extract method for clarity

bigframes/dataframe.py

@@ -1100,50 +1100,48 @@ def _assign_single_item(
             copy[k] = v(copy)
             return copy
         elif utils.is_list_like(v):
-            given_rows = len(v)
-            actual_rows = len(self)
-            assigning_to_empty_df = len(self.columns) == 0 and actual_rows == 0
-            if not assigning_to_empty_df and given_rows != actual_rows:
-                raise ValueError(
-                    f"Length of values ({given_rows}) does not match length of index ({actual_rows})"
-                )
+            return self._assign_single_item_listlike(k, v)
+        else:
+            return self._assign_scalar(k, v)
 
-            local_df = bigframes.dataframe.DataFrame(
-                {k: v}, session=self._get_block().expr.session
+    def _assign_single_item_listlike(self, k: str, v: Sequence) -> DataFrame:
+        given_rows = len(v)
+        actual_rows = len(self)
+        assigning_to_empty_df = len(self.columns) == 0 and actual_rows == 0
+        if not assigning_to_empty_df and given_rows != actual_rows:
+            raise ValueError(
+                f"Length of values ({given_rows}) does not match length of index ({actual_rows})"
             )
-            # local_df is likely (but not guarunteed) to be cached locally
-            # since the original list came from memory and so is probably < MAX_INLINE_DF_SIZE
-
-            new_column_block = local_df._block
-            original_index_column_ids = self._block.index_columns
-            self_block = self._block.reset_index(drop=False)
-            if assigning_to_empty_df:
-                if len(self._block.index_columns) > 1:
-                    # match error raised by pandas here
-                    raise ValueError(
-                        "Assigning listlike to a first column under multiindex is not supported."
-                    )
-                result_block = local_df._block
-                result_block = result_block.with_index_labels(self._block.index_labels)
-            else:
-                result_index, (
-                    get_column_left,
-                    get_column_right,
-                ) = self_block.index.join(
-                    new_column_block.index, how="left", block_identity_join=True
-                )
-                result_block = result_index._block
-                result_block = result_block.set_index(
-                    [get_column_left[col_id] for col_id in original_index_column_ids],
-                    index_labels=self._block.index_labels,
+
+        local_df = bigframes.dataframe.DataFrame(
+            {k: v}, session=self._get_block().expr.session
+        )
+        # local_df is likely (but not guarunteed) to be cached locally
+        # since the original list came from memory and so is probably < MAX_INLINE_DF_SIZE
+
+        new_column_block = local_df._block
+        original_index_column_ids = self._block.index_columns
+        self_block = self._block.reset_index(drop=False)
+        if assigning_to_empty_df:
+            if len(self._block.index_columns) > 1:
+                # match error raised by pandas here
+                raise ValueError(
+                    "Assigning listlike to a first column under multiindex is not supported."
                 )
-            return DataFrame(result_block)
+            result_block = new_column_block.with_index_labels(self._block.index_labels)
+            result_block = result_block.with_column_labels([k])
         else:
-            return self._assign_scalar(k, v)
+            result_index, (get_column_left, get_column_right,) = self_block.index.join(
+                new_column_block.index, how="left", block_identity_join=True
+            )
+            result_block = result_index._block
+            result_block = result_block.set_index(
+                [get_column_left[col_id] for col_id in original_index_column_ids],
+                index_labels=self._block.index_labels,
+            )
+        return DataFrame(result_block)
 
     def _assign_scalar(self, label: str, value: Union[int, float]) -> DataFrame:
-        # TODO(swast): Make sure that k is the ID / SQL name, not a label,
-        # which could be invalid SQL.
         col_ids = self._block.cols_matching_label(label)
 
         block, constant_col_id = self._block.create_constant(value, label)

tests/system/small/test_dataframe.py

@@ -567,7 +567,7 @@ def test_assign_existing_column(scalars_dfs):
     assert_pandas_df_equal_ignore_ordering(bf_result, pd_result)
 
 
-def test_assign_to_empty_df(session):
+def test_assign_listlike_to_empty_df(session):
     empty_df = dataframe.DataFrame(session=session)
     empty_pandas_df = pd.DataFrame()