class_docstr: Computes the average for a list of values.
  
  Args:
      skipna (bool): Determines if to use NA/null values. Defaults to
          True to skip NA/null.
  
  Examples:
      >>> mean = Mean()
      >>> mean([1, 2, 3, 4, 5, None])
      3.0
  
      We can also control the way `NaN` values are handled.
  
      >>> mean = Mean(skipna=False)
      >>> mean([1, 2, 3, 4, 5, None])
      nan
code: def get_function(self, agg_type=Library.PANDAS):
      if agg_type in [Library.DASK, Library.SPARK]:
          return "mean"
  
      if self.skipna:
          # np.mean of series is functionally nanmean
          return np.mean
  
      def mean(series):
          return np.mean(series.values)
  
      return mean
  
imports: import numpy
  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 2 for calling the Mean obj's underlying member method code with example usage: obj.get_function(agg_type) and returns: mean, str, np, np