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As a data scientist or developer, I want to build an application where a visualization's "height", "radius", or "color" is encoded directly into the source data as a property - for example, `"height": 2001. This matters because I can create buildings that are the exact correct height in a 3D extrusion visualization.
@ryanbaumann Would this be similar to setting height_function_type='match' and specifying the height_property='height'? It's a little clumsy, but just wanted to check if that's the same behavior you're looking for. I like your idea of including height_function_type='identity'. Then we can have the viz automatically specify the height property without the user having to edit two arguments.
@akacarlyann instead of using a height_function_type that was match, we want to create a Mapbox GL expression under the hood that sets the value from the data column directly equal to the value used in the map. The identity keyword would indicate to pass ['get', 'myColumnName]` as the expression to the layer created by the Python Viz function.
Problem
As a data scientist or developer, I want to build an application where a visualization's "height", "radius", or "color" is encoded directly into the source data as a property - for example, `"height": 2001. This matters because I can create buildings that are the exact correct height in a 3D extrusion visualization.
Solution
Add
identity
function tomapboxgl-jupyter/mapboxgl/viz.py
Line 589 in 6e95434
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