I need help to get this working. I have a pd.DataFrame (df)
, which I need to load to a MySQL database. I don't understand what the error message means and how to fix it.
Any help will be highly appreciated.
This is what I tried:
import MySQLdb
from pandas.io import sql
#METHOD 1
db=MySQLdb.connect(host="***",port=***,user="***",passwd="***",db="***")
df.to_sql(con=db, name='forecast', if_exists='replace', flavor='mysql')
##Also tried
sql.write_frame(df, con=db, name='forecast', if_exists='replace', flavor='mysql')
**DatabaseError**: Execution failed on sql: SHOW TABLES LIKE %s
(2006, 'MySQL server has gone away')
unable to rollback
#METHOD 2: using sqlalchemy
from sqlalchemy import create_engine
engine = create_engine("mysql+mysqldb://**username***:**passwd**@***host***:3306/**dbname**")
conn = engine.raw_connection()
df.to_sql(name='demand_forecast_t', con=conn,if_exists='replace', flavor='mysql',index=False, index_label='rowID')
conn.close()
The error message is:
**OperationalError**: DatabaseError: Execution failed on sql: SHOW TABLES LIKE %s
(2006, 'MySQL server has gone away') unable to rollback
When using sqlalchemy, you should pass the engine and not the raw connection:
engine = create_engine("mysql+mysqldb://...")
df.to_sql('demand_forecast_t', engine, if_exists='replace', index=False)
Writing to MySQL without sqlalchemy (so with specifying flavor='mysql'
) is deprecated.
When the problem is that you have a too large frame to write at once, you can use the chunksize
keyword (see the docstring). Eg:
df.to_sql('demand_forecast_t', engine, if_exists='replace', chunksize=10000)
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