| Title: | Implementation of the Radar-Boxplot |
| Version: | 1.0.5 |
| Description: | Creates the radar-boxplot, a plot that was created by the author during his Ph.D. in forest resources. The radar-boxplot is a visualization feature suited for multivariate classification/clustering. It provides an intuitive deep understanding of the data. |
| Suggests: | ggplot2 |
| Depends: | R (≥ 3.5) |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.2 |
| URL: | https://github.com/caiohamamura/radarBoxplot-R, https://radarboxplot.r-forge.r-project.org/ |
| BugReports: | https://github.com/caiohamamura/radarBoxplot-R/issues |
| Author: | Caio Hamamura [aut, cre] |
| Maintainer: | Caio Hamamura <caiohamamura@gmail.com> |
| Repository: | CRAN |
| Repository/R-Forge/Project: | radarboxplot |
| Repository/R-Forge/Revision: | 16 |
| Repository/R-Forge/DateTimeStamp: | 2021-10-06 17:10:06 |
| Date/Publication: | 2021-10-07 07:40:16 UTC |
| NeedsCompilation: | no |
| Packaged: | 2021-10-06 17:28:07 UTC; rforge |
Function to plot the radar-boxplot
Description
Function to plot the radar-boxplot
Usage
radarBoxplot(x, ...)
## S3 method for class 'formula'
radarBoxplot(x, data, ...)
## Default S3 method:
radarBoxplot(
x,
y,
IQR = 1.5,
use.ggplot2 = FALSE,
mfrow = NA,
oma = c(5, 4, 0, 0) + 0.1,
mar = c(0, 0, 1, 1) + 0.1,
innerPolygon = list(),
outerPolygon = list(),
innerBorder = list(),
outerBorder = list(),
medianLine = list(),
outlierPoints = list(),
nTicks = 4,
ticksArgs = list(),
axisArgs = list(),
labelsArgs = list(),
angleOffset = NA,
...
)
Arguments
x |
a data frame or matrix of attributes or a formula describing the attributes for the class |
... |
parameter to allow the usage of S3 methods |
data |
dataset for fomula variant for which formula was defined |
y |
a response vector |
IQR |
numeric. The factor to multiply the IQR to define the outlier threshold. Default 1.5 |
use.ggplot2 |
if ggplot2 are available it will use ggplot for plotting: Default FALSE |
mfrow |
mfrow argument for defining the subplots nrows and ncols: Default will calculate the minimum square |
oma |
outer margins of the subplots: Default c(5,4,0,0) + 0.1 |
mar |
margins of the subplots: Default c(0,0,1,1) + 0.1 |
innerPolygon |
a list of optional arguments to override Q2-Q3 'graphics::polygon()' style: Default list() |
outerPolygon |
a list of optional arguments to override the outer (range) 'graphics::polygon()' default style: Default list() |
innerBorder |
a list of optional arguments to override the inner border 'graphics::lines()' default style: Default list() |
outerBorder |
a list of optional arguments to override the outer border 'graphics::lines()' default style: Default list() |
medianLine |
a list of optional arguments to override the median line 'graphics::lines()' default style: Default list() |
outlierPoints |
a list of optional arguments to override the outliers 'graphics::points()' default style: Default list() |
nTicks |
number of ticks for the radar chart: Default 4 |
ticksArgs |
a list of optional arguments to override radar ticks 'graphics::lines()' default style: Default list() |
axisArgs |
a list of optional arguments to override radar axis 'graphics::lines()' default style: Default list() |
labelsArgs |
a list of optional arguments to override labels 'graphics::text()' default style: Default list() |
angleOffset |
offset for rotating the plots: Default will let the top free of axis to avoid its label overlapping the title |
Examples
library(radarBoxplot)
data("winequality_red")
# Regular
radarBoxplot(quality ~ ., winequality_red)
# Orange and green pattern with grey median
radarBoxplot(quality ~ ., winequality_red,
use.ggplot2=FALSE, medianLine=list(col="grey"),
innerPolygon=list(col="#FFA500CC"),
outerPolygon=list(col=rgb(0,.7,0,0.6)))
# Plot in 2 rows and 3 columns
# change columns order (counter clockwise)
radarBoxplot(quality ~ volatile.acidity + citric.acid +
residual.sugar + fixed.acidity + chlorides +
free.sulfur.dioxide + total.sulfur.dioxide +
density + pH + sulphates + alcohol,
data = winequality_red,
mfrow=c(2,3))
Red Wine Quality Dataset
Description
Related to red vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests
Usage
winequality_red
Format
A data frame with 1599 rows and 12 variables:
Source
https://archive.ics.uci.edu/ml/datasets/wine+quality
References
P. Cortez, A. Cerdeira, F. Almeida, T. Matos and J. Reis. Modeling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547-553, 2009.
White Wine Quality Dataset
Description
Related to white vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests
Usage
winequality_white
Format
A data frame with 4898 rows and 12 variables:
Source
https://archive.ics.uci.edu/ml/datasets/wine+quality
References
P. Cortez, A. Cerdeira, F. Almeida, T. Matos and J. Reis. Modeling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547-553, 2009.