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Principal component analysis (PCA) with Python

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File to download to obtain the code and example data files

Loading the compressed code and example data files [folder: "PCA_py.zip"]

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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)..

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Here is a sample of references from sites developing principal component analysis..
https://towardsdatascience.com/principal-component-analysis-pca-from-scratch-in-python-7f3e2a54
https://medium.com/swlh/principal-component-analysis-from-scratch-in-python-2f139c6420c9
https://www.datacamp.com/community/tutorials/principal-component-analysis-in-python
http://tutoriels-data-mining.blogspot.com/p/acp.html
http://eric.univ-lyon2.fr/~ricco/tanagra/fichiers/fr_Tanagra_ACP_Python.pdf
(the latter is the closest to the "Data Analysis" spirit)

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  Presentation of PCA from two examples, and full python code

Click below to get the presentation of the PCA from two examples

Commented examples and python program  

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