class_docstr: 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
code: def get_function(self, agg_type=Library.PANDAS):
      return pd.Series.skew
  
imports: import pandas
  from woodwork.column_schema import ColumnSchema
  from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
  from featuretools.utils.gen_utils import Library
label_desc: Use image node_id 1 for calling the Skew obj's underlying member method code with example usage: obj.get_function(agg_type) and returns: pd