The advantage of Python is that you can apply operations to larger datasets with hundreds, even thousands, of data points ...

This looks like a nice package, but I am having trouble installing it with the current versions of pandas, Python, conda, and pip. I even tried using the setup.py file, which is a deprecated method. I ...

├── csv_files/ │ ├── itens_pedido.csv │ └── pedidos.csv ├── etl_script.py ├── assets/ │ └── etl_pipeline.png │ └── e_shop_DER.png ├── ddl_database/ │ └── ddl.sql ├── README.md ...

Pandas works best for small or medium datasets with standard Python libraries. Polars excels at large data with multi-core processing and lower memory use. Combining both tools can maximize speed, ...