HoloViews Tutorials

The HoloViews tutorials are the best way to learn what HoloViews can do and how to use it. The web site has static copies of each tutorial, but you may also try out live copies on mybinder.org where you can also explore many other examples in our contrib repository . Lastly, for the most responsive experience, you can install HoloViews and try out the tutorial notebooks for yourself.

Introductory Tutorials

These explanatory tutorials are meant to be viewed and worked through in this order:

  • Showcase: Brief demonstration of what HoloViews can do for you and your data.
  • Introduction: How to use HoloViews – basic concepts and getting started.
  • Exploring Data: How to use HoloViews containers to flexibly hold all your data ready for selecting, sampling, slicing, viewing, combining, and animating.
  • Sampling Data: How to select data in multiple dimensions, returning a specific (potentially lower dimensional) region of the available space.
  • Columnar Data: How to work with table-like data, including options for storing the data, and how to apply operations to transform the data into complex visualizations easily.
  • Dynamic Map: How to work with datasets larger than the available memory by computing elements on-the-fly. Using DynamicMap you can immediately begin exploring huge volumes of data while keeping interaction responsive and without running out of memory.

Supplementary Tutorials

There are additional tutorials detailing other features of HoloViews:

  • Options: Listing and changing the many options that control how HoloViews visualizes your objects, from Python or IPython.
  • Exporting: How to save HoloViews output for use in reports and publications, as part of a reproducible yet interactive scientific workflow.
  • Continuous Coordinates: How to use continuous coordinates to work with real-world data or smooth functions.
  • Composing Data: Complete example of the full range of hierarchical, multidimensional discrete and continuous data structures supported by HoloViews.
  • Bokeh Backend: Additional interactivity available via the Bokeh backend, such as interactive zooming, panning, and selection linked automatically between plots.
  • Pandas Conversion: Using the DFrame conversion wrapper of HoloViews to convert pandas dataframes into HoloViews components.
  • Pandas and Seaborn: Specialized visualizations provided by pandas and seaborn.

Reference Notebooks

At any point, you can look through these comprehensive but less explanatory overview tutorials. For each of the HoloViews components available, these tutorials show how to create it, how the objects are plotted by default, and show how to list and change all of the visualization options for that object type:

  • Elements: Overview and examples of all HoloViews element types, the atomic items that can be combined together, available for either the Matplotlib or Bokeh plotting library backends.
  • Containers: Overview and examples of all the HoloViews container types.

For more detailed (but less readable!) information on any component described in these tutorials, please refer to the Reference Manual . For further notebooks demonstrating how to extend HoloViews and apply it to real world data see the Examples page.