class_docstr: Counts the number of `True` values.
  
  Description:
      Given a list of booleans, return the number
      of `True` values. Ignores 'NaN'.
  
  Examples:
      >>> num_true = NumTrue()
      >>> num_true([True, False, True, True, None])
      3
code: def get_function(self, agg_type=Library.PANDAS):
      if agg_type == Library.DASK:
  
          def chunk(s):
              chunk_sum = s.agg(np.sum)
              if chunk_sum.dtype == "bool":
                  chunk_sum = chunk_sum.astype("int64")
              return chunk_sum
  
          def agg(s):
              return s.agg(np.sum)
  
          return dd.Aggregation(self.name, chunk=chunk, agg=agg)
  
      return np.sum
  
imports: import numpy
  from woodwork.column_schema import ColumnSchema
  from woodwork.logical_types import Boolean, BooleanNullable, IntegerNullable
  from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
  from featuretools.utils.gen_utils import Library, import_or_none
label_desc: Use image node_id 1 for calling the NumTrue obj's underlying member method code with example usage: obj.get_function(agg_type) and returns: np, dd, chunk_sum, s