fix doc

Author: sinhrks

pandas/core/arrays/base.py

@@ -831,8 +831,8 @@ def _create_method(cls, op, coerce_to_dtype=True):
  `op` cannot be stored in the ExtensionArray. The dtype of the
  ndarray uses NumPy's normal inference rules.
 
- Example
- -------
+ Examples
+ --------
  Given an ExtensionArray subclass called MyExtensionArray, use
 
  >>> __add__ = cls._create_method(operator.add)
@@ -909,8 +909,8 @@ def _create_unary_method(cls, op, coerce_to_dtype=True):
  `op` cannot be stored in the ExtensionArray. The dtype of the
  ndarray uses NumPy's normal inference rules.
 
- Example
- -------
+ Examples
+ --------
  Given an ExtensionArray subclass called MyExtensionArray, use
  >>> __neg__ = cls._create_method(operator.neg)
 

pandas/tests/arrays/test_integer.py

@@ -363,7 +363,7 @@ def test_integer(self, dtype, op):
  # GH#23087
  arr = integer_array([1, 3, 2], dtype=dtype)
  result = op(arr)
- exp = integer_array(op(np.array([1, 3, 2], dtype=dtype)), dtype=dtype)
+ exp = integer_array(op(np.array([1, 3, 2], dtype=dtype.numpy_dtype)))
  tm.assert_extension_array_equal(result, exp)
 
  @pytest.mark.parametrize('op', [operator.pos, operator.neg,
@@ -378,19 +378,19 @@ def test_empty(self, dtype, op):
  operator.inv, operator.abs])
  def test_mask(self, dtype, op):
  # GH#23087
- arr = IntegerArray(np.array([1, 2, 3], dtype=dtype),
- np.array([False, True, False]))
+ arr = IntegerArray(np.array([1, 2, 3], dtype=dtype.numpy_dtype),
+ mask=np.array([False, True, False]))
  result = op(arr)
- exp = IntegerArray(op(np.array([1, 2, 3], dtype=dtype)),
- np.array([False, True, False]))
+ exp = IntegerArray(op(np.array([1, 2, 3], dtype=dtype.numpy_dtype)),
+ mask=np.array([False, True, False]))
  tm.assert_extension_array_equal(result, exp)
 
  @pytest.mark.parametrize('op', [operator.pos, operator.neg,
  operator.inv, operator.abs])
  def test_all_mask(self, dtype, op):
  # GH#23087
- arr = IntegerArray(np.array([1, 1, 1], dtype=dtype),
- np.array([True, True, True]))
+ arr = IntegerArray(np.array([1, 1, 1], dtype=dtype.numpy_dtype),
+ mask=np.array([True, True, True]))
  result = op(arr)
  tm.assert_extension_array_equal(result, arr)
 

pandas/tests/frame/test_arithmetic.py

@@ -651,9 +651,9 @@ def test_arith_non_pandas_object(self):
  index=df.index, columns=df.columns)
  tm.assert_frame_equal(df.add(val3), added)
 
+
 # ------------------------------------------------------------------
 # Unary
-
 class TestFrameUnary(object):
 
  @pytest.mark.parametrize('typ', ['int64', 'int32', 'int16', 'int8',

pandas/tests/series/test_arithmetic.py

@@ -255,18 +255,16 @@ def test_integer(self, typ, op):
  @pytest.mark.parametrize('op', [operator.pos, operator.neg,
  operator.abs])
  def test_float(self, float_dtype, op):
- typ = float_dtype
  # GH#23087
- ser = Series([1.1, 3.1, 2.1], index=range(3), dtype=typ)
+ ser = Series([1.1, 3.1, 2.1], index=range(3), dtype=float_dtype)
  result = op(ser)
  exp = Series(op(ser.values), index=ser.index)
  tm.assert_series_equal(result, exp)
 
  @pytest.mark.parametrize('op', [operator.inv])
  def test_float_inv_raise(self, float_dtype, op):
- typ = float_dtype
  # GH#23087
- ser = Series([1.1, 3.1, 2.1], index=range(3), dtype=typ)
+ ser = Series([1.1, 3.1, 2.1], index=range(3), dtype=float_dtype)
  pytest.raises(TypeError, op, ser)
  # consistent with numpy
  pytest.raises(TypeError, op, ser.values)