fix(describe): handle unsupported types and empty results

Author: shuoweil

bigframes/core/blocks.py

@@ -3417,6 +3417,11 @@ def unpivot(
         joined_array, (labels_mapping, column_mapping) = labels_array.relational_join(
             array_value, type="cross"
         )
+
+    if not labels_array.column_ids:
+        # A valid unpivot operation requires at least one row label to disambiguate the output rows.
+        raise ValueError("unpivot requires non-empty row_labels")
+
     new_passthrough_cols = [column_mapping[col] for col in passthrough_columns]
     # Last column is offsets
     index_col_ids = [labels_mapping[col] for col in labels_array.column_ids[:-1]]

bigframes/pandas/core/methods/describe.py

@@ -56,9 +56,10 @@ def describe(
             "max",
         ]
     ).intersection(describe_block.column_labels.get_level_values(-1))
-    describe_block = describe_block.stack(override_labels=stack_cols)
-
-    return dataframe.DataFrame(describe_block).droplevel(level=0)
+    if not stack_cols.empty:
+        describe_block = describe_block.stack(override_labels=stack_cols)
+        return dataframe.DataFrame(describe_block).droplevel(level=0)
+    return dataframe.DataFrame(describe_block)
 
 
 def _describe(
@@ -120,10 +121,7 @@ def _get_aggs_for_dtype(dtype) -> list[aggregations.UnaryAggregateOp]:
         dtypes.TIME_DTYPE,
     ]:
         return [aggregations.count_op, aggregations.nunique_op]
-    elif dtype in [
-        dtypes.JSON_DTYPE,
-        dtypes.OBJ_REF_DTYPE,
-    ]:
+    elif dtypes.is_json_like(dtype) or dtype == dtypes.OBJ_REF_DTYPE:
         return [aggregations.count_op]
     else:
         return []

tests/system/small/pandas/test_describe.py

@@ -371,3 +371,22 @@ def test_describe_json_and_obj_ref_returns_count(session):
     assert "count" in res.index
     assert res.loc["count", "json_col"] == 1.0
     assert res.loc["count", "obj_ref_col"] == 1.0
+
+
+def test_describe_with_unsupported_type_returns_empty_dataframe(session):
+    df = session.read_gbq("SELECT ST_GEOGPOINT(1.0, 2.0) AS geo_col")
+
+    res = df.describe().to_pandas()
+
+    assert len(res.columns) == 0
+    assert len(res.index) == 1
+
+
+def test_describe_empty_dataframe_returns_empty_dataframe(session):
+    df = session.read_gbq("SELECT 1 AS int_col LIMIT 0")
+    df = df.drop(columns=["int_col"])
+
+    res = df.describe().to_pandas()
+
+    assert len(res.columns) == 0
+    assert len(res.index) == 1