I would like to obtain a column with the denisity of the points using a kernel density function.
In 1 D, it will be something like histograms:
https://en.wikipedia.org/wiki/Kernel_density_estimation
Densities can be visualized in the graph builder, and calculated for 1 dimensional data. But I wonder how to do that systematically for multivariate data (more than one dimmension).
In statistics, kernel density estimation ( KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on as weights. KDE answers a fundamental data smoothing problem where ...
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