BUG: Add fillna at the beginning of _where not to fill NA. #60729

doc/source/whatsnew/v3.0.0.rst

@@ -711,6 +711,7 @@ Indexing
 - Bug in :meth:`DataFrame.loc` with inconsistent behavior of loc-set with 2 given indexes to Series (:issue:`59933`)
 - Bug in :meth:`Index.get_indexer` and similar methods when ``NaN`` is located at or after position 128 (:issue:`58924`)
 - Bug in :meth:`MultiIndex.insert` when a new value inserted to a datetime-like level gets cast to ``NaT`` and fails indexing (:issue:`60388`)
+- Bug in :meth:`Series.mask` unexpectedly filling ``pd.NA`` (:issue:`60729`)
 - Bug in printing :attr:`Index.names` and :attr:`MultiIndex.levels` would not escape single quotes (:issue:`60190`)
 - Bug in reindexing of :class:`DataFrame` with :class:`PeriodDtype` columns in case of consolidated block (:issue:`60980`, :issue:`60273`)
 

pandas/core/generic.py

@@ -28,6 +28,7 @@
 
 from pandas._libs import lib
 from pandas._libs.lib import is_range_indexer
+from pandas._libs.missing import NA
 from pandas._libs.tslibs import (
     Period,
     Timestamp,
@@ -9702,6 +9703,7 @@ def _where(
         # align the cond to same shape as myself
         cond = common.apply_if_callable(cond, self)
         if isinstance(cond, NDFrame):
+            cond = cond.fillna(True)
             # CoW: Make sure reference is not kept alive
             if cond.ndim == 1 and self.ndim == 2:
                 cond = cond._constructor_expanddim(
@@ -9712,10 +9714,11 @@ def _where(
             cond = cond.align(self, join="right")[0]
         else:
             if not hasattr(cond, "shape"):
-                cond = np.asanyarray(cond)
+                cond = np.asanyarray(cond, dtype=object)
             if cond.shape != self.shape:
                 raise ValueError("Array conditional must be same shape as self")
             cond = self._constructor(cond, **self._construct_axes_dict(), copy=False)
+            cond = cond.fillna(True)
 
         # make sure we are boolean
         fill_value = bool(inplace)
@@ -10096,7 +10099,17 @@ def mask(
 
         # see gh-21891
         if not hasattr(cond, "__invert__"):
-            cond = np.array(cond)
+            cond = np.array(cond, dtype=object)
+
+        if isinstance(cond, np.ndarray):
+            if all(
+                x is NA or isinstance(x, (np.bool_, bool)) or x is np.nan
+                for x in cond.flatten()
+            ):
+                if not cond.flags.writeable:
+                    cond.setflags(write=True)
+                cond[isna(cond)] = False
+                cond = cond.astype(bool)
 
         return self._where(
             ~cond,

pandas/tests/series/indexing/test_mask.py

@@ -1,6 +1,8 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
+
 from pandas import Series
 import pandas._testing as tm
 
@@ -67,3 +69,26 @@ def test_mask_inplace():
     rs = s.copy()
     rs.mask(cond, -s, inplace=True)
     tm.assert_series_equal(rs, s.mask(cond, -s))
+
+
+@pytest.mark.parametrize(
+    "dtype",
+    [
+        "Int64",
+        pytest.param("int64[pyarrow]", marks=td.skip_if_no("pyarrow")),
+    ],
+)
+@pytest.mark.parametrize("cond_type", [["series", "list", "numpy"]])
+def test_mask_na(dtype, cond_type):
+    # We should not be filling pd.NA. See GH#60729
+    series = Series([None, 1, 2, None, 3, 4, None], dtype=dtype)
+    cond = series <= 2
+    expected = Series([None, -99, -99, None, 3, 4, None], dtype=dtype)
+
+    if cond_type == "list":
+        cond = cond.to_list()
+    elif cond_type == "numpy":
+        cond = cond.to_numpy()
+
+    result = series.mask(cond, -99)
+    tm.assert_series_equal(result, expected)

pandas/tests/series/indexing/test_where.py

@@ -1,6 +1,8 @@
 import numpy as np
 import pytest
 
+from pandas._libs.missing import NA
+
 from pandas.core.dtypes.common import is_integer
 
 import pandas as pd
@@ -443,3 +445,13 @@ def test_where_datetimelike_categorical(tz_naive_fixture):
     res = pd.DataFrame(lvals).where(mask[:, None], pd.DataFrame(rvals))
 
     tm.assert_frame_equal(res, pd.DataFrame(dr))
+
+
+def test_where_list_with_nan():
+    ser = Series([None, 1, 2, np.nan, 3, 4, NA])
+    cond = [np.nan, False, False, np.nan, True, True, np.nan]
+    expected = Series([None, -99, -99, np.nan, 3, 4, NA])
+
+    res = ser.where(cond, -99)
+
+    tm.assert_series_equal(res, expected)