DEPR: Series.put, Series.real, Series.imag, Index.dtype_str (#27106)

Author: mroeschke

doc/source/whatsnew/v0.25.0.rst

@@ -604,7 +604,10 @@ Other deprecations
 - The :meth:`Series.ftype`, :meth:`Series.ftypes` and :meth:`DataFrame.ftypes` methods are deprecated and will be removed in a future version.
   Instead, use :meth:`Series.dtype` and :meth:`DataFrame.dtypes` (:issue:`26705`).
 - :meth:`Timedelta.resolution` is deprecated and replaced with :meth:`Timedelta.resolution_string`.  In a future version, :meth:`Timedelta.resolution` will be changed to behave like the standard library :attr:`timedelta.resolution` (:issue:`21344`)
-- func:`read_table` has been undeprecated. (:issue:`25220`)
+- :func:`read_table` has been undeprecated. (:issue:`25220`)
+- :attr:`Index.dtype_str` is deprecated. (:issue:`18262`)
+- :attr:`Series.imag` and :attr:`Series.real` are deprecated. (:issue:`18262`)
+- :meth:`Series.put` is deprecated. (:issue:`18262`)
 
 .. _whatsnew_0250.prior_deprecations:
 

pandas/core/arrays/categorical.py

@@ -1989,9 +1989,7 @@ def _repr_categories_info(self):
         """
 
         category_strs = self._repr_categories()
-        dtype = getattr(self.categories, 'dtype_str',
-                        str(self.categories.dtype))
-
+        dtype = str(self.categories.dtype)
         levheader = "Categories ({length}, {dtype}): ".format(
             length=len(self.categories), dtype=dtype)
         width, height = get_terminal_size()

pandas/core/indexes/base.py

@@ -690,7 +690,12 @@ def dtype(self):
     def dtype_str(self):
         """
         Return the dtype str of the underlying data.
+
+        .. deprecated:: 0.25.0
         """
+        warnings.warn('`dtype_str` has been deprecated. Call `str` on the '
+                      'dtype attribute instead.', FutureWarning,
+                      stacklevel=2)
         return str(self.dtype)
 
     def ravel(self, order='C'):

pandas/core/nanops.py

@@ -1275,7 +1275,7 @@ def _ensure_numeric(x):
             except (TypeError, ValueError):
                 x = x.astype(np.float64)
             else:
-                if not np.any(x.imag):
+                if not np.any(np.imag(x)):
                     x = x.real
     elif not (is_float(x) or is_integer(x) or is_complex(x)):
         try:

pandas/core/series.py

@@ -617,10 +617,14 @@ def put(self, *args, **kwargs):
         """
         Apply the `put` method to its `values` attribute if it has one.
 
+        .. deprecated:: 0.25.0
+
         See Also
         --------
         numpy.ndarray.put
         """
+        warnings.warn('`put` has been deprecated and will be removed in a'
+                      'future version.', FutureWarning, stacklevel=2)
         self._values.put(*args, **kwargs)
 
     def __len__(self):
@@ -793,7 +797,11 @@ def __array_prepare__(self, result, context=None):
     def real(self):
         """
         Return the real value of vector.
+
+        .. deprecated 0.25.0
         """
+        warnings.warn("`real` has be deprecated and will be removed in a "
+                      "future verison", FutureWarning, stacklevel=2)
         return self.values.real
 
     @real.setter
@@ -804,7 +812,11 @@ def real(self, v):
     def imag(self):
         """
         Return imag value of vector.
+
+        .. deprecated 0.25.0
         """
+        warnings.warn("`imag` has be deprecated and will be removed in a "
+                      "future verison", FutureWarning, stacklevel=2)
         return self.values.imag
 
     @imag.setter

pandas/core/util/hashing.py

@@ -269,7 +269,7 @@ def hash_array(vals, encoding='utf8', hash_key=None, categorize=True):
     # we'll be working with everything as 64-bit values, so handle this
     # 128-bit value early
     if np.issubdtype(dtype, np.complex128):
-        return hash_array(vals.real) + 23 * hash_array(vals.imag)
+        return hash_array(np.real(vals)) + 23 * hash_array(np.imag(vals))
 
