Better dataframes
Dataframes are an abstraction that proven extremely useful for data analysis in dynamic languages like S, R, Python, and Julia. The Pandas package has been dominant in Python for around 15 years but its design is now showing its age. There is now a vibrant and messy ecosystem of potential disruptors to the status quo for data analysis tasks in Python.
This talk will help you make sense of the mess. It will give you a comprehensive review of the strengths and weaknesses of the challengers, including Polars, Ibis, Vaex, Modin, Dask, and the PySpark Pandas API (formerly known as Koalas). It will also review efforts to unify the PyData landscape such as Apache Arrow, the dataframe interchange protocol, Narwhals, and the Ibis project from the original author of Pandas, Wes McKinney.
See this talk and many more by getting your ticket to PyCon AU now!
I want a ticket!The talk will provide context and guidance for deciding which dataframe library to choose for your next project. It will also explain the best ways to offer cross-dataframe support in your library code.
