geom Band
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.
default = Stat.count()
. The statistical transformation to use on the data for this layer. Supported transformations: Stat.identity
, Stat.bin()
, Stat.count()
, etc. see Stat.
Position adjustment: positionIdentity
, positionStack()
, positionDodge()
, etc. see Position.
default = true. false - do not show legend for this layer.
default = true. false - do not combine the layer aesthetic mappings with the plot shared mappings.
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. Set tooltips = tooltipsNone
to hide tooltips from the layer.
Lower bound for the vertical band.
Upper bound for the vertical band.
Lower bound for the horizontal band.
Upper bound for the horizontal band.
Transparency level of a layer. Understands numbers between 0 and 1.
Color of the band border. For more info see: aesthetics.html#color-and-fill.
Fill color. For more info see: aesthetics.html#color-and-fill.
Defines band border width.
Type of the line. Accept codes or names (0 = "blank", 1 = "solid", 2 = "dashed", 3 = "dotted", 4 = "dotdash", 5 = "longdash", 6 = "twodash"), a hex string (up to 8 digits for dash-gap lengths), or a pattern offset to listOf(dash, gap, ...)
/ listOf(dash, gap, ...)
. For more info see: aesthetics.html#line-types.
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".