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GoldenViz @goldenviz.bsky.social · 05/08/2026

✨GoldenVizR v0.1.0 is now available on CRAN. review your ggplot2 visualizations against 25 rules covering completeness, readability, and integrity, and generate structured feedback and HTML reports. 🔽 install.packages("GoldenVizR") cran.r-project.org/package=Gold... #rstats #Dataviz #Tidytuesday

cran.r-project.org

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 <<a href="https://goldenviz.org/" target="_top">https://golde...

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GoldenViz @goldenviz.bsky.social · 24/07/2026

🔹A chart should represent data honestly without misleading the reader. 🔹The Integrity principle covers : - truthful scales, - baselines, - uncertainty, - outliers, - proportional areas, - data selection, - granularity, - and neutral framing. 🟣 Nine rules from GoldenViz. goldenviz.org

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GoldenViz @goldenviz.bsky.social · 24/07/2026

🔹 A chart should be readable without unnecessary effort. 🔹 The Readability principle addresses: - typography, - accessible colors, clutter, scales, formatting, chart choice, direct labels, and visual hierarchy. 🟣 Ten rules from the GoldenViz framework. goldenviz.org

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GoldenViz @goldenviz.bsky.social · 24/07/2026

🔹 A chart should give readers everything they need to interpret it 🔹 The Completeness principle covers: -clear titles, - labelled axes, - missing data, - legends, - sources, - context, - and useful annotations. 🟣 Six rules from the 25 Golden Rules of Data Visualization goldenviz.org

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GoldenViz @goldenviz.bsky.social · 22/07/2026

GoldenVizR outputs rule-level results with PASS, WARNING, FAIL, and INFO statuses, summary counts, and formatted HTML reports for notebooks, reports, dashboards, and review workflows. github.com/WajdiBenSaad... #RStats #DataViz #ggplot2

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GoldenViz @goldenviz.bsky.social · 22/07/2026

GoldenVizR is an R package for reviewing ggplot2 visualizations against 25 practical rules covering completeness, readability, and integrity. It helps identify missing context, unclear labels, misleading scales, visual clutter, and other common issues.

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GoldenViz @goldenviz.bsky.social · 22/07/2026

📣 GoldenVizR v0.1.0 is now available on GitHub. An R package providing rule-based quality checks for ggplot2 visualizations, based on the 25 Golden Rules of Data Visualization. to try : 🔽 github.com/WajdiBenSaad... #RStats #DataViz #ggplot2 #TidyTuesday

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GoldenViz @goldenviz.bsky.social · 06/07/2026

That’s the foundation of GoldenViz: 1️⃣ Completeness gives the reader context. 2️⃣ Readability makes the message easy to decode. 3️⃣ Integrity keeps the visualization honest. You can explore the book, the rules, and the GoldenViz library here: goldenviz.org

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GoldenViz @goldenviz.bsky.social · 06/07/2026

Principle 3: Integrity A good chart should represent the data honestly. Scales, colors, chart types, baselines, and aspect ratios can all change how people perceive the message. The goal is not to make the data look impressive. The goal is to make it truthful. #DataViz #GoldenViz

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GoldenViz @goldenviz.bsky.social · 06/07/2026

Principle 2: Readability A good chart should be easy to decode at a glance. Clear labels, simple hierarchy, thoughtful colors, and reduced visual clutter help the reader focus on the message instead of fighting the design. Clarity first. Decoration second. #DataViz #GoldenViz

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GoldenViz @goldenviz.bsky.social · 06/07/2026

Principle 1: Completeness A good chart should not make the reader guess. The title, labels, units, legend, and annotations should give enough context to understand what the chart shows and why it matters. A chart is incomplete when the data is visible, but the meaning is not. #DataViz #GoldenViz

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GoldenViz @goldenviz.bsky.social · 06/07/2026

Let’s start the week with a focus on knowledge sharing and practical #DataViz principles. Before diving into the 25 Golden Rules of Data Visualization, here are the 3 core principles behind the #GoldenViz book and library: - Completeness - Readability - Integrity 🔽 🔽 🔽 🔽 🔽

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GoldenViz @goldenviz.bsky.social · 01/07/2026

Before publishing a chart, ask 3 questions: 1. Is it complete? 2. Is it easy to read? 3. Can the reader trust it? That’s the idea behind this GoldenViz cheat sheet: 25 practical rules to make charts clearer, cleaner, and more honest. #DataViz #Python #TidyTuesday #DataScience

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GoldenViz @goldenviz.bsky.social · 23/06/2026

