filldown

Fill empty fields in the data extract using values in the row above.

Introduction

Use the filldown instruction to fill in the empty fields in a data extract. Select which columns to check for empty values and choose what Adverity should treat as an empty field. Empty fields are populated with values from the fields in the row above.

Creating a custom script transformation using the filldown instruction

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

1. Create a custom script transformation.

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

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

Fields

Enter the names of the columns to search through for empty values. Leave this field blank to search through the whole of the data extract.

Select a column in one of the following ways:

• Select String and enter the name of the column.

• Select Integer and enter the position of the column in the data extract as an index value. Counting starts at 0. To select the first column, enter 0. To select the second column, enter 1. To select the last column in the data extract, enter -1.

Missing

Enter the missing value for Adverity to search. For example, a value like null or n/a could be treated as a missing value. Leave this field blank to search and fill only the fields that are empty.

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

Fields

Campaign

Ad Group

Missing

null

Data table before transformation

Campaign	Ad Group	Clicks
Brand	media	7
Brand	null	3
Dashboard	media|social	18
null	ecommerce

Data table after transformation

Campaign	Ad Group	Clicks
Brand	media	7
Brand	media	3
Dashboard	media|social	18
Dashboard	ecommerce