PERF: remove auto-boxing on isnull/notnull

doc/source/api.rst

@@ -258,6 +258,8 @@ Conversion / Constructors
    Series.__init__
    Series.astype
    Series.copy
+   Series.isnull
+   Series.notnull
 
 Indexing, iteration
 ~~~~~~~~~~~~~~~~~~~
@@ -472,6 +474,8 @@ Conversion / Constructors
    DataFrame.astype
    DataFrame.convert_objects
    DataFrame.copy
+   DataFrame.isnull
+   DataFrame.notnull
 
 Indexing, iteration
 ~~~~~~~~~~~~~~~~~~~
@@ -714,6 +718,8 @@ Conversion / Constructors
    Panel.__init__
    Panel.astype
    Panel.copy
+   Panel.isnull
+   Panel.notnull
 
 Getting and setting
 ~~~~~~~~~~~~~~~~~~~
@@ -976,7 +982,7 @@ Time/Date Components
   * **week**: Same as weekofyear
   * **dayofweek**: (0=Monday, 6=Sunday)
   * **weekday**: (0=Monday, 6=Sunday)
-  * **dayofyear** 
+  * **dayofyear**
   * **quarter**
 
   * **date**: Returns date component of Timestamps
@@ -990,7 +996,7 @@ Selecting
 
    DatetimeIndex.indexer_at_time
    DatetimeIndex.indexer_between_time
-   
+
 
 Time-specific operations
 ~~~~~~~~~~~~~~~~~~~~~~~~

doc/source/release.rst

@@ -323,6 +323,7 @@ See :ref:`Internal Refactoring<whatsnew_0130.refactoring>`
     - ``filter`` (also added axis argument to selectively filter on a different axis)
     - ``reindex,reindex_axis,take``
     - ``truncate`` (moved to become part of ``NDFrame``)
+    - ``isnull/notnull`` now available on ``NDFrame`` objects
 
  - These are API changes which make ``Panel`` more consistent with ``DataFrame``
 

pandas/core/common.py

@@ -182,7 +182,7 @@ def _use_inf_as_null(key):
 
 def _isnull_ndarraylike(obj):
 
-    values = obj
+    values = getattr(obj,'values',obj)
     dtype = values.dtype
 
     if dtype.kind in ('O', 'S', 'U'):
@@ -198,22 +198,15 @@ def _isnull_ndarraylike(obj):
 
     elif dtype in _DATELIKE_DTYPES:
         # this is the NaT pattern
-        v = getattr(values, 'asi8', None)
-        if v is None:
-            v = values.view('i8')
-        result = v == tslib.iNaT
+        result = values.view('i8') == tslib.iNaT
     else:
-        result = np.isnan(obj)
-
-    if isinstance(obj, ABCSeries):
-        from pandas import Series
-        result = Series(result, index=obj.index, copy=False)
+        result = np.isnan(values)
 
     return result
 
 
 def _isnull_ndarraylike_old(obj):
-    values = obj
+    values = getattr(obj,'values',obj)
     dtype = values.dtype
 
     if dtype.kind in ('O', 'S', 'U'):
@@ -229,16 +222,9 @@ def _isnull_ndarraylike_old(obj):
 
     elif dtype in _DATELIKE_DTYPES:
         # this is the NaT pattern
-        v = getattr(values, 'asi8', None)
-        if v is None:
-            v = values.view('i8')
-        result = v == tslib.iNaT
+        result = values.view('i8') == tslib.iNaT
     else:
-        result = -np.isfinite(obj)
-
-    if isinstance(obj, ABCSeries):
-        from pandas import Series
-        result = Series(result, index=obj.index, copy=False)
+        result = -np.isfinite(values)
 
     return result
 

pandas/core/generic.py

@@ -2019,6 +2019,18 @@ def interpolate(self, to_replace, method='pad', axis=0, inplace=False,
     #----------------------------------------------------------------------
     # Action Methods
 
