Add to changelog. Remove comment about destination tables.

Author: tswast

docs/source/changelog.rst

@@ -39,8 +39,16 @@ Enhancements
   (contributed by @johnpaton)
 - Read ``project_id`` in :func:`to_gbq` from provided ``credentials`` if
   available (contributed by @daureg)
+<<<<<<< Updated upstream
 - ``read_gbq`` uses the timezone-aware ``DatetimeTZDtype(unit='ns',
   tz='UTC')`` dtype for BigQuery ``TIMESTAMP`` columns. (:issue:`269`)
+||||||| merged common ancestors
+=======
+- Add ``use_bqstorage_api`` to :func:`read_gbq`. The BigQuery Storage API can
+  be used to download large query results (>125 MB) more quickly. If the BQ
+  Storage API can't be used, the BigQuery API is used instead. (:issue:`133`,
+  :issue:`270`)
+>>>>>>> Stashed changes
 
 .. _changelog-0.9.0:
 

docs/source/reading.rst

@@ -84,3 +84,10 @@ DATETIME           datetime64[ns]
 TIME               datetime64[ns]
 DATE               datetime64[ns]
 ================== =========================
+
+.. _reading-bqstorage-api:
+
+Using the BigQuery Storage API
+------------------------------
+
+The BigQuery Storage API

pandas_gbq/gbq.py

@@ -885,27 +885,6 @@ def read_gbq(
     -------
     df: DataFrame
         DataFrame representing results of query.
-
-    Examples
-    --------
-
-    Use the BigQuery Storage API to fetch results quickly, but at an addition
-    cost. Due to a known issue in the BigQuery Storage API, you must write
-    your query results to a destination table.
-
-    >>> pandas_gbq.read_gbq(
-    ...     query_string,
-    ...     configuration={
-    ...         'query': {
-    ...             'destinationTable': {
-    ...                 'projectId': 'your-project',
-    ...                 'datasetId': 'destination_dataset',
-    ...                 'tableId': 'new_table_name',
-    ...             }
-    ...         }
-    ...     },
-    ...     use_bqstorage_api=True,
-    ... )
     """
     global context