unpack#
Separate values contained in lists into columns in a data extract.
Note
This guide explains how to configure the unpack instruction. To learn about another instruction, go back to the Custom scripts available in Adverity overview.
Introduction#
Use the unpack instruction to separate lists contained in a single column of a data extract into separate columns. This transformation can also unpack a list of lists.
Before you unpack the lists, run the convertx transformation with the following Python expression:
__import__('ast').literal_eval({FIELD})
Replace FIELD
with the name of the column that contains the
lists. Running this transformation enables Adverity to read the
lists. For more information, see the Python
documentation.
Creating a custom script transformation using the unpack instruction#
To create and configure a custom script using the unpack instruction, follow these steps:
In the Instructions step, select the unpack instruction.
To configure the custom script instruction, fill in the following fields. Required fields are marked with an asterisk (*).
- Field
Enter the name of the column that contains the lists.
- Newfields
Enter the names of the new columns that are to be added to the data extract. Specify as many column names as the number of elements in the longest list.
- Includeoriginal
Select this checkbox to keep the column that contains the lists in the data extract.
- Missing
Enter a value with which Adverity populates empty columns. Use this option if the lists have different lengths.
Example#
Transformation configuration#
- Field*
Account IDs
- Newfields
ID 1
ID 2
ID 3
ID 4
- Includeoriginal
Select this checkbox.
- Missing
null
Data table before transformation#
Campaign |
Account IDs |
---|---|
Brand |
[1, 2, 3, 4] |
Brand |
[5, 6, 7] |
Dashboard |
([A, B, C], [D, E, F]) |
Data table after transformation#
Campaign |
Account IDs |
ID 1 |
ID 2 |
ID 3 |
ID 4 |
---|---|---|---|---|---|
Brand |
[1, 2, 3, 4] |
1 |
2 |
3 |
4 |
Brand |
[5, 6, 7] |
5 |
6 |
7 |
null |
Dashboard |
([A, B, C], [D, E, F]) |
[A, B, C] |
[D, E, F] |
null |
null |