我正在尝试从MySQL服务器查询数据，并使用panda.to_gbq API将其写入Google BigQuery。

def production_to_gbq(table_name_prod,prefix,table_name_gbq,dataset,project):
    # Extract data from Production

    q = """
        SELECT *
        FROM
            {}
        """.format(table_name_prod)

    df = pd.read_sql(q, con)

    # Write to gbq    
    df.to_gbq(dataset + table_name_gbq, project, chunksize=1000, verbose=True, reauth=False, if_exists='replace', private_key=None)

    return df

我一直收到400错误指示无效输入。

Load is 100.0% Complete
---------------------------------------------------------------------------
BadRequest                                Traceback (most recent call last)
/usr/local/lib/python3.6/site-packages/pandas_gbq/gbq.py in load_data(self, dataframe, dataset_id, table_id, chunksize, schema)
    569                     self.client, dataframe, dataset_id, table_id,
--> 570                     chunksize=chunksize):
    571                 self._print("\rLoad is {0}% Complete".format(

/usr/local/lib/python3.6/site-packages/pandas_gbq/_load.py in load_chunks(client, dataframe, dataset_id, table_id, chunksize, schema)
     73             destination_table,
---> 74             job_config=job_config).result()

/usr/local/lib/python3.6/site-packages/google/cloud/bigquery/job.py in result(self, timeout)
    527         # TODO: modify PollingFuture so it can pass a retry argument to done().
--> 528         return super(_AsyncJob, self).result(timeout=timeout)
    529 

/usr/local/lib/python3.6/site-packages/google/api_core/future/polling.py in result(self, timeout)
    110             # Pylint doesn't recognize that this is valid in this case.
--> 111             raise self._exception
    112 

BadRequest: 400 Error while reading data, error message: CSV table encountered too many errors, giving up. Rows: 10; errors: 1. Please look into the error stream for more details.

During handling of the above exception, another exception occurred:

GenericGBQException                       Traceback (most recent call last)
<ipython-input-73-ef9c7cec0104> in <module>()
----> 1 departments.to_gbq(dataset + table_name_gbq, project, chunksize=1000, verbose=True, reauth=False, if_exists='replace', private_key=None)
      2 

/usr/local/lib/python3.6/site-packages/pandas/core/frame.py in to_gbq(self, destination_table, project_id, chunksize, verbose, reauth, if_exists, private_key)
   1058         return gbq.to_gbq(self, destination_table, project_id=project_id,
   1059                           chunksize=chunksize, verbose=verbose, reauth=reauth,
-> 1060                           if_exists=if_exists, private_key=private_key)
   1061 
   1062     @classmethod

/usr/local/lib/python3.6/site-packages/pandas/io/gbq.py in to_gbq(dataframe, destination_table, project_id, chunksize, verbose, reauth, if_exists, private_key)
    107                       chunksize=chunksize,
    108                       verbose=verbose, reauth=reauth,
--> 109                       if_exists=if_exists, private_key=private_key)

/usr/local/lib/python3.6/site-packages/pandas_gbq/gbq.py in to_gbq(dataframe, destination_table, project_id, chunksize, verbose, reauth, if_exists, private_key, auth_local_webserver, table_schema)
    980     connector.load_data(
    981         dataframe, dataset_id, table_id, chunksize=chunksize,
--> 982         schema=table_schema)
    983 
    984 

/usr/local/lib/python3.6/site-packages/pandas_gbq/gbq.py in load_data(self, dataframe, dataset_id, table_id, chunksize, schema)
    572                     ((total_rows - remaining_rows) * 100) / total_rows))
    573         except self.http_error as ex:
--> 574             self.process_http_error(ex)
    575 
    576         self._print("\n")

/usr/local/lib/python3.6/site-packages/pandas_gbq/gbq.py in process_http_error(ex)
    453         # <https://cloud.google.com/bigquery/troubleshooting-errors>`__
    454 
--> 455         raise GenericGBQException("Reason: {0}".format(ex))
    456 
    457     def run_query(self, query, **kwargs):

GenericGBQException: Reason: 400 Error while reading data, error message: CSV table encountered too many errors, giving up. Rows: 10; errors: 1. Please look into the error stream for more details.

我研究了表模式，

id  INTEGER NULLABLE    
name    STRING  NULLABLE    
description STRING  NULLABLE    
created_at  INTEGER NULLABLE    
modified_at FLOAT   NULLABLE

它与 Dataframe 相同：

id                        int64
name                     object
description              object
created_at                int64
modified_at             float64

该表在GBQ中创建，但保持为空。
我在www.example.com _gbq API上读了一些东西，但没有找到太多pandas.to，除了这条似乎相关但没有回复的消息：
bigquery table is empty when using pandas to_gbq
我发现了一个关于对象数据类型中的数字的潜在解决方案，这些数字被传递到GBQ表中而不带引号，通过将列数据类型设置为字符串可以解决这个问题。
I use to_gbq on pandas for updating Google BigQuery and get GenericGBQException
我试过了：

for col in df.columns:
    if df[col].dtypes == object:
        df[col] = df[col].fillna('')
        df[col] = df[col].astype(str)

不幸的是，我仍然得到同样的错误。类似地，试图格式化丢失的数据并为int和float设置dtype也会给出同样的错误。
我是不是漏掉了什么？