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