diff --git a/doc/source/whatsnew/v0.23.0.txt b/doc/source/whatsnew/v0.23.0.txt index 8c94cef4d8ea7..da750c071c4ae 100644 --- a/doc/source/whatsnew/v0.23.0.txt +++ b/doc/source/whatsnew/v0.23.0.txt @@ -241,6 +241,7 @@ Removal of prior version deprecations/changes - :func:`read_csv` has dropped the ``buffer_lines`` parameter (:issue:`13360`) - :func:`read_csv` has dropped the ``compact_ints`` and ``use_unsigned`` parameters (:issue:`13323`) - The ``Timestamp`` class has dropped the ``offset`` attribute in favor of ``freq`` (:issue:`13593`) +- The ``Series``, ``Categorical``, and ``Index`` classes have dropped the ``reshape`` method (:issue:`13012`) .. _whatsnew_0230.performance: diff --git a/pandas/core/categorical.py b/pandas/core/categorical.py index 845d0243c39e9..baf15b3ca5bc4 100644 --- a/pandas/core/categorical.py +++ b/pandas/core/categorical.py @@ -471,32 +471,6 @@ def tolist(self): return [_maybe_box_datetimelike(x) for x in self] return np.array(self).tolist() - def reshape(self, new_shape, *args, **kwargs): - """ - .. deprecated:: 0.19.0 - Calling this method will raise an error in a future release. - - An ndarray-compatible method that returns `self` because - `Categorical` instances cannot actually be reshaped. - - Parameters - ---------- - new_shape : int or tuple of ints - A 1-D array of integers that correspond to the new - shape of the `Categorical`. For more information on - the parameter, please refer to `np.reshape`. - """ - warn("reshape is deprecated and will raise " - "in a subsequent release", FutureWarning, stacklevel=2) - - nv.validate_reshape(args, kwargs) - - # while the 'new_shape' parameter has no effect, - # we should still enforce valid shape parameters - np.reshape(self.codes, new_shape) - - return self - @property def base(self): """ compat, we are always our own object """ diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py index 79de63b0caeb6..128cd8a9325d6 100644 --- a/pandas/core/indexes/base.py +++ b/pandas/core/indexes/base.py @@ -1190,16 +1190,6 @@ def rename(self, name, inplace=False): """ return self.set_names([name], inplace=inplace) - def reshape(self, *args, **kwargs): - """ - NOT IMPLEMENTED: do not call this method, as reshaping is not - supported for Index objects and will raise an error. - - Reshape an Index. - """ - raise NotImplementedError("reshaping is not supported " - "for Index objects") - @property def _has_complex_internals(self): # to disable groupby tricks in MultiIndex diff --git a/pandas/core/series.py b/pandas/core/series.py index ab26a309533ef..360095c386e8b 100644 --- a/pandas/core/series.py +++ b/pandas/core/series.py @@ -910,37 +910,6 @@ def repeat(self, repeats, *args, **kwargs): return self._constructor(new_values, index=new_index).__finalize__(self) - def reshape(self, *args, **kwargs): - """ - .. deprecated:: 0.19.0 - Calling this method will raise an error. Please call - ``.values.reshape(...)`` instead. - - return an ndarray with the values shape - if the specified shape matches exactly the current shape, then - return self (for compat) - - See also - -------- - numpy.ndarray.reshape - """ - warnings.warn("reshape is deprecated and will raise " - "in a subsequent release. Please use " - ".values.reshape(...) instead", FutureWarning, - stacklevel=2) - - if len(args) == 1 and hasattr(args[0], '__iter__'): - shape = args[0] - else: - shape = args - - if tuple(shape) == self.shape: - # XXX ignoring the "order" keyword. - nv.validate_reshape(tuple(), kwargs) - return self - - return self._values.reshape(shape, **kwargs) - def get_value(self, label, takeable=False): """ Quickly retrieve single value at passed index label diff --git a/pandas/tests/indexes/test_base.py b/pandas/tests/indexes/test_base.py index 72b312f29a793..e09f4ad360843 100644 --- a/pandas/tests/indexes/test_base.py +++ b/pandas/tests/indexes/test_base.py @@ -1684,12 +1684,6 @@ def test_take_fill_value(self): with pytest.raises(IndexError): idx.take(np.array([1, -5])) - def test_reshape_raise(self): - msg = "reshaping is not supported" - idx = pd.Index([0, 1, 2]) - tm.assert_raises_regex(NotImplementedError, msg, - idx.reshape, idx.shape) - def test_reindex_preserves_name_if_target_is_list_or_ndarray(self): # GH6552 