R Observatory: Metrics for DataVisualizations version 1.4.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

DataVisualizations

1.4.0

Visualizations of High-Dimensional Data

15packages depend

13.2Kdownloads / year

–test coverage

8/13checks pass

Overview

About

Maintained by Michael ThrunFirst published 2018-01-3021 releasesCRAN page ↗GitHub ↗

Gives access to data visualisation methods that are relevant from the data scientist's point of view. The flagship idea of 'DataVisualizations' is the mirrored density plot (MD-plot) for either classified or non-classified multivariate data published in Thrun, M.C. et al.: "Analyzing the Fine Structure of Distributions" (2020), PLoS ONE, DOI:10.1371/journal.pone.0238835. The MD-plot outperforms the box-and-whisker diagram (box plot), violin plot and bean plot and geom_violin plot of ggplot2. Furthermore, a collection of various visualization methods for univariate data is provided. In the case of exploratory data analysis, 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through a combination of four methods. One of these methods is the Pareto density estimation (PDE) of the probability density function (pdf). Additionally, visualizations of the distribution of distances using PDE, the scatter-density plot using PDE for two variables as well as the Shepard density plot and the Bland-Altman plot are presented here. Pertaining to classified high-dimensional data, a number of visualizations are described, such as f.ex. the heat map and silhouette plot. A political map of the world or Germany can be visualized with the additional information defined by a classification of countries or regions. By extending the political map further, an uncomplicated function for a Choropleth map can be used which is useful for measurements across a geographic area. For categorical features, the Pie charts, slope charts and fan plots, improved by the ABC analysis, become usable. More detailed explanations are found in the book by Thrun, M.C.: "Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) DOI:10.1007/978-3-658-20540-9.

Install

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

install.packages("DataVisualizations", 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("Mthrun/DataVisualizations")

Development version from Mthrun/DataVisualizations. 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-datavisualizations

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

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-DataVisualizations

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-DataVisualizations

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

5NOTE8OK

Failing flavors

NOTE r-devel-linux-x86_64-debian-clang
NOTE r-devel-linux-x86_64-debian-gcc
NOTE r-devel-linux-x86_64-fedora-clang
NOTE r-devel-linux-x86_64-fedora-gcc
NOTE r-devel-windows-x86_64

Slowest check: 6.3 min · r-oldrel-windows-x86_64

Code health

None

Tests · ratio 0.00

not tracked

Coverage

100%

Documentation · exports

6

Dependencies · direct

Check history

NOTE2026-07-11
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-06-09
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-06-08
12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
OK2026-04-25
12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-04-22
11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Show 2 earlier snapshots

ERROR2026-04-18
10 OK · 3 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-03-10
11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 656 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 33% structuredCode of conductNoContributing guideNo

Examples that run: 95%
Documented parameters: 98%
Return-value docs: 83%
References docs: 61%

Downloads

13.2K

CRAN downloads in the past year

Rank #3,938 · ~36/day · ~1.1K/mo

Releases R versions

Daily download trend is not available in this view yet.

53230 days

2.2K90 days

13.2K1 year

Compare downloads with other packages →

Also on619 r2u19 autocran5.9K conda_forge44 c2d4u

Repository

GitHub ↗ mthrun/datavisualizations

8Stars

3Forks

0Open issues

0Open PRs

0Releases

276Commits

2Contributors

276 commits · Last activity 2026-08-09 · 0% stars, 30d

Stars over time

2024-05-25 · 72026-07-07 · 8

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/mthrun/datavisualizations on 2026-08-09.

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

31 external dependencies (excludes base and recommended)

Depends (1)

R >= 3.5

Imports (6)

Rcpp RcppParallel ggplot2 sp pracma reshape2

LinkingTo (2)

Rcpp RcppParallel

Suggests (24)

plyr MBA ggmap plotrix rworldmap rgl ABCanalysis parallelDist knitr rmarkdown vioplot ggExtra plotly htmlwidgets diptest moments signal ggrepelMASSROCit ScatterDensity colorspace viridis gridExtra

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

15direct

3indirect

AdaptGauss BIDistances FCPS Umatrix opGMMassessment opImputation pguIMP DRquality DatabionicSwarm GeneralizedUmatrix GeneralizedUmatrixGPU PDEnaiveBayes ProjectionBasedClustering ScatterDensity memshare

Code & Tests

Datasets

People & History

People (10)

Maintainer (1)

Michael Thrun

Author, Maintainer, Copyright holder

Authors (2)

Michael Thrun

Author, Maintainer, Copyright holder

Felix Pape

Author, Reviewer

Contributors (8)

Luca Brinkmann

Contractor, Contributor · added in 1.3.0

Winston Chang

Contributor · added in 1.3.5

Dirk Eddelbuettel

Contributor · added in 1.1.9

Onno Hansen-Goos

Contractor, Contributor

Quirin Stier

Contributor, Reviewer · added in 1.3.1

Hamza Tayyab

Contractor, Contributor · added in 1.2.1

Alfred Ultsch

Data contributor, Contributor, Contractor

Craig Varrichio

Contributor · added in 1.1.10

Copyright holders (1)

Michael Thrun

Author, Maintainer, Copyright holder

Reviewers (2)

Felix Pape

Author, Reviewer

Quirin Stier

Contributor, Reviewer · added in 1.3.1

Listed in earlier versions (2)

Fredericke Matz

no longer listed · 0.9.2 to 1.0.0

Peter Kampstra

no longer listed · 1.0.0

Package Timeline

21 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
1.4.0Latest
2025-10-31 · current release · diff ↗
1.3.5
2025-08-25 · diff ↗
R
R 4.5.0 released · 2025-04-11
1.3.3
2025-01-26 · diff ↗
R
R 4.4.0 released · 2024-04-24
1.3.2
2023-10-10 · diff ↗
1.3.1
2023-07-18 · diff ↗
1.3.0
2023-06-06 · diff ↗
R
R 4.3.0 released · 2023-04-21
1.2.3
2022-05-21 · diff ↗
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
1.2.2
2021-01-12 · diff ↗
1.2.1
2020-10-28 · diff ↗
1.2.0
2020-08-04 · diff ↗

Show 15 earlier events

1.1.12
2020-05-17 · diff ↗
R
R 4.0.0 released · 2020-04-24
1.1.11
2020-02-13 · diff ↗
1.1.10
2020-02-02 · diff ↗
1.1.9
2019-11-10 · diff ↗
1.1.8
2019-08-20 · diff ↗
R
R 3.6.0 released · 2019-04-26
1.1.6
2019-03-08 · diff ↗
1.1.5
2019-02-02 · diff ↗
1.1.4
2018-10-22 · diff ↗
1.1.1
2018-06-30 · diff ↗
1.0.0
2018-05-06 · diff ↗
R
R 3.5.0 released · 2018-04-23
0.9.2
2018-01-30
R
R 3.4.0 released · 2017-04-21

Package metadata

First published: 2018-01-30
Total releases: 21 / 8 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.5
Bundled data: 511 KB / 10 files
Download size: 3.3 MB
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("DataVisualizations")

Format

Thrun, M., Brinkmann, L., Chang, W., Eddelbuettel, D., Hansen-Goos, O., Pape, F., Stier, Q., Tayyab, H., Ultsch, A., & Varrichio, C. (2025). DataVisualizations: Visualizations of High-Dimensional Data (Version 1.4.0) [Computer software]. https://doi.org/10.32614/CRAN.package.DataVisualizations

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

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 DataVisualizations version 1.4.0 [Data set]. HJJB, LLC. Data release v2026-08-15. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-15, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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