featuretools.primitives.Skew¶
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class
featuretools.primitives.Skew[source]¶ 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
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__init__()¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__()Initialize self.
generate_name(base_feature_names, …)generate_names(base_feature_names, …)get_args_string()get_arguments()get_filepath(filename)get_function()Attributes
base_ofbase_of_excludecommutativedefault_valueinput_typesmax_stack_depthnamenumber_output_featuresstack_onstack_on_excludestack_on_selfuses_calc_time