reflect review

Author: baidoosik

doc/source/whatsnew/v0.24.0.txt

@@ -648,6 +648,7 @@ Interval
 Indexing
 ^^^^^^^^
 
+- Bug in :meth:`DataFrame.ne` fails if columns contain column name "dtype" (:issue:`22383`)
 - The traceback from a ``KeyError`` when asking ``.loc`` for a single missing label is now shorter and more clear (:issue:`21557`)
 - When ``.ix`` is asked for a missing integer label in a :class:`MultiIndex` with a first level of integer type, it now raises a ``KeyError``, consistently with the case of a flat :class:`Int64Index, rather than falling back to positional indexing (:issue:`21593`)
 - Bug in :meth:`DatetimeIndex.reindex` when reindexing a tz-naive and tz-aware :class:`DatetimeIndex` (:issue:`8306`)
@@ -656,8 +657,7 @@ Indexing
 - Fixed ``DataFrame[np.nan]`` when columns are non-unique (:issue:`21428`)
 - Bug when indexing :class:`DatetimeIndex` with nanosecond resolution dates and timezones (:issue:`11679`)
 - Bug where indexing with a Numpy array containing negative values would mutate the indexer (:issue:`21867`)
-- Bug Dataframe.ne fails if columns containing column name 'dtype'
-
+-
 
 Missing
 ^^^^^^^

pandas/core/computation/expressions.py

@@ -161,9 +161,7 @@ def _has_bool_dtype(x):
     try:
         if not isinstance(x.dtype, np.dtype):
             x = x.rename({'dtype': 'temporary_dtype'}, axis=1)
-            return x.dtype == bool
-        else:
-            return x.dtype == bool
+        return x.dtype == bool
     except AttributeError:
         try:
             return 'bool' in x.dtypes

pandas/tests/test_expressions.py

@@ -444,7 +444,7 @@ def test_bool_ops_warn_on_arithmetic(self):
                     tm.assert_frame_equal(r, e)
 
     def test_bool_ops_column_name_dtype(self):
-        # GH 22383 -  .ne fails if columns containing column name 'dtype'
+        # GH 22383 - .ne fails if columns containing column name 'dtype'
         df_has_error = DataFrame([[0, 1, 2, 'aa'], [0, 1, 2, 'aa'],
                                   [0, 1, 5, 'bb'], [0, 1, 5, 'bb'],
                                   [0, 1, 5, 'bb'], ['cc', 4, 4, 4]],