add test and what's new

Author: baidoosik

doc/source/whatsnew/v0.24.0.txt

@@ -654,6 +654,8 @@ 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/tests/test_expressions.py

@@ -10,7 +10,6 @@
 from numpy.random import randn
 
 import numpy as np
-
 from pandas.core.api import DataFrame, Panel
 from pandas.core.computation import expressions as expr
 from pandas import compat, _np_version_under1p11, _np_version_under1p13
@@ -37,6 +36,7 @@
 _integer2 = DataFrame(np.random.randint(1, 100, size=(101, 4)),
                       columns=list('ABCD'), dtype='int64')
 
+
 with catch_warnings(record=True):
     _frame_panel = Panel(dict(ItemA=_frame.copy(),
                               ItemB=(_frame.copy() + 3),
@@ -442,3 +442,19 @@ def test_bool_ops_warn_on_arithmetic(self):
                     r = f(df, True)
                     e = fe(df, True)
                     tm.assert_frame_equal(r, e)
+
+    def test_bool_ops_column_name_dtype(self):
+        # 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]],
+                                 columns=['a', 'b', 'c', 'dtype'])
+        df = 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]],
+                       columns=['a', 'b', 'c', 'd'])
+        result = df_has_error.loc[:, ['a', 'dtype']].ne(df_has_error.loc[:,
+                                                        ['a', 'dtype']])
+        assert_frame_equal(result,
+                           df.loc[:, ['a', 'd']].ne(df.loc[:, ['a', 'd']]).
+                           rename({'d': 'dtype'}, axis=1))