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stats[statplots, scatterplot]

Sunflower Plot

 Calling Sequence stats[statplots, scatterplot]( data, format=sunflower[l], ..) statplots[scatterplot](data, format=sunflower[l], ..) scatterplot(data, format=sunflower[l], ..)

Parameters

 data - l - maximum length of one side of an sunflower box plotoptions -

Description

 • 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.

Examples

Important: The stats package has been deprecated. Use the superseding package Statistics instead.

 > $\mathrm{with}\left(\mathrm{stats}\right):$
 > $\mathrm{with}\left({\mathrm{stats}}_{\mathrm{statplots}}\right):$
 > $\mathrm{data1}≔\left[\mathrm{random}[\mathrm{normald}]\left(30\right),\mathrm{random}[\mathrm{normald}[3,1]]\left(20\right)\right]:$
 > $\mathrm{data2}≔\left[\mathrm{random}[\mathrm{normald}]\left(30\right),\mathrm{random}[\mathrm{normald}[3,1]]\left(20\right)\right]:$
 > $\mathrm{scatterplot}\left(\mathrm{data1},\mathrm{data2},\mathrm{format}={\mathrm{sunflower}}_{1}\right)$
 > $\mathrm{data3}≔\left[12.00,\mathrm{Weight}\left(10,3\right),8..9.5,9.67,11.11,10.34\right]:$
 > $\mathrm{scatterplot}\left(\mathrm{data3},\mathrm{format}=\mathrm{sunflower}\right)$

 See Also