geom
Parameters
The data to be displayed in this layer. If null, the default, the data is inherited from the plot data as specified in the call to letsPlot.
The statistical transformation to use on the data for this layer. Supported transformations: Stat.identity, Stat.bin(), Stat.count(), etc. see Stat.
default = positionJitter(). Position adjustment: positionIdentity, positionStack(), positionDodge(), etc. see Position.
default = true. false - do not show legend for this layer.
String or result of the call to the layerKey() function. The key to show in the manual legend. Specifies the text for the legend label or advanced settings using the layerKey() function.
Result of the call to the samplingXxx() function. To prevent any sampling for this layer pass value samplingNone. For more info see sampling.html.
Result of the call to the layerTooltips() function. Specifies appearance, style and content.
A random seed to make the jitter reproducible. If null (the default value), the seed is initialised with a random value.
Width for jitter, default = 0.4. Typically ranges between 0 and 0.5. Values that are greater than 0.5 lead to overlapping of the points.
Height for jitter, default = 0.4. Typically ranges between 0 and 0.5. Values that are greater than 0.5 lead to overlapping of the points.
X-axis value.
Y-axis value.
Transparency level of points. Understands numbers between 0 and 1.
Color of the geometry. For more info see: aesthetics.html#color-and-fill.
Color to paint shape's inner points. Is applied only to the shapes having inner points. For more info see: aesthetics.html#color-and-fill.
Shape of the point. For more info see: aesthetics.html#point-shapes.
Size of the point.
Width of the shape border. Applied only to the shapes having border.
Rotation angle of the shape, in degrees.
default = "color" ("fill", "color", "paint_a", "paint_b", "paint_c"). Defines the color aesthetic for the geometry.
default = "fill" ("fill", "color", "paint_a", "paint_b", "paint_c"). Defines the fill aesthetic for the geometry.
Set of aesthetic mappings. Aesthetic mappings describe the way that variables in the data are mapped to plot "aesthetics".