Use it when you want to begin accessibility and standards work without writing the first draft from scratch.
Style Guide for Data Visualization AI Prompt
Create a data visualization style guide for this organization. Organization: {{organization}} Brand colors: {{brand_colors}} Primary tools: {{tools}} Typography system: {{typogr... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.
Create a data visualization style guide for this organization.
Organization: {{organization}}
Brand colors: {{brand_colors}}
Primary tools: {{tools}}
Typography system: {{typography}}
Audience for the style guide: {{audience}} (data analysts, developers, designers)
A style guide ensures all visualizations across the organization look coherent, communicate clearly, and meet accessibility standards.
1. Color system:
PRIMARY PALETTE (for data encoding):
- Primary: {{primary_color}} — use for the most important series or highlight
- Secondary: 3–5 supporting colors for categorical series
- Neutral: grey scale for non-data elements (axes, gridlines, background text)
- Alert: one red/orange for negative values or warnings
SEQUENTIAL PALETTES:
- Single-hue: light-to-dark of the primary color
- Multi-hue: define the start and end color (perceptually uniform progression)
DIVERGING PALETTES:
- Define: negative color, neutral midpoint color, positive color
RULES:
- Maximum 8 colors in any single chart
- Never use color as the only encoding (add labels, patterns, or shapes)
- All palettes must pass colorblind-safe test
2. Typography:
- Chart title: {{heading_font}}, {{title_size}}pt, bold
- Axis labels: {{body_font}}, 11pt, regular
- Data labels: {{body_font}}, 10pt, regular
- Annotations: {{body_font}}, 10pt, italic
- Numbers: use tabular figures (all same width) for alignment in tables
3. Chart formatting standards:
- Minimum chart width: 480px (for web); 3 inches (for print)
- Minimum height: 60% of width for most charts
- Background: white (#FFFFFF) or transparent
- Gridlines: horizontal only, light grey (#E0E0E0), 0.5pt
- No chart borders or shadows
- Axis lines: left axis only (y-axis), light grey, 0.5pt
- Tick marks: none unless necessary
4. Chart title standards:
- Format: insight statement (not a label)
- Length: 1 line maximum for presentation; 2 lines for reports
- Capitalization: sentence case (not title case)
- No period at end of title
5. Number formatting:
- Revenue: $1.2M (> $1M), $456K (> $1K), $123 (< $1K)
- Percentages: 23.4% (1 decimal), 100% (no decimal)
- Counts: comma separator every 3 digits
- Dates: 'Jan 2024' for months, 'Q1 2024' for quarters, '2024' for years
- Ratios: 2.3× (not 2.3x)
6. Template files:
- Provide: Tableau workbook template, Power BI template file, Python rcParams settings
Return: complete style guide document with all specifications, hex codes, template settings for each tool, and a one-page quick reference card.When to use this prompt
Use it when you want a more consistent structure for AI output across projects or datasets.
Use it when you want prompt-driven work to turn into a reusable notebook or repeatable workflow later.
Use it when you want a clear next step into adjacent prompts in Accessibility and Standards or the wider Data Visualization Specialist library.
What the AI should return
The AI should return a structured result that covers the main requested outputs, such as Color system:, Primary: {{primary_color}} — use for the most important series or highlight, Secondary: 3–5 supporting colors for categorical series. The final answer should stay clear, actionable, and easy to review inside a accessibility and standards workflow for data visualization specialist work.
How to use this prompt
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in Accessibility and Standards.
Frequently asked questions
What does the Style Guide for Data Visualization prompt do?+
It gives you a structured accessibility and standards starting point for data visualization specialist work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for data visualization specialist workflows and marked as advanced, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Style Guide for Data Visualization is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are Accessibility Audit for Data Viz.