Teradata Package for Python Function Reference | 20.00 - list_feature_groups - 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 - 20.00

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00.00.03
Published
December 2024
ft:locale
en-US
ft:lastEdition
2024-12-19
dita:id
TeradataPython_FxRef_Enterprise_2000
lifecycle
latest
Product Category
Teradata Vantage
teradataml.store.feature_store.feature_store.FeatureStore.list_feature_groups = list_feature_groups(self, archived=False) -> teradataml.dataframe.dataframe.DataFrame
DESCRIPTION:
    List all the FeatureGroups.
 
PARAMETERS:
    archived
        Optional Argument
        Specifies whether to list effective feature groups or archived feature groups.
        When set to False, effective feature groups in FeatureStore are listed,
        otherwise, archived feature groups are listed.
        Default Value: False
        Types: bool
 
RETURNS:
    teradataml DataFrame
 
RAISES:
    None
 
EXAMPLES:
    >>> from teradataml import FeatureGroup, FeatureStore, load_example_data
    >>> load_example_data("dataframe", "admissions_train")
    # Create teradataml DataFrame.
    >>> admissions=DataFrame("admissions_train")
    # Create FeatureStore for repo 'vfs_v1'.
    >>> fs = FeatureStore("vfs_v1")
    # Create a FeatureGroup from DataFrame.
    >>> fg = FeatureGroup.from_DataFrame("admissions", df=admissions, entity_columns='id')
    # Apply FeatureGroup to FeatureStore.
    >>> fs.apply(fg)
    True
 
    # Example 1: List all the effective FeatureGroups in the repo 'vfs_v1'.
    >>> fs.list_feature_groups()
               description data_source_name entity_name
    name
    admissions        None       admissions  admissions
    >>>
 
    # Example 2: List all the archived FeatureGroups in the repo 'vfs_v1'.
    # Let's first archive the FeatureGroup.
    >>> fs.archive_feature_group("admissions")
    True
    >>>
    # List archived FeatureGroups.
    >>> fs.list_feature_groups(archived=True)
             name description data_source_name entity_name               archived_time
    0  admissions        None       admissions  admissions  2024-09-30 12:05:39.220000
    >>>