A script for automatic visualisation of Multiple Correspondence Analysis (MCA) results from FactoMineR in 3 dimensions using Plotly (exported as html)
This repository is used as a reference for the multivariate analysis of the UNAL
Random Forest, Decision tree and Logistic Regression
Data analysis realized in R Shiny and Python about the French electric vehicle and charging station infrastructure
Here is an example of PCA performed on a movie data from IMDB. Data was downloaded from https://www.imdb.com/interfaces/, then merged and filtered into a single dataset of 5 (quite arbitrary) variables to do a PCA with FactoMiner package
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