Jaime Fernández - The Future of NumPy Indexing.
2,443 views · Published 30 April 2016 · 39:42 · Indexed 31 October 2026
Channel: PyData · 2016 · Science & Technology
PyData Madrid 2016 Most of the talks and workshop tutorials can be found here: https://github.com/PyDataMadrid2016/Conference-Info Advanced (a.k.a. fancy) indexing is one of NumPy's greatest features. Once past the rather steep learning curve, it enables a very expressive and powerful syntax, and makes coding a wide range of complex operations a breeze. But this versatility comes with a dark side of surprising results for some seemingly simple cases, and conflicts with the design choices of more recent data analysis packages. This has led to a viewpoint with growing support among the community that fancy indexing may be too fancy for its own good. This talk will review the workings of advanced indexing, highlighting where it excels, and where it falls short, and give some context on the logic behind some design decisions. It will also cover the existing NumPy Enhancement Proposal (NEP) to "implement an intuitive and fully featured advanced indexing." 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
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