Update existing row in database from pandas df
One way is to make use of an sqlalchemy "table class" and session.merge(row), session.commit():
Here is an example:
for row in range(0, len(df)): row_data = table_class(column_1=df.ix[i]['column_name'], column_2=df.ix[i]['column_name'], ... ) session.merge(row_data) session.commit()
For sql alchemy case of read table as df, change df, then update table values based on df, I found the df.to_sql to work with name=<table_name> index=False if_exists='replace'
This should replace the old values in the table with the ones you changed in the df