Fix: Handle single-column DataFrame dtypes in TableWidget

Author: shuoweil

bigframes/core/blocks.py

@@ -3471,28 +3471,6 @@ def _pd_index_to_array_value(
     Create an ArrayValue from a list of label tuples.
     The last column will be row offsets.
     """
-    if index.empty:
-        id_gen = bigframes.core.identifiers.standard_id_strings()
-        col_ids = [next(id_gen) for _ in range(index.nlevels + 1)]
-
-        data_dict = {}
-        if isinstance(index, pd.MultiIndex):
-            dtypes = index.dtypes.values.tolist()
-        else:
-            dtypes = [index.dtype]
-
-        for col_id, dtype in zip(col_ids[:-1], dtypes):
-            try:
-                bf_dtype = bigframes.dtypes.bigframes_type(dtype)
-                pa_type = bigframes.dtypes.bigframes_dtype_to_arrow_dtype(bf_dtype)
-            except TypeError:
-                pa_type = pa.string()
-            data_dict[col_id] = pa.array([], type=pa_type)
-
-        data_dict[col_ids[-1]] = pa.array([], type=pa.int64())
-        table = pa.Table.from_pydict(data_dict)
-        return core.ArrayValue.from_pyarrow(table, session=session)
-
     rows = []
     labels_as_tuples = utils.index_as_tuples(index)
     for row_offset in range(len(index)):

bigframes/display/anywidget.py

@@ -111,11 +111,10 @@ def __init__(self, dataframe: bigframes.dataframe.DataFrame):
         # TODO(b/463754889): Support non-string column labels for sorting.
         if all(isinstance(col, str) for col in dataframe.columns):
             # TODO(b/462525985): dataframe.dtypes should always be a Series.
-            items = (
-                dataframe.dtypes.items()
-                if isinstance(dataframe.dtypes, pd.Series)
-                else [(dataframe.columns[0], dataframe.dtypes)]
-            )
+            if isinstance(dataframe.dtypes, pd.Series):
+                items = dataframe.dtypes.items()
+            else:
+                items = [(dataframe.columns[0], dataframe.dtypes)]
             self.orderable_columns = [
                 str(col_name) for col_name, dtype in items if dtypes.is_orderable(dtype)
             ]

bigframes/session/bq_caching_executor.py

@@ -326,14 +326,13 @@ def _export_gbq(
             session=array_value.session,
         )
 
-        has_complex_col = any(
-            t in (bigframes.dtypes.TIMEDELTA_DTYPE, bigframes.dtypes.OBJ_REF_DTYPE)
-            for t in array_value.schema.dtypes
+        has_timedelta_col = any(
+            t == bigframes.dtypes.TIMEDELTA_DTYPE for t in array_value.schema.dtypes
         )
 
-        if spec.if_exists != "append" and has_complex_col:
+        if spec.if_exists != "append" and has_timedelta_col:
             # Only update schema if this is not modifying an existing table, and the
-            # new table contains complex columns (timedelta, object reference).
+            # new table contains timedelta columns.
             table = self.bqclient.get_table(spec.table)
             table.schema = array_value.schema.to_bigquery()
             self.bqclient.update_table(table, ["schema"])