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The comprehensive principal component analysis (PCA) program presented here is designed in the spirit of exploratory data analysis. We thus insist on the fundamental role, for the interpretations, of additional (or supplementary) variables (numerical or nominal) and additional (or supplementary) individuals.
This stand-alone program does not refer to existing PCA programs. It only uses the three classic python libraries NUMPY (for vector and matrix computation), PANDAS (for managing data tables) and MATPLOTLIB (for graphics)..
Click below to get the presentation of the PCA from two examples