geom Error Bar
Displays error bars defined by the upper and lower values. Represents a vertical interval, defined by x
, ymin
, ymax
, or a horizontal interval, defined by y
, xmin
, xmax
.
Examples
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.
Position adjustment: positionIdentity
, positionStack()
, positionDodge()
, etc. see Position.
default = true. false - do not show legend for this layer.
Result of the call to the samplingXxx()
function. To prevent any sampling for this layer pass value samplingNone
. For more info see sampling.md.
Result of the call to the layerTooltips()
function. Specifies appearance, style and content.
X-axis coordinates for the vertical error bar.
Lower bound for the vertical error bar.
Upper bound for the vertical error bar.
Width of the whiskers of the vertical error bar. Typically ranges between 0 and 1. Values that are greater than 1 lead to overlapping of the bars.
Y-axis coordinates for the horizontal error bar.
Lower bound for the horizontal error bar.
Upper bound for the horizontal error bar.
Height of the whiskers of the horizontal error bar. Typically ranges between 0 and 1. Values that are greater than 1 lead to overlapping of the bars.
Transparency level of a layer. Understands numbers between 0 and 1.
Color of geometry lines. String in the following formats:
RGB/RGBA (e.g. "rgb(0, 0, 255)")
HEX (e.g. "#0000FF")
color name (e.g. "red")
role name ("pen", "paper" or "brush")
Or an instance of the java.awt.Color
class.
Type of the line. Codes and names: 0 = "blank", 1 = "solid", 2 = "dashed", 3 = "dotted", 4 = "dotdash", 5 = "longdash", 6 = "twodash".
Line width.
default = "color" ("fill", "color", "paint_a", "paint_b", "paint_c"). Defines the color aesthetic for the geometry.
Set of aesthetic mappings. Aesthetic mappings describe the way that variables in the data are mapped to plot "aesthetics".