Provides an automated workflow for Principal Component Analysis (PCA)
that simplifies multivariate data analysis by performing
essential preprocessing, statistical tests, component extraction,
and visualization in a single function call. The package automatically
standardizes variables, computes correlation matrices,
performs Kaiser-Meyer-Olkin (KMO) and Bartlett's tests, determines
the optimal number of principal components using multiple selection
criteria, generates component loadings and scores, and produces
publication-ready tables and graphical outputs for researchers and students.
Methodological background is described in Shankar et al. (2024)