## Load data
data("iris")
## Compute principal components analysis
X <- pca(iris, scale = TRUE)
## Plot individuals
viz_individuals(X, panel.last = graphics::grid())
## Labels of the 10 individuals with highest cos2
viz_individuals(X, labels = list(how = "cos2", n = 10))
## Plot variables
viz_variables(X, panel.last = graphics::grid())
## Graphical parameters
## Continuous values
viz_individuals(X, extra_quanti = iris$Petal.Length, symbol = 16, size = c(1, 2))
viz_individuals(X, extra_quanti = iris$Petal.Length, symbol = 16, size = c(1, 2),
color = grDevices::hcl.colors(12, "RdPu"))
viz_variables(X, extra_quanti = "contribution",
color = grDevices::hcl.colors(12, "BluGrn", rev = TRUE),
size = c(0, 1))
## Discrete values
viz_individuals(X, extra_quali = iris$Species, symbol = 21:23)
viz_individuals(X, extra_quali = iris$Species, symbol = 21:23,
fill = c("#004488", "#DDAA33", "#BB5566"),
color = "black")
viz_variables(X, extra_quali = c("Petal", "Petal", "Sepal", "Sepal"),
color = c("#EE7733", "#0077BB"),
symbol = c(1, 3))
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