BUG: DataFrame.any with axis=1 and bool_only=True (pandas-dev#36106)

Author: jbrockmendel

doc/source/whatsnew/v1.2.0.rst

@@ -246,6 +246,7 @@ Timezones
 Numeric
 ^^^^^^^
 - Bug in :func:`to_numeric` where float precision was incorrect (:issue:`31364`)
+- Bug in :meth:`DataFrame.any` with ``axis=1`` and ``bool_only=True`` ignoring the ``bool_only`` keyword (:issue:`32432`)
 -
 
 Conversion

pandas/core/frame.py

@@ -8639,15 +8639,12 @@ def func(values):
             else:
                 return op(values, axis=axis, skipna=skipna, **kwds)
 
-        def _get_data(axis_matters: bool) -> DataFrame:
+        def _get_data() -> DataFrame:
             if filter_type is None:
                 data = self._get_numeric_data()
             elif filter_type == "bool":
-                if axis_matters:
-                    # GH#25101, GH#24434
-                    data = self._get_bool_data() if axis == 0 else self
-                else:
-                    data = self._get_bool_data()
+                # GH#25101, GH#24434
+                data = self._get_bool_data()
             else:  # pragma: no cover
                 msg = (
                     f"Generating numeric_only data with filter_type {filter_type} "
@@ -8659,7 +8656,7 @@ def _get_data(axis_matters: bool) -> DataFrame:
         if numeric_only is not None:
             df = self
             if numeric_only is True:
-                df = _get_data(axis_matters=True)
+                df = _get_data()
             if axis == 1:
                 df = df.T
                 axis = 0
@@ -8720,8 +8717,7 @@ def blk_func(values):
         except TypeError:
             # e.g. in nanops trying to convert strs to float
 
-            # TODO: why doesnt axis matter here?
-            data = _get_data(axis_matters=False)
+            data = _get_data()
             labels = data._get_agg_axis(axis)
 
             values = data.values

pandas/tests/reductions/test_reductions.py

@@ -914,6 +914,13 @@ def test_all_any_boolean(self):
         tm.assert_series_equal(s.all(level=0), Series([False, True, False]))
         tm.assert_series_equal(s.any(level=0), Series([False, True, True]))
 
+    def test_any_axis1_bool_only(self):
+        # GH#32432
+        df = pd.DataFrame({"A": [True, False], "B": [1, 2]})
+        result = df.any(axis=1, bool_only=True)
+        expected = pd.Series([True, False])
+        tm.assert_series_equal(result, expected)
+
     def test_timedelta64_analytics(self):
 
         # index min/max