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Li Jin - Improving Pandas and PySpark performance and interoperability with Apache Arrow
SF Big Analytics: Next-generation Python Big Data Tooling, powered by Apache Arrow
Will Ayd & Matt Topol - Practical Applications of Apache Arrow | PyData Virginia 2025
How Apache Arrow Made Spark Faster: A 10-Year Journey
Apache Arrow and Substrait, the secret foundations of Data Engineering — Alessandro Molina
How to install Apache Arrow for zero-copy analytics in Python - Detailed Guide
Panagiotis Moustafellos: Query like a Pro: ES|QL meets Apache Arrow and Pandas
An Introduction to Arrow for Python Programmers
Extending Pandas using Apache Arrow and Numba - Uwe L Korn
Polyglot data with python: Introducing Pandas and Apache Arrow by Robson Junior
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Last Updated: October 15, 2026
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Speaker: Arthur Andres, Software Developer at Tradewell Technologies Machine learning (ML) and deep learning (DL) fields have made amazing progress in the past few years. Modern ML/DL ... PyData New York City 2017 Slides: ... For years, PySpark users faced a silent performance killer: the "Serialization Wall." While Spark was revolutionary for distributed ... EuroPython 2023 — North Hall on 2023-07-19] ... Unlock the power of zero-copy analytics with our detailed guide on installing PyCon Greece 2025 - Athens, 29-30 August Sponsored talk by Elastic == About the talk == In this talk, we'll dive into how ES|QL ... Speaker: Marlene Mhangami, Developer Advocate at Voltron PyData Berlin 2018 With the latest release of Pandas the ability to extend it with custom dtypes was introduced. Using
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