Lonboard Effortlessly Renders 3 Million Points in Jupyther
Python library Lonboard promises super fast visualisation of huge geospatial datasets in Jupyter notebooks. The demo renders over three million data points in under three seconds; a load that brings other libraries to their knees.
We’re sharing lonboard, a new python library, to fill this need. On a dataset with 3 million points, ipyleaflet crashed after 3.5 minutes, pydeck crashed after 2.5 minutes, but lonboard successfully rendered in 2.5 seconds.
Impressive speed, all without clustering or downscaling the data. Lonboard renderes exactly the amount of features that it finds in the data set. How is this possible you ask? Lonboard employs efficient binary data encodings, as opposed to more traditional text-based formats like GeoJSON: