Interoperability with Other Python Libraries

Although Polars is an awesome tool that’s fast and efficient, there are times when interoperating with other tools or libraries is crucial in your data projects. The good news is that there are libraries out there already that can work with Polars. In Chapter 9, Time Series Analysis, you‘ve already seen that it works well with the functime and plotly libraries. Polars can also work with other Python libraries such as pandas, NumPy, PyArrow, and DuckDB to name a few. As Polars matures more as a tool, there will be more libraries and tools, making the integration and interoperability between Polars and the whole Python data ecosystem more seamless. For instance, having a seamless integration with other Python libraries benefits Polars by providing functionalities it doesn’t yet have. It’ll give you more options for how you implement your solution.

By the end of this chapter, you’ll gain an understanding...