<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>pandas on DataScience.LA</title><link>https://datasciencela.github.io/tag/pandas/</link><description>Recent content in pandas on DataScience.LA</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>DataScience.LA, 2014–2021 · Read-only archive: comments are closed.</copyright><lastBuildDate>Fri, 27 Feb 2015 11:47:50 -0800</lastBuildDate><atom:link href="https://datasciencela.github.io/tag/pandas/index.xml" rel="self" type="application/rss+xml"/><item><title>PyDSLA - Blaze: Connecting analysts to big computation</title><link>https://datasciencela.github.io/pydsla-blaze-connecting-analysts-to-big-computation/</link><pubDate>Sat, 07 Feb 2015 15:35:01 -0800</pubDate><guid>https://datasciencela.github.io/pydsla-blaze-connecting-analysts-to-big-computation/</guid><description>&lt;p&gt;Join PyDSLA for a talk by Matthew Rocklin about the high level APIs being developed for Python for expressive data manipulation and analysis.&lt;/p&gt;&#10;&lt;p&gt;&lt;strong&gt;Summary:&lt;/strong&gt;&lt;/p&gt;&#10;&lt;p&gt;Pandas and NumPy serve us well.  They give interactive high-level access to efficient low-level code.  As datasets grow larger than memory this low-level code becomes obsolete but the high-level interface remains valuable.  Blaze connects that high-level interface to a number of other computational systems like SQL, Mongo, or Spark, extending the scope of interactive analysis.  In this talk we go over common use cases and Blaze as well as a bit of its internal design.&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/pydsla-blaze-connecting-analysts-to-big-computation/feature.png"/></item><item><title>dplyr and a very basic benchmark</title><link>https://datasciencela.github.io/dplyr-and-a-very-basic-benchmark/</link><pubDate>Wed, 03 Dec 2014 09:35:05 -0800</pubDate><guid>https://datasciencela.github.io/dplyr-and-a-very-basic-benchmark/</guid><description>&lt;p&gt;Earlier this month I gave a short talk about dplyr at the Los Angeles R meetup. It was one of the 5 talks about the useR! 2014 conference, and you can see the summaries and slides from the other 4 talks &lt;a href="https://datasciencela.github.io/la-r-meetup-summary-highlights-from-user-2014-part-2/"&gt;here&lt;/a&gt;.&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/dplyr-and-a-very-basic-benchmark/feature.jpg"/></item><item><title>Python Data Science Meetup Summary: Data Science with Python</title><link>https://datasciencela.github.io/python-data-science-meetup-summary-data-science-with-python/</link><pubDate>Mon, 10 Nov 2014 10:02:46 -0800</pubDate><guid>https://datasciencela.github.io/python-data-science-meetup-summary-data-science-with-python/</guid><description>&lt;p&gt;Last week, the Python Data Science LA meetup debuted with a fabulous event. It was already much anticipated, with more than 250 people showing interest (RSVP+waiting list), and a lucky 100 converged upon the hip Venice Arts venue to hear our speakers. Our sponsor &lt;a href="http://www.openmail.com/"&gt;OpenMail&lt;/a&gt; has also done a fantastic job in getting us this venue, bringing food+drinks and taking care of all the details. Thanks OpenMail Team!&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/python-data-science-meetup-summary-data-science-with-python/feature.png"/></item><item><title>Python Data Science Meetup: Data Science with Python</title><link>https://datasciencela.github.io/python-data-science-meetup-data-science-with-python/</link><pubDate>Wed, 08 Oct 2014 09:37:41 -0700</pubDate><guid>https://datasciencela.github.io/python-data-science-meetup-data-science-with-python/</guid><description>&lt;p&gt;I&amp;rsquo;m pleased to announce the first event of our &lt;a href="https://datasciencela.github.io/announcing-the-new-pydata-la-meetup-group/"&gt;new Python Data Science LA&lt;/a&gt; meetup, started by two of us here at &lt;a href="https://datasciencela.github.io/"&gt;DataScience.LA&lt;/a&gt; (our very own &lt;a href="https://datasciencela.github.io/team/#szilard"&gt;Szilard&lt;/a&gt; and &lt;a href="https://datasciencela.github.io/team/#earino"&gt;Eduardo&lt;/a&gt;).&lt;/p&gt;&#10;&lt;p&gt;We&amp;rsquo;ll have 5 speakers at this event, covering various aspects of the Python Data Science ecosystem (NumPy, SciPy, pandas, matplotlib, scikit-learn, NetworkX, NLTK, IPython notebook, etc.)&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/python-data-science-meetup-data-science-with-python/feature.jpg"/></item></channel></rss>