factoextra (version 1.0.4)

fviz: Visualizing Multivariate Analyse Outputs

Description

Generic function to create a scatter plot of multivariate analyse outputs, including PCA, CA, MCA and MFA.

Usage

fviz(X, element, axes = c(1, 2), geom = "auto", label = "all",
  invisible = "none", labelsize = 4, pointsize = 1.5, pointshape = 19,
  arrowsize = 0.5, habillage = "none", addEllipses = FALSE,
  ellipse.level = 0.95, ellipse.type = "norm", ellipse.alpha = 0.1,
  color = "black", alpha = 1, gradient.cols = NULL,
  col.row.sup = "darkblue", col.col.sup = "darkred", select = list(name =
  NULL, cos2 = NULL, contrib = NULL), title = NULL,
  axes.linetype = "dashed", repel = FALSE, col.circle = "grey70",
  ggtheme = theme_minimal(), ...)

Arguments

X

an object of class PCA, CA, MCA, FAMD, MFA and HMFA [FactoMineR]; prcomp and princomp [stats]; dudi, pca, coa and acm [ade4]; ca [ca package]; expoOutput [ExPosition].

element

the element to subset from the output. Possible values are "row" or "col" for CA; "var" or "ind" for PCA and MCA; "mca.cor" for MCA; 'quanti.var', 'quali.var' , 'group' or 'ind' for FAMD, MFA and HMFA.

axes

a numeric vector specifying the axes of interest. Default values are 1:2 for axes 1 and 2.

geom

a text specifying the geometry to be used for the graph. Default value is "auto". Allowed values are the combination of c("point", "arrow", "text"). Use "point" (to show only points); "text" to show only labels; c("point", "text") or c("arrow", "text") to show both types.

label

a text specifying the elements to be labelled. Default value is "all". Allowed values are "none" or the combination of c("ind", "ind.sup", "quali", "var", "quanti.sup", "group.sup"). "ind" can be used to label only active individuals. "ind.sup" is for supplementary individuals. "quali" is for supplementary qualitative variables. "var" is for active variables. "quanti.sup" is for quantitative supplementary variables.

invisible

a text specifying the elements to be hidden on the plot. Default value is "none". Allowed values are the combination of c("ind", "ind.sup", "quali", "var", "quanti.sup", "group.sup").

labelsize

font size for the labels

pointsize

the size of points

pointshape

the shape of points

arrowsize

the size of arrows. Controls the thickness of arrows.

habillage

an optional factor variable for coloring the observations by groups. Default value is "none". If X is a PCA object from FactoMineR package, habillage can also specify the supplementary qualitative variable (by its index or name) to be used for coloring individuals by groups (see ?PCA in FactoMineR).

addEllipses

logical value. If TRUE, draws ellipses around the individuals when habillage != "none".

ellipse.level

the size of the concentration ellipse in normal probability.

ellipse.type

Character specifying frame type. Possible values are 'convex' or types supporeted by stat_ellipse including one of c("t", "norm", "euclid").

ellipse.alpha

Alpha for ellipse specifying the transparency level of fill color. Use alpha = 0 for no fill color.

color

color to be used for the specified geometries (point, text). Possible values include also : "cos2", "contrib", "coord", "x" or "y". In this case, the colors for individuals/variables are automatically controlled by their qualities of representation ("cos2"), contributions ("contrib"), coordinates (x^2+y^2, "coord"), x values ("x") or y values ("y"). To use automatic coloring (by cos2, contrib, ....), make sure that habillage ="none".

alpha

controls the transparency of individual and variable colors, respectively. The value can variate from 0 (total transparency) to 1 (no transparency). Default value is 1. Possible values include also : "cos2", "contrib", "coord", "x" or "y". In this case, the transparency for the individual/variable colors are automatically controlled by their qualities ("cos2"), contributions ("contrib"), coordinates (x^2+y^2, "coord"), x values("x") or y values("y"). To use this, make sure that habillage ="none".

gradient.cols

vector of colors to use for n-colour gradient. Allowed values include brewer and ggsci color palettes.

col.col.sup, col.row.sup

colors for the supplementary column and row points, respectively.

select

a selection of individuals/variables to be drawn. Allowed values are NULL or a list containing the arguments name, cos2 or contrib:

• name: is a character vector containing individuals/variables to be drawn

• cos2: if cos2 is in [0, 1], ex: 0.6, then individuals/variables with a cos2 > 0.6 are drawn. if cos2 > 1, ex: 5, then the top 5 individuals/variables with the highest cos2 are drawn.

• contrib: if contrib > 1, ex: 5, then the top 5 individuals/variables with the highest contrib are drawn

title

the title of the graph

axes.linetype

linetype of x and y axes.

repel

a boolean, whether to use ggrepel to avoid overplotting text labels or not.

col.circle

a color for the correlation circle. Used only when X is a PCA output.

ggtheme

function, ggplot2 theme name. Default value is theme_pubr(). Allowed values include ggplot2 official themes: theme_gray(), theme_bw(), theme_minimal(), theme_classic(), theme_void(), ....

...

Arguments to be passed to the functions ggpubr::ggscatter() & ggpubr::ggpar().

Value

a ggplot

Examples

# NOT RUN {
# Principal component analysis
# +++++++++++++++++++++++++++++
data(decathlon2)
decathlon2.active <- decathlon2[1:23, 1:10]
res.pca <- prcomp(decathlon2.active,  scale = TRUE)
fviz(res.pca, "ind") # Individuals plot
fviz(res.pca, "var") # Variables plot

# Correspondence Analysis
# ++++++++++++++++++++++++++
# Install and load FactoMineR to compute CA
# install.packages("FactoMineR")
library("FactoMineR")
data("housetasks")
res.ca <- CA(housetasks, graph = FALSE)
fviz(res.ca, "row") # Rows plot
fviz(res.ca, "col") # Columns plot

# Multiple Correspondence Analysis
# +++++++++++++++++++++++++++++++++
library(FactoMineR)
data(poison)
res.mca <- MCA(poison, quanti.sup = 1:2, 
              quali.sup = 3:4, graph=FALSE)
              
fviz(res.mca, "ind") # Individuals plot
fviz(res.mca, "var") # Variables plot

 
# }