ENH: EA.fillna copy=True

pandas/core/arrays/_mixins.py

@@ -296,7 +296,9 @@ def _fill_mask_inplace(
         func(self._ndarray.T, limit=limit, mask=mask.T)
 
     @doc(ExtensionArray.fillna)
-    def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
+    def fillna(
+        self, value=None, method=None, limit: int | None = None, copy: bool = True
+    ) -> Self:
         value, method = validate_fillna_kwargs(
             value, method, validate_scalar_dict_value=False
         )
@@ -313,7 +315,9 @@ def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
                 # TODO: check value is None
                 # (for now) when self.ndim == 2, we assume axis=0
                 func = missing.get_fill_func(method, ndim=self.ndim)
-                npvalues = self._ndarray.T.copy()
+                npvalues = self._ndarray.T
+                if copy:
+                    npvalues = npvalues.copy()
                 func(npvalues, limit=limit, mask=mask.T)
                 npvalues = npvalues.T
 
@@ -322,14 +326,20 @@ def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
                 new_values = self._from_backing_data(npvalues)
             else:
                 # fill with value
-                new_values = self.copy()
+                if copy:
+                    new_values = self.copy()
+                else:
+                    new_values = self[:]
                 new_values[mask] = value
         else:
             # We validate the fill_value even if there is nothing to fill
             if value is not None:
                 self._validate_setitem_value(value)
 
-            new_values = self.copy()
+            if not copy:
+                new_values = self[:]
+            else:
+                new_values = self.copy()
         return new_values
 
     # ------------------------------------------------------------------------

pandas/core/arrays/arrow/array.py

@@ -905,18 +905,16 @@ def fillna(
         value: object | ArrayLike | None = None,
         method: FillnaOptions | None = None,
         limit: int | None = None,
+        copy: bool = True,
     ) -> Self:
         value, method = validate_fillna_kwargs(value, method)
 
         if not self._hasna:
             # TODO(CoW): Not necessary anymore when CoW is the default
             return self.copy()
 
-        if limit is not None:
-            return super().fillna(value=value, method=method, limit=limit)
-
-        if method is not None:
-            return super().fillna(value=value, method=method, limit=limit)
+        if limit is not None or method is not None:
+            return super().fillna(value=value, method=method, limit=limit, copy=copy)
 
         if isinstance(value, (np.ndarray, ExtensionArray)):
             # Similar to check_value_size, but we do not mask here since we may
@@ -959,7 +957,7 @@ def convert_fill_value(value, pa_type, dtype):
             #   a kernel for duration types.
             pass
 
-        return super().fillna(value=value, method=method, limit=limit)
+        return super().fillna(value=value, method=method, limit=limit, copy=copy)
 
     def isin(self, values) -> npt.NDArray[np.bool_]:
         # short-circuit to return all False array.

pandas/core/arrays/base.py

@@ -872,6 +872,7 @@ def fillna(
         value: object | ArrayLike | None = None,
         method: FillnaOptions | None = None,
         limit: int | None = None,
+        copy: bool = True,
     ) -> Self:
         """
         Fill NA/NaN values using the specified method.
@@ -896,6 +897,14 @@ def fillna(
             maximum number of entries along the entire axis where NaNs will be
             filled.
 
+        copy : bool, default True
+            Whether to make a copy of the data before filling. If False, then
+            the original should be modified and no new memory should be allocated.
+            For ExtensionArray subclasses that cannot do this, it is at the
+            author's discretion whether to ignore "copy=False" or to raise.
+            The base class implementation ignores the keyword in pad/backfill
+            cases.
+
         Returns
         -------
         ExtensionArray
@@ -932,10 +941,16 @@ def fillna(
                     return self[::-1].take(indexer, allow_fill=True)
             else:
                 # fill with value
-                new_values = self.copy()
+                if not copy:
+                    new_values = self[:]
+                else:
+                    new_values = self.copy()
                 new_values[mask] = value
         else:
-            new_values = self.copy()
+            if not copy:
+                new_values = self[:]
+            else:
+                new_values = self.copy()
         return new_values
 
     def dropna(self) -> Self:

pandas/core/arrays/interval.py

@@ -889,7 +889,9 @@ def max(self, *, axis: AxisInt | None = None, skipna: bool = True) -> IntervalOr
         indexer = obj.argsort()[-1]
         return obj[indexer]
 
-    def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
+    def fillna(
+        self, value=None, method=None, limit: int | None = None, copy: bool = True
+    ) -> Self:
         """
         Fill NA/NaN values using the specified method.
 
