High Performance Data Processing in Python - Donald Whyte

PyData Warsaw 2018 numpy and numba are popular Python libraries for processing large quantities of data. This talk explains how numpy/numba work under the hood and how they use vectorisation to process large amounts of data extremely quickly. We use these tools to reduce the processing time of a large, real 600GB dataset from one month to 40 minutes, even when the code is run on a single Macbook Pro. === www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 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/YouTubeVi...