API/REGR: (re-)allow neg/pos unary operation on object dtype (pandas-dev#21590)

Author: jorisvandenbossche

doc/source/whatsnew/v0.23.2.txt

@@ -54,6 +54,7 @@ Fixed Regressions
 
 - Fixed regression in :meth:`to_csv` when handling file-like object incorrectly (:issue:`21471`)
 - Bug in both :meth:`DataFrame.first_valid_index` and :meth:`Series.first_valid_index` raised for a row index having duplicate values (:issue:`21441`)
+- Fixed regression in unary negative operations with object dtype (:issue:`21380`)
 - Bug in :meth:`Timestamp.ceil` and :meth:`Timestamp.floor` when timestamp is a multiple of the rounding frequency (:issue:`21262`)
 
 .. _whatsnew_0232.performance:

pandas/core/generic.py

@@ -27,6 +27,7 @@
  is_dict_like,
  is_re_compilable,
  is_period_arraylike,
+ is_object_dtype,
  pandas_dtype)
 from pandas.core.dtypes.cast import maybe_promote, maybe_upcast_putmask
 from pandas.core.dtypes.inference import is_hashable
@@ -1117,7 +1118,8 @@ def __neg__(self):
  values = com._values_from_object(self)
  if is_bool_dtype(values):
  arr = operator.inv(values)
- elif (is_numeric_dtype(values) or is_timedelta64_dtype(values)):
+ elif (is_numeric_dtype(values) or is_timedelta64_dtype(values)
+ or is_object_dtype(values)):
  arr = operator.neg(values)
  else:
  raise TypeError("Unary negative expects numeric dtype, not {}"
@@ -1128,7 +1130,8 @@ def __pos__(self):
  values = com._values_from_object(self)
  if (is_bool_dtype(values) or is_period_arraylike(values)):
  arr = values
- elif (is_numeric_dtype(values) or is_timedelta64_dtype(values)):
+ elif (is_numeric_dtype(values) or is_timedelta64_dtype(values)
+ or is_object_dtype(values)):
  arr = operator.pos(values)
  else:
  raise TypeError("Unary plus expects numeric dtype, not {}"

pandas/tests/frame/test_operators.py

@@ -3,6 +3,7 @@
 from __future__ import print_function
 from collections import deque
 from datetime import datetime
+from decimal import Decimal
 import operator
 
 import pytest
@@ -282,6 +283,17 @@ def test_neg_numeric(self, df, expected):
  assert_frame_equal(-df, expected)
  assert_series_equal(-df['a'], expected['a'])
 
+ @pytest.mark.parametrize('df, expected', [
+ (np.array([1, 2], dtype=object), np.array([-1, -2], dtype=object)),
+ ([Decimal('1.0'), Decimal('2.0')], [Decimal('-1.0'), Decimal('-2.0')]),
+ ])
+ def test_neg_object(self, df, expected):
+ # GH 21380
+ df = pd.DataFrame({'a': df})
+ expected = pd.DataFrame({'a': expected})
+ assert_frame_equal(-df, expected)
+ assert_series_equal(-df['a'], expected['a'])
+
  @pytest.mark.parametrize('df', [
  pd.DataFrame({'a': ['a', 'b']}),
  pd.DataFrame({'a': pd.to_datetime(['2017-01-22', '1970-01-01'])}),
@@ -307,6 +319,15 @@ def test_pos_numeric(self, df):
 
  @pytest.mark.parametrize('df', [
  pd.DataFrame({'a': ['a', 'b']}),
+ pd.DataFrame({'a': np.array([-1, 2], dtype=object)}),
+ pd.DataFrame({'a': [Decimal('-1.0'), Decimal('2.0')]}),
+ ])
+ def test_pos_object(self, df):
+ # GH 21380
+ assert_frame_equal(+df, df)
+ assert_series_equal(+df['a'], df['a'])
+
+ @pytest.mark.parametrize('df', [
  pd.DataFrame({'a': pd.to_datetime(['2017-01-22', '1970-01-01'])}),
  ])
  def test_pos_raises(self, df):