R Observatory: Metrics for deaviz version 0.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

deaviz

0.1.0Package record

Visualization of Data Envelopment Analysis Problems

0packages depend

1.2Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Shahin AshkianiCRAN page ↗GitHub ↗Issues ↗

High-dimensional visualization methods for data envelopment analysis (DEA), gathering in one place techniques that have appeared in the literature but remained scattered and largely unimplemented: cross-efficiency matrix unfolding, the Porembski network with lambda edges, principal component analysis biplots, multidimensional-scaling colour-plots, self-organizing maps, the Costa bi-dimensional efficient frontier, parallel coordinates, radar charts, panel-data trajectory biplots, peer and reference networks, and a set of descriptive plots. The package is built around a single validated dea_data() object and uses the 'Benchmarking' package as its DEA engine. The implemented methods draw on a body of literature; representative references include Doyle and Green (1994) doi:10.1057/jors.1994.84, Porembski, Breitenstein and Alpar (2005) doi:10.1007/s11123-005-1328-5 and Bana e Costa, Soares de Mello and Angulo Meza (2016) doi:10.1016/j.ejor.2016.05.012.

Changes in 0.1.0

First release: a from-scratch rebuild of the DEA-Viz visualization methods as an R package.
All functions are built on a single validated dea_data object and follow a compute_* / plot_* naming convention.
Analysis: compute_efficiency(), compute_cross_efficiency(), compute_cross_efficiency_weights(), standardize_weights(), compute_multiplier_weights(), compute_som().
Visualization: plot_efficiency_bar(), plot_efficiency_comparison(), plot_cross_efficiency(), plot_cem_unfolding(), plot_cross_efficiency_weights_heatmap(), plot_pca_biplot(), plot_mds(), plot_porembski_network(), plot_panel_biplot(), plot_som(), plot_som_components(), plot_costa_frontier(), plot_parallel_coordinates(), plot_3d_scatter(), plot_histograms(), plot_dotplots(), plot_pairwise_scatter(), plot_input_output_heatmap().

Show all changes in 0.1.0Hide the rest of the changes in 0.1.0

Ships the chinese_cities example dataset (35 cities, 3 inputs, 3 outputs).
Consistent, colour-blind-safe visual style across all plots: Okabe-Ito qualitative palette, viridis sequential palette, and a shared minimal theme.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("deaviz", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("Pomelo64/deaviz")

Development version from Pomelo64/deaviz. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-deaviz

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-deaviz

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-deaviz

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.5 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK6 OK2026-07-03

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.0

READMEYes · 510 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 0.1.0Citation fileYes · cites a publication

Help pages: 30 (1 internal)includes a package overview page
Examples that run: 100%27 run in a plain check (22 of them under a condition)
Exported functions with examples: 100%
Documented parameters: 95%
Return-value docs: 100%
Help pages citing references: 27%

Vignettes (1)

Getting started with deaviz HTML

How these are measured

Downloads

1.2K

CRAN downloads in the past year

Rank #11,226 · ~3/day · ~98/mo

Releases R versions

Daily download trend is not available in this view yet.

32130 days

94990 days

1.2K1 year

Compare downloads with other packages →

Also on25 r2u4 autocran

How downloads are counted

Repository

pomelo64/deaviz ↗Account: Pomelo64

1Stars

1Forks

0Open issues

0Open PRs

0Releases

8Commits

1Commit identities

License file reads as AGPL-3.0 · 8 commits · Last activity 2026-06-26 · 0% stars, 30d

Responsiveness

not measured

Stars over time

2026-07-07 · 02026-07-13 · 1

How these are measured

PracticesBeta

5 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/pomelo64/deaviz on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (1)

GitHub Pages site last deployed 2026-08-08

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

14 external dependencies (excludes base and recommended)

Installing deaviz adds 17 packages (7 with compiled code, 14 MB of source tarballs). Heaviest: ggplot2 6.0 MB, isoband 1.5 MB, farver 1.2 MB.

Depends (1)

R >= 3.6.0

Imports (6)

rlangstatsutilsgrDevicesgraphicsggplot2

LinkingTo (0)

none

Suggests (13)

Benchmarking lpSolve lpSolveAPI kohonen smacof plotly ggrepel igraph graphlayoutsMASStestthat knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (1)

Shahin Ashkiani

Author, Maintainer since 0.1.0 (2026)

Releases (1)

0.1.0Latest
record
2026-07-02 · current release
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-07-02
Total releases: 1 / 1 yrs
License: AGPL (>= 3) OSI
Minimum R: ≥ 3.6.0
Bundled data: 3.0 KB / 2 files
Download size: 1.1 MB

Cite

Cite this package

Run in R for the authors' entry:

citation("deaviz")

The package provides a citation file, so citation() returns the authors' own entry.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for deaviz version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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