How to Efficiently Insert Pandas DataFrames into MySQL Databases?

Inserting Pandas DataFrames into MySQL Databases Using mysqldb

The Query

You wish to efficiently populate an existing table within a MySQL database with data from a Pandas DataFrame. The challenge lies in understanding whether a direct insertion is feasible or if iterating over rows is necessary.

Implementation

Direct Insertion via 'to_sql' Method

Since Pandas version 0.14, the recommended approach is to utilize the 'to_sql' method. This method simplifies the process by allowing direct insertion of DataFrames into SQL tables.

MySQL Database Connection Setup

Optional: Iterative Insertion

If iterating over rows is desired, the 'write_frame' method can be used with the 'flavor' parameter set to 'mysql'.

Handling Existing Tables

The 'if_exists' parameter determines how the insertion handles existing tables:

• 'fail': Do not insert if the table already exists.
• 'replace': Drop and recreate the table before inserting.
• 'append': Insert into the table if it exists, or create it if it does not.

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