NOTICE

The upcoming release of Featuretools 1.0.0 contains several breaking changes. Users are encouraged to test this version prior to release:

pip install featuretools==1.0.0rc1

For details on migrating to the new version, refer to Transitioning to Featuretools Version 1.0. Please report any issues in the Featuretools GitHub repo or by messaging in Alteryx Open Source Slack.


featuretools.primitives.Entropy

class featuretools.primitives.Entropy(dropna=False, base=None)[source]

Calculates the entropy for a categorical variable

Description:

Given a list of observations from a categorical variable return the entropy of the distribution. NaN values can be treated as a category or dropped.

Parameters
  • dropna (bool) – Whether to consider NaN values as a separate category Defaults to False.

  • base (float) – The logarithmic base to use Defaults to e (natural logarithm)

Examples

>>> pd_entropy = Entropy()
>>> pd_entropy([1,2,3,4])
1.3862943611198906
__init__(dropna=False, base=None)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([dropna, base])

Initialize self.

generate_name(base_feature_names, …)

generate_names(base_feature_names, …)

get_args_string()

get_arguments()

get_description(input_column_descriptions[, …])

get_filepath(filename)

get_function([agg_type])

Attributes

base_of

base_of_exclude

commutative

compatibility

default_value

description_template

input_types

max_stack_depth

name

number_output_features

stack_on

stack_on_exclude

stack_on_self

uses_calc_time