Assign Feature Types

The .feature_type property is used to assign the feature types that are to be associated with a feature. It accepts an ordered list of the custom, default, and tag feature types.

The .feature_type property is defined on a Pandas Series and dataframe. There are small differences between the ways that they are used are defined.

The order that you specify custom feature types defines the inheritance chain so controls which attribute or method is dispatched a feature. The default feature type doesn’t have to be specified. If you specify it, it is placed after the custom feature types in the inheritance chain. Tag feature types are always placed after the default feature type.

It is best practice to list the custom feature type first, then default, and then the tag feature types. The order matters so list any custom features first in the list.

When using the .feature_type property, the provided list accepts class names and custom feature type objects. For example, assume that CreditCard is a custom feature type and has the class name 'credit_card'. The following .feature_type statements are equivalent:

CreditCard = feature_type_manager.feature_type_object('credit_card')
String = feature_type_manager.feature_type_object('string') = ['credit_card', 'string'] = [CreditCard, String] = [CreditCard, 'string']


Like a Pandas Series, you can use .feature_type on a dataframe to set the feature types for the columns in the dataframe. This property accepts a dictionary where the key in the dictionary is the column name, and the value is a list of feature types associated with that column.

attrition_path = os.path.join('/opt', 'notebooks', 'ads-examples', 'oracle_data', 'orcl_attrition.csv')
df = pd.read_csv(attrition_path,
                 usecols=['Attrition', 'TravelForWork', 'JobFunction', 'EducationalLevel']) = {'Attrition': ['boolean', 'category'],
                         'TravelForWork': ['category'],
                         'JobFunction': ['category'],
                         'EducationalLevel': ['category']}


When working with a Pandas Series you can access the ADS feature type attributes and properties by accessing the .ads method on the Pandas Series.

To assign feature types to a Pandas Series, use the .ads.feature_type property. The next example creates a series of credit card numbers. Then it uses the .feature_type property with a list of strings of the class names of the feature types.

series = pd.Series(["4532640527811543", "4556929308150929", "4539944650919740", "4485348152450846"], name='Credit Card') = ['credit_card', 'string']