sumup#
Add a column containing a running total to your data extract.
Note
This guide explains how to configure the sumup instruction. To learn about another instruction, go back to the Custom scripts available in Adverity overview.
Introduction#
Use the sumup instruction to add a new column to the data extract that contains a running total of a selected column. You can add in discriminators to reset the running total if a certain value is found.
Warning
To use the sumup custom script instruction, the values used in the instruction must be in numeric format. If necessary, use the convertnumbers custom script instruction to convert string values to a numeric format. Add the convertnumbers instruction to the same custom script transformation before the sumup instruction.
Creating a custom script transformation using the sumup instruction#
To create and configure a custom script using the sumup instruction, follow these steps:
In the Instructions step, select the sumup instruction.
To configure the custom script instruction, fill in the following fields. Required fields are marked with an asterisk (*).
- Input Field
Enter the name of the column that contains the values to sum up. This column must contain numerical values.
- Output Field
Enter a name for the new column to add to the data extract. This column will contain the running total values.
- Discriminators
Enter the names of the columns that contain the distinct values that reset the count. See the example below.
- 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#
- Input Field
Clicks
- Output Field
Sum of Clicks
- Discriminators
Campaign
Ad Group
Data table before transformation#
Campaign |
Ad Group |
Clicks |
---|---|---|
Brand |
ecommerce |
7 |
Brand |
ecommerce |
3 |
Dashboard |
ecommerce |
18 |
Brand |
ecommerce |
4 |
Dashboard |
media |
5 |
Dashboard |
media |
11 |
Data table after transformation#
Campaign |
Ad Group |
Clicks |
Sum of Clicks |
---|---|---|---|
Brand |
ecommerce |
7 |
7 |
Brand |
ecommerce |
3 |
10 |
Dashboard |
ecommerce |
18 |
18 |
Brand |
ecommerce |
4 |
22 |
Dashboard |
media |
5 |
5 |
Dashboard |
media |
11 |
16 |