[REVIEW] Series/DataFrame notnull

CHANGELOG.md

@@ -24,6 +24,7 @@
 - PR #2786 Add benchmarks option to root build.sh
 - PR #2773 Add Fisher's unbiased kurtosis and skew for Series/DataFrame
 - PR #2748 Parquet Reader: Add option to specify loading of PANDAS index
+- PR #2844 ADd Series/DataFrame notnull
 
 ## Improvements
 

python/cudf/cudf/core/dataframe.py

@@ -3063,20 +3063,25 @@ def _create_output_frame(data, percentiles=None):
 
         return output_frame
 
-    def isnull(self, **kwargs):
+    def isnull(self):
         """Identify missing values in a DataFrame.
         """
-        return self._apply_support_method("isnull", **kwargs)
+        return self._apply_support_method("isnull")
 
-    def isna(self, **kwargs):
+    def isna(self):
         """Identify missing values in a DataFrame. Alias for isnull.
         """
-        return self.isnull(**kwargs)
+        return self.isnull()
 
-    def notna(self, **kwargs):
+    def notna(self):
         """Identify non-missing values in a DataFrame.
         """
-        return self._apply_support_method("notna", **kwargs)
+        return self._apply_support_method("notna")
+
+    def notnull(self):
+        """Identify non-missing values in a DataFrame. Alias for notna.
+        """
+        return self.notna()
 
     def to_pandas(self):
         """

python/cudf/cudf/core/series.py

@@ -1287,6 +1287,11 @@ def notna(self):
         mask = cudautils.notna_mask(self.data, self.nullmask.mem)
         return Series(mask, name=self.name, index=self.index)
 
+    def notnull(self):
+        """Identify non-missing values in a Series. Alias for notna.
+        """
+        return self.notna()
+
     def nans_to_nulls(self):
         """
         Convert nans (if any) to nulls

python/cudf/cudf/tests/test_dataframe.py

@@ -2527,7 +2527,7 @@ def test_isnull_isna():
     assert_eq(ps.isna(), gs.isna())
 
 
-def test_notna():
+def test_notna_notnull():
     # float & strings some missing
     ps = pd.DataFrame(
         {
@@ -2538,12 +2538,16 @@ def test_notna():
     gs = DataFrame.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
     assert_eq(ps.a.notna(), gs.a.notna())
+    assert_eq(ps.notnull(), gs.notnull())
+    assert_eq(ps.a.notnull(), gs.a.notnull())
 
     # integer & string none missing
     ps = pd.DataFrame({"a": [0, 1, 2, 3, 4], "b": ["a", "b", "u", "h", "d"]})
     gs = DataFrame.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
     assert_eq(ps.a.notna(), gs.a.notna())
+    assert_eq(ps.notnull(), gs.notnull())
+    assert_eq(ps.a.notnull(), gs.a.notnull())
 
     # all missing
     ps = pd.DataFrame(
@@ -2552,35 +2556,46 @@ def test_notna():
     gs = DataFrame.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
     assert_eq(ps.a.notna(), gs.a.notna())
+    assert_eq(ps.notnull(), gs.notnull())
+    assert_eq(ps.a.notnull(), gs.a.notnull())
 
     # empty
     ps = pd.DataFrame({"a": []})
     gs = DataFrame.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
     assert_eq(ps.a.notna(), gs.a.notna())
+    assert_eq(ps.notnull(), gs.notnull())
+    assert_eq(ps.a.notnull(), gs.a.notnull())
 
     # one missing
     ps = pd.DataFrame({"a": [np.nan], "b": [None]})
     gs = DataFrame.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
     assert_eq(ps.a.notna(), gs.a.notna())
+    assert_eq(ps.notnull(), gs.notnull())
+    assert_eq(ps.a.notnull(), gs.a.notnull())
 
     # strings missing
     ps = pd.DataFrame({"a": ["a", "b", "c", None, "e"]})
     gs = DataFrame.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
     assert_eq(ps.a.notna(), gs.a.notna())
+    assert_eq(ps.notnull(), gs.notnull())
+    assert_eq(ps.a.notnull(), gs.a.notnull())
 
     # strings none missing
     ps = pd.DataFrame({"a": ["a", "b", "c", "d", "e"]})
     gs = DataFrame.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
     assert_eq(ps.a.notna(), gs.a.notna())
+    assert_eq(ps.notnull(), gs.notnull())
+    assert_eq(ps.a.notnull(), gs.a.notnull())
 
     # unnamed series
     ps = pd.Series([0, 1, 2, np.nan, 4, None, 6])
     gs = Series.from_pandas(ps)
     assert_eq(ps.notna(), gs.notna())
+    assert_eq(ps.notnull(), gs.notnull())
 
 
 def test_ndim():