@@ -911,11 +913,18 @@ def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
             be partially filled. If method is not specified, this is the
             maximum number of entries along the entire axis where NaNs will be
             filled.
+        copy : bool, default True
+            Whether to make a copy of the data before filling. If False, then
+            the original should be modified and no new memory should be allocated.
+            For ExtensionArray subclasses that cannot do this, it is at the
+            author's discretion whether to ignore "copy=False" or to raise.
 
         Returns
         -------
         filled : IntervalArray with NA/NaN filled
         """
+        if copy is False:
+            raise NotImplementedError
         if method is not None:
             return super().fillna(value=value, method=method, limit=limit)
 

pandas/core/arrays/masked.py

@@ -185,7 +185,9 @@ def __getitem__(self, item: PositionalIndexer) -> Self | Any:
         return self._simple_new(self._data[item], newmask)
 
     @doc(ExtensionArray.fillna)
-    def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
+    def fillna(
+        self, value=None, method=None, limit: int | None = None, copy: bool = True
+    ) -> Self:
         value, method = validate_fillna_kwargs(value, method)
 
         mask = self._mask
@@ -195,16 +197,25 @@ def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
         if mask.any():
             if method is not None:
                 func = missing.get_fill_func(method, ndim=self.ndim)
-                npvalues = self._data.copy().T
-                new_mask = mask.copy().T
+                npvalues = self._data.T
+                new_mask = mask.T
+                if copy:
+                    npvalues = npvalues.copy()
+                    new_mask = new_mask.copy()
                 func(npvalues, limit=limit, mask=new_mask)
                 return self._simple_new(npvalues.T, new_mask.T)
             else:
                 # fill with value
-                new_values = self.copy()
+                if copy:
+                    new_values = self.copy()
+                else:
+                    new_values = self[:]
                 new_values[mask] = value
         else:
-            new_values = self.copy()
+            if copy:
+                new_values = self.copy()
+            else:
+                new_values = self[:]
         return new_values
 
     @classmethod

pandas/core/arrays/period.py

@@ -790,16 +790,18 @@ def searchsorted(
         m8arr = self._ndarray.view("M8[ns]")
         return m8arr.searchsorted(npvalue, side=side, sorter=sorter)
 
-    def fillna(self, value=None, method=None, limit: int | None = None) -> Self:
+    def fillna(
+        self, value=None, method=None, limit: int | None = None, copy: bool = True
+    ) -> Self:
         if method is not None:
             # view as dt64 so we get treated as timelike in core.missing,
             #  similar to dtl._period_dispatch
             dta = self.view("M8[ns]")
-            result = dta.fillna(value=value, method=method, limit=limit)
+            result = dta.fillna(value=value, method=method, limit=limit, copy=copy)
             # error: Incompatible return value type (got "Union[ExtensionArray,
             # ndarray[Any, Any]]", expected "PeriodArray")
             return result.view(self.dtype)  # type: ignore[return-value]
-        return super().fillna(value=value, method=method, limit=limit)
+        return super().fillna(value=value, method=method, limit=limit, copy=copy)
 
     # ------------------------------------------------------------------
     # Arithmetic Methods

pandas/core/arrays/sparse/array.py

@@ -717,6 +717,7 @@ def fillna(
         value=None,
         method: FillnaOptions | None = None,
         limit: int | None = None,
+        copy: bool = True,
     ) -> Self:
         """
         Fill missing values with `value`.
@@ -734,6 +735,9 @@ def fillna(
 
         limit : int, optional
 
+        copy: bool, default True
+            Ignored for SparseArray.
+
         Returns
         -------
         SparseArray

pandas/core/internals/blocks.py

@@ -10,6 +10,7 @@
     cast,
     final,
 )
+import warnings
 
 import numpy as np
 
@@ -41,6 +42,7 @@
 )
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly
+from pandas.util._exceptions import find_stack_level
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.astype import (
@@ -1895,12 +1897,32 @@ def pad_or_backfill(
         using_cow: bool = False,
     ) -> list[Block]:
         values = self.values
+        copy, refs = self._get_refs_and_copy(using_cow, inplace)
+
         if values.ndim == 2 and axis == 1:
             # NDArrayBackedExtensionArray.fillna assumes axis=0
-            new_values = values.T.fillna(method=method, limit=limit).T
+            new_values = values.T.fillna(method=method, limit=limit, copy=copy).T
         else:
-            new_values = values.fillna(method=method, limit=limit)
-        return [self.make_block_same_class(new_values)]
+            try:
+                new_values = values.fillna(method=method, limit=limit, copy=copy)
+            except TypeError:
+                # 3rd party EA that has not implemented copy keyword yet
+                refs = None
+                new_values = values.fillna(method=method, limit=limit)
+                # issue the warning *after* retrying, in case the TypeError
+                #  was caused by an invalid fill_value
+                warnings.warn(
+                    # GH#53278
+                    "ExtensionArray.fillna added a 'copy' keyword in pandas "
+                    "2.1.0. In a future version, ExtensionArray subclasses will "
+                    "need to implement this keyword or an exception will be "
+                    "raised. In the interim, the keyword is ignored by "
+                    f"{type(self.values).__name__}.",
+                    FutureWarning,
+                    stacklevel=find_stack_level(),
+                )
+
+        return [self.make_block_same_class(new_values, refs=refs)]
 
