booklet

Multivariate exploratory data analysis in R

Overview

booklet is a ground-up rewrite of FactoMineR that provides a set of functions for multivariate exploratory data analysis. It is designed to be a more user-friendly version of FactoMineR. The main goal was to make the package more intuitive and easier to use. The package is still under development, and some functions are not yet implemented. However, the main functions are already available.

Installation

The latest version can be installed from GitHub as follows:

install.packages("devtools")
devtools::install_github("alexym1/booklet")

Example

library(booklet)

# Get active individuals
X_active <- pca_standardize_norm(iris[, -5])
head(X_active)
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width
#> 1   -0.8976739  1.01560199    -1.335752   -1.311052
#> 2   -1.1392005 -0.13153881    -1.335752   -1.311052
#> 3   -1.3807271  0.32731751    -1.392399   -1.311052
#> 4   -1.5014904  0.09788935    -1.279104   -1.311052
#> 5   -1.0184372  1.24503015    -1.335752   -1.311052
#> 6   -0.5353840  1.93331463    -1.165809   -1.048667

# Get eigs
eigs <- pca_eigen(X_active)
eigs$values
#> [1] 434.856175 136.190540  21.866774   3.086511

# Get principal components
ind_coords <- pca_ind_coords(eigs)
head(ind_coords)
#>       Dim.1      Dim.2       Dim.3        Dim.4
#> 1 -2.257141 -0.4784238  0.12727962  0.024087508
#> 2 -2.074013  0.6718827  0.23382552  0.102662845
#> 3 -2.356335  0.3407664 -0.04405390  0.028282305
#> 4 -2.291707  0.5953999 -0.09098530 -0.065735340
#> 5 -2.381863 -0.6446757 -0.01568565 -0.035802870
#> 6 -2.068701 -1.4842053 -0.02687825  0.006586116

Code of conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.