     # First, turn whatever array this is into unsigned 64-bit ints, if we can
     # manage it.

pandas/io/packers.py

@@ -523,16 +523,16 @@ def encode(obj):
             return {'typ': 'np_scalar',
                     'sub_typ': 'np_complex',
                     'dtype': obj.dtype.name,
-                    'real': obj.real.__repr__(),
-                    'imag': obj.imag.__repr__()}
+                    'real': np.real(obj).__repr__(),
+                    'imag': np.imag(obj).__repr__()}
         else:
             return {'typ': 'np_scalar',
                     'dtype': obj.dtype.name,
                     'data': obj.__repr__()}
     elif isinstance(obj, complex):
         return {'typ': 'np_complex',
-                'real': obj.real.__repr__(),
-                'imag': obj.imag.__repr__()}
+                'real': np.real(obj).__repr__(),
+                'imag': np.imag(obj).__repr__()}
 
     return obj
 

pandas/tests/indexes/multi/test_format.py

@@ -8,9 +8,10 @@
 
 
 def test_dtype_str(indices):
-    dtype = indices.dtype_str
-    assert isinstance(dtype, str)
-    assert dtype == str(indices.dtype)
+    with tm.assert_produces_warning(FutureWarning):
+        dtype = indices.dtype_str
+        assert isinstance(dtype, str)
+        assert dtype == str(indices.dtype)
 
 
 def test_format(idx):

pandas/tests/indexes/period/test_period.py

@@ -132,12 +132,14 @@ def test_shallow_copy_changing_freq_raises(self):
 
     def test_dtype_str(self):
         pi = pd.PeriodIndex([], freq='M')
-        assert pi.dtype_str == 'period[M]'
-        assert pi.dtype_str == str(pi.dtype)
+        with tm.assert_produces_warning(FutureWarning):
+            assert pi.dtype_str == 'period[M]'
+            assert pi.dtype_str == str(pi.dtype)
 
-        pi = pd.PeriodIndex([], freq='3M')
-        assert pi.dtype_str == 'period[3M]'
-        assert pi.dtype_str == str(pi.dtype)
+        with tm.assert_produces_warning(FutureWarning):
+            pi = pd.PeriodIndex([], freq='3M')
+            assert pi.dtype_str == 'period[3M]'
+            assert pi.dtype_str == str(pi.dtype)
 
     def test_view_asi8(self):
         idx = pd.PeriodIndex([], freq='M')

pandas/tests/indexes/test_common.py

@@ -155,9 +155,10 @@ def test_set_name_methods(self, indices):
         assert indices.names == [name]
 
     def test_dtype_str(self, indices):
-        dtype = indices.dtype_str
-        assert isinstance(dtype, str)
-        assert dtype == str(indices.dtype)
+        with tm.assert_produces_warning(FutureWarning):
+            dtype = indices.dtype_str
+            assert isinstance(dtype, str)
+            assert dtype == str(indices.dtype)
 
     def test_hash_error(self, indices):
         index = indices

pandas/tests/series/test_dtypes.py

@@ -428,17 +428,25 @@ def test_astype_empty_constructor_equality(self, dtype):
             as_type_empty = Series([]).astype(dtype)
             tm.assert_series_equal(init_empty, as_type_empty)
 
+    @pytest.mark.filterwarnings('ignore::FutureWarning')
     def test_complex(self):
         # see gh-4819: complex access for ndarray compat
         a = np.arange(5, dtype=np.float64)
         b = Series(a + 4j * a)
 
-        tm.assert_numpy_array_equal(a, b.real)
-        tm.assert_numpy_array_equal(4 * a, b.imag)
+        tm.assert_numpy_array_equal(a, np.real(b))
+        tm.assert_numpy_array_equal(4 * a, np.imag(b))
 
         b.real = np.arange(5) + 5
-        tm.assert_numpy_array_equal(a + 5, b.real)
-        tm.assert_numpy_array_equal(4 * a, b.imag)
+        tm.assert_numpy_array_equal(a + 5, np.real(b))
+        tm.assert_numpy_array_equal(4 * a, np.imag(b))
+
+    def test_real_imag_deprecated(self):
+        # GH 18262
+        s = pd.Series([1])
+        with tm.assert_produces_warning(FutureWarning):
+            s.imag
+            s.real
 
     def test_arg_for_errors_in_astype(self):
         # see gh-14878

pandas/tests/series/test_internals.py

@@ -221,3 +221,10 @@ def test_hasnans_unchached_for_series():
     ser.iloc[-1] = np.nan
     assert ser.hasnans is True
     assert Series.hasnans.__doc__ == pd.Index.hasnans.__doc__
+
+
+def test_put_deprecated():
+    # GH 18262
+    s = pd.Series([1])
+    with tm.assert_produces_warning(FutureWarning):
+        s.put(0, 0)

pandas/tests/test_nanops.py

@@ -144,9 +144,9 @@ def _coerce_tds(targ, res):
             # but nanops doesn't, so make that an exception
             elif targ.dtype.kind == 'O':
                 raise
-            tm.assert_almost_equal(targ.real, res.real,
+            tm.assert_almost_equal(np.real(targ), np.real(res),
                                    check_dtype=check_dtype)
-            tm.assert_almost_equal(targ.imag, res.imag,
+            tm.assert_almost_equal(np.imag(targ), np.imag(res),
                                    check_dtype=check_dtype)
 
     def check_fun_data(self, testfunc, targfunc, testarval, targarval,