API: avoid silent consolidation

doc/source/whatsnew/v2.0.0.rst

@@ -348,6 +348,7 @@ Other API changes
 - Changed behavior of :class:`Index` constructor with sequence containing at least one ``NaT`` and everything else either ``None`` or ``NaN`` to infer ``datetime64[ns]`` dtype instead of ``object``, matching :class:`Series` behavior (:issue:`49340`)
 - :func:`read_stata` with parameter ``index_col`` set to ``None`` (the default) will now set the index on the returned :class:`DataFrame` to a :class:`RangeIndex` instead of a :class:`Int64Index` (:issue:`49745`)
 - Changed behavior of :class:`Index` constructor with an object-dtype ``numpy.ndarray`` containing all-``bool`` values or all-complex values, this will now retain object dtype, consistent with the :class:`Series` behavior (:issue:`49594`)
+- :meth:`DataFrame.values`, :meth:`DataFrame.to_numpy`, :meth:`DataFrame.xs`, :meth:`DataFrame.reindex`, :meth:`DataFrame.fillna`, and :meth:`DataFrame.replace` no longer silently consolidate the underlying arrays; do ``df = df.copy()`` to ensure consolidation (:issue:`49356`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/frame.py

@@ -165,6 +165,7 @@
 )
 from pandas.core.arrays.sparse import SparseFrameAccessor
 from pandas.core.construction import (
+    ensure_wrapped_if_datetimelike,
     extract_array,
     sanitize_array,
     sanitize_masked_array,
@@ -960,20 +961,18 @@ def _values(  # type: ignore[override]
         """
         Analogue to ._values that may return a 2D ExtensionArray.
         """
-        self._consolidate_inplace()
-
         mgr = self._mgr
 
         if isinstance(mgr, ArrayManager):
             if len(mgr.arrays) == 1 and not is_1d_only_ea_dtype(mgr.arrays[0].dtype):
                 # error: Item "ExtensionArray" of "Union[ndarray, ExtensionArray]"
                 # has no attribute "reshape"
                 return mgr.arrays[0].reshape(-1, 1)  # type: ignore[union-attr]
-            return self.values
+            return ensure_wrapped_if_datetimelike(self.values)
 
         blocks = mgr.blocks
         if len(blocks) != 1:
-            return self.values
+            return ensure_wrapped_if_datetimelike(self.values)
 
         arr = blocks[0].values
         if arr.ndim == 1:
@@ -1804,7 +1803,6 @@ def to_numpy(
         array([[1, 3.0, Timestamp('2000-01-01 00:00:00')],
                [2, 4.5, Timestamp('2000-01-02 00:00:00')]], dtype=object)
         """
-        self._consolidate_inplace()
         if dtype is not None:
             dtype = np.dtype(dtype)
         result = self._mgr.as_array(dtype=dtype, copy=copy, na_value=na_value)
@@ -11291,7 +11289,6 @@ def values(self) -> np.ndarray:
                ['lion', 80.5, 1],
                ['monkey', nan, None]], dtype=object)
         """
-        self._consolidate_inplace()
         return self._mgr.as_array()
 
     @overload

pandas/core/generic.py

@@ -3777,7 +3777,6 @@ def _take(
 
         See the docstring of `take` for full explanation of the parameters.
         """
-        self._consolidate_inplace()
 
         new_data = self._mgr.take(
             indices,
@@ -3934,8 +3933,6 @@ class   animal   locomotion
         else:
             index = self.index
 
-        self._consolidate_inplace()
-
         if isinstance(index, MultiIndex):
             loc, new_index = index._get_loc_level(key, level=0)
             if not drop_level:
@@ -5190,8 +5187,6 @@ def reindex(self: NDFrameT, *args, **kwargs) -> NDFrameT:
                 f'argument "{list(kwargs.keys())[0]}"'
             )
 
-        self._consolidate_inplace()
-
         # if all axes that are requested to reindex are equal, then only copy
         # if indicated must have index names equal here as well as values
         if all(
@@ -6730,8 +6725,6 @@ def fillna(
         inplace = validate_bool_kwarg(inplace, "inplace")
         value, method = validate_fillna_kwargs(value, method)
 
-        self._consolidate_inplace()
-
         # set the default here, so functions examining the signaure
         # can detect if something was set (e.g. in groupby) (GH9221)
         if axis is None:
@@ -7049,8 +7042,6 @@ def replace(
         if not is_bool(regex) and to_replace is not None:
             raise ValueError("'to_replace' must be 'None' if 'regex' is not a bool")
 
-        self._consolidate_inplace()
-
         if value is lib.no_default or method is not lib.no_default:
             # GH#36984 if the user explicitly passes value=None we want to
             #  respect that. We have the corner case where the user explicitly

pandas/tests/frame/methods/test_values.py

@@ -256,11 +256,7 @@ def test_private_values_dt64tz_multicol(self):
         df2 = df - df
         tm.assert_equal(df2._values, tda)
 
-    def test_private_values_dt64_multiblock(self, using_array_manager, request):
-        if using_array_manager:
-            mark = pytest.mark.xfail(reason="returns ndarray")
-            request.node.add_marker(mark)
-
+    def test_private_values_dt64_multiblock(self):
         dta = date_range("2000", periods=8)._data
 
         df = DataFrame({"A": dta[:4]}, copy=False)

pandas/tests/frame/test_block_internals.py

@@ -85,12 +85,6 @@ def test_consolidate_inplace(self, float_frame):
         for letter in range(ord("A"), ord("Z")):
             float_frame[chr(letter)] = chr(letter)
 
-    def test_values_consolidate(self, float_frame):
-        float_frame["E"] = 7.0
-        assert not float_frame._mgr.is_consolidated()
-        _ = float_frame.values
-        assert float_frame._mgr.is_consolidated()
-
     def test_modify_values(self, float_frame):
         float_frame.values[5] = 5
         assert (float_frame.values[5] == 5).all()
@@ -99,10 +93,10 @@ def test_modify_values(self, float_frame):
         float_frame["E"] = 7.0
         col = float_frame["E"]
         float_frame.values[6] = 6
-        assert (float_frame.values[6] == 6).all()
+        # as of 2.0 .values does not consolidate, so subsequent calls to .values
+        #  does not share data
+        assert not (float_frame.values[6] == 6).all()
 
-        # check that item_cache was cleared
-        assert float_frame["E"] is not col
         assert (col == 7).all()
 
     def test_boolean_set_uncons(self, float_frame):