The output fields for the sample value and associated probability. The default is ["value", "density"].
Build the transformation
The vega dataflow instance
The vega-dataflow node that is the parent of this node
The chart-parts dataset
Required. An object describing the distribution type and parameters. See the distribution reference for more.
A [min, max] domain from which to sample the distribution. This argument is required in most cases, but can be omitted in the case of distributions (namely, kde) that can deduce their own extent.
The type of distribution to generate.
The number of uniformly spaced steps to take along the extent domain (default 100). A total of steps + 1 uniformly-spaced samples are drawn from the distribution.
The density transform generates a new data stream of uniformly-spaced samples drawn from a one-dimensional probability density function (pdf) or cumulative distribution function (cdf). This transform is useful for representing probability distributions and generating continuous distributions from discrete samples using kernel density estimation.