These geoms add reference lines (sometimes called rules) to a plot, either horizontal, vertical, or diagonal (specified by slope and intercept). These are useful for annotating plots.

 "mapping" = null,
 "data" = null,
 "na.rm" = false,
 "show.legend" = NA

 "mapping" = null,
 "data" = null,
 "na.rm" = false,
 "show.legend" = NA

 "mapping" = null,
 "data" = null,
 "na.rm" = false,
 "show.legend" = NA



Set of aesthetic mappings created by aes() or aes_().


The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to cxplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).


Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.


If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.


logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

xintercept, yintercept, slope, intercept

Parameters that control the position of the line. If these are set, data, mapping and show.legend are overridden.


These geoms act slightly differently from other geoms. You can supply the parameters in two ways: either as arguments to the layer function, or via aesthetics. If you use arguments, e.g. geom_abline(intercept = 0, slope = 1), then behind the scenes the geom makes a new data frame containing just the data you've supplied. That means that the lines will be the same in all facets; if you want them to vary across facets, construct the data frame yourself and use aesthetics.

Unlike most other geoms, these geoms do not inherit aesthetics from the plot default, because they do not understand x and y aesthetics which are commonly set in the plot. They also do not affect the x and y scales.


These geoms are drawn using with geom_line() so support the same aesthetics: alpha, color, linetype and size. They also each have aesthetics that control the position of the line:

geom_vline(): xintercept

geom_hline(): yintercept

geom_abline(): slope and intercept


// Fixed values
var cxp = new cxplot("canvas1", mtcars, aes("wt", "mpg"));
cxp.geom_vline({"xintercept": 5})
var cxp = new cxplot("canvas2", mtcars, aes("wt", "mpg")); cxp.geom_point(); cxp.geom_vline({"xintercept": [1, 2, 3, 4, 5]})
var cxp = new cxplot("canvas3", mtcars, aes("wt", "mpg")); cxp.geom_point(); cxp.geom_hline({"yintercept": 20})
// Calculate slope and intercept of line of best fit using your own function // (Intercept) wt // 37.285126 -5.344472 var cxp = new cxplot("canvas4", mtcars, aes("wt", "mpg")); cxp.geom_point(); cxp.geom_abline({"intercept": 37, "slope": -5})
// To show different lines in different facets, use aesthetics var mean_wt = [["cyl", "wt"], [4, 2.28], [6, 3.11], [8, 4]]; var cxp = new cxplot("canvas5", mtcars, aes({"x": "mpg", "y": "wt"})); cxp.geom_point(); cxp.geom_hline(aes({"yintercept": "wt"}, mean_wt)); cxp.facet_wrap("cyl");
// You can also control other aesthetics var mean_wt = [["cyl", "wt"], [4, 2.28], [6, 3.11], [8, 4]]; var cxp = new cxplot("canvas6", mtcars, aes({"x": "mpg", "y": "wt"})); cxp.geom_point(); cxp.geom_hline(aes({"yintercept": "wt", "color": "wt"}, mean_wt)); cxp.facet_wrap("cyl");