Teradata Package for Python Function Reference on VantageCloud Lake - datasets - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.

Teradata® Package for Python Function Reference on VantageCloud Lake

Deployment
VantageCloud
Edition
Lake
Product
Teradata Package for Python
Release Number
20.00.00.08
Published
November 2025
ft:locale
en-US
ft:lastEdition
2025-12-05
dita:id
TeradataPython_FxRef_Lake_2000
Product Category
Teradata Vantage
teradataml.store.feature_store.models.DataDomain.datasets
DESCRIPTION:
    Returns the list of Dataset objects associated with corresponding data domain.
 
PARAMETERS:
    None
 
RETURNS:
    list of Dataset.
 
RAISES:
    None
 
EXAMPLES:
    # Load data to be used.
    >>> from teradataml import load_example_data, DataFrame
    >>> load_example_data('dataframe', ['sales'])
    >>> df = DataFrame('sales')
 
    # Define repo and data doamin.
    >>> repo = 'vfs_test'
    >>> data_domain = 'sales'
 
    # Create a FeatureStore.
    >>> from teradataml import FeatureStore
    >>> fs = FeatureStore(repo=repo, data_domain=data_domain)
    Repo vfs_test does not exist. Run FeatureStore.setup() to create the repo and setup FeatureStore.
    >>> fs.setup()
    True
 
    # Run FeatureProcess to ingest features.
    >>> from teradataml import FeatureProcess
    >>> fp = FeatureProcess(repo=repo,
    ...                     data_domain=data_domain,
    ...                     object=df,
    ...                     entity='accounts',
    ...                     features=['Jan', 'Feb', 'Mar', 'Apr'])
    >>> fp.run()
    Process '4098c3ea-6c8d-11f0-837a-24eb16d15109' started.
    Process '4098c3ea-6c8d-11f0-837a-24eb16d15109' completed.
 
    # Build dataset.
    >>> from teradataml import DatasetCatalog
    >>> dataset_catalog = DatasetCatalog(repo=repo, data_domain=data_domain)
    >>> dataset_catalog.build_dataset(entity='accounts',
    ...                               selected_features={
    ...                                   'Jan': fp.process_id,
    ...                                   'Feb': fp.process_id,
    ...                                   'Mar': fp.process_id},
    ...                               view_name='dd_test_view',
    ...                               description='DataDomain Test')
         accounts    Jan    Feb    Mar
    0  Yellow Inc    NaN   90.0    NaN
    1    Alpha Co  200.0  210.0  215.0
    2   Jones LLC  150.0  200.0  140.0
    3    Blue Inc   50.0   90.0   95.0
    4  Orange Inc    NaN  210.0    NaN
    5     Red Inc  150.0  200.0  140.0
 
    # Example 1: Get the datasets in data domain.
    # Create DataDomain object.
    >>> from teradataml import DataDomain
    >>> dd = DataDomain(repo=repo,
    ...                 data_domain=data_domain)
 
    # List datasets.
    >>> dd.datasets
    [<teradataml.store.feature_store.models.Dataset at 0x1b6bf9f12d0>]