Skip to content

key: Union[StrictInt, StrictFloat, StrictStr, bool, Feature]
) -> Feature


Computes the relative frequency of a specific key in the Cross Aggregate feature. The key may either be a lookup feature or a scalar value. If the key does not exist, the relative frequency will be 0.


  • key: Union[StrictInt, StrictFloat, StrictStr, bool, Feature]
    Key to lookup the value for.


  • Feature
    A new Feature object.


Create a new feature by computing the relative frequency for a particular key:

>>> counts = catalog.get_feature("CustomerProductGroupCounts_7d")
>>> new_feature ="Chips et Tortillas")
>>> = "Chips et Tortillas Relative Frequency"
Preview the features:

>>> features = fb.FeatureGroup([counts, new_feature])
>>> df = features.preview(pd.DataFrame([{"POINT_IN_TIME": "2022-04-15 10:00:00", "GROCERYCUSTOMERGUID": "2f4c1578-29d6-44b7-83da-7c5bfb981fa0"}]))
Dictionary feature:

>>> df["CustomerProductGroupCounts_7d"].iloc[0]
{'Chips et Tortillas': 1, 'Colas, Thés glacés et Sodas': 3, 'Crèmes et Chantilly': 1, 'Pains': 1, 'Œufs': 1}

New feature:

>>> df["Chips et Tortillas Relative Frequency"].iloc[0]