chore: remove an unused parameter in _rows_to_dataframe (#813)

Thank you for opening a Pull Request! Before submitting your PR, there are a few things you can do to make sure it goes smoothly:
- [ ] Make sure to open an issue as a [bug/issue](https://togithub.com/googleapis/python-bigquery-dataframes/issues/new/choose) before writing your code!  That way we can discuss the change, evaluate designs, and agree on the general idea
- [X] Ensure the tests and linter pass
- [X] Code coverage does not decrease (if any source code was changed)
- [ ] Appropriate docs were updated (if necessary)

Fixes #<issue_number_goes_here> 🦕

Author: chelsea-lin

bigframes/core/blocks.py

@@ -438,9 +438,7 @@ def reorder_levels(self, ids: typing.Sequence[str]):
 
     def _to_dataframe(self, result) -> pd.DataFrame:
         """Convert BigQuery data to pandas DataFrame with specific dtypes."""
-        dtypes = dict(zip(self.index_columns, self.index.dtypes))
-        dtypes.update(zip(self.value_columns, self.dtypes))
-        result_dataframe = self.session._rows_to_dataframe(result, dtypes)
+        result_dataframe = self.session._rows_to_dataframe(result)
         # Runs strict validations to ensure internal type predictions and ibis are completely in sync
         # Do not execute these validations outside of testing suite.
         if "PYTEST_CURRENT_TEST" in os.environ:
@@ -2582,15 +2580,14 @@ def to_pandas(self, *, ordered: Optional[bool] = None) -> pd.Index:
             )
         # Project down to only the index column. So the query can be cached to visualize other data.
         index_columns = list(self._block.index_columns)
-        dtypes = dict(zip(index_columns, self.dtypes))
         expr = self._expr.select_columns(index_columns)
         results, _ = self.session._execute(
             expr,
             ordered=ordered
             if (ordered is not None)
             else self.session._strictly_ordered,
         )
-        df = expr.session._rows_to_dataframe(results, dtypes)
+        df = expr.session._rows_to_dataframe(results)
         df = df.set_index(index_columns)
         index = df.index
         index.names = list(self._block._index_labels)  # type:ignore

bigframes/session/__init__.py

@@ -2038,7 +2038,7 @@ def _get_table_size(self, destination_table):
         return table.num_bytes
 
     def _rows_to_dataframe(
-        self, row_iterator: bigquery.table.RowIterator, dtypes: Dict
+        self, row_iterator: bigquery.table.RowIterator
     ) -> pandas.DataFrame:
         # Can ignore inferred datatype until dtype emulation breaks 1:1 mapping between BQ types and bigframes types
         dtypes_from_bq = bigframes.dtypes.bf_type_from_type_kind(row_iterator.schema)