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The loess transform (for locally-estimated scatterplot smoothing) uses locally-estimated regression to produce a trend line. Loess performs a sequence of local weighted regressions over a sliding window of nearest-neighbor points. For standard parametric regression options, see the regression transform.

// Any View Specification
  "transform": [
    {"loess": ...} // Loess Transform

Loess Transform Definition

Property Type Description
loess String

Required. The data field of the dependent variable to smooth.

on String

Required. The data field of the independent variable to use a predictor.

groupby String[]

The data fields to group by. If not specified, a single group containing all data objects will be used.

bandwidth Number

A bandwidth parameter in the range [0, 1] that determines the amount of smoothing.

Default value: 0.3

as String[]

The output field names for the smoothed points generated by the loess transform.

Default value: The field names of the input x and y values.


{"loess": "y", "on": "x", "bandwidth": 0.5}

Generate a loess trend line that models field "y" as a function of "x", using a bandwidth parameter of 0.5. The output data stream can then be visualized with a line mark, and takes the form:

  {"x": 1, "y": 2.3},
  {"x": 2, "y": 2.9},
  {"x": 3, "y": 2.7},

If the groupby parameter is provided, separate trend lines will be fit per-group, and the output records will additionally include all groupby field values.