Align concat Series name behavior in pandas 2.2 (#15032)

Fixed in pandas by pandas-dev/pandas#56365 Authors: - Matthew Roeschke (https://github.com/mroeschke) Approvers: - GALI PREM SAGAR (https://github.com/galipremsagar) URL: #15032
rapidsai · Feb 15, 2024 · aa9d484 · aa9d484
1 parent 0f694d3
commit aa9d484
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Showing 2 changed files with 73 additions and 40 deletions.
diff --git a/python/cudf/cudf/core/reshape.py b/python/cudf/cudf/core/reshape.py
@@ -102,17 +102,17 @@ def _normalize_series_and_dataframe(objs, axis):
     """Convert any cudf.Series objects in objs to DataFrames in place."""
     # Default to naming series by a numerical id if they are not named.
     sr_name = 0
-    for idx, o in enumerate(objs):
-        if isinstance(o, cudf.Series):
-            if axis == 1:
-                name = o.name
-                if name is None:
+    for idx, obj in enumerate(objs):
+        if isinstance(obj, cudf.Series):
+            name = obj.name
+            if name is None:
+                if axis == 0:
+                    name = 0
+                else:
                     name = sr_name
                     sr_name += 1
-            else:
-                name = sr_name
 
-            objs[idx] = o.to_frame(name=name)
+            objs[idx] = obj.to_frame(name=name)
 
 
 def concat(objs, axis=0, join="outer", ignore_index=False, sort=None):

diff --git a/python/cudf/cudf/tests/test_concat.py b/python/cudf/cudf/tests/test_concat.py
@@ -10,7 +10,7 @@
 
 import cudf
 from cudf.api.types import _is_categorical_dtype
-from cudf.core._compat import PANDAS_GE_200
+from cudf.core._compat import PANDAS_GE_200, PANDAS_GE_220
 from cudf.core.dtypes import Decimal32Dtype, Decimal64Dtype, Decimal128Dtype
 from cudf.testing._utils import (
     assert_eq,
@@ -459,42 +459,75 @@ def test_concat_mixed_input():
         [pd.Series([1, 2, 3]), pd.DataFrame({"a": []})],
         [pd.Series([], dtype="float64"), pd.DataFrame({"a": []})],
         [pd.Series([], dtype="float64"), pd.DataFrame({"a": [1, 2]})],
-        [pd.Series([1, 2, 3.0, 1.2], name="abc"), pd.DataFrame({"a": [1, 2]})],
-        [
-            pd.Series(
-                [1, 2, 3.0, 1.2], name="abc", index=[100, 110, 120, 130]
-            ),
-            pd.DataFrame({"a": [1, 2]}),
-        ],
-        [
-            pd.Series(
-                [1, 2, 3.0, 1.2], name="abc", index=["a", "b", "c", "d"]
+        pytest.param(
+            [
+                pd.Series([1, 2, 3.0, 1.2], name="abc"),
+                pd.DataFrame({"a": [1, 2]}),
+            ],
+            marks=pytest.mark.xfail(
+                not PANDAS_GE_220,
+                reason="https://github.com/pandas-dev/pandas/pull/56365",
             ),
-            pd.DataFrame({"a": [1, 2]}, index=["a", "b"]),
-        ],
-        [
-            pd.Series(
-                [1, 2, 3.0, 1.2, 8, 100],
-                name="New name",
-                index=["a", "b", "c", "d", "e", "f"],
+        ),
+        pytest.param(
+            [
+                pd.Series(
+                    [1, 2, 3.0, 1.2], name="abc", index=[100, 110, 120, 130]
+                ),
+                pd.DataFrame({"a": [1, 2]}),
+            ],
+            marks=pytest.mark.xfail(
+                not PANDAS_GE_220,
+                reason="https://github.com/pandas-dev/pandas/pull/56365",
             ),
-            pd.DataFrame(
-                {"a": [1, 2, 4, 10, 11, 12]},
-                index=["a", "b", "c", "d", "e", "f"],
+        ),
+        pytest.param(
+            [
+                pd.Series(
+                    [1, 2, 3.0, 1.2], name="abc", index=["a", "b", "c", "d"]
+                ),
+                pd.DataFrame({"a": [1, 2]}, index=["a", "b"]),
+            ],
+            marks=pytest.mark.xfail(
+                not PANDAS_GE_220,
+                reason="https://github.com/pandas-dev/pandas/pull/56365",
             ),
-        ],
-        [
-            pd.Series(
-                [1, 2, 3.0, 1.2, 8, 100],
-                name="New name",
-                index=["a", "b", "c", "d", "e", "f"],
+        ),
+        pytest.param(
+            [
+                pd.Series(
+                    [1, 2, 3.0, 1.2, 8, 100],
+                    name="New name",
+                    index=["a", "b", "c", "d", "e", "f"],
+                ),
+                pd.DataFrame(
+                    {"a": [1, 2, 4, 10, 11, 12]},
+                    index=["a", "b", "c", "d", "e", "f"],
+                ),
+            ],
+            marks=pytest.mark.xfail(
+                not PANDAS_GE_220,
+                reason="https://github.com/pandas-dev/pandas/pull/56365",
             ),
-            pd.DataFrame(
-                {"a": [1, 2, 4, 10, 11, 12]},
-                index=["a", "b", "c", "d", "e", "f"],
+        ),
+        pytest.param(
+            [
+                pd.Series(
+                    [1, 2, 3.0, 1.2, 8, 100],
+                    name="New name",
+                    index=["a", "b", "c", "d", "e", "f"],
+                ),
+                pd.DataFrame(
+                    {"a": [1, 2, 4, 10, 11, 12]},
+                    index=["a", "b", "c", "d", "e", "f"],
+                ),
+            ]
+            * 7,
+            marks=pytest.mark.xfail(
+                not PANDAS_GE_220,
+                reason="https://github.com/pandas-dev/pandas/pull/56365",
             ),
-        ]
-        * 7,
+        ),
     ],
 )
 def test_concat_series_dataframe_input(objs):