We are pleased to announce the fourth public release of HoloViews,
a Python package for simplifying the exploration of scientific data:
HoloViews provides composable, sliceable, declarative data
structures for building even complex visualizations easily.
The goal of HoloViews is to let your data just visualize itself,
allowing you to work with large datasets as easily as you work
with simple datatypes at the Python prompt.
You can obtain the new version using conda or pip:
conda install -c ioam holoviews
pip install --upgrade 'holoviews[recommended]'
This release includes a substantial number of new features and
API improvements, most of which have been suggested by our growing
- Major optimizations throughout, both for working with HoloViews
data structures and for visualization.
- Improved widget appearance and greatly reduced flickering
issues when interactively exploring data in the browser.
- Improved handling of unicode and LaTeX text throughout,
using Python 3's better unicode support (when available).
- New Polygons, ErrorBars, and Spread Element types.
- Support for multiple matplotlib backends (vanilla matplotlib, mpld3
and nbagg) with support for other plotting systems (such as Bokeh)
in development. Easily switching between backends allows you to take
advantage of the unique features of each one, such as good SVG/PDF
output, interactive zooming and panning, or 3D viewpoint control.
- Streamlined the API based on user feedback; now even more things
"just work". This includes new, easy to use constructors for
common Element types as well as easy conversion between them.
- More customizability of plot and style options, including easier
control over font sizes, legend positions, background color, and
multiple color bars. Polar projections now supported throughout.
- More flexible and customizable Layouts, allowing the user to
define blank spaces (using the Empty object) as well as more
control over positioning and aspect ratios.
- Support for a holoviews.rc file, integration with IPython Notebook
interact widgets, improvements to the Pandas interface, easy
saving and loading of data via pickling, and much more.
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:
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, and check out our upcoming SciPy and EuroSciPy
talks in Austin and Cambridge (or read the paper at http://goo.gl/NH9FTB)!
Jean-Luc R. Stevens
James A. Bednar
The University of Edinburgh
School of Informatics
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.