Facets
Edit pageLast modified: 05 February 2024Creating 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.
One facet
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`)
}
Two facets
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.
Facet Wrap One Column
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`)
}
}
Facet Wrap Two Columns
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)
}
}