featuretools.primitives.
Skew
Computes the extent to which a distribution differs from a normal distribution.
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, …)
generate_name
generate_names(base_feature_names, …)
generate_names
get_args_string()
get_args_string
get_arguments()
get_arguments
get_description(input_column_descriptions[, …])
get_description
get_filepath(filename)
get_filepath
get_function([agg_type])
get_function
Attributes
base_of
base_of_exclude
commutative
compatibility
default_value
description_template
input_types
max_stack_depth
name
number_output_features
return_type
stack_on
stack_on_exclude
stack_on_self
uses_calc_time