Jupyter environments offer unique opportunities for two-way data interaction, sharing data between the Python backend and visualization in deck.gl.
- Data updates. By calling
pydeck.bindings.deck.Deckobject with a new visualization configuration, you can seamless push new data into a pre-existing visualization.
- Binary data transfer. For certain data sets pydeck can support many millions of points by using Jupyter’s socket-level communication. Further documentation is here.
- Data selection. Data can be selected within a pydeck visualization and pushed back to the client. Holding Command while clicking allows the user to select multiple points.
Interactive examples for these features are available on mybinder.org. Click the Binder logo below: