DEPR: remove FrozenNDarray

doc/source/whatsnew/v1.0.0.rst

@@ -434,6 +434,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 - Removed previously deprecated :func:`pandas.tseries.plotting.tsplot` (:issue:`18627`)
 - Removed the previously deprecated ``reduce`` and ``broadcast`` arguments from :meth:`DataFrame.apply` (:issue:`18577`)
 - Removed the previously deprecated ``assert_raises_regex`` function in ``pandas.util.testing`` (:issue:`29174`)
+- Removed the previously deprecated ``FrozenNDArray`` class in ``pandas.core.indexes.frozen`` (:issue:`29335`)
 - Removed previously deprecated "nthreads" argument from :func:`read_feather`, use "use_threads" instead (:issue:`23053`)
 - Removed :meth:`Index.is_lexsorted_for_tuple` (:issue:`29305`)
 - Removed support for nexted renaming in :meth:`DataFrame.aggregate`, :meth:`Series.aggregate`, :meth:`DataFrameGroupBy.aggregate`, :meth:`SeriesGroupBy.aggregate`, :meth:`Rolling.aggregate` (:issue:`29608`)

pandas/compat/pickle_compat.py

@@ -89,21 +89,8 @@ def __new__(cls) -> "DataFrame":  # type: ignore
 _class_locations_map = {
     ("pandas.core.sparse.array", "SparseArray"): ("pandas.core.arrays", "SparseArray"),
     # 15477
-    #
-    # TODO: When FrozenNDArray is removed, add
-    # the following lines for compat:
-    #
-    # ('pandas.core.base', 'FrozenNDArray'):
-    #     ('numpy', 'ndarray'),
-    # ('pandas.core.indexes.frozen', 'FrozenNDArray'):
-    #     ('numpy', 'ndarray'),
-    #
-    # Afterwards, remove the current entry
-    # for `pandas.core.base.FrozenNDArray`.
-    ("pandas.core.base", "FrozenNDArray"): (
-        "pandas.core.indexes.frozen",
-        "FrozenNDArray",
-    ),
+    ("pandas.core.base", "FrozenNDArray"): ("numpy", "ndarray"),
+    ("pandas.core.indexes.frozen", "FrozenNDArray"): ("numpy", "ndarray"),
     ("pandas.core.base", "FrozenList"): ("pandas.core.indexes.frozen", "FrozenList"),
     # 10890
     ("pandas.core.series", "TimeSeries"): ("pandas.core.series", "Series"),

pandas/core/indexes/frozen.py

@@ -4,14 +4,8 @@
 These are used for:
 
 - .names (FrozenList)
-- .levels & .codes (FrozenNDArray)
 
 """
-import warnings
-
-import numpy as np
-
-from pandas.core.dtypes.cast import coerce_indexer_dtype
 
 from pandas.core.base import PandasObject
 
@@ -111,77 +105,3 @@ def __repr__(self) -> str:
 
