The Feature class represents a single feature with its metadata and properties.
Syntax
Feature(name, column, feature_type=FeatureType.CONTINUOUS, description=None, tags=None, status=FeatureStatus.ACTIVE)
Required Parameters
- name
- Specifies unique name of the Feature.
- column
- Specifies the DataFrame Column.
Optional Parameters
- feature_type
- Specifies whether a feature is continuous or discrete.
Default value: FeatureType.CONTINUOUS
- description
- Specifies the human readable description of the Feature.
- tags
- Specifies the tags for the Feature.
- status
- Specifies whether the feature is archived or active.
Example setup
>>> from teradataml import DataFrame, Feature, FeatureType, load_example_data, FeatureStatus
Load the sales data to the database.
>>> load_example_data("dataframe", "sales")
Create DataFrame on sales data.
>>> df = DataFrame("sales")
>>> df
Feb Jan Mar Apr datetime
accounts
Orange Inc 210.0 NaN NaN 250.0 04/01/2017
Jones LLC 200.0 150.0 140.0 180.0 04/01/2017
Blue Inc 90.0 50.0 95.0 101.0 04/01/2017
Alpha Co 210.0 200.0 215.0 250.0 04/01/2017
Yellow Inc 90.0 NaN NaN NaN 04/01/2017
Example 1: Create a Categorical Feature for column 'Feb' for 'sales' DataFrame
This example creates a Categorical Feature for column 'Feb' for 'sales' DataFrame and names it 'sales_Feb'.
>>> from teradataml import Feature
>>> feature = Feature('sales_Feb', column=df.Feb,
... feature_type=FeatureType.CATEGORICAL, status=FeatureStatus.ACTIVE)
>>> feature
Feature(name=sales_Feb)
Example 2: Create a Continuous Feature for column 'Jan' for 'sales' DataFrame
This example creates a Continuous Feature for column 'Jan' for 'sales' DataFrame and names it 'sales_Jan'.
>>> feature = Feature('sales_Jan', column='Jan',
... feature_type=FeatureType.CONTINUOUS, status=FeatureStatus.ACTIVE)
>>> feature
Feature(name=sales_Jan)