DEPR: GroupBy.quantile with bool dtype (pandas-dev#53975)

doc/source/whatsnew/v2.1.0.rst

@@ -296,6 +296,7 @@ Deprecations
 - Deprecated :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` for object-dtype (:issue:`53631`)
 - Deprecated :meth:`Series.last` and :meth:`DataFrame.last` (please create a mask and filter using ``.loc`` instead) (:issue:`53692`)
 - Deprecated allowing arbitrary ``fill_value`` in :class:`SparseDtype`, in a future version the ``fill_value`` will need to be compatible with the ``dtype.subtype``, either a scalar that can be held by that subtype or ``NaN`` for integer or bool subtypes (:issue:`23124`)
+- Deprecated allowing bool dtype in :meth:`DataFrameGroupBy.quantile` and :meth:`SeriesGroupBy.quantile`, consistent with the :meth:`Series.quantile` and :meth:`DataFrame.quantile` behavior (:issue:`51424`)
 - 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 bytes input to :func:`read_excel`. To read a file path, use a string or path-like object. (:issue:`53767`)
 - Deprecated constructing :class:`SparseArray` from scalar data, pass a sequence instead (:issue:`53039`)

pandas/core/groupby/groupby.py

@@ -4166,6 +4166,17 @@ def pre_processor(vals: ArrayLike) -> tuple[np.ndarray, DtypeObj | None]:
                 inference = np.dtype(np.int64)
             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)
             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_function.py

@@ -1589,6 +1589,13 @@ 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):
+            # GH#51424
+            result = method(*args, numeric_only=True)
+            expected = method(*args, numeric_only=False)
+        tm.assert_series_equal(result, expected)
     else:
         result = method(*args, numeric_only=True)
         expected = method(*args, numeric_only=False)