We are pleased to announce the fourth public release of HoloViews, a Python package for simplifying the exploration of scientific data:
http://holoviews.org 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 userbase: - 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: https://github.com/ioam/holoviews/releases 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)! Philipp Rudiger 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. ------------------------------------------------------------------------------ Don't Limit Your Business. Reach for the Cloud. GigeNET's Cloud Solutions provide you with the tools and support that you need to offload your IT needs and focus on growing your business. Configured For All Businesses. Start Your Cloud Today. https://www.gigenetcloud.com/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
