get_pca: Extract the results for individuals/variables - PCA

In factoextra: Extract and Visualize the Results of Multivariate Data Analyses

Description

Extract all the results (coordinates, squared cosine, contributions) for the active individuals/variables from Principal Component Analysis (PCA) outputs.

• get_pca(): Extract the results for variables and individuals

• get_pca_ind(): Extract the results for individuals only

• get_pca_var(): Extract the results for variables only

Usage

get_pca(res.pca, element = c("var", "ind"))

get_pca_ind(res.pca, ...)

get_pca_var(res.pca)

Arguments

res.pca	an object of class PCA [FactoMineR]; prcomp and princomp [stats]; pca, dudi [adea4]; epPCA [ExPosition].
element	the element to subset from the output. Allowed values are "var" (for active variables) or "ind" (for active individuals).
...	not used

Value

a list of matrices containing all the results for the active individuals/variables including:

coord	coordinates for the individuals/variables
cos2	cos2 for the individuals/variables
contrib	contributions of the individuals/variables

Author(s)

Alboukadel Kassambara [e-mail]

References

http://www.sthda.com/english/

Examples

# Principal Component Analysis
# +++++++++++++++++++++++++++++
 data(iris)
 res.pca <- prcomp(iris[, -5],  scale = TRUE)
 # Extract the results for individuals
 ind <- get_pca_ind(res.pca)
 print(ind)
 head(ind$coord) # coordinates of individuals
 head(ind$cos2) # cos2 of individuals
 head(ind$contrib) # contributions of individuals
 
 # Extract the results for variables
 var <- get_pca_var(res.pca)
 print(var)
 head(var$coord) # coordinates of variables
 head(var$cos2) # cos2 of variables
 head(var$contrib) # contributions of variables
 
 # You can also use the function get_pca()
 get_pca(res.pca, "ind") # Results for individuals
 get_pca(res.pca, "var") # Results for variable categories
 

factoextra documentation built on April 2, 2020, 1:09 a.m.