Macro for regression / loess

[davidanthoff]

One thing that folks seem to use a lot with ggplot is to add a regression line to a plot with something like geom_smooth(method = "lm", se = FALSE). Would be great if there was a way to do something like that in vega-lite as well.

[g3o2]

Check this issue in vega

As of now, you have two choices in vega-lite:

1. use a calculate transform to generate the line based on the model formula fitted outside of the vega ecosystem,
2. directly provide the relevant points as data, the model still being fitted outside of vegalite.

[davidanthoff]

I think it would be great if this could be done in pure vega-lite. Yes, i can run the regression outside of vega-lite, but that is way more cumbersome than what you get with ggplot. Also, imagine a situation where this is combined with interactivity, and then one would have to precompute potentially a lot of stuff outside of the plot.

[domoritz]

I agree that this would be a nice feature for Vega-Lite. Maybe the best way to implement this is with a custom mark type.

[jacoduplessis]

Vega now has a regression transform: https://vega.github.io/vega/docs/transforms/regression/

Can't wait to see this in Vega-Lite!

[domoritz]

It's coming in Vega-Lite 4.

@kanitw we can close this issue, right?

[kanitw]

The question is do we want to provide a macro for this in Vega-Lite?

A few options to consider with some examples to begin conversation:

A) Inline Regression Transform

For example, I can see layer_point_line_regression have the following shorter form:

{
  "$schema": "https://vega.github.io/schema/vega-lite/v3.json",
  "data": {
    "url": "data/movies.json"
  },
  "layer": [
    {
      "mark": {
        "type": "point",
        "filled": true
      },
      "encoding": {
        "x": {
          "field": "Rotten_Tomatoes_Rating",
          "type": "quantitative"
        },
        "y": {
          "field": "IMDB_Rating",
          "type": "quantitative"
        }
      }
    },
    {
      "mark": {
        "type": "line",
        "color": "firebrick"
      },
      "encoding": {
        "x": {
          "field": "Rotten_Tomatoes_Rating",
          "type": "quantitative"
        },
        "y": {
          // if the regression property is with y, it's on x and vice-versa.  
          // other non groupby field can be used as x-y
          "regression/loess": true | {method: 'linear' | ..., order: ..., extent: ..., }
          "field": "IMDB_Rating",
          "type": "quantitative"
        }
      }
    }
  ]
}

This is clearly more concise that the full-form that we currently support and consistently with aggregation / timeUnit that have a short form in encoding. That said, one danger of this approach is that regression may not support clean combination with aggregate. (It's unclear what we should do if both aggregation and regression are specified.

B) Composite Mark

This would be another option, which would work well for supporting regression line in polestar.

{
  "$schema": "https://vega.github.io/schema/vega-lite/v3.json",
  "data": {
    "url": "data/movies.json"
  },
  "mark": {
    "type": "point",
    "filled": true,
    "loess/regression": true | {
       "mark": "line" // this should be implicit by default
       "type": "linear" // default
       "on": "x": // default  (on: "y" would be a transpose of this)
    }
  },
    "encoding": {
      "x": {
        "field": "Rotten_Tomatoes_Rating",
        "type": "quantitative"
      },
      "y": {
        "field": "IMDB_Rating",
        "type": "quantitative"
      }
    }
}