fix more issues

bigframes/series.py

@@ -978,9 +978,13 @@ def quantile(self, q: Union[float, Sequence[float]] = 0.5) -> Union[Series, floa
         qs = tuple(q) if utils.is_list_like(q) else (q,)
         result = block_ops.quantile(self._block, (self._value_column,), qs=qs)
         if utils.is_list_like(q):
-            result = result.stack()
-            result = result.drop_levels([result.index_columns[0]])
-            return Series(result)
+            # Drop the first level, since only one column
+            result = result.with_column_labels(result.column_labels.droplevel(0))
+            result, index_col = result.create_constant(self.name, None)
+            result = result.set_index([index_col])
+            return Series(
+                result.transpose(original_row_index=pandas.Index([self.name]))
+            )
         else:
             return cast(float, Series(result).to_pandas().squeeze())
 

bigframes/session/__init__.py

@@ -812,9 +812,12 @@ def _read_gbq_table(
             )
 
         # ----------------------------------------------------
-        # Create Block & default index if len(index_cols) == 0
+        # Create Default Index if DefaultIndexKind provided, or no index provided
         # ----------------------------------------------------
 
+        if not index_col:
+            index_col = bigframes.enums.DefaultIndexKind.SEQUENTIAL_INT64
+
         index_names: Sequence[Hashable] = index_cols
         if index_col == bigframes.enums.DefaultIndexKind.SEQUENTIAL_INT64:
             sequential_index_col = bigframes.core.guid.generate_guid("index_")

tests/system/small/test_empty_index.py

@@ -21,7 +21,7 @@ def test_empty_index_series_repr(
     pd_result = (
         scalars_pandas_df_default_index["int64_too"]
         .head(5)
-        .to_string(dtype=True, index=False, name=True, length=True)
+        .to_string(dtype=True, index=False, name=True)
     )
     assert bf_result == pd_result
 

tests/system/small/test_series.py

@@ -1429,13 +1429,13 @@ def test_numeric_literal(scalars_dfs):
     assert bf_result.dtype == pd.ArrowDtype(pa.decimal128(38, 9))
 
 
-def test_repr(scalars_dfs):
+def test_series_small_repr(scalars_dfs):
     scalars_df, scalars_pandas_df = scalars_dfs
 
     col_name = "int64_col"
     bf_series = scalars_df[col_name]
     pd_series = scalars_pandas_df[col_name]
-    assert repr(bf_series) == repr(pd_series)
+    assert repr(bf_series) == pd_series.to_string(length=True, dtype=True, name=True)
 
 
 def test_sum(scalars_dfs):