Package: prefviz 0.1.3

Linh Ngo

prefviz: Visualizes Preferential Data in One and More Contests

A visualization toolkit for preferential data, such as ranked-choice election results, tournament outcomes, and survey responses. The package provides methods to visualise the preference distribution of one contest with bar charts and pairwise comparisons of two contestants, as well as methods to visualise multiple contests through 2D and high-dimensional simplex plots both statically and interactively. HD simplex displays are implemented via projection methods using the 'tourr' and 'detourr' packages, enabling dynamic exploration of high-dimensional preference structure. For more details on HD simplex projection, see Wickham et al. (2011) <doi:10.21105/joss.03419>.

Authors:Linh Ngo [aut, cre], Dianne Cook [aut], Damjan Vukcevic [aut]

prefviz_0.1.3.tar.gz
prefviz_0.1.3.zip(r-4.7)prefviz_0.1.3.zip(r-4.6)prefviz_0.1.3.zip(r-4.5)
prefviz_0.1.3.tgz(r-4.6-any)prefviz_0.1.3.tgz(r-4.5-any)
prefviz_0.1.3.tar.gz(r-4.7-any)prefviz_0.1.3.tar.gz(r-4.6-any)
prefviz_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
prefviz/json (API)

# Install 'prefviz' in R:
install.packages('prefviz', repos = c('https://numbats.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/numbats/prefviz/issues

Pkgdown/docs site:https://numbats.github.io

Datasets:
  • aecdop_2022 - Distribution of preferences by candidate by division in the Australian Federal Election
  • aecdop_2025 - Distribution of preferences by candidate by division in the Australian Federal Election
  • aecdop22_transformed - Distribution of preferences in wide form for selected parties
  • aecdop25_transformed - Distribution of preferences in wide form for selected parties
  • elb_centroid - Centroids of electoral divisions in the 2025 Australian Federal Election
  • elb_map - Electoral boundaries map for the 2025 Australian Federal Election

On CRAN:

Conda:

5.98 score 1 stars 15 scripts 441 downloads 18 exports 32 dependencies

Last updated from:4561c33def. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK176
source / vignettesOK216
linux-release-x86_64OK154
macos-release-arm64OK81
macos-oldrel-arm64OK92
windows-develOK118
windows-releaseOK101
windows-oldrelOK121
wasm-releaseOK123

Exports:add_ternary_baseadd_vertex_labelsas_ternabledop_bardop_irvdop_transformgeom_ternary_regionget_tern_data2dget_tern_datahdget_tern_edgesget_tern_labelshelmert_transformpairwise_calculatorpairwise_heatmapstat_ordered_pathstat_ternary_regionStatOrderedPathStatTernaryRegion

Dependencies:bitopsclicpp11dplyrfarvergenericsgeozooggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigprefiopurrrR6RColorBrewerrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Adding ordered path to your ternary plot
2D ternary plot | High-dimensional ternary plot
Rendered fromadd_ordered_path.Rmdusingknitr::rmarkdown

Last update: 2026-04-21
Started: 2026-01-20

Using ternable object to draw ternary plots
ternable object | ternable helpers - get_tern_*() | Drawing a 2D ternary plot | Drawing a high-dimensional ternary plot
Rendered fromdraw_ternary_plot.Rmdusingknitr::rmarkdown

Last update: 2026-04-21
Started: 2025-12-31

Transforming voting data to ternable-friendly format
Introduction | ternable-friendly data | PrefLib-formatted data | Raw ballot data in long and wide formats | AEC distribution of preferences
Rendered fromtransform_raw_data.Rmdusingknitr::rmarkdown

Last update: 2026-02-26
Started: 2025-12-18