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Python module for Factorial Analysis : Simple and Multiple Correspondence Analysis, Principal Components Analysis

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fanalysis

fanalysis is a Python module for Factorial Analysis distributed under the 3-Clause BSD license.

With this fanalysis package, you can perform:

  • Simple Correspondence Analysis
  • Multiple Correspondence Analysis
  • Principal Components Analysis

Those statistical methods can be used in two ways:

  • as descriptive methods ("datamining approach")
  • as reduction methods in scikit-learn pipelines ("machine learning approach")

Installation

Dependencies

fanalysis requires:

Python 3
NumPy >= 1.11.0
Matplotlib >= 2.0.0
Scikit-learn >= 0.18.0
Pandas >= 0.19.0

User installation

You can install fanalysis using pip:

pip install fanalysis

Running the tests

After installation, you can launch the test suite from outside the source directory:

python -m unittest

The philosophy of the unit tests consists in comparing the outputs of fanalysis (with various combinations of parameters) with the outputs of the R FactoMineR package.

Documentation

The docstring is written in english.

Tutorials are available in french:

https://github.com/OlivierGarciaDev/fanalysis/blob/master/doc/ca_tutorial.ipynb
https://github.com/OlivierGarciaDev/fanalysis/blob/master/doc/mca_tutorial.ipynb
https://github.com/OlivierGarciaDev/fanalysis/blob/master/doc/pca_tutorial.ipynb

Author

Olivier Garcia (o.garcia.dev@gmail.com)

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