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 __init__(self, skipna=True):
      self.skipna = skipna
  
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 1 to create a new Mean object from inherited base classes: AggregationPrimitive with example: obj = Mean(skipna)