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entropy( ) -> Feature


Computes the entropy of the Cross Aggregate feature over the feature keys. The values are normalized to sum to 1 and used as the probability of each key in the entropy calculation.


  • Feature
    A new Feature object.


Create a new feature by calculating the entropy of the dictionary feature:

>>> counts = catalog.get_feature("CustomerProductGroupCounts_7d")
>>> new_feature =
>>> = "CustomerProductGroupCountsEntropy_7d"
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["CustomerProductGroupCountsEntropy_7d"].iloc[0]