DEPR: remove itemsize, data, base, flags, strides

doc/source/whatsnew/v1.0.0.rst

@@ -458,7 +458,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 - Changed the default value for the `raw` argument in :func:`Series.rolling().apply() <pandas.core.window.Rolling.apply>`, :func:`DataFrame.rolling().apply() <pandas.core.window.Rolling.apply>`,
 - :func:`Series.expanding().apply() <pandas.core.window.Expanding.apply>`, and :func:`DataFrame.expanding().apply() <pandas.core.window.Expanding.apply>` to ``False`` (:issue:`20584`)
 - Removed previously deprecated :attr:`Timestamp.weekday_name`, :attr:`DatetimeIndex.weekday_name`, and :attr:`Series.dt.weekday_name` (:issue:`18164`)
--
+- Removed the previously deprecated :attr:`Series.base`, :attr:`Index.base`, :attr:`Categorical.base`, :attr:`Series.flags`, :attr:`Index.flags`, :attr:`PeriodArray.flags`, :attr:`Series.strides`, :attr:`Index.strides`, :attr:`Series.itemsize`, :attr:`Index.itemsize`, :attr:`Series.data`, :attr:`Index.data` (:issue:`20721`)
 
 .. _whatsnew_1000.performance:
 

pandas/core/arrays/categorical.py

@@ -540,13 +540,6 @@ def tolist(self) -> list:
 
     to_list = tolist
 
-    @property
-    def base(self) -> None:
-        """
-        compat, we are always our own object
-        """
-        return None
-
     @classmethod
     def _from_inferred_categories(
         cls, inferred_categories, inferred_codes, dtype, true_values=None

pandas/core/arrays/period.py

@@ -618,14 +618,6 @@ def astype(self, dtype, copy=True):
             return self.asfreq(dtype.freq)
         return super().astype(dtype, copy=copy)
 
-    @property
-    def flags(self):
-        # TODO: remove
-        # We need this since reduction.SeriesBinGrouper uses values.flags
-        # Ideally, we wouldn't be passing objects down there in the first
-        # place.
-        return self._data.flags
-
     # ------------------------------------------------------------------
     # Arithmetic Methods
     _create_comparison_method = classmethod(_period_array_cmp)

pandas/core/base.py

@@ -5,7 +5,6 @@
 from collections import OrderedDict
 import textwrap
 from typing import Dict, FrozenSet, List, Optional
-import warnings
 
 import numpy as np
 
@@ -628,15 +627,7 @@ class IndexOpsMixin:
     # ndarray compatibility
     __array_priority__ = 1000
     _deprecations: FrozenSet[str] = frozenset(
-        [
-            "tolist",  # tolist is not deprecated, just suppressed in the __dir__
-            "base",
-            "data",
-            "item",
-            "itemsize",
-            "flags",
-            "strides",
-        ]
+        ["tolist"]  # tolist is not deprecated, just suppressed in the __dir__
     )
 
     def transpose(self, *args, **kwargs):
@@ -693,49 +684,14 @@ def item(self):
         """
         Return the first element of the underlying data as a python scalar.
 
-        .. deprecated:: 0.25.0
-
         Returns
         -------
         scalar
             The first element of %(klass)s.
         """
-        warnings.warn(
-            "`item` has been deprecated and will be removed in a future version",
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self.values.item()
-
-    @property
-    def data(self):
-        """
-        Return the data pointer of the underlying data.
-
-        .. deprecated:: 0.23.0
-        """
-        warnings.warn(
-            "{obj}.data is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self.values.data
-
-    @property
-    def itemsize(self):
-        """
-        Return the size of the dtype of the item of the underlying data.
-
-        .. deprecated:: 0.23.0
-        """
-        warnings.warn(
-            "{obj}.itemsize is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self._ndarray_values.itemsize
+        if len(self) == 1:
+            return next(iter(self))
+        raise ValueError("can only convert an array of size 1 to a Python scalar")
 
     @property
     def nbytes(self):
@@ -744,58 +700,13 @@ def nbytes(self):
         """
         return self._values.nbytes
 
-    @property
-    def strides(self):
-        """
-        Return the strides of the underlying data.
-
-        .. deprecated:: 0.23.0
-        """
-        warnings.warn(
-            "{obj}.strides is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self._ndarray_values.strides
-
     @property
     def size(self):
         """
         Return the number of elements in the underlying data.
         """
         return len(self._values)
 
-    @property
-    def flags(self):
-        """
-        Return the ndarray.flags for the underlying data.
-
-        .. deprecated:: 0.23.0
-        """
-        warnings.warn(
-            "{obj}.flags is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self.values.flags
-
-    @property
-    def base(self):
-        """
-        Return the base object if the memory of the underlying data is shared.
-
-        .. deprecated:: 0.23.0
-        """
-        warnings.warn(
-            "{obj}.base is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self.values.base
-
     @property
     def array(self) -> ExtensionArray:
         """

pandas/core/indexes/interval.py

@@ -2,7 +2,6 @@
 from operator import le, lt
 import textwrap
 from typing import Any, Optional, Tuple, Union
-import warnings
 
 import numpy as np
 
@@ -455,19 +454,6 @@ def size(self):
         # Avoid materializing ndarray[Interval]
         return self._data.size
 
