Facets

Creating multi-panel plots using `facets`.

Problem

You want to see more aspects of your data, and it's not practical to use the regular aesthetics approach for that.

Solution - `facets`

You can add one or more new dimensions to your plot using faceting.

This approach allows you to split up your data by one or more variables and plot the subsets of data together.

In this demo, we will explore how various faceting functions work, as well as the built-in sorting and formatting options.

To learn more about formatting templates, see: Formatting.

val dataset = DataFrame.readCSV(
    "https://raw.githubusercontent.com/JetBrains/lets-plot-kotlin/master/docs/examples/data/mpg2.csv",
    parserOptions = ParserOptions(Locale.ENGLISH)
)

dataset.head(3)

miles per gallon	number of cylinders	engine displacement \(cu. inches\)	engine horsepower	vehicle weight \(lbs.\)	time to accelerate \(sec.\)	model year	origin of car	vehicle name
18	8	307	130	3504	12	70	US	chevrolet chevelle malibu
15	8	350	165	3693	11.5	70	US	buick skylark 320
18	8	318	150	3436	11	70	US	plymouth satellite

One plot

Create a scatter plot to show how mpg is related to a car's engine horsepower.

Also use the color aesthetic to visualize the region where a car was designed.

dataset.plot {
    x(`engine horsepower`)
    y(`miles per gallon`)
    points {
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
        size = 800 to 350
    }
}

More dimensions

There are two functions for faceting:

facetGrid()
facetWrap()

The former creates 2-D matrix of plot panels, and the latter creates 1-D strip of plot panels.

We'll be using the number of cylinders variable as the first faceting variable, and sometimes the origin of car as a second faceting variable.

facetGrid()

The data can be split up by one or two variables that vary in the X and/or Y direction.

Let's split up the data by number of cylinders.

dataset.plot {
    points {
        x(`engine horsepower`)
        y(`miles per gallon`)
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
    }
    facetGridX(`number of cylinders`)
}

Split up the data by two faceting variables: number of cylinders and origin of car.

dataset.plot {
    points {
        x(`engine horsepower`)
        y(`miles per gallon`)
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
    }
    facetGrid(`number of cylinders`, `origin of car`)
}

Formatting and sorting.

Apply a formatting template to the number of cylinders and sort the origin of car values in descending order.

To learn more about formatting templates, see: Formatting.

dataset.plot {
    points {
        x(`engine horsepower`)
        y(`miles per gallon`)
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
    }
    facetGrid(`number of cylinders`, `origin of car`, xFormat = "{d} cyl", yOrder = OrderDirection.DESCENDING)
}

facetWrap()

The data can be split up by one or more variables. The panel layout is flexible and controlled by ncol, nrow and dir options.

Split data by the number of cylinders variable and arrange tiles in two rows.

dataset.plot {
    points {
        x(`engine horsepower`)
        y(`miles per gallon`)
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
    }
    facetWrap(nRow = 2) {
        facet(`number of cylinders`)
    }
}

Split data by origin of car and number of cylinders and arrange tiles in five columns.

dataset.plot {
    points {
        x(`engine horsepower`)
        y(`miles per gallon`)
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
    }
    facetWrap(nCol = 5) {
        facet(`origin of car`)
        facet(`number of cylinders`)
    }
}

Arrange panels vertically.

Use the dir parameter to arrange tiles by columns, in three columns (the default tile arrangement is "by row").

Also, format number of cylinders labels and reverse the sorting direction for this faceting variable.

dataset.plot {
    points {
        x(`engine horsepower`)
        y(`miles per gallon`)
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
    }
    facetWrap(nCol = 3, direction = Direction.VERTICAL) {
        facet(`origin of car`, OrderDirection.ASCENDING, null)
        facet(`number of cylinders`, OrderDirection.DESCENDING, "{} cyl")
    }
}

Free scales on faceted plot

dataset.plot {
    x(`engine horsepower`)
    y("engine displacement (cu. inches)"<Double>())
    points {
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
        size = 800 to 350
    }
}

Faceted plot

`facetGrid()` with `fixed` scales (the default)

Scales are constant across all panels.

dataset.plot {
    x(`engine horsepower`)
    y("engine displacement (cu. inches)"<Double>())
    points {
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
        size = 800 to 500
    }
    facetGridY(`origin of car`)
}

`facetGrid()` with `free` Y-scales

dataset.plot {
    x(`engine horsepower`)
    y("engine displacement (cu. inches)"<Double>())
    points {
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
        size = 800 to 500
    }
    facetGridY(`origin of car`, scalesSharing = ScalesSharing.FREE_Y)
}

`facetWrap()` with `fixed` scales (the default)

Scales are constant across all panels.

dataset.plot {
    x(`engine horsepower`)
    y("engine displacement (cu. inches)"<Double>())
    points {
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
        size = 800 to 500
    }
    facetWrap {
        facet(`number of cylinders`, order = OrderDirection.ASCENDING)
    }
}

`facetWrap()` with `free` scales along both axes

dataset.plot {
    x(`engine horsepower`)
    y("engine displacement (cu. inches)"<Double>())
    points {
        color(`origin of car`)
    }
    layout {
        style(Style.Grey)
        size = 800 to 500
    }
    facetWrap(scalesSharing = ScalesSharing.FREE) {
        facet(`number of cylinders`, order = OrderDirection.ASCENDING)
    }
}

Last modified: 05 February 2024

kandy 0.8.0-RC1 Help

Creating multi-panel plots using `facets`.

Problem

Solution - `facets`

One plot

More dimensions

facetGrid()

One facet

Two facets

Formatting and sorting.

facetWrap()

Facet Wrap One Column

Facet Wrap Two Columns

Arrange panels vertically.

Free scales on faceted plot

Faceted plot

`facetGrid()` with `fixed` scales (the default)

`facetGrid()` with `free` Y-scales

`facetWrap()` with `fixed` scales (the default)

`facetWrap()` with `free` scales along both axes

Facets

Creating multi-panel plots using facets.

Problem

Solution - facets

One plot

More dimensions

facetGrid()

One facet

Two facets

Formatting and sorting.

facetWrap()

Facet Wrap One Column

Facet Wrap Two Columns

Arrange panels vertically.

Free scales on faceted plot

Faceted plot

facetGrid() with fixed scales (the default)

facetGrid() with free Y-scales

facetWrap() with fixed scales (the default)

facetWrap() with free scales along both axes

Creating multi-panel plots using `facets`.

Solution - `facets`

`facetGrid()` with `fixed` scales (the default)

`facetGrid()` with `free` Y-scales

`facetWrap()` with `fixed` scales (the default)

`facetWrap()` with `free` scales along both axes