Use the following functions to search for the relevant component in FeatureStore.
list_features
Use list_features() to retrieve available Features in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Feature details.
Example:
>>> fs.list_features()
column_name description creation_time modified_time tags data_type feature_type status group_name name Mar Mar None 2024-09-30 11:21:43.314118 None None BIGINT CONTINUOUS ACTIVE sales Jan Jan None 2024-09-30 11:21:42.655343 None None BIGINT CONTINUOUS ACTIVE sales Apr Apr None 2024-09-30 11:21:44.143402 None None BIGINT CONTINUOUS ACTIVE sales Feb Feb None 2024-09-30 11:21:41.542627 None None FLOAT CONTINUOUS ACTIVE sales >>>
list_entities
Use list_entities() to retrieve available Entities in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Entity details.
Example:
>>> fs.list_entities()
description name entity_column sales accounts None >>>
list_data_sources
Use list_data_sources() to retrieve available Data Sources in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Data Source details.
Example:
>>> fs.list_data_sources()
description timestamp_col_name source name admissions None None select * from "admissions_train" >>>
list_feature_groups
Use list_feature_groups() to retrieve available Feature Groups in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Feature Group details.
>>> fs.list_feature_groups()
description data_source_name entity_name name admissions None admissions admissions >>>