 
 class ExtensionBlock(libinternals.Block, EABackedBlock):
@@ -1938,8 +1960,29 @@ def fillna(
             refs = self.refs
             new_values = self.values
         else:
-            refs = None
-            new_values = self.values.fillna(value=value, method=None, limit=limit)
+            copy, refs = self._get_refs_and_copy(using_cow, inplace)
+
+            try:
+                new_values = self.values.fillna(
+                    value=value, method=None, limit=limit, copy=copy
+                )
+            except TypeError:
+                # 3rd party EA that has not implemented copy keyword yet
+                refs = None
+                new_values = self.values.fillna(value=value, method=None, limit=limit)
+                # issue the warning *after* retrying, in case the TypeError
+                #  was caused by an invalid fill_value
+                warnings.warn(
+                    # GH#53278
+                    "ExtensionArray.fillna added a 'copy' keyword in pandas "
+                    "2.1.0. In a future version, ExtensionArray subclasses will "
+                    "need to implement this keyword or an exception will be "
+                    "raised. In the interim, the keyword is ignored by "
+                    f"{type(self.values).__name__}.",
+                    FutureWarning,
+                    stacklevel=find_stack_level(),
+                )
+
         nb = self.make_block_same_class(new_values, refs=refs)
         return nb._maybe_downcast([nb], downcast, using_cow=using_cow)
 

pandas/tests/copy_view/test_interp_fillna.py

@@ -331,19 +331,23 @@ def test_fillna_inplace_ea_noop_shares_memory(
     view = df[:]
     df.fillna(100, inplace=True)
 
-    assert not np.shares_memory(get_array(df, "a"), get_array(view, "a"))
+    if isinstance(df["a"].dtype, ArrowDtype) or using_copy_on_write:
+        assert not np.shares_memory(get_array(df, "a"), get_array(view, "a"))
+    else:
+        # MaskedArray can actually respect inplace=True
+        assert np.shares_memory(get_array(df, "a"), get_array(view, "a"))
 
+    assert np.shares_memory(get_array(df, "b"), get_array(view, "b"))
     if using_copy_on_write:
-        assert np.shares_memory(get_array(df, "b"), get_array(view, "b"))
         assert not df._mgr._has_no_reference(1)
         assert not view._mgr._has_no_reference(1)
-    elif isinstance(df.dtypes.iloc[0], ArrowDtype):
-        # arrow is immutable, so no-ops do not need to copy underlying array
-        assert np.shares_memory(get_array(df, "b"), get_array(view, "b"))
-    else:
-        assert not np.shares_memory(get_array(df, "b"), get_array(view, "b"))
+
     df.iloc[0, 1] = 100
-    tm.assert_frame_equal(df_orig, view)
+    if isinstance(df["a"].dtype, ArrowDtype) or using_copy_on_write:
+        tm.assert_frame_equal(df_orig, view)
+    else:
+        # we actually have a view
+        tm.assert_frame_equal(df, view)
 
 
 def test_fillna_chained_assignment(using_copy_on_write):

pandas/tests/extension/decimal/array.py

@@ -281,6 +281,17 @@ def convert_values(param):
     def value_counts(self, dropna: bool = True):
         return value_counts(self.to_numpy(), dropna=dropna)
 
+    # Simulate a 3rd-party EA that has not yet updated to include a "copy"
+    #  keyword in its fillna method.
+    # error: Signature of "fillna" incompatible with supertype "ExtensionArray"
+    def fillna(  # type: ignore[override]
+        self,
+        value=None,
+        method=None,
+        limit: int | None = None,
+    ):
+        return super().fillna(value=value, method=method, limit=limit, copy=True)
+
 
 def to_decimal(values, context=None):
     return DecimalArray([decimal.Decimal(x) for x in values], context=context)