Fix Series.isin dtype and value semantics for masked (nullable) dtypes

python/cudf/cudf/core/column/numerical.py

@@ -943,6 +943,22 @@ def _process_values_for_isin(
                 rhs = rhs.astype(lhs.dtype)
             elif lhs.can_cast_safely(rhs.dtype):
                 lhs = lhs.astype(rhs.dtype)
+            elif (
+                isinstance(lhs.dtype, np.dtype)
+                and isinstance(rhs.dtype, np.dtype)
+                and lhs.dtype.kind in "biuf"
+                and rhs.dtype.kind in "biuf"
+                and "b" in (lhs.dtype.kind, rhs.dtype.kind)
+            ):
+                # A boolean column compares by value against numeric needles
+                # (``True == 1``) like numpy/pandas. ``can_cast_safely`` reports
+                # bool<->numeric as unsafe, so promote the boolean side to the
+                # numeric dtype (a bool always fits) rather than bailing out to
+                # an all-False result.
+                if lhs.dtype.kind == "b":
+                    lhs = lhs.astype(rhs.dtype)
+                else:
+                    rhs = rhs.astype(lhs.dtype)
         return lhs, rhs
 
     def _can_return_nan(self, skipna: bool | None = None) -> bool:

python/cudf/cudf/core/series.py

@@ -70,9 +70,10 @@
     get_dtype_of_same_kind,
     is_mixed_with_object_dtype,
     is_pandas_nullable_extension_dtype,
+    is_pandas_nullable_numpy_dtype,
 )
 from cudf.utils.performance_tracking import _performance_tracking
-from cudf.utils.utils import _EQUALITY_OPS, _is_same_name
+from cudf.utils.utils import _EQUALITY_OPS, _is_same_name, is_na_like
 
 if TYPE_CHECKING:
     from collections.abc import Hashable, Iterable, MutableMapping
@@ -3141,8 +3142,41 @@ def isin(self, values):
                 f"to isin(), you passed a [{type(values).__name__}]"
             )
 
+        if is_pandas_nullable_numpy_dtype(self.dtype) and not isinstance(
+            self.dtype, pd.StringDtype
+        ):
+            # Mirror pandas' BaseMaskedArray.isin for masked (nullable
+            # integer/float/boolean) dtypes:
+            #  * matching is done on the underlying numpy values, so e.g. a
+            #    boolean element equals the integer 1,
+            #  * an NA element is considered present only when pd.NA itself
+            #    is one of the passed values (a plain NaN/None/NaT does not
+            #    match), and
+            #  * the result is a nullable BooleanDtype with no missing values.
+            numpy_dtype = self.dtype.numpy_dtype
+            na_mask = self._column.isnull()
+            placeholder = False if numpy_dtype.kind == "b" else 0
+            data_col = self._column.astype(numpy_dtype).fillna(placeholder)
+            # NA-like sentinels (pd.NA/None/NaT) never match a real value and
+            # would otherwise raise when mixed with numeric values; NA rows
+            # are handled by the mask below instead.
+            cleaned_values = [
+                value for value in values if not is_na_like(value)
+            ]
+            result_col = data_col.isin(cleaned_values)
+            if na_mask.any():
+                values_have_NA = any(value is pd.NA for value in values)
+                result_col = (
+                    result_col | na_mask
+                    if values_have_NA
+                    else result_col & ~na_mask
+                )
+            result_col = result_col.astype(pd.BooleanDtype())
+        else:
+            result_col = self._column.isin(values)
+
         return Series._from_column(
-            self._column.isin(values),
+            result_col,
             name=self.name,
             index=self.index,
             attrs=self.attrs,

