test: fixup test suite for cudf.pandas (#1837)

narwhals/_pandas_like/utils.py

@@ -478,9 +478,11 @@ def native_to_narwhals_dtype(
     dtypes = import_dtypes_module(version)
 
     if dtype.startswith(("large_list", "list", "struct", "fixed_size_list")):
-        if implementation is Implementation.CUDF:
-            return arrow_native_to_narwhals_dtype(native_column.dtype.to_arrow(), version)
-        return arrow_native_to_narwhals_dtype(native_column.dtype.pyarrow_dtype, version)
+        native_dtype = native_column.dtype
+        if hasattr(native_dtype, "to_arrow"):  # pragma: no cover
+            # cudf, cudf.pandas
+            return arrow_native_to_narwhals_dtype(native_dtype.to_arrow(), version)
+        return arrow_native_to_narwhals_dtype(native_dtype.pyarrow_dtype, version)
     if dtype != "object":
         return non_object_native_to_narwhals_dtype(dtype, version, implementation)
     if implementation is Implementation.DASK:

tests/utils.py

@@ -106,7 +106,9 @@ def assert_equal_data(result: Any, expected: dict[str, Any]) -> None:
         result_value = result[key]
         for i, (lhs, rhs) in enumerate(zip_strict(result_value, expected_value)):
             if isinstance(lhs, float) and not math.isnan(lhs):
-                are_equivalent_values = math.isclose(lhs, rhs, rel_tol=0, abs_tol=1e-6)
+                are_equivalent_values = rhs is not None and math.isclose(
+                    lhs, rhs, rel_tol=0, abs_tol=1e-6
+                )
             elif isinstance(lhs, float) and math.isnan(lhs):
                 are_equivalent_values = rhs is None or math.isnan(rhs)
             elif isinstance(rhs, float) and math.isnan(rhs):