Discrete Distribution Data Analysis with Wasserstein Distance R package DDAWASS version 1.0.0 S4 classes and methods for the analysis of data described by discrete distributions with finite support (e.g. frequency distributions of ratings, scores or counts observed on groups of individuals), using the L2 Wasserstein metric between quantile functions. It is the discrete counterpart of 'HistDAWass' and provides exact Wasserstein distances (in C++), barycenters, Wasserstein variance, covariance and correlation, k-means and hierarchical clustering, quantile-based principal component and multiple factor analysis, two-component linear regression and reliability (Cronbach's alpha) indices. See Crocetta, Irpino, Antonucci and Marin (2025) <doi:10.1007/s11135-024-01956-0>. Software Depends: R (>= 4.0.0), methods Imports: Rcpp (>= 1.0.0), HistDAWass, FactoMineR, ggplot2, rlang, tibble, stats, utils, grDevices LinkingTo: Rcpp Suggests: testthat (>= 3.0.0), knitr, rmarkdown, CUB Antonio Irpino <antonio.irpino@unicampania.it> Comprehensive R Archive Network (CRAN) Antonio Irpino [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-9293-7180>) GPL (>= 3) 2026-11-04 application/tgz https://CRAN.R-project.org/package=DDAWASS doi:10.32614/CRAN.package.DDAWASS