python/cudf/cudf/pandas/scripts/pandas-testing-plugin.py

@@ -4116,18 +4116,6 @@ def pytest_unconfigure(config):
     "tests/series/methods/test_info.py::test_info_series[False]": "TODO: Add a reason for failure",
     "tests/series/methods/test_info.py::test_info_series[True]": "TODO: Add a reason for failure",
     "tests/series/methods/test_info.py::test_info_show_counts_false": "assert '<class 'pand...: 140.0 bytes' == '<class 'pand...ge: 8.0 bytes'",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data0-values0-expected0-Float64]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data0-values0-expected0-Int64]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data0-values0-expected0-boolean]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data2-values2-expected2-Float64]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data2-values2-expected2-Int64]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data2-values2-expected2-boolean]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data4-values4-expected4-Float64]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data4-values4-expected4-Int64]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data4-values4-expected4-boolean]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data5-values5-expected5-Int64]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::TestSeriesIsIn::test_isin_masked_types[data5-values5-expected5-boolean]": "TODO: Add a reason for failure",
-    "tests/series/methods/test_isin.py::test_isin_large_series_and_pdNA[boolean-data3-values3-expected3]": "AssertionError: Attributes of Series are different",
     "tests/series/methods/test_map.py::test_map_callable[MockEngineDecorator]": "AssertionError: assert Index([], dtype='object', name='bar') is Index([], dtype='object', name='bar')",
     "tests/series/methods/test_map.py::test_map_callable[None]": "AssertionError: assert Index([], dtype='object', name='bar') is Index([], dtype='object', name='bar')",
     "tests/series/methods/test_map.py::test_map_categorical_na_action[None-expected0]": "TODO: Add a reason for failure",

python/cudf/cudf/tests/series/methods/test_isin.py

@@ -1,8 +1,9 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 import numpy as np
 import pandas as pd
+import pyarrow as pa
 import pytest
 
 import cudf
@@ -159,3 +160,67 @@ def test_isin_categorical(data, values):
     got = gsr.isin(values)
     expected = psr.isin(values)
     assert_eq(got, expected)
+
+
+@pytest.mark.parametrize("dtype", ["boolean", "Int64", "Float64"])
+@pytest.mark.parametrize(
+    "data,values",
+    [
+        ([0, 1, 0], [1]),
+        ([0, 1, 0], [1, pd.NA]),
+        ([0, pd.NA, 0], [1, 0]),
+        ([0, 1, pd.NA], [1, pd.NA]),
+        ([0, 1, pd.NA], [1, np.nan]),
+        ([0, pd.NA, pd.NA], [np.nan, pd.NaT, None]),
+    ],
+)
+def test_isin_masked_types(dtype, data, values):
+    # Series.isin on a pandas masked (nullable integer/float/boolean) dtype
+    # returns a nullable BooleanDtype result and matches pandas' NA semantics:
+    #  * comparison is done on the underlying values (a boolean element equals
+    #    the integer 1), and
+    #  * an NA element is considered present only when pd.NA itself is one of
+    #    ``values`` (a plain NaN/None/NaT does not match).
+    psr = pd.Series(data, dtype=dtype)
+    gsr = cudf.Series(data, dtype=dtype)
+
+    got = gsr.isin(values)
+    expected = psr.isin(values)
+
+    assert got.dtype == pd.BooleanDtype()
+    assert_eq(got, expected)
+
+
+@pytest.mark.parametrize(
+    "values",
+    [[1], [0], [1, 0], [2], [1.0], [1.5], [True], [False]],
+)
+def test_isin_bool_against_numeric(values):
+    # A boolean Series compares equal to the integers/floats 0 and 1, matching
+    # numpy/pandas value semantics (previously cudf returned all-False for a
+    # numeric ``values`` argument).
+    psr = pd.Series([True, False, False, True])
+    gsr = cudf.Series([True, False, False, True])
+
+    got = gsr.isin(values)
+    assert got.dtype == np.dtype("bool")
+    assert_eq(got, psr.isin(values))
+
+
+@pytest.mark.parametrize(
+    "psr",
+    [
+        pd.Series([0, 1, 0], dtype=pd.ArrowDtype(pa.int64())),
+        pd.Series([1.0, 2.0, None], dtype=pd.ArrowDtype(pa.float64())),
+        pd.Series([True, False, True], dtype=pd.ArrowDtype(pa.bool_())),
+        pd.Series(["a", "b", "a"], dtype="category"),
+    ],
+)
+def test_isin_non_masked_extension_returns_numpy_bool(psr):
+    # Arrow and categorical inputs yield a numpy bool result (only masked
+    # numeric/boolean dtypes upgrade to nullable boolean).
+    gsr = cudf.from_pandas(psr)
+
+    got = gsr.isin([psr.iloc[0]])
+    assert got.dtype == np.dtype("bool")
+    assert_eq(got, psr.isin([psr.iloc[0]]))