apply() | FeatureGroup Method | Teradata Package for Python - apply() - Teradata Package for Python

Use the apply() method to attach objects (feature, entity, data source) to a feature group.

Required Parameter

object

Specifies the object to update a feature group.

Example setup

>>> load_example_data('dataframe', ['sales'])
>>> df = DataFrame("sales")

>>> from teradataml import Feature, Entity, DataSource, FeatureGroup

Create the feature.

>>> feature = Feature('sales:Feb', df.Feb)

Create an entity.

>>> entity = Entity('sales:accounts', df.accounts)

Create a data source.

>>> data_source = DataSource('Sales_Data', df)

Create a feature group with name 'sales'.

>>> fg = FeatureGroup('Sales',
...                   features=feature,
...                   entity=entity,
...                   data_source=data_source)

Example 1: Create a new feature for column df.Mar and apply the feature to the feature group

Create a feature.

>>> feature = Feature('sales:Mar', df.Mar)

Register the feature with the feature group.

>>> fg.apply(feature)

True

Get the features from the feature group.

>>> fg.features

[Feature(name=sales:Feb), Feature(name=sales:Mar)]

Example 2: Register the data source with the feature group

>>> load_example_data("dataframe", "admissions_train")

>>> admissions = DataFrame("admissions_train")
>>> admissions_source = DataSource('admissions', admissions)

Register the data source with the feature group.

>>> fg.apply(admissions_source)

True

Get the data source from a feature group.

>>> fg.data_source

DataSource(name=admissions)

Example 3: Register the entity with the feature group

>>> entity = Entity('admissions:accounts', admissions.accounts)

Register the entity with the feature group.

>>> fg.apply(entity)

True