class_docstr: Determines the number of values that fall outside a certain range.
  
  Args:
      lower (float): Lower boundary of range (exclusive). Default is 0.
      upper (float): Upper boundary of range (exclusive). Default is 1.
      skipna (bool): Determines if to use NA/null values. Defaults to
          True to skip NA/null.
  
  Examples:
      >>> count_outside_range = CountOutsideRange(lower=1.5, upper=3.6)
      >>> count_outside_range([1, 2, 3, 4, 5])
      3
  
      The way NaNs are treated can be controlled.
  
      >>> count_outside_range_skipna = CountOutsideRange(skipna=False)
      >>> count_outside_range_skipna([1, 2, 3, 4, 5, None])
      nan
code: def get_function(self):
      def count_outside_range(x):
          if not self.skipna and x.isnull().values.any():
              return np.nan
          cond = (x < self.lower) | (x > self.upper)
          return cond.sum()
  
      return count_outside_range
  
imports: import numpy
  from woodwork.column_schema import ColumnSchema
  from woodwork.logical_types import IntegerNullable
  from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
label_desc: Use image node_id 2 for calling the CountOutsideRange obj's underlying member method code with example usage: obj.get_function() and returns: count_outside_range, cond, np