+    def isnull(self):
+        """
+        Return a boolean same-sized object indicating if the values are null
+        """
+        return self.__class__(isnull(self),**self._construct_axes_dict())._propogate_attributes(self)
+
+    def notnull(self):
+        """
+        Return a boolean same-sized object indicating if the values are not null
+        """
+        return self.__class__(notnull(self),**self._construct_axes_dict())._propogate_attributes(self)
+
     def clip(self, lower=None, upper=None, out=None):
         """
         Trim values at input threshold(s)

pandas/core/ops.py

@@ -539,7 +539,7 @@ def wrapper(self, other):
 
             # mask out the invalids
             if mask.any():
-                res[mask.values] = masker
+                res[mask] = masker
 
             return res
     return wrapper

pandas/core/series.py

@@ -2174,9 +2174,6 @@ def dropna(self):
 
     valid = lambda self: self.dropna()
 
-    isnull = isnull
-    notnull = notnull
-
     def first_valid_index(self):
         """
         Return label for first non-NA/null value

pandas/tests/test_common.py

@@ -64,11 +64,9 @@ def test_notnull():
         assert result.sum() == 2
 
     with cf.option_context("mode.use_inf_as_null", False):
-        float_series = Series(np.random.randn(5))
-        obj_series = Series(np.random.randn(5), dtype=object)
-        assert(isinstance(notnull(float_series), Series))
-        assert(isinstance(notnull(obj_series), Series))
-
+        for s in [tm.makeFloatSeries(),tm.makeStringSeries(),
+                  tm.makeObjectSeries(),tm.makeTimeSeries(),tm.makePeriodSeries()]:
+            assert(isinstance(isnull(s), np.ndarray))
 
 def test_isnull():
     assert not isnull(1.)
@@ -77,10 +75,9 @@ def test_isnull():
     assert not isnull(np.inf)
     assert not isnull(-np.inf)
 
-    float_series = Series(np.random.randn(5))
-    obj_series = Series(np.random.randn(5), dtype=object)
-    assert(isinstance(isnull(float_series), Series))
-    assert(isinstance(isnull(obj_series), Series))
+    for s in [tm.makeFloatSeries(),tm.makeStringSeries(),
+              tm.makeObjectSeries(),tm.makeTimeSeries(),tm.makePeriodSeries()]:
+        assert(isinstance(isnull(s), np.ndarray))
 
     # call on DataFrame
     df = DataFrame(np.random.randn(10, 5))

pandas/tests/test_frame.py

@@ -1546,7 +1546,7 @@ def test_set_value_resize(self):
         res = self.frame.copy()
         res3 = res.set_value('foobar', 'baz', 5)
         self.assert_(com.is_float_dtype(res3['baz']))
-        self.assert_(isnull(res3['baz'].drop(['foobar'])).values.all())
+        self.assert_(isnull(res3['baz'].drop(['foobar'])).all())
         self.assertRaises(ValueError, res3.set_value, 'foobar', 'baz', 'sam')
 
     def test_set_value_with_index_dtype_change(self):

pandas/tests/test_series.py

@@ -3667,17 +3667,17 @@ def test_valid(self):
 
     def test_isnull(self):
         ser = Series([0, 5.4, 3, nan, -0.001])
-        assert_series_equal(
-            ser.isnull(), Series([False, False, False, True, False]))
+        np.array_equal(
+            ser.isnull(), Series([False, False, False, True, False]).values)
         ser = Series(["hi", "", nan])
-        assert_series_equal(ser.isnull(), Series([False, False, True]))
+        np.array_equal(ser.isnull(), Series([False, False, True]).values)
 
     def test_notnull(self):
         ser = Series([0, 5.4, 3, nan, -0.001])
-        assert_series_equal(
-            ser.notnull(), Series([True, True, True, False, True]))
+        np.array_equal(
+            ser.notnull(), Series([True, True, True, False, True]).values)
         ser = Series(["hi", "", nan])
-        assert_series_equal(ser.notnull(), Series([True, True, False]))
+        np.array_equal(ser.notnull(), Series([True, True, False]).values)
 
     def test_shift(self):
         shifted = self.ts.shift(1)