Keep the dtype family in GroupBy.rank results

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

@@ -882,8 +882,26 @@ def rank(x):
 
         result = self.agg(rank)
 
-        # pandas always returns floats:
-        return result.astype(np.dtype(np.float64))
+        # pandas always returns floats, staying within the value column's
+        # dtype family: numpy -> float64, masked (Int64/Float32/...) ->
+        # Float64, arrow -> double[pyarrow]
+        target = np.dtype(np.float64)
+        if result.ndim == 1:
+            source_dtype = (
+                self.obj.dtype if self.obj.ndim == 1 else result.dtype
+            )
+            return result.astype(get_dtype_of_same_kind(source_dtype, target))
+        return result.astype(
+            {
+                label: get_dtype_of_same_kind(
+                    self.obj._data[label].dtype
+                    if self.obj.ndim == 2 and label in self.obj._data
+                    else result_dtype,
+                    target,
+                )
+                for label, result_dtype in result._dtypes
+            }
+        )
 
     @property
     def _groupby(self):

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

@@ -1877,10 +1877,6 @@ def pytest_unconfigure(config):
     "tests/groupby/methods/test_nth.py::test_slice[arg2-expected_rows2]": "TODO: Add a reason for failure",
     "tests/groupby/methods/test_nth.py::test_slice[arg3-expected_rows3]": "TODO: Add a reason for failure",
     "tests/groupby/methods/test_quantile.py::test_groupby_quantile_nonmulti_levels_order": "tm.assert_equal compares MultiIndex.levels, which cudf returns as a list rather than the FrozenList pandas produces",
-    "tests/groupby/methods/test_rank.py::test_rank_avg_even_vals[True-int32]": "TODO: Add a reason for failure",
-    "tests/groupby/methods/test_rank.py::test_rank_avg_even_vals[True-int64]": "TODO: Add a reason for failure",
-    "tests/groupby/methods/test_rank.py::test_rank_avg_even_vals[True-uint32]": "TODO: Add a reason for failure",
-    "tests/groupby/methods/test_rank.py::test_rank_avg_even_vals[True-uint64]": "TODO: Add a reason for failure",
     "tests/groupby/test_all_methods.py::test_not_c_contiguous_mask[all]": "assert not True",
     "tests/groupby/test_all_methods.py::test_not_c_contiguous_mask[any]": "assert not True",
     "tests/groupby/test_all_methods.py::test_not_c_contiguous_mask[bfill]": "assert not True",

python/cudf/cudf/tests/groupby/test_rank.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2023-2025, NVIDIA CORPORATION.
+# SPDX-FileCopyrightText: Copyright (c) 2023-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 import numpy as np
 import pandas as pd
@@ -58,3 +58,27 @@ def test_groupby_rank_fails():
     )
     with pytest.raises(NotImplementedError):
         gdf.groupby(["a"]).rank(method="min", axis=1)
+
+
+@pytest.mark.parametrize(
+    "dtype, expected_dtype",
+    [
+        ("int64", "float64"),
+        ("float32", "float64"),
+        ("Int64", "Float64"),
+        ("Float32", "Float64"),
+    ],
+)
+def test_rank_dtype_family(dtype, expected_dtype):
+    # pandas' groupby rank always returns floats within the value column's
+    # dtype family: numpy -> float64, masked -> Float64
+    pdf = pd.DataFrame(
+        {"key": ["a"] * 4, "val": pd.array([1, 2, 2, 3], dtype=dtype)}
+    )
+    gdf = cudf.from_pandas(pdf)
+
+    expect = pdf.groupby("key").rank()
+    got = gdf.groupby("key").rank()
+
+    assert str(got["val"].dtype) == expected_dtype
+    assert_groupby_results_equal(expect, got)