Backport PR pandas-dev#54670: BUG: drop_duplicates raising for boolea…

…n arrow dtype with missing values

doc/source/whatsnew/v2.1.0.rst

@@ -626,6 +626,7 @@ Performance improvements
 - Performance improvement in :meth:`DataFrame.transpose` when transposing a DataFrame with a single masked dtype, e.g. :class:`Int64` (:issue:`52836`)
 - Performance improvement in :meth:`Series.add` for PyArrow string and binary dtypes (:issue:`53150`)
 - Performance improvement in :meth:`Series.corr` and :meth:`Series.cov` for extension dtypes (:issue:`52502`)
+- Performance improvement in :meth:`Series.drop_duplicates` for ``ArrowDtype`` (:issue:`54667`).
 - Performance improvement in :meth:`Series.ffill`, :meth:`Series.bfill`, :meth:`DataFrame.ffill`, :meth:`DataFrame.bfill` with PyArrow dtypes (:issue:`53950`)
 - Performance improvement in :meth:`Series.str.get_dummies` for PyArrow-backed strings (:issue:`53655`)
 - Performance improvement in :meth:`Series.str.get` for PyArrow-backed strings (:issue:`53152`)
@@ -830,6 +831,7 @@ ExtensionArray
 - Bug in :class:`~arrays.ArrowExtensionArray` converting pandas non-nanosecond temporal objects from non-zero values to zero values (:issue:`53171`)
 - Bug in :meth:`Series.quantile` for PyArrow temporal types raising ``ArrowInvalid`` (:issue:`52678`)
 - Bug in :meth:`Series.rank` returning wrong order for small values with ``Float64`` dtype (:issue:`52471`)
+- Bug in :meth:`Series.unique` for boolean ``ArrowDtype`` with ``NA`` values (:issue:`54667`)
 - Bug in :meth:`~arrays.ArrowExtensionArray.__iter__` and :meth:`~arrays.ArrowExtensionArray.__getitem__` returning python datetime and timedelta objects for non-nano dtypes (:issue:`53326`)
 - Bug where the :class:`DataFrame` repr would not work when a column had an :class:`ArrowDtype` with a ``pyarrow.ExtensionDtype`` (:issue:`54063`)
 - Bug where the ``__from_arrow__`` method of masked ExtensionDtypes (e.g. :class:`Float64Dtype`, :class:`BooleanDtype`) would not accept PyArrow arrays of type ``pyarrow.null()`` (:issue:`52223`)

pandas/core/algorithms.py

@@ -55,6 +55,7 @@
 )
 from pandas.core.dtypes.concat import concat_compat
 from pandas.core.dtypes.dtypes import (
+    ArrowDtype,
     BaseMaskedDtype,
     CategoricalDtype,
     ExtensionDtype,
@@ -996,9 +997,13 @@ def duplicated(
     -------
     duplicated : ndarray[bool]
     """
-    if hasattr(values, "dtype") and isinstance(values.dtype, BaseMaskedDtype):
-        values = cast("BaseMaskedArray", values)
-        return htable.duplicated(values._data, keep=keep, mask=values._mask)
+    if hasattr(values, "dtype"):
+        if isinstance(values.dtype, ArrowDtype):
+            values = values._to_masked()  # type: ignore[union-attr]
+
+        if isinstance(values.dtype, BaseMaskedDtype):
+            values = cast("BaseMaskedArray", values)
+            return htable.duplicated(values._data, keep=keep, mask=values._mask)
 
     values = _ensure_data(values)
     return htable.duplicated(values, keep=keep)

pandas/tests/series/methods/test_drop_duplicates.py

@@ -249,3 +249,10 @@ def test_drop_duplicates_ignore_index(self):
         result = ser.drop_duplicates(ignore_index=True)
         expected = Series([1, 2, 3])
         tm.assert_series_equal(result, expected)
+
+    def test_duplicated_arrow_dtype(self):
+        pytest.importorskip("pyarrow")
+        ser = Series([True, False, None, False], dtype="bool[pyarrow]")
+        result = ser.drop_duplicates()
+        expected = Series([True, False, None], dtype="bool[pyarrow]")
+        tm.assert_series_equal(result, expected)