plotCircular | R Documentation |

A circular plot useful for visualising monthly or weekly data.

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 = ""), ... )

`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 grey. |

`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 |

`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 ‘grey’ 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 |

`...` |
additional arguments to |

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’.

Adrian Barnett a.barnett@qut.edu.au

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

# 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")

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