DataVisualizations (version 1.1.12)

Piechart: The pie chart

Description

the pie chart represents amount of values given in data.

Usage

Piechart(Datavector,Names,Labels,MaxNumberOfSlices,
main='',col,Rline=1,...)

Arguments

Datavector

[1:n] a vector of n non unique values

Names

Optional, [1:k] names to search for in Datavector, if not set unique of Datavector is calculated.

Labels

Optional, [1:k] Labels if they are specially named, if not Names are used.

MaxNumberOfSlices

Default is k, integer value defining how many labels will be shown. Everything else will be summed up to Other.

main

Optional, title below the fan pie, see plot

col

Optional, default as other colors in this packages, else the same as in plot

Rline

Optional, the radius of the pie in numerical numbers

…

Optional, further arguments passed on to plot

Value

silent output by calling invisible of a list with

Percentages

[1:k] percent values visualized in fanplot

Labels

[1:k] see input Labels, only relevant ones

Details

If Number of Slices is higher than MaxNumberOfSlices then ABCanalysis is applied (see [Ultsch/Lotsch, 2015]) and group A chosen. If Number of Slices in group A is higher than MaxNumberOfSlices, then the most important ones out of group A are chosen. If MaxNumberOfSlices is higher than Slices in group A, additional slices are shown depending on the percentage (from high to low). Parameters of visualization a set as in [Schwabish, 2014] defined.

References

[Schwabish, 2014] Schwabish, Jonathan A. An Economist's Guide to Visualizing Data. Journal of Economic Perspectives, 28 (1): 209-34. DOI: 10.1257/jep.28.1.209, 2014.

[Ultsch/Lotsch, 2015] Ultsch. A ., Lotsch J.: Computed ABC Analysis for Rational Selection of Most Informative Variables in Multivariate Data, PloS one, Vol. 10(6), pp. e0129767. doi 10.1371/journal.pone.0129767, 2015.

Examples

# NOT RUN {
data(categoricalVariable)
Piechart(categoricalVariable)
# }