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 get_function(self):
      def percent_unique(x):
          return x.nunique(dropna=self.skipna) / (x.shape[0] * 1.0)
  
      return percent_unique
  
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 2 for calling the PercentUnique obj's underlying member method code with example usage: obj.get_function() and returns: percent_unique, unknown