plotCircular: Circular plot using segments

In season: Seasonal analysis of health data

Description

A circular plot useful for visualising monthly or weekly data.

Usage

plotCircular(area1,area2=NULL,spokes=NULL,scale=0.8,
       labels,stats=TRUE,dp=1,clockwise=TRUE,spoke.col='black',
       lines=FALSE,centrecirc=0.03, main="", xlab="", ylab="",
       pieces.col=c("white","gray"), length=FALSE, legend=TRUE,
       auto.legend=list(x="bottomright",fill=NULL, labels=NULL, title=""),...)

Arguments

area1	variable to plot, the area of the segments (or petals) are proportional to this variable.
area2	2nd variable to plot (optional), the area of the segments are plotted in gray.
spokes	spokes that overlay segments, for example standard errors (optional).
scale	scale the overall size of the segments (default:0.8).
labels	optional labels to appear at the ends of the segments (there should be as many labels as there are area1).
stats	put area values at the ends of the segments, default:TRUE.
dp	decimal places for statistics, default:1.
clockwise	plot in a clockwise direction, default:TRUE.
spoke.col	spoke colour, default:black.
lines	add dotted lines to separate petals, default:FALSE.
centrecirc	controls the size of the circle at the centre of the plot, default:0.03.
main	title for plot, default:blank
xlab	x axis label, default:blank
ylab	y axis label, default:blank
pieces.col	colours for circular pieces, default:‘white’ for 1st and ‘gray’ for second variable. Note that a list of available colours may be found with ‘colors()’
length	make the length of the segments proportional to the dependent variable, default:FALSE
legend	whether to include legend or not, default:TRUE when plotting two variables
auto.legend	list of parameters for legend, see legend
...	additional arguments to plot and/or legend. See par for more details

Details

A circular plot can be useful for spotting the shape of the seasonal pattern. This function can be used to plot any circular patterns, e.g., weekly or monthly. The number of segments will be the length of the variable area1.

The plots are also called rose diagrams, with the segments then called ‘petals’.

Author(s)

Adrian Barnett a.barnett<at>qut.edu.au

References

Fisher, N.I. (1993) Statistical Analysis of Circular Data. Cambridge University Press, Cambridge.

Examples

# months (dummy data)
plotCircular(area1=seq(1,12,1),scale=0.7,labels=month.abb,dp=0)
# weeks (random data)
daysoftheweek<-c('Monday','Tuesday','Wednesday','Thursday','Friday',
'Saturday','Sunday')
weekfreq<-table(round(runif(100,min=1,max=7)))
plotCircular(area1=weekfreq,labels=daysoftheweek,dp=0)
# Observed number of AFL players with expected values
data(AFL)
plotCircular(area1=AFL$players,area2=AFL$expected,scale=0.72,
  labels=month.abb,dp=0,lines=TRUE,legend=FALSE)
plotCircular(area1=AFL$players,area2=AFL$expected,scale=0.72,
  labels=month.abb,dp=0,lines=TRUE, pieces.col=c("green","red"),
  auto.legend=list(labels=c("Obs","Exp"),title="# players"),
  main="Observed and Expected AFL players")

Example output

Loading required package: ggplot2
Loading required package: MASS
Loading required package: survival

season documentation built on May 2, 2019, 5:22 p.m.