Simon Byrne - Julia for Data Analysis features, interfaces and future directions
1,891 views · Published 11 May 2016 · 43:25 · Indexed 18 October 2026
Channel: PyData · 2016 · Science & Technology
PyData London 2016 This will showcase the data analysis features of Julia, a new high-performance, dynamic language for technical computing. We will give an overview of the various data, statistics and graphics libraries, interfaces with Python and R, as well as outline future directions for this new and exciting language. Julia has a rapidly developing ecosystem of packages for data analysis. This talk will give an introduction to some of these, such as Distributions.jl, DataFrames.jl and Gadfly.jl. We will also demonstrate how to leverage existing libraries in Python and R, via the PyCall.jl and RCall.jl packages. Finally, we will describe the future plans, funded by a Moore Foundation grant. Slides available here: https://gist.github.com/simonbyrne/53b3bd29d2f347fc4f6539cf7d2442e1 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