fix: Fix single row broadcast with null index (#1803)

Author: TrevorBergeron

bigframes/core/blocks.py

@@ -2895,7 +2895,7 @@ def join_with_single_row(
         combined_expr,
         index_columns=index_cols_post_join,
         column_labels=left.column_labels.append(single_row_block.column_labels),
-        index_labels=[left.index.name],
+        index_labels=left.index.names,
     )
     return (
         block,

tests/system/small/test_dataframe.py

@@ -2657,16 +2657,16 @@ def test_listlike_binop_axis_1_bf_index(scalars_dfs):
     assert_pandas_df_equal(bf_result, pd_result, check_dtype=False)
 
 
-def test_binop_with_self_aggregate(session, scalars_dfs):
-    scalars_df, scalars_pandas_df = scalars_dfs
+def test_binop_with_self_aggregate(scalars_dfs_maybe_ordered):
+    scalars_df, scalars_pandas_df = scalars_dfs_maybe_ordered
 
     df_columns = ["int64_col", "float64_col", "int64_too"]
 
     # Ensure that this takes the optimized single-query path by counting executions
-    execution_count_before = session._metrics.execution_count
+    execution_count_before = scalars_df._session._metrics.execution_count
     bf_df = scalars_df[df_columns]
     bf_result = (bf_df - bf_df.mean()).to_pandas()
-    execution_count_after = session._metrics.execution_count
+    execution_count_after = scalars_df._session._metrics.execution_count
 
     pd_df = scalars_pandas_df[df_columns]
     pd_result = pd_df - pd_df.mean()
@@ -2677,6 +2677,29 @@ def test_binop_with_self_aggregate(session, scalars_dfs):
     assert_pandas_df_equal(bf_result, pd_result, check_dtype=False)
 
 
+def test_binop_with_self_aggregate_w_index_reset(scalars_dfs_maybe_ordered):
+    scalars_df, scalars_pandas_df = scalars_dfs_maybe_ordered
+
+    df_columns = ["int64_col", "float64_col", "int64_too"]
+
+    # Ensure that this takes the optimized single-query path by counting executions
+    execution_count_before = scalars_df._session._metrics.execution_count
+    bf_df = scalars_df[df_columns].reset_index(drop=True)
+    bf_result = (bf_df - bf_df.mean()).to_pandas()
+    execution_count_after = scalars_df._session._metrics.execution_count
+
+    pd_df = scalars_pandas_df[df_columns].reset_index(drop=True)
+    pd_result = pd_df - pd_df.mean()
+
+    executions = execution_count_after - execution_count_before
+
+    assert executions == 1
+    pd_result.index = pd_result.index.astype("Int64")
+    assert_pandas_df_equal(
+        bf_result, pd_result, check_dtype=False, check_index_type=False
+    )
+
+
 @pytest.mark.parametrize(
     ("left_labels", "right_labels"),
     [