Source code for featuretools.primitives.standard.aggregation.skew

import pandas as pd
from woodwork.column_schema import ColumnSchema

from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
from featuretools.utils.gen_utils import Library

[docs]class Skew(AggregationPrimitive): """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 """ name = "skew" input_types = [ColumnSchema(semantic_tags={"numeric"})] return_type = ColumnSchema(semantic_tags={"numeric"}) stack_on = [] stack_on_self = False description_template = "the skewness of {}" def get_function(self, agg_type=Library.PANDAS): return pd.Series.skew