Saving Dataframes into Oracle Database with Python

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Using Python to Save a Dataframe into Oracle Database

You can use the pandas library in combination with the sqlalchemy and cx_Oracle libraries to save a dataframe to an Oracle database in Python.

Replace 'username', 'password', 'hostname', 'port', and 'service_name' with your actual Oracle database credentials, connection details.

Please replace your_table_name with the actual lowercase name of the table in your Oracle database. Otherwise, you may encounter InvalidRequestError: Could not reflect: requested table(s) not available in Engine.

When you run this script, it will establish a connection to the Oracle database, create a sample dataframe, and then save the dataframe to the specified table in the Oracle database.

Make sure the table structure has been created in the database before proceeding

Option 1: Create Table Structure using SQL

Keep in mind that you will need to create the table structure in the Oracle database before attempting to save the dataframe to it.

The table structure should match the structure of the dataframe in terms of column names and data types.

You can create the table structure in your Oracle database using SQL. Here's an example of how you might create a table in Oracle to match the structure of your dataframe:

Option 2: Create Table Structure using Python

You can run the SQL script in Python using the engine.execute() method provided by the SQLAlchemy library. Here's an example of how you can execute an SQL script after creating the engine:

Make sure to replace your_table_name, column1_name, column1_data_type, etc. with your actual table and column names and data types.

Conclusion

Once the table structure is in place, you can then use the method I mentioned earlier to save the dataframe to the Oracle database. The to_sql method will automatically insert the data from the dataframe into the existing table in the database, as long as the column names and data types match.