How do I write a pandas dataframe to SQL server table?

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I have a pandas dataframe which i want to write over to sql database

dfmodwh
date subkey amount age 
09/12 0012  12.8   18
09/13 0009  15.0   20

there is an existing table in sql warehouse with the same column names. The table is called dim.h2oresults

I tried

import pyodbc
conn = pyodbc.connect('dsn=azure_warehouse_dev;'
                      'Trusted_Connection=yes;')


from sqlalchemy import create_engine, MetaData, Table, select
dfmodwh.to_sql(name='dim.h2oresults',con=conn, index=False, if_exists='append')

But this just gives me an execution error. Is there a way to write to the table through pyodbc instead of sqlalchemy such that if there is a new data everyday in dfmodwh it just keeps appending and not over writing?

pandas pyodbc sqlalchemy python
1 Answers

I believe you are going to want to use to_sql()

df.to_sql('<Table_Name', con=<Your_Connection>, if_exists='append')
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