Fix groupby any/all on null-containing string columns

python/cudf/cudf/core/groupby/groupby.py

@@ -55,6 +55,7 @@
     cudf_dtype_to_pa_type,
     dtype_from_pylibcudf_column,
     get_dtype_of_same_kind,
+    is_pandas_nullable_extension_dtype,
     is_pandas_nullable_numpy_dtype,
 )
 from cudf.utils.performance_tracking import _performance_tracking
@@ -3401,11 +3402,24 @@ def _to_bool_col(col):
             else:
                 # For numeric/bool inputs, cast to bool preserving nulls.
                 bool_col = col != 0
-            # Normalize away pandas-extension bool dtypes so the downstream
-            # aggregation always sees ``np.bool_``.
-            bool_col = bool_col.astype(bool_dtype, copy=False)
+            if col.has_nulls() and bool_col.null_count != col.null_count:
+                # ``na_value=np.nan`` dtypes don't propagate missingness
+                # through the comparison above (NaN compares as False), so
+                # restore the source column's null positions.
+                bool_col = bool_col.set_mask(col.mask, col.null_count)
             if not skipna:
+                # NA values must not flip ``all`` to False nor stop ``any``
+                # from being True, so treat them as True.
                 bool_col = bool_col.fillna(True)
+            # Normalize away pandas-extension bool dtypes so the downstream
+            # aggregation sees ``np.bool_``, but only when no nulls remain:
+            # casting a null-containing extension dtype to numpy bool is
+            # (intentionally) rejected in pandas-compatible mode. A nullable
+            # bool column aggregates correctly as-is, and the result is
+            # normalized to ``np.bool_`` after empty/skipna groups are
+            # filled below.
+            if not bool_col.has_nulls():
+                bool_col = bool_col.astype(bool_dtype, copy=False)
             return bool_col
 
         if is_series:
@@ -3431,12 +3445,25 @@ def _to_bool_col(col):
         )
         result = bool_gb.agg(agg_name)
 
+        def _bool_result_dtype(input_dtype):
+            # Mirror pandas' any/all output dtype to the input's "flavor":
+            # masked nullable -> ``boolean``, pyarrow -> ``bool[pyarrow]``,
+            # numpy/string -> numpy ``bool``.
+            if isinstance(input_dtype, pd.ArrowDtype):
+                return pd.ArrowDtype(pa.bool_())
+            if is_pandas_nullable_extension_dtype(
+                input_dtype
+            ) and not is_dtype_obj_string(input_dtype):
+                return pd.BooleanDtype()
+            return np.dtype(np.bool_)
+
         # Empty groups (skipna=True with all-NA values) yield NA from
         # min/max — pandas treats these as ``True`` for ``all`` and
         # ``False`` for ``any``.
-        bool_np = np.dtype(np.bool_)
         if isinstance(result, Series):
-            result = result.fillna(fill_value).astype(bool_np)
+            result = result.fillna(fill_value).astype(
+                _bool_result_dtype(self.obj.dtype)
+            )
         else:
             # With ``as_index=False`` the group-key columns are present in the
             # result; only the aggregated value columns must be coerced to
@@ -3446,8 +3473,9 @@ def _to_bool_col(col):
             for col_name in result._column_names:
                 if col_name in key_names:
                     continue
+                target = _bool_result_dtype(self.obj._data[col_name].dtype)
                 result[col_name] = (
-                    result[col_name].fillna(fill_value).astype(bool_np)
+                    result[col_name].fillna(fill_value).astype(target)
                 )
 
         if min_count and min_count > 0:

