Read External SQL File into Pandas Dataframe

I have a solution that might work for you. It should give you a nice little pandas.DataFrame.

First, you have to read the query inside the sql file. Then just use the pd.read_sql_query() instead of pd.read_sql()

I am sure you know it, but here is the doc for the function: http://pandas.pydata.org/pandas-docs/version/0.20/generated/pandas.read_sql_query.html#pandas.read_sql_query

# Read the sql filequery = open('filename.sql', 'r')# connection == the connection to your database, in your case prob_dbDF = pd.read_sql_query(query.read(),connection)query.close() 

I can assure you that it is working with T-SQL, but I never used it with MySQL.

This is a MWE of how it worked for me:

query = open('./query_file.sql', 'r') db_config = {            'server': server address,            'port': port,            'user': user,            'password': password,            'database': db name        }    try:        sql_conn = pymssql.connect(**db_config)        logging.info('SQL connection is opened')               avise_me_df = pd.read_sql(query.read(),sql_conn)        logging.info('pandas df recorded')    except OperationalError as e:        connected = False        logging.error('Error reading data from SQL table')    else:        connected = True    finally:        if connected:            sql_conn.close()            logging.info('SQL connection is closed')

I hope this might help.