Backport PR #51631 on branch 2.0.x (BUG: Series.any and Series.all for empty or all-null pyarrow-backed dtypes) (#51999)

Co-authored-by: Luke Manley <lukemanley@gmail.com>

Author: phofl

doc/source/whatsnew/v2.0.0.rst

@@ -1362,6 +1362,7 @@ ExtensionArray
 - Bug in :class:`Series` constructor unnecessarily overflowing for nullable unsigned integer dtypes (:issue:`38798`, :issue:`25880`)
 - Bug in setting non-string value into ``StringArray`` raising ``ValueError`` instead of ``TypeError`` (:issue:`49632`)
 - Bug in :meth:`DataFrame.reindex` not honoring the default ``copy=True`` keyword in case of columns with ExtensionDtype (and as a result also selecting multiple columns with getitem (``[]``) didn't correctly result in a copy) (:issue:`51197`)
+- Bug in :meth:`Series.any` and :meth:`Series.all` returning ``NA`` for empty or all null pyarrow-backed data when ``skipna=True`` (:issue:`51624`)
 - Bug in :class:`~arrays.ArrowExtensionArray` logical operations ``&`` and ``|`` raising ``KeyError`` (:issue:`51688`)
 
 Styler

pandas/core/arrays/arrow/array.py

@@ -1145,6 +1145,10 @@ def pyarrow_meth(data, skip_nulls, **kwargs):
                 # Let ExtensionArray._reduce raise the TypeError
                 return super()._reduce(name, skipna=skipna, **kwargs)
 
+        # GH51624: pyarrow defaults to min_count=1, pandas behavior is min_count=0
+        if name in ["any", "all"] and "min_count" not in kwargs:
+            kwargs["min_count"] = 0
+
         try:
             result = pyarrow_meth(data_to_reduce, skip_nulls=skipna, **kwargs)
         except (AttributeError, NotImplementedError, TypeError) as err:

pandas/tests/extension/test_arrow.py

@@ -2328,9 +2328,13 @@ def test_dt_tz_localize(unit):
     tm.assert_series_equal(result, expected)
 
 
-def test_concat_empty_arrow_backed_series(dtype):
-    # GH#51734
-    ser = pd.Series([], dtype=dtype)
-    expected = ser.copy()
-    result = pd.concat([ser[np.array([], dtype=np.bool_)]])
-    tm.assert_series_equal(result, expected)
+@pytest.mark.parametrize("skipna", [True, False])
+def test_boolean_reduce_series_all_null(all_boolean_reductions, skipna):
+    # GH51624
+    ser = pd.Series([None], dtype="float64[pyarrow]")
+    result = getattr(ser, all_boolean_reductions)(skipna=skipna)
+    if skipna:
+        expected = all_boolean_reductions == "all"
+    else:
+        expected = pd.NA
+    assert result is expected