stats[statplots, scatterplot]
Sunflower Plot
Calling Sequence
Parameters
Description
Examples
stats[statplots, scatterplot]( data, format=sunflower[l], ..)
statplots[scatterplot](data, format=sunflower[l], ..)
scatterplot(data, format=sunflower[l], ..)
data
-
statistical list(s)
l
maximum length of one side of an sunflower box
plotoptions
plot options
Important: The stats package has been deprecated. Use the superseding package Statistics instead.
The function scatterplot with the format parameter format=sunflower of the subpackage stats[statplots] organizes data clusters into sunflowers.
This type of plot is often used or when there is a large number of data points involved. The idea is that it is not necessary to have the detail of each individual point in a plot. Closely grouped points are plotted instead as sunflowers.
A sunflower is a two dimensional object centered in a cube with side length l. One radial arm extends from the center point for each real point contained within the cube.
Fractionally weighted points produce only a fraction of a radial arm. Two points of weight 1/2, in the same cube will produce one radial arm.
All points in this plot are replaced by sunflowers. The replacement is done in a systematic way, so there will be one sunflower per cube with side-length l in a standard lattice of cubes.
If l is zero, or unspecified, a default value will be used. The default value is one-tenth the range of the x-coordinate data.
Class data is converted to classmarks before generating the plot. Weighted data is accounted for. Missing data is ignored.
The command with(stats[statplots] allows the use of the abbreviated form of this command.
with⁡stats:
with⁡statsstatplots:
data1≔randomnormald⁡30,randomnormald3,1⁡20:
data2≔randomnormald⁡30,randomnormald3,1⁡20:
scatterplot⁡data1,data2,format=sunflower1
data3≔12.00,Weight⁡10,3,8..9.5,9.67,11.11,10.34:
scatterplot⁡data3,format=sunflower
See Also
Statistics
Statistics[ScatterPlot]
statplots(deprecated)[scatterplot]
stats(deprecated)[data]
stats(deprecated)[statplots]
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