-    @property
-    def itemsize(self):
-        msg = (
-            "IntervalIndex.itemsize is deprecated and will be removed in "
-            "a future version"
-        )
-        warnings.warn(msg, FutureWarning, stacklevel=2)
-
-        # suppress the warning from the underlying left/right itemsize
-        with warnings.catch_warnings():
-            warnings.simplefilter("ignore")
-            return self.left.itemsize + self.right.itemsize
-
     def __len__(self) -> int:
         return len(self.left)
 

pandas/core/indexes/period.py

@@ -911,62 +911,17 @@ def __setstate__(self, state):
 
     _unpickle_compat = __setstate__
 
-    @property
-    def flags(self):
-        """ return the ndarray.flags for the underlying data """
-        warnings.warn(
-            "{obj}.flags is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self._ndarray_values.flags
-
     def item(self):
         """
-        return the first element of the underlying data as a python
-        scalar
-
-        .. deprecated:: 0.25.0
-
+        Return the first element of the underlying data as a python scalar.
         """
-        warnings.warn(
-            "`item` has been deprecated and will be removed in a future version",
-            FutureWarning,
-            stacklevel=2,
-        )
-        # TODO(DatetimeArray): remove
         if len(self) == 1:
             return self[0]
         else:
             # TODO: is this still necessary?
             # copy numpy's message here because Py26 raises an IndexError
             raise ValueError("can only convert an array of size 1 to a Python scalar")
 
-    @property
-    def data(self):
-        """ return the data pointer of the underlying data """
-        warnings.warn(
-            "{obj}.data is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return np.asarray(self._data).data
-
-    @property
-    def base(self):
-        """ return the base object if the memory of the underlying data is
-        shared
-        """
-        warnings.warn(
-            "{obj}.base is deprecated and will be removed "
-            "in a future version".format(obj=type(self).__name__),
-            FutureWarning,
-            stacklevel=2,
-        )
-        return np.asarray(self._data)
-
     def memory_usage(self, deep=False):
         result = super().memory_usage(deep=deep)
         if hasattr(self, "_cache") and "_int64index" in self._cache:

pandas/tests/indexes/interval/test_interval.py

@@ -836,17 +836,6 @@ def test_nbytes(self):
         expected = 64  # 4 * 8 * 2
         assert result == expected
 
-    def test_itemsize(self):
-        # GH 19209
-        left = np.arange(0, 4, dtype="i8")
-        right = np.arange(1, 5, dtype="i8")
-        expected = 16  # 8 * 2
-
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            result = IntervalIndex.from_arrays(left, right).itemsize
-
-        assert result == expected
-
     @pytest.mark.parametrize("new_closed", ["left", "right", "both", "neither"])
     def test_set_closed(self, name, closed, new_closed):
         # GH 21670

pandas/tests/indexes/test_category.py

@@ -788,8 +788,10 @@ def test_ensure_copied_data(self, indices):
         # Index.__new__ is honored.
         #
         # Must be tested separately from other indexes because
-        # self.value is not an ndarray.
-        _base = lambda ar: ar if ar.base is None else ar.base
+        # self.values is not an ndarray.
+        # GH#????? Index.base has been removed
+        # FIXME: is this test still meaningful?
+        _base = lambda ar: ar if getattr(ar, "base", None) is None else ar.base
 
         result = CategoricalIndex(indices.values, copy=True)
         tm.assert_index_equal(indices, result)

pandas/tests/series/test_api.py

@@ -433,11 +433,10 @@ def f(x):
         tm.assert_series_equal(result, expected)
 
         # .item()
-        with tm.assert_produces_warning(FutureWarning):
-            s = Series([1])
-            result = s.item()
-            assert result == 1
-            assert s.item() == s.iloc[0]
+        s = Series([1])
+        result = s.item()
+        assert result == 1
+        assert s.item() == s.iloc[0]
 
         # using an ndarray like function
         s = Series(np.random.randn(10))

pandas/tests/test_base.py

@@ -333,31 +333,17 @@ def test_ndarray_compat_properties(self):
                 assert getattr(o, p, None) is not None
 
             # deprecated properties
-            for p in ["flags", "strides", "itemsize"]:
-                with tm.assert_produces_warning(FutureWarning):
-                    assert getattr(o, p, None) is not None
-
-            with tm.assert_produces_warning(FutureWarning):
-                assert hasattr(o, "base")
-
-            # If we have a datetime-like dtype then needs a view to work
-            # but the user is responsible for that
-            try:
-                with tm.assert_produces_warning(FutureWarning):
-                    assert o.data is not None
-            except ValueError:
-                pass
+            for p in ["flags", "strides", "itemsize", "base", "data"]:
+                assert not hasattr(o, p)
 
             with pytest.raises(ValueError):
-                with tm.assert_produces_warning(FutureWarning):
-                    o.item()  # len > 1
+                o.item()  # len > 1
 
             assert o.ndim == 1
             assert o.size == len(o)
 
-        with tm.assert_produces_warning(FutureWarning):
-            assert Index([1]).item() == 1
-            assert Series([1]).item() == 1
+        assert Index([1]).item() == 1
+        assert Series([1]).item() == 1
 
     def test_value_counts_unique_nunique(self):
         for orig in self.objs: