title: Inserting rows into Microsoft SQL Server using pandas raises precision error
body: <p>I am trying to insert data into a mssql database. I needed as fast method for this so I set the fast_executemany param to true. The upload works fine for most part but if one of the column is a datetime with timezone it crashes raising: <code>(pyodbc.Error) ('HY104', '[HY104] [Microsoft][ODBC Driver 17 for SQL Server]Invalid precision value (0) (SQLBindParameter)')</code>
  If I insert the same data with fast_executemany as False then everythhing works perfectly. Did anyone came across a similar problem or know what might be the issue?</p>
  <p>Sample code</p>
  <pre><code>from sqlalchemy import create_engine, engine
  import pytz
  import pandas as pd
  from sqlalchemy.dialects.mssql import DATETIMEOFFSET
  import datetime
  
  
  engine_url = engine.URL.create(
              drivername='mssql',
              username='admin',
              password='**',
              host='**',
              port='1433',
              database='mytestdb1',
              query={'driver': &quot;ODBC Driver 17 for SQL Server&quot;}
          )
  mssql_engine = create_engine(engine_url, echo=False, fast_executemany=True)
  
  
  
  base = datetime.datetime.today().replace(tzinfo=pytz.utc)
  date_list = [base - datetime.timedelta(days=x) for x in range(20)]
  df = pd.DataFrame(date_list, columns = ['date_time'])
  df.to_sql('test_insert', mssql_engine, schema='testschema1', if_exists='replace', dtype = {'date_time':DATETIMEOFFSET})
  </code></pre>
  <p>response:</p>
  <pre><code>DBAPIError: (pyodbc.Error) ('HY104', '[HY104] [Microsoft][ODBC Driver 17 for SQL Server]Invalid precision value (0) (SQLBindParameter)')
  [SQL: INSERT INTO testschema1.test_datetime ([index], date_time) VALUES (?, ?)]
  [parameters: ((0, '2022-05-06 16:40:05.434984 +00:00'), (1, '2022-05-05 16:40:05.434984 +00:00'), (2, '2022-05-04 16:40:05.434984 +00:00'), (3, '2022-05-03 16:40:05.434984 +00:00'), (4, '2022-05-02 16:40:05.434984 +00:00'), (5, '2022-05-01 16:40:05.434984 +00:00'), (6, '2022-04-30 16:40:05.434984 +00:00'), (7, '2022-04-29 16:40:05.434984 +00:00')  ... displaying 10 of 20 total bound parameter sets ...  (18, '2022-04-18 16:40:05.434984 +00:00'), (19, '2022-04-17 16:40:05.434984 +00:00'))]
   (Background on this error at: http://sqlalche.me/e/14/dbapi)
  </code></pre>
  <p>sqlalchemy==1.4, pyodbc==4.0.32 and pandas==1.2.0</p>
  <p>As I said the code works perfectly if I dont use fast_executemany.</p>