HoloViz is a set of compatible tools to make it easier to see and understand your data at every stage needed by users, research groups, and projects:
Why "Holo"? "holo-", from the Greek root "hólos", means "whole, entire, complete".
Sure! That's how it ended up with:
Because each tool is typically limited to one or two of the stages in the data life cycle, supporting some well but not the others:
To avoid having to abandon all your work on one stage to reach the next, HoloViz tools reduce friction and gaps between the stages:
Throughout the tutorial, you'll see these principles at work:
HoloViz currently covers this subset of viz tools
These tools are the most fully supported and are often entirely sufficient on their own.
To address the above issues, we have developed a set of open-source Python packages to streamline the process of working with small and large datasets (from a few datapoints to billions or more) in a web browser, whether doing exploratory analysis, making simple widget-based tools, or building full-featured dashboards. The main libraries in this ecosystem include:
Beyond the specific HoloViz tools, all these approaches work with and often rely upon a wide range of other open-source libraries for their implementation, including:
In this tutorial, we'll focus on an example set of data about earthquake events, using it to illustrate how to:
The tutorial is organized around the most general to the most specific, in terms of tool support. We first look at Panel package, which works with nearly any plotting library, then hvPlot, which works with nearly any data library and shares an API with many other plotting libraries, and then dive deeper into HoloViz-specific approaches that let you work with large data, provide deep interactivity, and other advanced features.
Before going further, it's worth exploring some examples of what you can get with HoloViz, to make sure that it covers your needs:
And then you can browse through the already-run versions of the HoloViz tutorials to see what they cover and how it all fits together. But everything on this website is a Jupyter Notebook that you can run yourself, once you follow the installation instructions, so the next step is then to try it all out and have fun exploring it!