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.
| Version: | 1.0.0 | 
| Depends: | R (≥ 4.1.0) | 
| Suggests: | covr, devtools, factoextra, FactoMineR, knitr, renv, testthat | 
| Published: | 2025-04-24 | 
| DOI: | 10.32614/CRAN.package.booklet | 
| Author: | Alex Yahiaoui Martinez | 
| Maintainer: | Alex Yahiaoui Martinez <yahiaoui-martinez.alex at outlook.com> | 
| BugReports: | https://github.com/alexym1/booklet/issues | 
| License: | MIT + file LICENSE | 
| URL: | https://github.com/alexym1/booklet, https://alexym1.github.io/booklet/ | 
| NeedsCompilation: | no | 
| Materials: | README | 
| CRAN checks: | booklet results | 
| Reference manual: | booklet.html , booklet.pdf | 
| Vignettes: | Comparison with FactoMineR (source, R code) Introduction to booklet (source, R code) Data visualization with factoextra (source, R code) | 
| Package source: | booklet_1.0.0.tar.gz | 
| Windows binaries: | r-devel: booklet_1.0.0.zip, r-release: booklet_1.0.0.zip, r-oldrel: booklet_1.0.0.zip | 
| macOS binaries: | r-release (arm64): booklet_1.0.0.tgz, r-oldrel (arm64): booklet_1.0.0.tgz, r-release (x86_64): booklet_1.0.0.tgz, r-oldrel (x86_64): booklet_1.0.0.tgz | 
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