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Fernando Perez
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Research areas in the Paul Allen Library at UW Seattle
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This week, +Kester Tong and I gave a talk at #SciPy201  about PNaCl, Python, scientific Python, why we'd want to do this, and the amazing work on coLaboratory that he, +Kayur Patel and their team have worked on with +Fernando Perez , +Brian Granger , +Min RK and the rest of the IPython team.  I was pretty happy with the talk, and pretty excited about the possibilities, but more than anything else, I'm honored to have worked with such an amazing group of people -- both the ones I've named here, and the +Portable Native Client (PNaCl) team, especially the ever-patient +Sam Clegg.

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Over the last year I've worked with some awesome folks (+Kester Tong  +Mark Sandler, +Corinna Cortes , +Matthew Turk,  +Gideon Mann  +Arnaud Sahuguet, +Adam Berenzweig) to understand how people collaborate on data analysis and to build better tools to support them. Yesterday, with the help of +Fernando Perez and +Wes McKinney we revealed this work at PyCon APAC.

We've created an interactive, collaborative analytics tool by integrating Google Docs, Chrome, and IPython. You can open a notebook from Drive. You can share notebooks like you would share a Google Doc. You can comment and edit collaboratively, in realtime. There is zero setup, because all the computation happens in Chrome. You can even quickly and easily package your analytics pipeline into a GUI for folks that don't want to program. In effect, you can go from zero to analytics with little impedance.  

What's even better is that you can build on our work. It will all be open source on top of public Google APIs. We'll have a larger Google Research blog post about this work when we release the code and the Chrome application.
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Implementing Reproducible Research by +Victoria Stodden Friedrich Leisch and Roger D. Peng has been released.  All chapters are CC BY 3.0 and available from +Open Science.  https://osf.io/s9tya/wiki/home/  Definitely recommended reading.

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Climbing with Brian Forst and friends at Allez Up after PyCon 2014. Awesome gym. 
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4/13/14
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stem-and-leaf plots using numpy in 140 characters: stem() expects an array or list of integers, and prints all stems that span the range of the data provided.

from _future_ import print_function
import numpy as np
def stem(d):
    "A stem-and-leaf plot that fits in a tweet by @ivanov"
    l,t=np.sort(d),10
    O=range(l[0]-l[0]%t,l[-1]+11,t)
    I=np.searchsorted(l,O)
    for e,a,f in zip(I,I[1:],O): print('%3d|'%(f/t),*(l[e:a]-f),sep='')

http://pirsquared.org/blog/stem-tweet.html

#python  
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IPython notebook General Exam
#ipython
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IPython dev meeting starting soon.

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Python and IPython will have a strong presence at the upcoming Strata'2014 conference. This blog post by +Brian Granger summarizes the landscape.

Brian and I will be teaching a tutorial about IPython together as well as holding "office hours", and then Brian will give a talk at the conference about our new interactive widget framework.

Note that with the "IPY20" registration code, you can get a 20% discount for the conference and tutorials.
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