unpackdict

Separate values contained in dictionaries into columns in a data extract.

Introduction

Use the unpackdict instruction to separate values contained in dictionaries into columns in a data extract. The dictionary values are placed into new columns named after the dictionary keys.

Before you unpack the dictionaries, 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 dictionaries. Running this transformation enables Adverity to read the dictionaries. For more information, see the Python documentation.

Creating a custom script transformation using the unpackdict instruction

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

1. Create a custom script transformation.

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

3. 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 dictionaries.

Keys

Enter the names of the dictionary keys to unpack. Adverity adds new columns to the data extract named after the dictionary keys entered into the Keys field. Adverity populates the separated dictionary values into these new columns. Specify as many keys as the number of keys in the longest dictionary.

Leave the Keys field empty to let Adverity automatically separate the dictionary values from the keys.

Includeoriginal

Select this checkbox to keep the column that contains the dictionaries in the data extract.

Samplesize

If you have not defined any keys in the Keys field, enter the number of rows where Adverity searches for keys and values to separate.

Missing

Enter a value with which Adverity populates empty columns. Use this option if the dictionaries have different lengths.

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 1 - Unpacking a dictionary with defined keys

Transformation configuration

Field*

Users

Keys

Name

Email

ID

Includeoriginal

Select this checkbox.

Missing

null

Data table before transformation

Clicks	Users
1946	{'Name':'Jane Doe', 'Email':'j.doe@acme.com', 'ID':'AD-17'}
3901	{'Name':'Joanne Bloggs', 'Email':'j.bloggs@acme.com', 'ID':'AE-23'}
4958	([A, B, C], [D, E, F])

Data table after transformation

Clicks	Users	Name	Email	ID
1946	{'Name':'Jane Doe' 'Email':'j.doe@acme.com', 'ID':'AD-17'}	Jane Doe	j.doe@acme.com	AD-17
3901	{'Name':'Joanne Bloggs', 'Email':'j.bloggs@acme.com', 'ID':'AE-23'}	Joanne Bloggs	j.bloggs@acme.com	AE-23
4958	([A, B, C], [D, E, F])	null	null	null

Example 2 - Unpacking a dictionary with no defined keys

Transformation configuration

Field*

Users

Includeoriginal

Select this checkbox.

Samplesize

100

Missing

null

Data table before transformation

Clicks	Users
1946	{'key_1':'Jane Doe', 'key_2':'j.doe@acme.com', 'key_3':'AD-17'}
3901	{'key_1':'Joanne Bloggs', 'key_2':'j.bloggs@acme.com', 'key_3':'AE-23'}
4958	([A, B, C], [D, E, F])

Data table after transformation

Clicks	Users	key_1	key_2	key_3
1946	{'key_1':'Jane Doe', 'key_2':'j.doe@acme.com', 'key_3':'AD-17'}	Jane Doe	j.doe@acme.com	AD-17
3901	{'key_1':'Joanne Bloggs', 'key_2':'j.bloggs@acme.com', 'key_3':'AE-23'}	Joanne Bloggs	j.bloggs@acme.com	AE-23
4958	([A, B, C], [D, E, F])	null	null	null