Support for maintainable, reproducible research

  • Supports a truly reproducible workflow by minimizing the code needed for analysis and visualization.
  • Already used in a variety of research projects, from conception to final publication.
  • All HoloViews objects can be pickled and unpickled.
  • Provides comparison utilities for testing, so you know when your results have changed and why.
  • Core data structures only depend on the numpy and param libraries.
  • Provides export and archival facilities for keeping track of your work throughout the lifetime of a project.

Analysis and data access features

  • Allows you to annotate your data with dimensions, units, labels and data ranges.
  • Easily slice and access regions of your data, no matter how high the dimensionality.
  • Apply any suitable function to collapse your data or reduce dimensionality.
  • Helpful textual representation to inform you how every level of your data may be accessed.
  • Includes small library of common operations for any scientific or engineering data.
  • Highly extensible: add new operations to easily apply the data transformations you need.

Visualization features

  • Useful default settings make it easy to inspect data, with minimal code.
  • Powerful normalization system to make understanding your data across plots easy.
  • Build complex animations or interactive visualizations in seconds instead of hours or days.
  • Refine the visualization of your data interactively and incrementally.
  • Separation of concerns: all visualization settings are kept separate from your data objects.
  • Support for fully interactive plots using the Bokeh backend .

Jupyter Notebook support

  • Support for all recent releases of IPython and Jupyter Notebooks.
  • Automatic tab-completion everywhere.
  • Exportable sliders and scrubber widgets.
  • Custom interactivity using streams and notebook comms to dynamically updating plots.
  • Automatic display of animated formats in the notebook or for export, including gif, webm, and mp4.
  • Useful IPython magics for configuring global display options and for customizing objects.
  • Automatic archival and export of notebooks , including extracting figures as SVG, generating a static HTML copy of your results for reference, and storing your optional metadata like version control information.