idx = pd.Index([0, 1, 2]) diff --git a/pandas/tests/reshape/test_reshape.py b/pandas/tests/reshape/test_reshape.py index f472c6ae9383c..0312af12e0715 100644 --- a/pandas/tests/reshape/test_reshape.py +++ b/pandas/tests/reshape/test_reshape.py @@ -476,41 +476,6 @@ def test_reshaping_panel_categorical(self): index=p.major_axis.set_names('major')) tm.assert_frame_equal(result, expected) - def test_reshape_categorical(self): - cat = Categorical([], categories=["a", "b"]) - tm.assert_produces_warning(FutureWarning, cat.reshape, 0) - - with tm.assert_produces_warning(FutureWarning): - cat = Categorical([], categories=["a", "b"]) - tm.assert_categorical_equal(cat.reshape(0), cat) - - with tm.assert_produces_warning(FutureWarning): - cat = Categorical([], categories=["a", "b"]) - tm.assert_categorical_equal(cat.reshape((5, -1)), cat) - - with tm.assert_produces_warning(FutureWarning): - cat = Categorical(["a", "b"], categories=["a", "b"]) - tm.assert_categorical_equal(cat.reshape(cat.shape), cat) - - with tm.assert_produces_warning(FutureWarning): - cat = Categorical(["a", "b"], categories=["a", "b"]) - tm.assert_categorical_equal(cat.reshape(cat.size), cat) - - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - msg = "can only specify one unknown dimension" - cat = Categorical(["a", "b"], categories=["a", "b"]) - tm.assert_raises_regex(ValueError, msg, cat.reshape, (-2, -1)) - - def test_reshape_categorical_numpy(self): - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - cat = Categorical(["a", "b"], categories=["a", "b"]) - tm.assert_categorical_equal(np.reshape(cat, cat.shape), cat) - - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - msg = "the 'order' parameter is not supported" - tm.assert_raises_regex(ValueError, msg, np.reshape, - cat, cat.shape, order='F') - class TestMakeAxisDummies(object): diff --git a/pandas/tests/series/test_analytics.py b/pandas/tests/series/test_analytics.py index 203a0b4a54858..0dae6aa96ced1 100644 --- a/pandas/tests/series/test_analytics.py +++ b/pandas/tests/series/test_analytics.py @@ -1542,66 +1542,6 @@ def test_shift_categorical(self): assert_index_equal(s.values.categories, sp1.values.categories) assert_index_equal(s.values.categories, sn2.values.categories) - def test_reshape_deprecate(self): - x = Series(np.random.random(10), name='x') - tm.assert_produces_warning(FutureWarning, x.reshape, x.shape) - - def test_reshape_non_2d(self): - # see gh-4554 - with tm.assert_produces_warning(FutureWarning): - x = Series(np.random.random(201), name='x') - assert x.reshape(x.shape, ) is x - - # see gh-2719 - with tm.assert_produces_warning(FutureWarning): - a = Series([1, 2, 3, 4]) - result = a.reshape(2, 2) - expected = a.values.reshape(2, 2) - tm.assert_numpy_array_equal(result, expected) - assert isinstance(result, type(expected)) - - def test_reshape_2d_return_array(self): - x = Series(np.random.random(201), name='x') - - with tm.assert_produces_warning(FutureWarning): - result = x.reshape((-1, 1)) - assert not isinstance(result, Series) - - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - result2 = np.reshape(x, (-1, 1)) - assert not isinstance(result2, Series) - - with tm.assert_produces_warning(FutureWarning): - result = x[:, None] - expected = x.reshape((-1, 1)) - tm.assert_almost_equal(result, expected) - - def test_reshape_bad_kwarg(self): - a = Series([1, 2, 3, 4]) - - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - msg = "'foo' is an invalid keyword argument for this function" - tm.assert_raises_regex( - TypeError, msg, a.reshape, (2, 2), foo=2) - - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - msg = r"reshape\(\) got an unexpected keyword argument 'foo'" - tm.assert_raises_regex( - TypeError, msg, a.reshape, a.shape, foo=2) - - def test_numpy_reshape(self): - a = Series([1, 2, 3, 4]) - - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - result = np.reshape(a, (2, 2)) - expected = a.values.reshape(2, 2) - tm.assert_numpy_array_equal(result, expected) - assert isinstance(result, type(expected)) - - with tm.assert_produces_warning(FutureWarning, check_stacklevel=False): - result = np.reshape(a, a.shape) - tm.assert_series_equal(result, a) - def test_unstack(self): from numpy import nan