featuretools.primitives.Skew

class featuretools.primitives.Skew

Computes the extent to which a distribution differs from a normal distribution.

Description:

For normally distributed data, the skewness should be about 0. A skewness value > 0 means that there is more weight in the left tail of the distribution.

Examples

>>> skew = Skew()
>>> skew([1, 10, 30, None])
1.0437603722639681
__init__()

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

Methods

__init__()

Initialize self.

generate_name(base_feature_names, …)

get_args_string()

get_arguments()

get_filepath(filename)

get_function()

Attributes

allow_where

base_of

base_of_exclude

commutative

default_value

input_types

max_stack_depth

name

number_output_features

stack_on

stack_on_exclude

stack_on_self

uses_calc_time