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

@@ -2451,7 +2451,6 @@ def pytest_unconfigure(config):
     "tests/groupby/test_missing.py::test_indices_with_missing": "TODO: Add a reason for failure",
     "tests/groupby/test_numeric_only.py::TestNumericOnly::test_extrema[max]": "Failed: DID NOT RAISE <class 'TypeError'>",
     "tests/groupby/test_numeric_only.py::TestNumericOnly::test_extrema[min]": "Failed: DID NOT RAISE <class 'TypeError'>",
-    "tests/groupby/test_reductions.py::test_any": 'AssertionError: Column name="B" are different',
     "tests/groupby/test_reductions.py::test_basic_aggregations[float32]": "AssertionError: Attributes of Series are different",
     "tests/groupby/test_reductions.py::test_basic_aggregations[int32]": "AssertionError: Attributes of Series are different",
     "tests/groupby/test_reductions.py::test_first_last_skipna[Float32-False-False-first]": "TODO: Add a reason for failure",
@@ -2546,7 +2545,6 @@ def pytest_unconfigure(config):
     "tests/groupby/test_reductions.py::test_first_last_skipna[uint8[pyarrow]-False-False-last]": "TODO: Add a reason for failure",
     "tests/groupby/test_reductions.py::test_first_last_skipna[uint8[pyarrow]-True-False-first]": "TODO: Add a reason for failure",
     "tests/groupby/test_reductions.py::test_first_last_skipna[uint8[pyarrow]-True-False-last]": "TODO: Add a reason for failure",
-    "tests/groupby/test_reductions.py::test_groupby_bool_aggs[True-any-vals12]": 'AssertionError: Column name="val" are different',
     "tests/groupby/test_reductions.py::test_groupby_mean_no_overflow": "TODO: Add a reason for failure",
     "tests/groupby/test_reductions.py::test_groupby_sum_mincount_boolean[0]": "TODO: Add a reason for failure",
     "tests/groupby/test_reductions.py::test_idxmin_idxmax_extremes_skipna[False-float-idxmax]": "TODO: Add a reason for failure",
@@ -2571,46 +2569,6 @@ def pytest_unconfigure(config):
     "tests/groupby/test_reductions.py::test_multifunc_skipna[True-prod-values3-float64-float64]": "AssertionError: Series are different",
     "tests/groupby/test_reductions.py::test_nunique_with_NaT[key1-data1-True-expected1]": "TODO: Add a reason for failure",
     "tests/groupby/test_reductions.py::test_nunique_with_timegrouper": "TODO: Add a reason for failure",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-False-False-0]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-False-False-1]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-False-True-0]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-False-True-1]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-True-False-0]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-True-False-1]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-True-True-0]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-all-True-True-1]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-any-False-False-0]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-any-False-False-1]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-any-False-True-0]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[pyarrow]-any-False-True-1]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-False-False-0]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-False-False-1]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-False-True-0]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-False-True-1]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-True-False-0]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-True-False-1]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-True-True-0]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-all-True-True-1]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-any-False-False-0]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-any-False-False-1]": 'AssertionError: DataFrame.iloc[:, 0] (column name="b") values are different',
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-any-False-True-0]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=str[python]-any-False-True-1]": "AssertionError: Series values are different",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-all-False-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-all-False-False-1]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-all-True-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-all-True-False-1]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-any-False-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-any-False-False-1]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-any-True-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[pyarrow]-any-True-False-1]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-all-False-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-all-False-False-1]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-all-True-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-all-True-False-1]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-any-False-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-any-False-False-1]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-any-True-False-0]": "AssertionError: DataFrame shape mismatch",
-    "tests/groupby/test_reductions.py::test_string_dtype_all_na[string=string[python]-any-True-False-1]": "AssertionError: DataFrame shape mismatch",
     "tests/groupby/test_reductions.py::test_sum_skipna[False-values0-float64]": "AssertionError: Series are different",
     "tests/groupby/test_reductions.py::test_sum_skipna[False-values3-timedelta64[ns]]": "AssertionError: Series are different",
     "tests/groupby/test_reductions.py::test_sum_skipna_object[False]": "AssertionError: Series are different",

python/cudf/cudf/tests/groupby/test_reductions.py

@@ -1,4 +1,4 @@
-# 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
@@ -1327,6 +1327,55 @@ def test_groupby_string_min_max_preserves_dtype(string_dtype, op):
     assert got["b"].dtype == expect["b"].dtype
 
 
+@pytest.mark.parametrize(
+    "string_dtype",
+    [
+        pd.StringDtype(storage="python", na_value=pd.NA),
+        pd.StringDtype(storage="python", na_value=np.nan),
+        pd.StringDtype(storage="pyarrow", na_value=pd.NA),
+        pd.StringDtype(storage="pyarrow", na_value=np.nan),
+    ],
+)
+@pytest.mark.parametrize("op", ["any", "all"])
+@pytest.mark.parametrize("skipna", [True, False])
+def test_groupby_any_all_string_nulls(string_dtype, op, skipna):
+    # any/all over string groups must treat nulls like pandas regardless of
+    # the StringDtype's na_value: an all-null group is empty under skipna
+    # (``all`` -> True, ``any`` -> False), and non-empty/empty strings map
+    # to True/False. Groups here are either all-null or all-valued so the
+    # result is unambiguous (no Kleene NA propagation).
+    pdf = pd.DataFrame(
+        {
+            "a": [1, 1, 2, 3],
+            "b": pd.array([pd.NA, pd.NA, "x", ""], dtype=string_dtype),
+        }
+    )
+    gdf = cudf.from_pandas(pdf)
+    with cudf.option_context("mode.pandas_compatible", True):
+        got = getattr(gdf.groupby("a"), op)(skipna=skipna)
+    expect = getattr(pdf.groupby("a"), op)(skipna=skipna)
+    assert_eq(expect, got)
+
+
+@pytest.mark.parametrize(
+    "dtype",
+    ["int64", "Int64", "UInt16", "Float64", "boolean", "int64[pyarrow]"],
+)
+@pytest.mark.parametrize("op", ["any", "all"])
+def test_groupby_any_all_result_dtype(dtype, op):
+    # any/all output dtype mirrors the input's flavor, matching pandas:
+    # numpy -> bool, masked-nullable -> boolean, pyarrow -> bool[pyarrow].
+    pdf = pd.DataFrame(
+        {"a": ["x", "y", "y"], "b": pd.array([1, 0, 1], dtype=dtype)}
+    )
+    gdf = cudf.from_pandas(pdf)
+    with cudf.option_context("mode.pandas_compatible", True):
+        got = getattr(gdf.groupby("a"), op)()
+    expect = getattr(pdf.groupby("a"), op)()
+    assert_eq(expect, got)
+    assert got["b"].dtype == expect["b"].dtype
+
+
 def test_groupby_series_identity_column_exclusion():
     pdf = pd.DataFrame(
         {"a": [1, 1, 2, 2, 3, 3], "b": [10, 20, 30, 40, 50, 60]}