The sunflowerplot() function for repeated numerical data

A scatterplot represents each (x, y) pair in a dataset by a single point. If some of these pairs are repeated (i.e. if the same combination of x and y values appears more than once and thus lie on top of each other), we can't see this in a scatterplot. Several approaches have been developed to deal with this problem, including jittering, which adds small random values to each x and y value, so repeated points will appear as clusters of nearby points.

A useful alternative that is equally effective in representing repeated data points is the sunflowerplot, which represents each repeated point by a "sunflower," with one "petal" for each repetition of a data point.

This exercise asks you to construct both a scatterplot and a sunflowerplot from the same dataset, one that contains repeated data points. Comparing these plots allows you to see how much information can be lost in a standard scatterplot when some data points appear many times.

Use the par() function to set the mfrow parameter for a side-by-side plot array.
For the left-hand plot, use the plot() function to construct a scatterplot of the rad variable versus the zn variable, both from the Boston data frame in the MASS package.
Use the title() function to add the title "Standard scatterplot" to this plot.
For the right-hand plot, apply the sunflowerplot() function to the same data to see the presence of repeated data points, not evident from the scatterplot on the left.
Use the title() function to add the title "Sunflower plot".

Take Hint (-30 XP)

Exercise

The sunflowerplot() function for repeated numerical data

Instructions