If you want to go deeper, here is the free online book/course explaining the full framework: "The 25 Golden Rules of Data Visualization" It includes the 3 principles, all 25 rules, examples, bad chart case studies, and practical guidance for teaching or self-study. 👇 www.goldenviz.org

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GoldenViz @goldenviz.bsky.social · 23/06/2026

3. Integrity A chart must not mislead. Scales, chart types, color maps, dual axes, baselines, aspect ratios, and zero references can all distort interpretation. A good chart respects the data and the reader. #DataViz

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GoldenViz @goldenviz.bsky.social · 23/06/2026

2. Readability A chart must be easy to decode. Labels, colors, categories, precision, dates, and visual complexity should help the reader, not slow them down. A good chart reduces unnecessary effort. #DataViz

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GoldenViz @goldenviz.bsky.social · 23/06/2026

1. Completeness A chart must give the reader enough information to understand it. That means clear titles, axis labels, units, legends, annotations, and uncertainty cues when needed. If the chart is incomplete, interpretation starts with guesswork. #DataViz

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GoldenViz @goldenviz.bsky.social · 23/06/2026

Today, let’s talk about the 25 Golden Rules of Data Visualization. They are organized around 3 core principles: - Completeness - Readability - Integrity Each rule helps answer a simple question: is the chart understandable, readable, and honest? www.goldenviz.org ⬇️

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GoldenViz @goldenviz.bsky.social · 22/06/2026

Here they are, the first 5 rules of the @goldenviz.bsky.social Library. if you want to go further, follow us, and visit: goldenviz.org/en/ #30DayChartChallenge #DataViz #DataScience

goldenviz.org

The 25 Golden Rules of Data Visualization

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GoldenViz @goldenviz.bsky.social · 22/06/2026

🟥 Rule 5 · Annotation context Important events or takeaways should be visible when they explain the pattern. Some charts need more than labels and scales. They need a visible message. A short sentence inside the figure can sometimes do more than a paragraph outside it.

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GoldenViz @goldenviz.bsky.social · 22/06/2026

🟥 Rule 4 · Legend clarity The reader needs a clean bridge between the marks and their meaning. If that bridge is weak, reading slows down immediately. A missing legend delays interpretation. A vague legend weakens the chart even when the graphic itself is technically correct.

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GoldenViz @goldenviz.bsky.social · 22/06/2026

🟥 Rule 3 · Units and scale clarity A value without a unit is incomplete information. This matters even more when a figure circulates outside the notebook or slide deck in which it was created. goldenviz.org/en/completen...

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GoldenViz @goldenviz.bsky.social · 22/06/2026

🟥 Rule 2 · Axis labels Axis labels and units make the measurement unambiguous. Axes are not decoration. They tell the reader what the values mean. Without them, even a visually clean chart can remain ambiguous. goldenviz.org/en/completen...

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GoldenViz @goldenviz.bsky.social · 22/06/2026

🟥 Rule 1 · Clear title A title should tell the reader what the chart is about before they inspect the marks. A good title should not merely name a topic. It should help frame what the chart is about. goldenviz.org/en/completen...

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GoldenViz @goldenviz.bsky.social · 22/06/2026

Let's go a bit deeper into the 25 Golden Rules of Data Viz. Today we will share the first five rules, with some examples ( very simplified) to allow you to understand the rule's main impact 👇

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GoldenViz @goldenviz.bsky.social · 21/06/2026

GoldenViz is paired with an open online book explaining the 25-rule framework behind the library, with examples, bad chart case studies, and teaching material. goldenviz.org

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GoldenViz @goldenviz.bsky.social · 21/06/2026

GoldenViz generates an HTML report that summarizes chart quality at a glance: PASS, WARNING, and FAIL checks are grouped by chart axis, with each issue linked to a specific rule and followed by a short explanation or suggested fix.

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GoldenViz @goldenviz.bsky.social · 21/06/2026

GoldenViz is a Python library that makes data visualization feedback more systematic. It checks charts against 25 rules covering completeness, readability, and integrity. Goal: help students, analysts, and educators identify common chart problems faster and explain them clearly

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GoldenViz @goldenviz.bsky.social · 21/06/2026

📣 GoldenViz 1st stable release is out: v0.1.1 A Python library to check & improve charts using the 25 Golden Rules of Data Visualization. Features: chart diagnostics, rule-based feedback, teaching examples. Useful for students, analysts and educators 👇 goldenviz.readthedocs.io

goldenviz.readthedocs.io

GoldenViz documentation — GoldenViz 0.1.1 documentation

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