Add a component to FeatureStore | Teradata Package for Python - Add a component to FeatureStore - Teradata VantageCloud Lake

Use the apply() method to register the Feature, Entity, DataSource or FeatureGroup to a repo.

Example: Adding a Feature to FeatureStore

Create a Feature for column 'Feb' from 'sales' DataFrame and register with repo 'vfs_v1'.

>>> from teradataml import Feature, FeatureStore

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

>>> fs = FeatureStore('vfs_v1')

>>> fs.apply(feature)
True
>>>

Example: Adding an Entity to FeatureStore

Create an Entity for 'sales' DataFrame and register with repo 'vfs_v1'.

>>> from teradataml import Entity, FeatureStore

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

>>> fs = FeatureStore('vfs_v1')

>>> fs.apply(entity)
True
>>>

Example: Adding a DataSource to FeatureStore

Create a DataSource for 'sales' DataFrame and register with repo 'vfs_v1'.

>>> from teradataml import DataSource, FeatureStore

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

>>> fs = FeatureStore('vfs_v1')

>>> fs.apply(ds)
True
>>>

Example: Adding a FeatureGroup to FeatureStore

Create a FeatureStore with all objects created using the components in the previous examples and register with repo 'vfs_v1'.

>>> from teradataml import FeatureGroup, FeatureStore

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

>>> fs = FeatureStore('vfs_v1')

>>> fs.apply(fg)
True
>>>

Example: Create a Feature Group and add the Feature Group and associated Components to a FeatureStore

>>> load_example_data("byom", "iris_test")

>>> iris_df = DataFrame("iris_test")

>>> from teradataml import FeatureGroup, FeatureStore
>>> fg = FeatureGroup.from_DataFrame('iris_data', df=iris_df, entity_columns='id')

>>> fs = FeatureStore('vfs_v1')

>>> fs.apply(fg)
True
>>>