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Python library for multidimensional analysis

Project description

scientisttools : Python library for multidimensional analysis

About scientisttools

scientisttools is a Python package dedicated to multivariate Exploratory Data Analysis.

Why use scientisttools?

  • It performs classical principal component methods :
    • Principal Components Analysis (PCA)
    • Principal Components Analysis with partial correlation matrix (PPCA)
    • Weighted Principal Components Analysis (WPCA)
    • Expectation-Maximization Principal Components Analysis (EMPCA)
    • Exploratory Factor Analysis (EFA)
    • Classical Multidimensional Scaling (CMSCALE)
    • Metric and Non - Metric Multidimensional Scaling (MDS)
    • Correspondence Analysis (CA)
    • Multiple Correspondence Analysis (MCA)
    • Factor Analysis of Mixed Data (FAMD)
  • In some methods, it allowed to add supplementary informations such as supplementary individuals and/or variables.
  • It provides a geometrical point of view, a lot of graphical outputs.
  • It provides efficient implementations, using a scikit-learn API.

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

scientisttools requires

Python >=3.10
Numpy >= 1.23.5
Matplotlib >= 3.5.3
Scikit-learn >=  1.2.2
Pandas >= 1.5.3
mapply >= 0.1.21
Plotnine >= 0.10.1
Plydata >= 0.4.3

User installation

You can install scientisttools using pip :

pip install scientisttools

Tutorial are available

https://github.com/enfantbenidedieu/scientisttools/blob/master/ca_example2.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/classic_mds.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/efa_example.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/famd_example.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/ggcorrplot.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/mca_example.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/mds_example.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/partial_pca.ipynb
https://github.com/enfantbenidedieu/scientisttools/blob/master/pca_example.ipynb

Author

Duvérier DJIFACK ZEBAZE (duverierdjifack@gmail.com)

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