napari is a “a fast, interactive viewer for multi-dimensional [arrays] in Python” It is widely used in bioimaging, where performance of data visualization is critical. In a cross domain collaboration napari user’s have long wanted to use Xarray more. In fact allowing napari to fully utilize the metadata from Xarray objects is one of the longest desired features in napari.
Similarly current Xarray user’s may be able to benefit by using napari’s powerful visualization capabilities. If you are interested in learning more about napari for your pangeo uses please let me know! Or even grab some time with me here: Getting Help — Xarray for Biology
To this end the Xarray team and the napari team worked together at the SciPy 2025 sprints on a plan to better integrate these two powerful tools! You can read it on the Xarray blog.
If you are napari user who wants to use Xarray, or an Xarray user who wants to use napari, or any other combination we’re really interested in hearing your feedback. Please come introduce yourself on github ( 
Introductions · Issue #8 · napari/napari-xarray · GitHub ) or on Zulip ( Public view of napari | Zulip team chat )
Excited for the future and to hear what you think about this plan.
The team in action!
From left to right: @TimMonko @psobolewskiPhD @gnodar @ianhi @bcimini @willingc