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unhcr-dataviz

Apply UNHCR data visualization guidelines to R, Python, and Plotly outputs.

Updated Apr 8, 2026
Search Tags:#plotly#matplotlib#palette#ggplot2#dataviz#unhcr#visualization-guidelines
One-click install
npx skills add https://github.com/masud90/unhcr_dataviz_claude_skill --skill unhcr-dataviz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: unhcr-dataviz
Source: https://github.com/masud90/unhcr_dataviz_claude_skill/tree/main
Command: npx skills add https://github.com/masud90/unhcr_dataviz_claude_skill --skill unhcr-dataviz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Teams struggle to consistently apply UNHCR's visual identity across dashboards, reports, and code-generated visuals.

Core Features & Use Cases

  • Guided visual standards: enforces UNHCR color palettes, typography (Lato), and layout for charts produced in R, Python, Plotly, and more.
  • Cross-language compatibility: usable with ggplot2, matplotlib, and Plotly workflows to ensure brand-consistent visuals.
  • Real-world use: generate publication-ready charts for displacement data, humanitarian reports, and dashboards with minimal customization.

Quick Start

Provide a UNHCR-branded chart example using your dataset.

Frequently Asked Questions about unhcr-dataviz

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I apply UNHCR data visualization guidelines to charts in Python and R?▼

To apply UNHCR data visualization guidelines, use this Skill to enforce UNHCR color palettes, Lato typography, and layout standards for charts generated in Python and R workflows like matplotlib and ggplot2.

Can I use Plotly to build interactive dashboards that follow UNHCR branding standards?▼

Yes, you can use Plotly to build interactive dashboards following UNHCR branding standards. This Skill guides color palettes, typography, layout, and attribution to ensure outputs meet UNHCR accessibility standards.

What is the best way to format displacement data visuals for humanitarian reports?▼

The best way to format displacement data visuals is by applying UNHCR visual guidelines to your code outputs. This ensures publication-ready charts, maps, and dashboards remain brand-consistent and accessible across various chart types.

Does this visualization guidance work with both matplotlib and ggplot2 workflows?▼

Yes, this visualization guidance works with both matplotlib and ggplot2 workflows. It offers cross-language compatibility to enforce UNHCR visual standards across R, Python, and other charting tools with minimal customization.

How do I ensure my generated charts meet UNHCR accessibility and visual identity standards?▼

To ensure your generated charts meet UNHCR accessibility and visual identity standards, apply the enforced color palettes, typography, and layout guidelines provided by this Skill across your displacement-related visuals and dashboards.

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