class_docstr: Determines the percent of unique values.
  
  Description:
      Given a list of values, determine what percent of the
      list is made up of unique values.  Multiple `NaN` values
      are treated as one unique value.
  
  Args:
      skipna (bool): Determines whether to ignore `NaN` values.
          Defaults to True.
  
  Examples:
      >>> percent_unique = PercentUnique()
      >>> percent_unique([1, 1, 2, 2, 3, 4, 5, 6, 7, 8])
      0.8
  
      We can control whether or not `NaN` values are ignored.
  
      >>> percent_unique = PercentUnique()
      >>> percent_unique([1, 1, 2, None])
      0.5
      >>> percent_unique_skipna = PercentUnique(skipna=False)
      >>> percent_unique_skipna([1, 1, 2, None])
      0.75
code: def __init__(self, skipna=True):
      self.skipna = skipna
  
imports: from woodwork.column_schema import ColumnSchema
  from woodwork.logical_types import Double
  from featuretools.primitives.base import AggregationPrimitive
label_desc: Use image node_id 1 to create a new PercentUnique object from inherited base classes: AggregationPrimitive with example: obj = PercentUnique(skipna)