Jeffrey Tratner: Pandas Under The Hood: Peeking behind the scenes of a high performance data analys
4,677 views · Published 10 August 2015 · 41:08 · Indexed 10 November 2026
Channel: PyData · 2015 · Science & Technology
PyData Seattle 2015 This talk will give a broad, accessible overview of pandas’ internal structure and help explain how pandas works behind the scenes, including the libraries it relies on, its internal data structures (NDFrame, BlockManager, Index, etc), and how they all tie together to provide a flexible and performant API. I’ll also explore how you can use this background to build up a better intuition about how to use pandas effectively. Materials available here: Interactive slides: http://bit.ly/1M5ISBn PDF slides: http://bit.ly/1hkGJGu 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
More from this channel
-
31:23
Kostas Perifanos - Authorship Attribution Using Python
-
31:08
Prash Majmudar - Measuring the Digital Economy Using Big Data
-
36:26
Ian Ozsvald - The High Performance Python Landscape
-
37:48
Mike Muller - Shared Memory Parallelism with Python
-
35:01
Martin Goodson - Most Winning A/B Test Results are Illusory
-
30:19
Mark Basham - Python for High Throughput Science
-
1:13:42
David Cournapeau & Simon Jagoe - Narrowing the Gap Between Array Computing and Databases
-
31:38
Emlyn Clay - Phython, Pharmaceuticals & Discovery