add test for to_pandas for typed instances

tests/tests_unit/test_data_classes/test_data_models/test_typed_instances.py

@@ -345,6 +345,8 @@ def test_cognite_asset_read_and_write(
             xid = "externalId" if camel_case else "external_id"
             assert xid in dumped
             # Check that type/type_ are correctly dumped:
+            # - not starting with double underscore
+            # - not ending with single underscore
             assert dumped["type"] == {"space": "should-be", xid: "at-root"}
             if is_write:
                 properties = dumped["sources"][0]["properties"]
@@ -354,6 +356,41 @@ def test_cognite_asset_read_and_write(
             # Check that properties are cased according to use_attribute_name:
             assert ("source_created_time" if use_attribute_name else "sourceCreatedTime") in properties
 
+@pytest.mark.dsl
+@pytest.mark.parametrize("camel_case", (True, False))
+def test_cognite_asset_read_and_write__to_pandas(
+    self, cognite_asset_kwargs: dict[str, Any], camel_case: bool
+) -> None:
+    import pandas as pd
+
+    # When calling to_pandas, `use_attribute_name = not camel_case` due to how we expect
+    # attributes to be snake cased in python (in general).
+    asset_write = CogniteAssetApply(**cognite_asset_kwargs)
+    asset_read = CogniteAsset(**cognite_asset_kwargs, version=1, last_updated_time=10, created_time=5)
+
+    # TODO: Implement expand_properties=True for Apply classes?
+    write_df = asset_write.to_pandas(camel_case=camel_case)
+    read_df = asset_read.to_pandas(expand_properties=False, camel_case=camel_case)
+    read_expanded_df = asset_read.to_pandas(expand_properties=True, camel_case=camel_case)
+
+    xid = "externalId" if camel_case else "external_id"
+    for df in [write_df, read_df]:
+        assert df.index.is_unique
+        assert df.index[1] == xid
+        assert df.at["type", "value"] == {"space": "should-be", xid: "at-root"}
+
+    assert not read_expanded_df.index.is_unique  # because 'type' is repeated
+    expected_type_df = pd.DataFrame(
+        [
+            ({"space": "should-be", xid: "at-root"},),
+            ({"space": "should-be", xid: "in-properties"},),
+        ],
+        columns=["value"],
+        index=["type", "type"],
+    )
+    pd.testing.assert_frame_equal(read_expanded_df.loc["type"], expected_type_df)
+    assert ("sourceCreatedTime" if camel_case else "source_created_time") in read_expanded_df.index
+
 
 @pytest.mark.parametrize(
     "name, instance",
@@ -394,4 +431,4 @@ def test_typed_instances_overrides_inherited_methods_from_instance_cls(
         del instance["external_id"]
 
     with pytest.raises(TypeError, match=f"argument of type {name!r} is not iterable"):
-        "foo" in instance
+        "foo" in instance