     __setitem__ = __setslice__ = __delitem__ = __delslice__ = _disabled
     pop = append = extend = remove = sort = insert = _disabled
-
-
-class FrozenNDArray(PandasObject, np.ndarray):
-
-    # no __array_finalize__ for now because no metadata
-    def __new__(cls, data, dtype=None, copy=False):
-        warnings.warn(
-            "\nFrozenNDArray is deprecated and will be removed in a "
-            "future version.\nPlease use `numpy.ndarray` instead.\n",
-            FutureWarning,
-            stacklevel=2,
-        )
-
-        if copy is None:
-            copy = not isinstance(data, FrozenNDArray)
-        res = np.array(data, dtype=dtype, copy=copy).view(cls)
-        return res
-
-    def _disabled(self, *args, **kwargs):
-        """This method will not function because object is immutable."""
-        raise TypeError(
-            "'{cls}' does not support mutable operations.".format(cls=self.__class__)
-        )
-
-    __setitem__ = __setslice__ = __delitem__ = __delslice__ = _disabled
-    put = itemset = fill = _disabled
-
-    def _shallow_copy(self):
-        return self.view()
-
-    def values(self):
-        """returns *copy* of underlying array"""
-        arr = self.view(np.ndarray).copy()
-        return arr
-
-    def __repr__(self) -> str:
-        """
-        Return a string representation for this object.
-        """
-        prepr = pprint_thing(self, escape_chars=("\t", "\r", "\n"), quote_strings=True)
-        return f"{type(self).__name__}({prepr}, dtype='{self.dtype}')"
-
-    def searchsorted(self, value, side="left", sorter=None):
-        """
-        Find indices to insert `value` so as to maintain order.
-
-        For full documentation, see `numpy.searchsorted`
-
-        See Also
-        --------
-        numpy.searchsorted : Equivalent function.
-        """
-
-        # We are much more performant if the searched
-        # indexer is the same type as the array.
-        #
-        # This doesn't matter for int64, but DOES
-        # matter for smaller int dtypes.
-        #
-        # xref: https://github.com/numpy/numpy/issues/5370
-        try:
-            value = self.dtype.type(value)
-        except ValueError:
-            pass
-
-        return super().searchsorted(value, side=side, sorter=sorter)
-
-
-def _ensure_frozen(array_like, categories, copy=False):
-    array_like = coerce_indexer_dtype(array_like, categories)
-    array_like = array_like.view(FrozenNDArray)
-    if copy:
-        array_like = array_like.copy()
-    return array_like

pandas/core/indexes/multi.py

@@ -13,6 +13,7 @@
 from pandas.errors import PerformanceWarning, UnsortedIndexError
 from pandas.util._decorators import Appender, cache_readonly
 
+from pandas.core.dtypes.cast import coerce_indexer_dtype
 from pandas.core.dtypes.common import (
     ensure_int64,
     ensure_platform_int,
@@ -40,7 +41,7 @@
     _index_shared_docs,
     ensure_index,
 )
-from pandas.core.indexes.frozen import FrozenList, _ensure_frozen
+from pandas.core.indexes.frozen import FrozenList
 import pandas.core.missing as missing
 from pandas.core.sorting import (
     get_group_index,
@@ -821,17 +822,15 @@ def _set_codes(
 
         if level is None:
             new_codes = FrozenList(
-                _ensure_frozen(level_codes, lev, copy=copy)._shallow_copy()
+                _coerce_indexer_frozen(level_codes, lev, copy=copy).view()
                 for lev, level_codes in zip(self._levels, codes)
             )
         else:
             level_numbers = [self._get_level_number(lev) for lev in level]
             new_codes = list(self._codes)
             for lev_num, level_codes in zip(level_numbers, codes):
                 lev = self.levels[lev_num]
-                new_codes[lev_num] = _ensure_frozen(
-                    level_codes, lev, copy=copy
-                )._shallow_copy()
+                new_codes[lev_num] = _coerce_indexer_frozen(level_codes, lev, copy=copy)
             new_codes = FrozenList(new_codes)
 
         if verify_integrity:
@@ -1095,7 +1094,8 @@ def _format_native_types(self, na_rep="nan", **kwargs):
             if mask.any():
                 nan_index = len(level)
                 level = np.append(level, na_rep)
-                level_codes = level_codes.values()
+                assert not level_codes.flags.writeable  # i.e. copy is needed
+                level_codes = level_codes.copy()  # make writeable
                 level_codes[mask] = nan_index
             new_levels.append(level)
             new_codes.append(level_codes)
@@ -2000,7 +2000,7 @@ def _assert_take_fillable(
             if mask.any():
                 masked = []
                 for new_label in taken:
-                    label_values = new_label.values()
+                    label_values = new_label
                     label_values[mask] = na_value
                     masked.append(np.asarray(label_values))
                 taken = masked
@@ -3433,3 +3433,26 @@ def maybe_droplevels(index, key):
             pass
 
