[SciPy-User] ANN: Stop plotting your data -- HoloViews 1.4 released!

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[SciPy-User] ANN: Stop plotting your data -- HoloViews 1.4 released!

James A. Bednar
We are pleased to announce the fifth public release of HoloViews,
a Python package for exploring and visualizing numerical data:

   http://holoviews.org

HoloViews provides composable, sliceable, declarative data structures
for building even complex visualizations easily.  Instead of you
having to explicitly and laboriously plot your data, HoloViews lets
you simply annotate your data so that any part of it visualizes itself
automatically.  You can now work with large datasets as easily as
you work with simple datatypes at the Python prompt.

The new version can be installed using conda:

   conda install -c ioam holoviews

Release 1.4 introduces major new features, incorporating over 1700 new
commits and closing 142 issues:

- Now supports both Bokeh (bokeh.pydata.org) and matplotlib backends,
  with Bokeh providing extensive interactive features such as panning
  and zooming linked axes, and customizable callbacks

- DynamicMap: Allows exploring live streams from ongoing data
  collection or simulation, or parameter spaces too large to fit into
  your
  computer's or your browser's memory, from within a Jupyter notebook

- Columnar data support: Underlying data storage can now be in Pandas
  dataframes, NumPy arrays, or Python dictionaries, allowing you to
  define HoloViews objects without copying or reformatting your data

- New Element types: Area (area under or between curves),
  Spikes (sequence of lines, e.g. spectra, neural spikes, or rug
  plots),
  BoxWhisker (summary of a distribution), QuadMesh (nonuniform
  rasters),
  Trisurface (Delaunay-triangulated surface plots)

- New Container type: GridMatrix (grid of heterogenous Elements)

- Improved layout handling, with better support for varying aspect
  ratios and plot sizes

- Improved help system, including recursively listing and searching
  the help for all the components of a composite object

- Improved Jupyter/IPython notebook support, including improved
  export using nbconvert, and standalone HTML output that supports
  dynamic widgets even without a Python server

- Significant performance improvements for large or highly nested data

And of course we have fixed a number of bugs found by our very
dedicated users; please keep filing Github issues if you find any!

For the full list of changes, see:

   https://github.com/ioam/holoviews/releases

HoloViews is now supported by Continuum Analytics, and is being used
in a wide range of scientific and industrial projects.  HoloViews
remains freely available under a BSD license, is Python 2 and 3
compatible, and has minimal external dependencies, making it easy to
integrate into your workflow. Try out the extensive tutorials at
holoviews.org today!

Jean-Luc R. Stevens
Philipp Rudiger
James A. Bednar

Continuum Analytics, Inc., Austin, TX, USA
School of Informatics, The University of Edinburgh, UK

--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.

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