Teradata Package for Python Function Reference on VantageCloud Lake - get_raw_data_with_id - 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.automl.AutoChurn.get_raw_data_with_id = get_raw_data_with_id(self, data, use_loaded_models=False)
- DESCRIPTION:
Get the raw data with id column used further for feature engineering, data preparation,
model training and evaluation.
PARAMETERS:
data:
Required Argument.
Specifies the dataset which needs to be fetched with id column.
Types: teradataml DataFrame
use_loaded_models:
Optional Argument.
Specifies whether to use loaded models for transformation.
Default Value: False
Types: bool
RETURNS:
teradataml DataFrame containing raw data with id column.
RAISES:
TeradataMlException, TypeError, ValueError
EXAMPLES:
# Create an instance of the AutoML called "automl_obj" by referring
# "AutoML()" or "AutoRegressor()" or "AutoClassifier()" or
# "AutoFraud()" or "AutoChurn()" or "AutoCluster()" method.
# Example 1: Get raw data with id column after performing AutoML fit.
# Perform fit() operation on the "automl_obj".
>>> raw_data_with_id = automl_obj.get_raw_data_with_id(admissions_train)
>>> raw_data_with_id
# Example 2: Get raw data with id column after performing AutoML load.
# Load models from the specified table.
>>> raw_data_with_id = automl_obj.get_raw_data_with_id(admissions_train, use_loaded_models=True)
>>> raw_data_with_id