DEPR: inplace in GroupBy.fillna

doc/source/whatsnew/v2.1.0.rst

@@ -269,7 +269,7 @@ Deprecations
 - Deprecated behavior of :func:`assert_series_equal` and :func:`assert_frame_equal` considering NA-like values (e.g. ``NaN`` vs ``None`` as equivalent) (:issue:`52081`)
 - Deprecated constructing :class:`SparseArray` from scalar data, pass a sequence instead (:issue:`53039`)
 - Deprecated positional indexing on :class:`Series` with :meth:`Series.__getitem__` and :meth:`Series.__setitem__`, in a future version ``ser[item]`` will *always* interpret ``item`` as a label, not a position (:issue:`50617`)
--
+- Deprecated the ``inplace`` argument of :class:`SeriesGroupBy.fillna` and :class:`DataFrameGroupBy.fillna`; setting ``inplace=True`` is currently broken (:issue:`48792`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_210.performance:

pandas/core/groupby/generic.py

@@ -830,7 +830,7 @@ def fillna(
         value: object | ArrayLike | None = None,
         method: FillnaOptions | None = None,
         axis: Axis | None | lib.NoDefault = lib.no_default,
-        inplace: bool = False,
+        inplace: bool | lib.NoDefault = lib.no_default,
         limit: int | None = None,
         downcast: dict | None = None,
     ) -> Series | None:
@@ -860,6 +860,10 @@ def fillna(
 
         inplace : bool, default False
             Broken. Do not set to True.
+
+            .. deprecated:: 2.1.0
+                The inplace argument will be removed in a future version of pandas.
+
         limit : int, default None
             If method is specified, this is the maximum number of consecutive
             NaN values to forward/backward fill within a group. In other words,
@@ -925,6 +929,17 @@ def fillna(
         5    NaN
         dtype: float64
         """
+        if inplace is not lib.no_default:
+            warnings.warn(
+                message=(
+                    "Setting inplace=True is currently broken. The inplace argument "
+                    "is deprecated and will be removed in a future version of pandas."
+                ),
+                category=FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+        else:
+            inplace = False
         result = self._op_via_apply(
             "fillna",
             value=value,
@@ -2353,7 +2368,7 @@ def fillna(
         value: Hashable | Mapping | Series | DataFrame = None,
         method: FillnaOptions | None = None,
         axis: Axis | None | lib.NoDefault = lib.no_default,
-        inplace: bool = False,
+        inplace: bool | lib.NoDefault = lib.no_default,
         limit: int | None = None,
         downcast=None,
     ) -> DataFrame | None:
@@ -2387,6 +2402,10 @@ def fillna(
 
         inplace : bool, default False
             Broken. Do not set to True.
+
+            .. deprecated:: 2.1.0
+                The inplace argument will be removed in a future version of pandas.
+
         limit : int, default None
             If method is specified, this is the maximum number of consecutive
             NaN values to forward/backward fill within a group. In other words,
@@ -2473,6 +2492,17 @@ def fillna(
         3  3.0  NaN  2.0
         4  3.0  NaN  NaN
         """
+        if inplace is not lib.no_default:
+            warnings.warn(
+                message=(
+                    "Setting inplace=True is currently broken. The inplace argument "
+                    "is deprecated and will be removed in a future version of pandas."
+                ),
+                category=FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+        else:
+            inplace = False
         result = self._op_via_apply(
             "fillna",
             value=value,

pandas/tests/groupby/test_function.py

@@ -1719,3 +1719,38 @@ def test_regression_allowlist_methods(op, axis, skipna, sort):
         if sort:
             expected = expected.sort_index(axis=axis)
         tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize("inplace", [True, False, lib.no_default])
+def test_fillna_inplace_depr_frame(inplace):
+    # GH#48792
+    df = DataFrame({"a": [1, 1, 2], "b": [3, 4, 5]})
+    gb = df.groupby("a")
+    if inplace is lib.no_default:
+        result = gb.fillna(method="ffill", inplace=inplace)
+    else:
+        with tm.assert_produces_warning(
+            FutureWarning, match="The inplace argument is deprecated"
+        ):
+            result = gb.fillna(method="ffill", inplace=inplace)
+    expected = DataFrame() if inplace and inplace is not lib.no_default else df[["b"]]
+    tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize("inplace", [True, False, lib.no_default])
+def test_fillna_inplace_depr_series(inplace):
+    # GH#48792
+    ser = Series([3, 4, 5])
+    gb = ser.groupby([1, 1, 2])
+    if inplace is lib.no_default:
+        result = gb.fillna(method="ffill", inplace=inplace)
+    else:
+        with tm.assert_produces_warning(
+            FutureWarning, match="The inplace argument is deprecated"
+        ):
+            result = gb.fillna(method="ffill", inplace=inplace)
+    if inplace and inplace is not lib.no_default:
+        expected = Series([None, None], dtype=object, index=[1, 2])
+    else:
+        expected = ser
+    tm.assert_series_equal(result, expected)