DEPR: treating object-dtype blocks as bool_only (pandas-dev#46188)

Author: jbrockmendel

doc/source/whatsnew/v1.2.0.rst

@@ -354,6 +354,7 @@ of columns could result in a larger Series result. See (:issue:`37799`).
 *New behavior*:
 
 .. ipython:: python
+   :okwarning:
 
     In [5]: df.all(bool_only=True)
 

doc/source/whatsnew/v1.5.0.rst

@@ -280,6 +280,7 @@ Other Deprecations
 - Deprecated the behavior of :meth:`Series.fillna` and :meth:`DataFrame.fillna` with ``timedelta64[ns]`` dtype and incompatible fill value; in a future version this will cast to a common dtype (usually object) instead of raising, matching the behavior of other dtypes (:issue:`45746`)
 - Deprecated the ``warn`` parameter in :func:`infer_freq` (:issue:`45947`)
 - Deprecated allowing non-keyword arguments in :meth:`ExtensionArray.argsort` (:issue:`46134`)
+- Deprecated treating all-bool ``object``-dtype columns as bool-like in :meth:`DataFrame.any` and :meth:`DataFrame.all` with ``bool_only=True``, explicitly cast to bool instead (:issue:`46188`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/dtypes/inference.py

@@ -4,11 +4,13 @@
 from numbers import Number
 import re
 from typing import Pattern
+import warnings
 
 import numpy as np
 
 from pandas._libs import lib
 from pandas._typing import ArrayLike
+from pandas.util._exceptions import find_stack_level
 
 is_bool = lib.is_bool
 
@@ -447,5 +449,16 @@ def is_inferred_bool_dtype(arr: ArrayLike) -> bool:
     if dtype == np.dtype(bool):
         return True
     elif dtype == np.dtype("object"):
-        return lib.is_bool_array(arr)
+        result = lib.is_bool_array(arr)
+        if result:
+            # GH#46188
+            warnings.warn(
+                "In a future version, object-dtype columns with all-bool values "
+                "will not be included in reductions with bool_only=True. "
+                "Explicitly cast to bool dtype instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+        return result
+
     return False

pandas/tests/frame/test_reductions.py

@@ -1219,6 +1219,8 @@ def test_any_all_object(self):
         assert result is False
 
     def test_any_all_object_bool_only(self):
+        msg = "object-dtype columns with all-bool values"
+
         df = DataFrame({"A": ["foo", 2], "B": [True, False]}).astype(object)
         df._consolidate_inplace()
         df["C"] = Series([True, True])
@@ -1228,29 +1230,36 @@ def test_any_all_object_bool_only(self):
 
         # The underlying bug is in DataFrame._get_bool_data, so we check
         #  that while we're here
-        res = df._get_bool_data()
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            res = df._get_bool_data()
         expected = df[["B", "C"]]
         tm.assert_frame_equal(res, expected)
 
-        res = df.all(bool_only=True, axis=0)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            res = df.all(bool_only=True, axis=0)
         expected = Series([False, True], index=["B", "C"])
         tm.assert_series_equal(res, expected)
 
         # operating on a subset of columns should not produce a _larger_ Series
-        res = df[["B", "C"]].all(bool_only=True, axis=0)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            res = df[["B", "C"]].all(bool_only=True, axis=0)
         tm.assert_series_equal(res, expected)
 
-        assert not df.all(bool_only=True, axis=None)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert not df.all(bool_only=True, axis=None)
 
-        res = df.any(bool_only=True, axis=0)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            res = df.any(bool_only=True, axis=0)
         expected = Series([True, True], index=["B", "C"])
         tm.assert_series_equal(res, expected)
 
         # operating on a subset of columns should not produce a _larger_ Series
-        res = df[["B", "C"]].any(bool_only=True, axis=0)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            res = df[["B", "C"]].any(bool_only=True, axis=0)
         tm.assert_series_equal(res, expected)
 
-        assert df.any(bool_only=True, axis=None)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert df.any(bool_only=True, axis=None)
 
     @pytest.mark.parametrize("method", ["any", "all"])
     def test_any_all_level_axis_none_raises(self, method):

pandas/tests/internals/test_internals.py

@@ -784,14 +784,16 @@ def test_get_numeric_data(self):
         )
 
     def test_get_bool_data(self):
+        msg = "object-dtype columns with all-bool values"
         mgr = create_mgr(
             "int: int; float: float; complex: complex;"
             "str: object; bool: bool; obj: object; dt: datetime",
             item_shape=(3,),
         )
         mgr.iset(6, np.array([True, False, True], dtype=np.object_))
 
-        bools = mgr.get_bool_data()
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            bools = mgr.get_bool_data()
         tm.assert_index_equal(bools.items, Index(["bool", "dt"]))
         tm.assert_almost_equal(
             mgr.iget(mgr.items.get_loc("bool")).internal_values(),
@@ -805,7 +807,8 @@ def test_get_bool_data(self):
         )
 
         # Check sharing
-        bools2 = mgr.get_bool_data(copy=True)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            bools2 = mgr.get_bool_data(copy=True)
         bools2.iset(0, np.array([False, True, False]))
         tm.assert_numpy_array_equal(
             mgr.iget(mgr.items.get_loc("bool")).internal_values(),