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>]