Juan Luis Cano Rodríguez - Expressive & fast dataframes in Python with polars | PyData Global 2022

The pandas library is one of the key factors that enabled the growth of Python in the Data Science industry and continues to help data scientists thrive almost 15 years after its creation. Because of this success, nowadays several open-source projects claim to improve pandas in various ways, either by bringing it to a distributed computing setting (Dask), accelerating its performance with minimal changes (Modin), or offering slightly different API that solves some of its shortcomings (Polars).

In this talk we will dive into Polars, a new dataframe library backed by Arrow and Rust that offers an expressive API for dataframe manipulation with excellent performance.

If you are a seasoned pandas user willing to explore alternatives, or a beginner user wondering what all the fuzz about these new dataframe libraries is, this talk is for you!

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