ENH: Add NotNullFilter.

zipline/pipeline/classifiers/classifier.py

@@ -20,7 +20,7 @@ from zipline.utils.numpy_utils import (
     vectorized_is_element,
 )
 
-from ..filters import ArrayPredicate, NullFilter, NumExprFilter
+from ..filters import ArrayPredicate, NotNullFilter, NullFilter, NumExprFilter
 from ..mixins import (
     CustomTermMixin,
     LatestMixin,
@@ -64,7 +64,7 @@ class Classifier(RestrictedDTypeMixin, ComputableTerm):
         """
         A Filter producing True for values where this term has complete data.
         """
-        return ~self.isnull()
+        return NotNullFilter(self)
 
     # We explicitly don't support classifier to classifier comparisons, since
     # the stored values likely don't mean the same thing. This may be relaxed

zipline/pipeline/factors/factor.py

@@ -27,6 +27,7 @@ from zipline.pipeline.filters import (
     Filter,
     NumExprFilter,
     PercentileFilter,
+    NotNullFilter,
     NullFilter,
 )
 from zipline.pipeline.mixins import (
@@ -1013,7 +1014,7 @@ class Factor(RestrictedDTypeMixin, ComputableTerm):
         Equivalent to ``~self.isnan()` when ``self.dtype`` is float64.
         Otherwise equivalent to ``(self != self.missing_value)``.
         """
-        return ~self.isnull()
+        return NotNullFilter(self)
 
     @if_not_float64_tell_caller_to_use_isnull
     def isnan(self):

zipline/pipeline/filters/__init__.py

@@ -3,6 +3,7 @@ from .filter import (
     CustomFilter,
     Filter,
     Latest,
+    NotNullFilter,
     NullFilter,
     NumExprFilter,
     PercentileFilter,
@@ -14,6 +15,7 @@ __all__ = [
     'CustomFilter',
     'Filter',
     'Latest',
+    'NotNullFilter',
     'NullFilter',
     'NumExprFilter',
     'PercentileFilter',

zipline/pipeline/filters/filter.py

@@ -250,6 +250,30 @@ class NullFilter(SingleInputMixin, Filter):
         return is_missing(arrays[0], self.inputs[0].missing_value)
 
 
+class NotNullFilter(SingleInputMixin, Filter):
+    """
+    A Filter indicating whether input values are **not** missing from an input.
+
+    Parameters
+    ----------
+    factor : zipline.pipeline.Term
+        The factor to compare against its missing_value.
+    """
+    window_length = 0
+
+    def __new__(cls, term):
+        return super(NotNullFilter, cls).__new__(
+            cls,
+            inputs=(term,),
+        )
+
+    def _compute(self, arrays, dates, assets, mask):
+        data = arrays[0]
+        if isinstance(data, LabelArray):
+            return ~data.is_missing()
+        return ~is_missing(arrays[0], self.inputs[0].missing_value)
+
+
 class PercentileFilter(SingleInputMixin, Filter):
     """
     A Filter representing assets falling between percentile bounds of a Factor.