     return index
+
+
+def _coerce_indexer_frozen(array_like, categories, copy: bool = False) -> np.ndarray:
+    """
+    Coerce the array_like indexer to the smallest integer dtype that can encode all
+    of the given categories.
+
+    Parameters
+    ----------
+    array_like : array-like
+    categories : array-like
+    copy : bool
+
+    Returns
+    -------
+    np.ndarray
+        Non-writeable.
+    """
+    array_like = coerce_indexer_dtype(array_like, categories)
+    if copy:
+        array_like = array_like.copy()
+    array_like.flags.writeable = False
+    return array_like

pandas/tests/indexes/multi/test_integrity.py

@@ -210,7 +210,7 @@ def test_metadata_immutable(idx):
     # ditto for labels
     with pytest.raises(TypeError, match=mutable_regex):
         codes[0] = codes[0]
-    with pytest.raises(TypeError, match=mutable_regex):
+    with pytest.raises(ValueError, match="assignment destination is read-only"):
         codes[0][0] = codes[0][0]
     # and for names
     names = idx.names

pandas/tests/indexes/test_frozen.py

@@ -1,11 +1,7 @@
-import warnings
-
-import numpy as np
 import pytest
 
-from pandas.core.indexes.frozen import FrozenList, FrozenNDArray
+from pandas.core.indexes.frozen import FrozenList
 from pandas.tests.test_base import CheckImmutable, CheckStringMixin
-import pandas.util.testing as tm
 
 
 class TestFrozenList(CheckImmutable, CheckStringMixin):
@@ -55,61 +51,3 @@ def test_tricky_container_to_bytes_raises(self):
         msg = "^'str' object cannot be interpreted as an integer$"
         with pytest.raises(TypeError, match=msg):
             bytes(self.unicode_container)
-
-
-class TestFrozenNDArray(CheckImmutable, CheckStringMixin):
-    mutable_methods = ("put", "itemset", "fill")
-
-    def setup_method(self, _):
-        self.lst = [3, 5, 7, -2]
-        self.klass = FrozenNDArray
-
-        with warnings.catch_warnings(record=True):
-            warnings.simplefilter("ignore", FutureWarning)
-
-            self.container = FrozenNDArray(self.lst)
-            self.unicode_container = FrozenNDArray(["\u05d0", "\u05d1", "c"])
-
-    def test_constructor_warns(self):
-        # see gh-9031
-        with tm.assert_produces_warning(FutureWarning):
-            FrozenNDArray([1, 2, 3])
-
-    def test_tricky_container_to_bytes(self):
-        bytes(self.unicode_container)
-
-    def test_shallow_copying(self):
-        original = self.container.copy()
-        assert isinstance(self.container.view(), FrozenNDArray)
-        assert not isinstance(self.container.view(np.ndarray), FrozenNDArray)
-        assert self.container.view() is not self.container
-        tm.assert_numpy_array_equal(self.container, original)
-
-        # Shallow copy should be the same too
-        assert isinstance(self.container._shallow_copy(), FrozenNDArray)
-
-        # setting should not be allowed
-        def testit(container):
-            container[0] = 16
-
-        self.check_mutable_error(testit, self.container)
-
-    def test_values(self):
-        original = self.container.view(np.ndarray).copy()
-        n = original[0] + 15
-
-        vals = self.container.values()
-        tm.assert_numpy_array_equal(original, vals)
-
-        assert original is not vals
-        vals[0] = n
-
-        assert isinstance(self.container, FrozenNDArray)
-        tm.assert_numpy_array_equal(self.container.values(), original)
-        assert vals[0] == n
-
-    def test_searchsorted(self):
-        expected = 2
-        assert self.container.searchsorted(7) == expected
-
-        assert self.container.searchsorted(value=7) == expected