👑 Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

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

This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.

Supporting information for the paper "The narrative of sustainability and circular economy – a longitudinal review of two decades of research” - https://doi.org/10.1016/j.resconrec.2020.105073

This is a repository for the paper "Contrastive Multiple Correspondence Analysis (cMCA): Applying the Contrastive Learning Method to Identify Political Subgroups."

Multivariate analysis and statistical modeling (with dimensional reduction) of NYC urban life pathologies

A script for automatic visualisation of Multiple Correspondence Analysis (MCA) results from FactoMineR in 3 dimensions using Plotly (exported as html)

This scientific paper was developed by the Latin American Bike Knowledge Sharing LABIKS with peers, after analyzing the original database from the annual report called "Bike Sharing Systems in Latin America". In this repository you will find the code script (R version 4.0.4) that will allow you to replicate the methodology for data analysis and …

Analysis of credit ratings of bank customers based on several features

Analysis of the survey data

R Data Science & Stats