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This conference talk from PyCon US explores the transition of Pandas from using NumPy as its back-end storage to adopting PyArrow. Discover what Arrow and PyArrow are, how they currently impact Pandas users, and what changes to expect in the future. Learn when PyArrow offers performance advantages over the traditional Pandas backend and when it's most appropriate to implement in your data analysis workflows. In this 32-minute presentation, get introduced to PyArrow's capabilities and practical applications for enhancing your Pandas-based data processing.
