I’m happy to announce the release of Dash HoloViews. This collaboration between the HoloViews and Dash projects makes it possible to build certain classes of interactive Dash applications without the need to manually define any callbacks
Two particularly powerful use cases are the ability to automatically link selections across multiple plots (also known as crossfiltering) and to display large datasets using Datashader. Both of these use cases can be implemented on top of pandas, Dask, or GPU accelerated cuDF DataFrames.
This functionality with released today with
To learn more, check out the blog post…
the new Dash HoloViews documentation…
and register for the December 18th webinar
Many thanks to the RAPIDS project for funding this work!
I just love this integration. I’m so happy to see datashader, crossfiltering, & aggregations become more accessible. These apps were possible to write before with callbacks (https://dash.plotly.com/interactive-graphing) but it was more or less boilerplate (and quite a bit of it, too!). So many of our Dash Enterprise customers & community members wrote callbacks for crossfiltered graphs that were more or less the same and so it’s a great relief to standardize this use case
Looking forward to see what everyone makes!
Thanks a lot to the team - both at Plotly as well as Datashader / Holoviews for making this happen.
Having read the examples on the page -
there is one thing I wanted some clarity on…the last section - “Mapbox datashader and linked selections” doesn’t have the code for ‘linked_selection’ or the creation of the histogram plot. Can this be rectified please?