featuretools.primitives.Entropy

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

Calculates the entropy for a categorical column

Description:

Given a list of observations from a categorical column 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)

Methods

__init__([dropna, base])
flatten_nested_input_types(input_types)	Flattens nested column schema inputs into a single list.
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()

Attributes

base_of
base_of_exclude
commutative
default_value	Default value this feature returns if no data found.
description_template
input_types	woodwork.ColumnSchema types of inputs
max_stack_depth
name	Name of the primitive
number_output_features	Number of columns in feature matrix associated with this feature
return_type	ColumnSchema type of return
stack_on
stack_on_exclude
stack_on_self
uses_calc_time