Backport PR #57388 on branch 2.2.x (BUG: map(na_action=ignore) not respected for Arrow & masked types) (#57413)

Backport PR #57388: BUG: map(na_action=ignore) not respected for Arrow & masked types

Co-authored-by: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>

Author: meeseeksmachine

doc/source/whatsnew/v2.2.1.rst

@@ -24,6 +24,7 @@ Fixed regressions
 - Fixed regression in :meth:`CategoricalIndex.difference` raising ``KeyError`` when other contains null values other than NaN (:issue:`57318`)
 - Fixed regression in :meth:`DataFrame.groupby` raising ``ValueError`` when grouping by a :class:`Series` in some cases (:issue:`57276`)
 - Fixed regression in :meth:`DataFrame.loc` raising ``IndexError`` for non-unique, masked dtype indexes where result has more than 10,000 rows (:issue:`57027`)
+- Fixed regression in :meth:`DataFrame.map` with ``na_action="ignore"`` not being respected for NumPy nullable and :class:`ArrowDtypes` (:issue:`57316`)
 - Fixed regression in :meth:`DataFrame.merge` raising ``ValueError`` for certain types of 3rd-party extension arrays (:issue:`57316`)
 - Fixed regression in :meth:`DataFrame.shift` raising ``AssertionError`` for ``axis=1`` and empty :class:`DataFrame` (:issue:`57301`)
 - Fixed regression in :meth:`DataFrame.sort_index` not producing a stable sort for a index with duplicates (:issue:`57151`)

pandas/core/arrays/arrow/array.py

@@ -1414,7 +1414,7 @@ def to_numpy(
 
     def map(self, mapper, na_action=None):
         if is_numeric_dtype(self.dtype):
-            return map_array(self.to_numpy(), mapper, na_action=None)
+            return map_array(self.to_numpy(), mapper, na_action=na_action)
         else:
             return super().map(mapper, na_action)
 

pandas/core/arrays/masked.py

@@ -1333,7 +1333,7 @@ def max(self, *, skipna: bool = True, axis: AxisInt | None = 0, **kwargs):
         return self._wrap_reduction_result("max", result, skipna=skipna, axis=axis)
 
     def map(self, mapper, na_action=None):
-        return map_array(self.to_numpy(), mapper, na_action=None)
+        return map_array(self.to_numpy(), mapper, na_action=na_action)
 
     def any(self, *, skipna: bool = True, axis: AxisInt | None = 0, **kwargs):
         """

pandas/tests/extension/test_arrow.py

@@ -3379,3 +3379,10 @@ def test_to_numpy_timestamp_to_int():
     result = ser.to_numpy(dtype=np.int64)
     expected = np.array([1577853000000000000])
     tm.assert_numpy_array_equal(result, expected)
+
+
+def test_map_numeric_na_action():
+    ser = pd.Series([32, 40, None], dtype="int64[pyarrow]")
+    result = ser.map(lambda x: 42, na_action="ignore")
+    expected = pd.Series([42.0, 42.0, np.nan], dtype="float64")
+    tm.assert_series_equal(result, expected)

pandas/tests/extension/test_masked.py

@@ -179,6 +179,15 @@ def test_map(self, data_missing, na_action):
             expected = data_missing.to_numpy()
         tm.assert_numpy_array_equal(result, expected)
 
+    def test_map_na_action_ignore(self, data_missing_for_sorting):
+        zero = data_missing_for_sorting[2]
+        result = data_missing_for_sorting.map(lambda x: zero, na_action="ignore")
+        if data_missing_for_sorting.dtype.kind == "b":
+            expected = np.array([False, pd.NA, False], dtype=object)
+        else:
+            expected = np.array([zero, np.nan, zero])
+        tm.assert_numpy_array_equal(result, expected)
+
     def _get_expected_exception(self, op_name, obj, other):
         try:
             dtype = tm.get_dtype(obj)