stat Summary Bin
Displays a distribution by dividing variable mapped to x-axis into bins and applying aggregation functions to each bin.
Notes
Computed variables:
..y.. : result of calculating of
fn
...ymin.. : result of calculating of
fnMin
...ymax.. : result of calculating of
fnMax
.
To hide axis tooltips, set "blank" or the result of elementBlank()
to the axisTooltip
or axisTooltipX
parameter of the theme()
.
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 geometry to display the binned summary stat for this layer, default is Geom.pointrange()
, see Geom.
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.
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.
Specifies the axis that the layer's stat and geom should run along, default = "x". Possible values: "x", "y".
default = "mean" ("count", "sum", "mean", "median", "min", "max", "lq", "mq", "uq"). Name of function computing stat variable ..y..
. Names "lq", "mq", "uq" correspond to lower, middle and upper quantiles, default = listOf(0.25, 0.5, 0.75).
default = "min" ("count", "sum", "mean", "median", "min", "max", "lq", "mq", "uq"). Name of function computing stat variable ..ymin..
. Names "lq", "mq", "uq" correspond to lower, middle and upper quantiles, default = listOf(0.25, 0.5, 0.75).
default = "max" ("count", "sum", "mean", "median", "min", "max", "lq", "mq", "uq"). Name of function computing stat variable ..ymax..
. Names "lq", "mq", "uq" correspond to lower, middle and upper quantiles, default = listOf(0.25, 0.5, 0.75).
default = listOf(0.25, 0.5, 0.75). A list of probabilities defining the quantile functions "lq", "mq" and "uq". Must contain exactly 3 values between 0 and 1.
Number of bins. Overridden by binwidth
.
The width of the bins. The default is to use bin widths that cover the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.
Specifies x-value to align bin centers to.
Specifies x-value to align bin boundary (i.e. point between bins) to.
default = null Only bins with a ..count..
greater than the threshold will be displayed. This is useful for free scales in facets - use threshold=0 to make the plot take up the entire panel space.
X-axis coordinates for vertical interval / position of mid-point for horizontal interval.
Y-axis coordinates for horizontal interval / position of mid-point for vertical interval.
Lower bound for vertical interval.
Upper bound for vertical interval.
Lower bound for horizontal interval.
Upper bound for horizontal interval.
Transparency level of a layer. Understands numbers between 0 and 1.
Color of the geometry. For more info see: aesthetics.html#color-and-fill.
Fill color. For more info see: aesthetics.html#color-and-fill.
Lines width, size of mid-point.
Width of the shape border. Applied only to the shapes having border.
Line width.
Type of the line of border. 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.
Shape of the mid-point. For more info see: aesthetics.html#point-shapes.
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".