scientisttools 0.1.4

Python library for multidimensional analysis, classification - clustering analysis

scientisttools : Python library for multidimensional analysis

About scientisttools

scientisttools is a Python package dedicated to multivariate Exploratory Data Analysis, clustering analysis and discriminant analysis.

Why use scientisttools?

• It performs classical principal component methods :

  • Principal Components Analysis (PCA)
  • Principal Components Analysis with partial correlation matrix (PartialPCA)
  • Exploratory Factor Analysis (EFA)
  • Classical Multidimensional Scaling (CMDSCALE)
  • Metric and Non - Metric Multidimensional Scaling (MDS)
  • Correspondence Analysis (CA)
  • Multiple Correspondence Analysis (MCA)
  • Factor Analysis of Mixed Data (FAMD)
  • Multiple Factor Analysis (MFA)
  • Multiple Factor Analysis for qualitatives/categoricals variables (MFAQUAL)
  • Multiple Factor Analysis of Mixed Data (MFAMIX)
  • Multiple Factor Analysis of Contingence Tables (MFACT)

• 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")

scientisttools also performs clustering analysis

• Clustering analysis:
  • Hierarchical Clustering on Principal Components (HCPC)
  • Variables Hierarchical Clustering Analysis (VARHCA)
  • Variables Hierarchical Clustering Analysis on Principal Components (VARHCPC)
  • Categorical Variables Hierarchical Clustering Analysis (CATVARHCA)

Notebooks are availabled.

Installation

Dependencies

scientisttools requires

numpy>=1.26.2
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
pingouin>=0.5.3
scientistmetrics>=0.0.3
ggcorrplot>=0.0.2

User installation

You can install scientisttools using pip :

pip install scientisttools

Tutorial are available

Author

Duvérier DJIFACK ZEBAZE ([e-mail])