reflect review

Author: baidoosik

pandas/core/computation/expressions.py

@@ -8,6 +8,7 @@
 
 import warnings
 import numpy as np
+from pandas.core.dtypes.generic import ABCDataFrame
 
 import pandas.core.common as com
 from pandas.core.computation.check import _NUMEXPR_INSTALLED
@@ -158,13 +159,11 @@ def _where_numexpr(cond, a, b):
 
 
 def _has_bool_dtype(x):
-    try:
-        if not isinstance(x.dtype, np.dtype):
-            x = x.rename(columns={'dtype': 'temporary_dtype'})
-        return x.dtype == bool
-    except AttributeError:
+    if isinstance(x, ABCDataFrame):
+        return 'bool' in x.dtypes
+    else:
         try:
-            return 'bool' in x.dtypes
+            return x.dtype == bool
         except AttributeError:
             return isinstance(x, (bool, np.bool_))
 

pandas/tests/test_expressions.py

@@ -36,7 +36,6 @@
 _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),
@@ -443,18 +442,15 @@ def test_bool_ops_warn_on_arithmetic(self):
                     e = fe(df, True)
                     tm.assert_frame_equal(r, e)
 
-    def test_bool_ops_column_name_dtype(self):
+    def test_has_bool_ops_column_name_dtype(self, eq, ne):
         # 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))
+        expected = DataFrame([[False, False], [False, False],
+                             [False, False], [False, False]],
+                             columns=["a", "dtype"])
+        assert_frame_equal(expected,
+                           df_has_error.loc[:, ['a', 'dtype']].
+                           ne(df_has_error.loc[:, ['a', 'dtype']]))