featuretools.primitives.Entropy#
- class featuretools.primitives.Entropy(dropna=False, base=None)[source]#
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
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
([agg_type])Attributes
base_of
base_of_exclude
commutative
compatibility
Additional compatible libraries
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
series_library
stack_on
stack_on_exclude
stack_on_self
uses_calc_time