Package: GoldenVizR 0.1.0

Wajdi Ben Saad

GoldenVizR: Rule-Based Quality Checks for 'ggplot2' Visualizations Based on the 25 Golden Rules of Data Visualization

Quality-checking tools for reviewing R data visualizations built with the 'ggplot2' library against the 25 GoldenViz rules described at <https://goldenviz.org/>. The package provides a visual QA and teaching layer that helps users identify common chart clarity, readability, and integrity issues.

Authors:Wajdi Ben Saad [aut, cre]

GoldenVizR_0.1.0.tar.gz
GoldenVizR_0.1.0.zip(r-4.7-any)GoldenVizR_0.1.0.zip(r-4.6-any)GoldenVizR_0.1.0.zip(r-4.5-any)
GoldenVizR_0.1.0.tgz(r-4.6-any)GoldenVizR_0.1.0.tgz(r-4.5-any)
GoldenVizR_0.1.0.tar.gz(r-4.7-any)GoldenVizR_0.1.0.tar.gz(r-4.6-any)
GoldenVizR_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GoldenVizR/json (API)

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

Bug tracker:https://github.com/wajdibensaad/goldenviz_r/issues

On CRAN:

Conda:

analyticschartsdata-analysisdatasciencedatavisualizationdatavizvisualization

5.85 score 7 stars 6 scripts 285 downloads 6 exports 21 dependencies

Last updated from:200a95083a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK112
source / vignettesOK172
linux-releaseOK107
macos-releaseOK184
macos-oldrelOK166
windows-develOK89
windows-releaseOK58
windows-oldrelOK87
wasm-releaseOK84

Exports:analyze_plotgoldenviz_check_rulesgoldenviz_rulesrender_reportsave_reportview_report

Dependencies:base64encclicpp11digestfarverfastmapggplot2gluegtablehtmltoolsisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

How GoldenVizR Checks Work
Inspection pipeline | Status logic | Evidence used by the rules | Current rule behavior | How legend clarity is interpreted | Why some rules return INFO | Practical interpretation
Rendered fromhow-checks-work.Rmdusingknitr::rmarkdown

Last update: 2026-07-05
Started: 2026-07-05

The 25 Golden Rules Behind GoldenVizR
Programmatic rule registry
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Last update: 2026-07-05
Started: 2026-07-05

Installation
Install from CRAN | Development version | Check your installation | Development setup
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Quickstart
Basic workflow | What the report contains | Manual analysis | Render an HTML report | How to read statuses
Rendered fromquickstart.Rmdusingknitr::rmarkdown

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Examples
Completeness | Rule 1: Clear title | Rule 2: Axis labels | Rule 3: Missing values and gaps | Rule 4: Legend clarity | Rule 5: Source and context | Rule 6: Annotation for key message | Readability | Rule 7: Readable text | Rule 8: Accessible color choices | Rule 9: Avoid clutter | Rule 10: Grid and guide balance | Rule 11: Consistent formatting | Rule 12: Appropriate chart type | Rule 13: Readable scale labels | Rule 14: Overplotting management | Rule 15: Direct labeling when useful | Rule 16: Visual hierarchy | Integrity | Rule 17: Truthful scale | Rule 18: No distorted baseline | Rule 19: Avoid misleading encodings | Rule 20: Handle outliers honestly | Rule 21: Proportional areas | Rule 22: Uncertainty when needed | Rule 23: Avoid cherry picking | Rule 24: Respect data granularity | Rule 25: Neutral framing
Rendered fromexamples.Rmdusingknitr::rmarkdown

Last update: 2026-07-05
Started: 2026-07-05