[IPython-dev] ANN: HoloViews 1.0 released

[William Stein]

On Thu, Mar 19, 2015 at 10:35 AM, Jean-Luc Stevens <jlstevens at ed.ac.uk> wrote:
> We are pleased to announce the first public release of HoloViews, a
> Python package for scientific and engineering data visualization:
>
>     http://ioam.github.io/holoviews
>
> HoloViews provides composable, sliceable, declarative data structures
> for building even complex visualizations easily.

Nice.  I've added holoviews so it is available by default for all
projects on SageMathCloud (https://cloud.sagemath.com).  Here's an
example IPython notebook:

   https://cloud.sagemath.com/projects/4a5f0542-5873-4eed-a85c-a18c706e8bcd/files/support/2015-03-19-111401-holoviews.html

and Sage worksheet:

   https://cloud.sagemath.com/projects/4a5f0542-5873-4eed-a85c-a18c706e8bcd/files/support/2015-03-19-111407-holoviews.sagews

 -- William

>
> It's designed to exploit the rich ecosystem of scientific Python tools
> already available, using Numpy for data storage, matplotlib and mpld3
> as plotting backends, and integrating fully with IPython Notebook to
> make your data instantly visible.
>
> If you look at the website for just about any other visualization
> package, you'll see a long list of pretty pictures, each one of which
> has a page or two of code putting it together.  There are pretty
> pictures in HoloViews too, but there is *no* hidden code -- *all* of
> the steps needed to build a given figure are shown right before the
> HoloViews plot, with just a few lines needed for nearly all of our
> examples, even complex multi-figure subplots and animations.  This
> concise but flexible specification makes it practical to explore and
> analyze your data interactively, while leaving a full record for later
> reproducibility in the notebook.
>
> It may sound like magic, but it's not -- HoloViews simply lets you
> annotate your data with appropriate metadata, and then the data can
> display itself!  HoloViews provides a set of general, compositional,
> multidimensional data structures suitable for both discrete and
> continuous real-world data, and pairs them with separate customizable
> plotting classes to visualize them without extensive coding.  A
> large collection of continuously tested IPython Notebook tutorials
> accompanies HoloViews, showing you precisely the small number of steps
> required to generate any of the plots.
>
> Some of the most important features:
>
> - Freely available under a BSD license
> - Python 2 and 3 compatible
> - Minimal external dependencies -- easy to integrate into your workflow
> - Builds figures by slicing, sampling, and composing your data
> - Builds web-embeddable animations without any extra coding
> - Easily customizable without obscuring the underlying data objects
> - Includes interfaces to pandas and Seaborn
> - Winner of the 2015 UK Open Source Award
>
> For the rest, check out ioam.github.io/holoviews!
>
> Jean-Luc Stevens
> Philipp Rudiger
> James A. Bednar
>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
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-- 
William (http://wstein.org)
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