Description
Multivariate Exploratory Data Analysis.
Description
Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) when variables are categorical, Multiple Factor Analysis (MFA) when variables are structured in groups.
README.md
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.