Factoextra: visualization of multivariate statistics

factoextra Several other multivariate dimensionality reduction methods are similar to principal component analysis , The functions used and the graphics drawn are also similar . For the following methods , I won't elaborate on every function .

This data set is called glass, Taken from the R package anacor, By 3497 A contingency table of the occupations of fathers and sons of British families . The rows and columns of the dataset are the occupational categories of father and son respectively , Include PROF（ Professionals and leaders ）、EXEC（ Managers and executives ）、HSUP（ Senior management ）LSUP（ Junior managers ）、SKIL（ Skilled workers ）SEMI（ Semi skilled workers ）、UNSK（ Unskilled workers ）. Originally, the names of rows and columns are capitalized , In order to distinguish between , Change the name of the column to lowercase .

factoextra The corresponding analysis display method provided by the package （ And the display method of factor analysis introduced below ） Similar to the presentation method of principal component analysis , It mainly includes （1） Extraction of analysis results （2） Gravel map showing the contribution of factors （3） Show row points and column points respectively in the factor coordinate system （4） stay biplot Show row points and column points at the same time . For this example , We only see biplot graphics

### Load data , Show contingency table 
data(glass,package="anacor")
glass