social

5

Branding

media

11