Practical Guide To Principal Component Methods ... -

The book categorizes methods based on the types of data you are analyzing:

: Principal Component Analysis (PCA) for quantitative variables. Practical Guide To Principal Component Methods ...

: The book heavily utilizes the author's own factoextra R package , which creates elegant, ggplot2 -based graphs to help interpret results. The book categorizes methods based on the types

: Specifically those looking to move beyond "old-school" base R graphics to more modern, publication-ready visualizations. Practical Guide To Principal Component Methods in R Practical Guide To Principal Component Methods in R

The by Alboukadel Kassambara is widely considered an excellent resource for those who want to apply multivariate analysis without getting bogged down in heavy mathematical proofs. Why It Is Highly Rated

: Those who need to analyze large multivariate datasets for research or business but prefer practical implementation over theoretical derivation.

: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA) for datasets with both continuous and categorical variables.