CLN: Enforce deprecation of groupby.quantile supporting bool dtype (#…

…57744)

doc/source/whatsnew/v3.0.0.rst

@@ -205,6 +205,7 @@ Removal of prior version deprecations/changes
 - In :meth:`DataFrame.stack`, the default value of ``future_stack`` is now ``True``; specifying ``False`` will raise a ``FutureWarning`` (:issue:`55448`)
 - Methods ``apply``, ``agg``, and ``transform`` will no longer replace NumPy functions (e.g. ``np.sum``) and built-in functions (e.g. ``min``) with the equivalent pandas implementation; use string aliases (e.g. ``"sum"`` and ``"min"``) if you desire to use the pandas implementation (:issue:`53974`)
 - Passing both ``freq`` and ``fill_value`` in :meth:`DataFrame.shift` and :meth:`Series.shift` and :meth:`.DataFrameGroupBy.shift` now raises a ``ValueError`` (:issue:`54818`)
+- Removed :meth:`.DataFrameGroupBy.quantile` and :meth:`.SeriesGroupBy.quantile` supporting bool dtype (:issue:`53975`)
 - Removed :meth:`DateOffset.is_anchored` and :meth:`offsets.Tick.is_anchored` (:issue:`56594`)
 - Removed ``DataFrame.applymap``, ``Styler.applymap`` and ``Styler.applymap_index`` (:issue:`52364`)
 - Removed ``DataFrame.bool`` and ``Series.bool`` (:issue:`51756`)

pandas/core/groupby/groupby.py

@@ -4279,16 +4279,8 @@ def pre_processor(vals: ArrayLike) -> tuple[np.ndarray, DtypeObj | None]:
             elif is_bool_dtype(vals.dtype) and isinstance(vals, ExtensionArray):
                 out = vals.to_numpy(dtype=float, na_value=np.nan)
             elif is_bool_dtype(vals.dtype):
-                # GH#51424 deprecate to match Series/DataFrame behavior
-                warnings.warn(
-                    f"Allowing bool dtype in {type(self).__name__}.quantile is "
-                    "deprecated and will raise in a future version, matching "
-                    "the Series/DataFrame behavior. Cast to uint8 dtype before "
-                    "calling quantile instead.",
-                    FutureWarning,
-                    stacklevel=find_stack_level(),
-                )
-                out = np.asarray(vals)
+                # GH#51424 remove to match Series/DataFrame behavior
+                raise TypeError("Cannot use quantile with bool dtype")
             elif needs_i8_conversion(vals.dtype):
                 inference = vals.dtype
                 # In this case we need to delay the casting until after the

pandas/tests/groupby/test_numeric_only.py

@@ -368,18 +368,11 @@ def test_deprecate_numeric_only_series(dtype, groupby_func, request):
             msg = "cannot be performed against 'object' dtypes"
         else:
             msg = "is not supported for object dtype"
-        warn = FutureWarning if groupby_func == "fillna" else None
-        warn_msg = "DataFrameGroupBy.fillna is deprecated"
-        with tm.assert_produces_warning(warn, match=warn_msg):
-            with pytest.raises(TypeError, match=msg):
-                method(*args)
+        with pytest.raises(TypeError, match=msg):
+            method(*args)
     elif dtype is object:
-        warn = FutureWarning if groupby_func == "fillna" else None
-        warn_msg = "SeriesGroupBy.fillna is deprecated"
-        with tm.assert_produces_warning(warn, match=warn_msg):
-            result = method(*args)
-        with tm.assert_produces_warning(warn, match=warn_msg):
-            expected = expected_method(*args)
+        result = method(*args)
+        expected = expected_method(*args)
         if groupby_func in obj_result:
             expected = expected.astype(object)
         tm.assert_series_equal(result, expected)
@@ -419,12 +412,10 @@ def test_deprecate_numeric_only_series(dtype, groupby_func, request):
         with pytest.raises(TypeError, match=msg):
             method(*args, numeric_only=True)
     elif dtype == bool and groupby_func == "quantile":
-        msg = "Allowing bool dtype in SeriesGroupBy.quantile"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
+        msg = "Cannot use quantile with bool dtype"
+        with pytest.raises(TypeError, match=msg):
             # GH#51424
-            result = method(*args, numeric_only=True)
-            expected = method(*args, numeric_only=False)
-        tm.assert_series_equal(result, expected)
+            method(*args, numeric_only=False)
     else:
         result = method(*args, numeric_only=True)
         expected = method(*args, numeric_only=False)