They both have perks, so it depends on what you are doing. If your work involves heavy integration with other tools that use Apache Arrow or if you need robust support for various file formats and data sources, PyArrow might be more suitable. If you're looking for sheer performance in data processing and an easy-to-use API for exploratory data analysis, Polars might be the better choice. Ultimately, the best library for you might depend on your specific workflow, the size and complexity of your data, and your performance requirements. Testing both libraries with your actual datasets is often the best way to determine which one fits your needs better.
Thank you, it is very helpful.
which library is better? pyarrow or polars
They both have perks, so it depends on what you are doing.
If your work involves heavy integration with other tools that use Apache Arrow or if you need robust support for various file formats and data sources, PyArrow might be more suitable.
If you're looking for sheer performance in data processing and an easy-to-use API for exploratory data analysis, Polars might be the better choice.
Ultimately, the best library for you might depend on your specific workflow, the size and complexity of your data, and your performance requirements. Testing both libraries with your actual datasets is often the best way to determine which one fits your needs better.