class_docstr: A Term that should be computed from a tuple of inputs.
  
  This is the base class for :class:`zipline.pipeline.Factor`,
  :class:`zipline.pipeline.Filter`, and :class:`zipline.pipeline.Classifier`.
class_docstr_tok: ["A","Term","that","should","be","computed","from","a","tuple","of","inputs",".","This","is","the","base","class","for",":","class",":","`","zipline.pipeline.Factor","`",",",":","class",":","`","zipline.pipeline.Filter","`",",","and",":","class",":","`","zipline.pipeline.Classifier","`","."]
docstr: A Filter producing True for values where this Factor has missing data.
  
  Equivalent to self.isnan() when ``self.dtype`` is float64.
  Otherwise equivalent to ``self.eq(self.missing_value)``.
  
  Returns
  -------
  filter : zipline.pipeline.Filter
docstr_tok: ["A","Filter","producing","True","for","values","where","this","Factor","has","missing","data",".","Equivalent","to","self.isnan","(",")","when","``","self.dtype","``","is","float64",".","Otherwise","equivalent","to","``","self.eq","(","self.missing_value",")","``",".","Returns","--","--","--","-","filter",":","zipline.pipeline.Filter"]
code: def isnull(self):
      """
      A Filter producing True for values where this Factor has missing data.
  
      Equivalent to self.isnan() when ``self.dtype`` is float64.
      Otherwise equivalent to ``self.eq(self.missing_value)``.
  
      Returns
      -------
      filter : zipline.pipeline.Filter
      """
      if self.dtype == bool_dtype:
          raise TypeError("isnull() is not supported for Filters")
  
      from .filters import NullFilter
  
      if self.dtype == float64_dtype:
          # Using isnan is more efficient when possible because we can fold
          # the isnan computation with other NumExpr expressions.
          return self.isnan()
      else:
          return NullFilter(self)
  
imports: from abc import ABCMeta, abstractproperty, abstractmethod
  from bisect import insort
  from collections import Mapping
  from weakref import WeakValueDictionary
  from numpy import array, dtype, ndarray
  from six import with_metaclass
  from zipline.assets import Asset
  from zipline.errors import DTypeNotSpecified, InvalidOutputName, NonSliceableTerm, NonWindowSafeInput, NotDType, NonPipelineInputs, TermInputsNotSpecified, TermOutputsEmpty, UnsupportedDType, WindowLengthNotSpecified
  from zipline.lib.adjusted_array import can_represent_dtype
  from zipline.lib.labelarray import LabelArray
  from zipline.utils.input_validation import expect_types
  from zipline.utils.memoize import classlazyval, lazyval
  from zipline.utils.numpy_utils import bool_dtype, categorical_dtype, datetime64ns_dtype, default_missing_value_for_dtype, float64_dtype
  from zipline.utils.sharedoc import templated_docstring, PIPELINE_ALIAS_NAME_DOC, PIPELINE_DOWNSAMPLING_FREQUENCY_DOC
  from .domain import Domain, GENERIC, infer_domain
  from .downsample_helpers import expect_downsample_frequency
  from .sentinels import NotSpecified
label_desc: Use image node_id 13 for calling the ComputableTerm obj's underlying member method code with example usage: obj.isnull() and returns: self, NullFilter