fviz_ca: Quick Correspondence Analysis data visualization using factoextra - R software and data mining

Description
Install and load factoextra
Usage
Arguments
Details
Value
Examples
Infos

Description

Graph of column/row variables from the output of Correspondence Analysis (CA).

The following functions, from factoextra package are use:

fviz_ca_row(): Graph of row variables
fviz_ca_col(): Graph of column variables
fviz_ca_biplot(): Biplot of row and column variables
fviz_ca(): An alias of fviz_ca_biplot()

These functions are included in factoextra package.

Install and load factoextra

The package devtools is required for the installation as factoextra is hosted on github.

# install.packages("devtools")
library("devtools")
install_github("kassambara/factoextra")

Load factoextra :

library("factoextra")

Usage

# Graph of row variables
fviz_ca_row(X, axes = c(1, 2), shape.row = 19,
  geom = c("point", "text"), label = "all", 
  invisible = "none", labelsize = 4, pointsize = 2,
  col.row = "blue", col.row.sup = "darkblue", alpha.row = 1,
  select.row = list(name = NULL, cos2 = NULL, contrib = NULL),
  map = "symmetric",
  jitter = list(what = "label", width = NULL, height = NULL), ...)
# Graph of column variables
fviz_ca_col(X, axes = c(1, 2), shape.col = 17,
  geom = c("point", "text"), label = "all",
  invisible = "none", labelsize = 4, pointsize = 2,
  col.col = "red", col.col.sup = "darkred", alpha.col = 1,
  select.col = list(name = NULL, cos2 = NULL, contrib = NULL),
  map = "symmetric",
 jitter = list(what = "label", width = NULL, height = NULL), ...)
# Biplot of row and column  variables
fviz_ca_biplot(X, axes = c(1, 2), shape.row = 19, shape.col = 17,
  geom = c("point", "text"), label = "all", invisible = "none",
  labelsize = 4, pointsize = 2, col.col = "red",
  col.col.sup = "darkred", alpha.col = 1, col.row = "blue",
  col.row.sup = "darkblue", alpha.row = 1,
  select.col = list(name = NULL, cos2 = NULL, contrib = NULL),
  select.row = list(name = NULL, cos2 = NULL, contrib = NULL),
  map = "symmetric", arrows = c(FALSE, FALSE),
  jitter = list(what = "label", width = NULL, height = NULL), ...)
# An alias of fviz_ca_biplot()
fviz_ca(X, ...)

Arguments

Argument	Description
X	an object of class CA [FactoMineR], ca [ca], coa [ade4]; correspondence [MASS].
axes	a numeric vector of length 2 specifying the dimensions to be plotted.
shape.row,shape.col	the point shapes to be used for row/column variables. Default values are 19 for rows and 17 for columns.
geom	a text specifying the geometry to be used for the graph. 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 character vector specifying the elements to be labelled. Default value is “all”. Allowed values are “none” or the combination of c(“row”, “row.sup”, “col”, “col.sup”). Use “col” to label only active column variables; “col.sup” to label only supplementary columns; etc
invisible	a character value specifying the elements to be hidden on the plot. Default value is “none”. Allowed values are the combination of c(“row”, “row.sup”, “col”, col.sup“).
labelsize	font size for the labels.
pointsize	the size of points.
map	character string specifying the map type. Allowed options include: “symmetric”, “rowprincipal”, “colprincipal”, “symbiplot”, “rowgab”, “colgab”, “rowgreen” and “colgreen”. See details
jitter	a parameter used to jitter the points in order to reduce overplotting. It's a list containing the objects what, width and height (Ex.; jitter = list(what, width, height)). what: the element to be jittered. Possible values are "point" or "p"; "label" or "l"; "both" or "b". width: degree of jitter in x direction (ex: 0.2). height: degree of jitter in y direction (ex: 0.2).
col.col,col.row	color for column/row points. The default values are “red” and “blue”, respectively. Allowed values include also : “cos2”, “contrib”, “coord”, “x” or “y”. In this case, the colors for row/column variables are automatically controlled by their qualities (“cos2”), contributions (“contrib”), coordinates (x^2 + y^2, “coord”), x values(“x”) or y values(“y”)
col.col.sup,col.row.sup	colors for the supplementary column and row points, respectively.
alpha.col,alpha.row	controls the transparency of colors. The value can variate from 0 (total transparency) to 1 (no transparency). Default value is 1. Allowed values include also : "cos2", "contrib", "coord", "x" or "y" as for the arguments col.col and col.row..
select.col,select.row	a selection of columns/rows to be drawn. Allowed values are NULL or a list containing the arguments name, cos2 or contrib: name: is a character vector containing columns/rows to be drawn cos2: if cos2 is in [0, 1], ex: 0.6, then columns/rows with a cos2 > 0.6 are drawn. if cos2 > 1, ex: 5, then the top 5 columns/rows with the highest cos2 are drawn. contrib: if contrib > 1, ex: 5, then the top 5 columns/rows with the highest cos2 are drawn
arrows	Vector of two logicals specifying if the plot should contain points (FALSE, default) or arrows (TRUE). First value sets the rows and the second value sets the columns.
…	Optional arguments.

Details

The default plot of CA is a “symmetric” plot in which both rows and columns are in principal coordinates. In this situation, it’s not possible to interpret the distance between row points and column points. To overcome this problem, the simplest way is to make an asymmetric plot. This means that, the column profiles must be presented in row space or vice-versa. The allowed options for the argument map are:

“rowprincipal” or “colprincipal”: asymmetric plots with either rows in principal coordinates and columns in standard coordinates, or vice versa. These plots preserve row metric or column metric respectively.
“symbiplot”: Both rows and columns are scaled to have variances equal to the singular values (square roots of eigenvalues), which gives a symmetric biplot but does not preserve row or column metrics.
“rowgab” or “colgab”: Asymmetric maps, proposed by Gabriel & Odoroff (1990), with rows (respectively, columns) in principal coordinates and columns (respectively, rows) in standard coordinates multiplied by the mass of the corresponding point.
“rowgreen” or “colgreen”: The so-called contribution biplots showing visually the most contributing points (Greenacre 2006b). These are similar to “rowgab” and “colgab” except that the points in standard coordinates are multiplied by the square root of the corresponding masses, giving reconstructions of the standardized residuals.

Value

A ggplot2 plot

Examples

Correspondence Analysis

Correspondence Analysis (CA) is performed using the function CA() [in FactoMineR] and housetasks data [in factoextra]:

# Install and load FactoMineR to compute CA
# install.packages("FactoMineR")
library("FactoMineR")
data(housetasks)
head(housetasks)

           Wife Alternating Husband Jointly
Laundry     156          14       2       4
Main_meal   124          20       5       4
Dinner       77          11       7      13
Breakfeast   82          36      15       7
Tidying      53          11       1      57
Dishes       32          24       4      53

res.ca <- CA(housetasks, graph=FALSE)