Teradata Package for Python Function Reference | 20.00 - delete_feature - 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.delete_feature = delete_feature(self, feature)
- DESCRIPTION:
Removes the archived Feature from repository.
PARAMETERS:
feature:
Required Argument.
Specifies either the name of Feature or Object of Feature
to remove from repository.
Types: str OR Feature
RETURNS:
bool.
RAISES:
TeradataMLException, TypeError, ValueError
EXAMPLES:
>>> from teradataml import DataFrame, Feature, FeatureStore
>>> load_example_data('dataframe', ['sales'])
# Create teradataml DataFrame.
>>> df = DataFrame("sales")
# Create Feature for Column 'Feb'.
>>> feature = Feature(name="sales_data_Feb", column=df.Feb)
# Create a feature store with name "staging_repo".
>>> fs = FeatureStore("staging_repo")
# Add the feature created above in the feature store.
>>> fs.apply(feature)
True
# Let's first archive the Feature.
>>> fs.archive_feature(feature=feature)
Feature 'sales_data_Feb' is archived.
True
# Delete Feature with name "sales_data_Feb".
>>> fs.delete_feature(feature=feature)
Feature 'sales_data_Feb' is deleted.
True
>>>