Fixed tests for latest numpy

pandas/compat/numpy/__init__.py

@@ -12,6 +12,7 @@
 _np_version_under1p13 = _nlv < LooseVersion('1.13')
 _np_version_under1p14 = _nlv < LooseVersion('1.14')
 _np_version_under1p15 = _nlv < LooseVersion('1.15')
+_np_version_under1p16 = _nlv < LooseVersion('1.16')
 
 
 if _nlv < '1.12':

pandas/core/ops.py

@@ -23,10 +23,11 @@
  construct_1d_object_array_from_listlike, find_common_type,
  maybe_upcast_putmask)
 from pandas.core.dtypes.common import (
- ensure_object, is_bool_dtype, is_categorical_dtype, is_datetime64_dtype,
- is_datetime64_any_dtype, is_datetime64tz_dtype, is_datetimelike_v_numeric,
- is_extension_array_dtype, is_integer_dtype, is_list_like, is_object_dtype,
- is_period_dtype, is_scalar, is_timedelta64_dtype, needs_i8_conversion)
+ ensure_object, is_bool_dtype, is_categorical_dtype,
+ is_datetime64_any_dtype, is_datetime64_dtype, is_datetime64tz_dtype,
+ is_datetimelike_v_numeric, is_extension_array_dtype, is_integer_dtype,
+ is_list_like, is_object_dtype, is_period_dtype, is_scalar,
+ is_timedelta64_dtype, needs_i8_conversion)
 from pandas.core.dtypes.generic import (
  ABCDataFrame, ABCIndex, ABCIndexClass, ABCPanel, ABCSeries, ABCSparseArray,
  ABCSparseSeries)

pandas/tests/frame/test_arithmetic.py

@@ -762,6 +762,9 @@ def test_timedelta_mixed_inv_raise(self, typ, op):
  df = df.astype({'a': typ, 'b': typ})
  pytest.raises(TypeError, op, df)
 
+ @pytest.mark.skipif(not pd.compat.numpy._np_version_under1p16,
+ reason='NumPy 1.6 or later shows warning when op '
+ 'performed against non-numeric dtype')
  @pytest.mark.parametrize('typ', ['Int64', 'Int32', 'Int16', 'Int8'])
  @pytest.mark.parametrize('op', [operator.pos])
  def test_object_mixed(self, typ, op):

pandas/tests/frame/test_operators.py

@@ -62,10 +62,21 @@ def test_invert(self):
 
  @pytest.mark.parametrize('df', [
  pd.DataFrame({'a': [-1, 1]}),
+ pd.DataFrame({'a': [0.0, 1.1]}),
+ ])
+ def test_pos_numeric(self, df):
+ # GH#16073
+ assert_frame_equal(+df, df)
+ assert_series_equal(+df['a'], df['a'])
+
+ @pytest.mark.skipif(not pd.compat.numpy._np_version_under1p16,
+ reason='NumPy 1.6 or later shows warning when op '
+ 'performed against non-numeric dtype')
+ @pytest.mark.parametrize('df', [
  pd.DataFrame({'a': [False, True]}),
  pd.DataFrame({'a': pd.Series(pd.to_timedelta([-1, 1]))}),
  ])
- def test_pos_numeric(self, df):
+ def test_pos_non_numeric(self, df):
  # GH#16073
  assert_frame_equal(+df, df)
  assert_series_equal(+df['a'], df['a'])

pandas/tests/series/test_arithmetic.py

@@ -222,6 +222,9 @@ def test_float_inv_raise(self, float_dtype, op):
  # consistent with numpy
  pytest.raises(TypeError, op, ser.values)
 
+ @pytest.mark.skipif(not pd.compat.numpy._np_version_under1p16,
+ reason='NumPy 1.6 or later shows warning when op '
+ 'performed against non-numeric dtype')
  @pytest.mark.parametrize('typ', ['bool'])
  @pytest.mark.parametrize('op', [operator.pos, operator.neg,
  operator.inv, operator.abs])
@@ -245,6 +248,9 @@ def test_bool(self, typ, op):
  exp = Series(op(ser.values), index=ser.index)
  tm.assert_series_equal(result, exp)
 
+ @pytest.mark.skipif(not pd.compat.numpy._np_version_under1p16,
+ reason='NumPy 1.6 or later shows warning when op '
+ 'performed against non-numeric dtype')
  @pytest.mark.parametrize('typ', ['datetime64[ns]', 'datetime64[ns, GMT]',
  'datetime64[ns, US/Eastern]'])
  @pytest.mark.parametrize('op', [operator.pos])
@@ -290,6 +296,9 @@ def test_timedelta_inv_raise(self, typ, op):
  # consistent with numpy
  pytest.raises(TypeError, op, ser.values)
 
+ @pytest.mark.skipif(not pd.compat.numpy._np_version_under1p16,
+ reason='NumPy 1.6 or later shows warning when op '
+ 'performed against non-numeric dtype')
  @pytest.mark.parametrize('typ', ['str', 'object'])
  @pytest.mark.parametrize('op', [operator.pos])
  def test_object(self, typ, op):