Fix valerror dataframe array

pandas/core/generic.py

@@ -6038,7 +6038,12 @@ def __finalize__(self, other, method: str | None = None, **kwargs) -> Self:
             if all(bool(obj.attrs) for obj in objs):
                 # all concatenate arguments have non-empty attrs
                 attrs = objs[0].attrs
-                have_same_attrs = all(obj.attrs == attrs for obj in objs[1:])
+                have_same_attrs = all(
+                    (obj.attrs == attrs).all()
+                    if isinstance(obj.attrs, np.ndarray)
+                    else obj.attrs == attrs
+                    for obj in objs[1:]
+                )
                 if have_same_attrs:
                     self.attrs = deepcopy(attrs)
 

pandas/tests/generic/test_finalize.py

@@ -55,6 +55,7 @@
     (pd.Series, ([0, 0],), operator.methodcaller("notna")),
     (pd.Series, ([0, 0],), operator.methodcaller("notnull")),
     (pd.Series, ([1],), operator.methodcaller("add", pd.Series([1]))),
+    (pd.Series, ([0],), operator.methodcaller("concat")),
     # TODO: mul, div, etc.
     (
         pd.Series,
@@ -710,3 +711,15 @@ def test_finalize_frame_series_name():
     df = pd.DataFrame({"name": [1, 2]})
     result = pd.Series([1, 2]).__finalize__(df)
     assert result.name is None
+
+
+def test_finalize_attrs_ndarray():
+    # create two separate df's as single series as input
+    df1 = pd.DataFrame({"A": [1, 2, 3]})
+    df2 = pd.DataFrame({"A": [4, 5, 6]})
+
+    df1.attrs["array_attr"] = np.array([1, 2, 3])
+    df2.attrs["array_attr"] = np.array([1, 2, 3])
+
+    result = df1.__finalize__(df2, method="concat")
+    assert (result.attrs["array_attr"] == np.array([1, 2, 3])).all()