Fix return value of 'any()' and 'all()' on pd.Series

Author: MomIsBestFriend

pandas/core/nanops.py

@@ -407,7 +407,7 @@ def nanany(values, axis=None, skipna: bool = True, mask=None):
 
     Returns
     -------
-    result : bool
+    bool
 
     Examples
     --------
@@ -421,7 +421,16 @@ def nanany(values, axis=None, skipna: bool = True, mask=None):
     >>> nanops.nanany(s)
     False
     """
-    values, _, _, _, _ = _get_values(values, skipna, fill_value=False, mask=mask)
+    values, _, dtype, _, _ = _get_values(values, skipna, fill_value=False, mask=mask)
+
+    # GH #12863
+    # Checking if the `axis` is None because numpy
+    # doesn't handle ``any`` and ``all`` on
+    # object arrays correclty. see
+    # https://github.com/numpy/numpy/issues/4352
+    if is_object_dtype(dtype) and values.size <= 2 and axis is None:
+        return any(values)
+
     return values.any(axis)
 
 
@@ -439,7 +448,7 @@ def nanall(values, axis=None, skipna: bool = True, mask=None):
 
     Returns
     -------
-    result : bool
+    bool
 
     Examples
     --------
@@ -453,7 +462,16 @@ def nanall(values, axis=None, skipna: bool = True, mask=None):
     >>> nanops.nanall(s)
     False
     """
-    values, _, _, _, _ = _get_values(values, skipna, fill_value=True, mask=mask)
+    values, _, dtype, _, _ = _get_values(values, skipna, fill_value=True, mask=mask)
+
+    # GH #12863
+    # Checking if the `axis` is None because numpy
+    # doesn't handle ``any`` and ``all`` on
+    # object arrays correclty. see
+    # https://github.com/numpy/numpy/issues/4352
+    if is_object_dtype(dtype) and values.size <= 2 and axis is None:
+        return all(values)
+
     return values.all(axis)
 
 

pandas/tests/reductions/test_reductions.py

@@ -811,19 +811,33 @@ def test_all_any(self):
         assert not bool_series.all()
         assert bool_series.any()
 
-        # Alternative types, with implicit 'object' dtype.
-        s = Series(["abc", True])
-        assert "abc" == s.any()  # 'abc' || True => 'abc'
+        # GH 12863
+        s1 = Series(["abc", True])
+        s2 = Series(["abc", False])
+
+        assert s1.all()
+        assert s1.any()
+
+        assert not s2.all()
+        assert s2.any()
 
     def test_all_any_params(self):
         # Check skipna, with implicit 'object' dtype.
         s1 = Series([np.nan, True])
         s2 = Series([np.nan, False])
-        assert s1.all(skipna=False)  # nan && True => True
+
         assert s1.all(skipna=True)
-        assert np.isnan(s2.any(skipna=False))  # nan || False => nan
+        assert s1.any(skipna=True)
+
+        assert s1.all(skipna=False)
+        assert s1.any(skipna=False)
+
+        assert not s2.all(skipna=True)
         assert not s2.any(skipna=True)
 
+        assert not s2.all(skipna=False)
+        assert s2.any(skipna=False)
+
         # Check level.
         s = pd.Series([False, False, True, True, False, True], index=[0, 0, 1, 1, 2, 2])
         tm.assert_series_equal(s.all(level=0), Series([False, True, False]))