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data-visualization

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UpdatedMarch 11, 2026 at 22:42

Use when creating charts, plots, graphs, dashboards, Excel reports with openpyxl, infographics, generative art, statistical plots, animations, heatmaps, treemaps, sankey diagrams, choropleth maps, geographic maps, network graphs, D3.js custom visualizations, or accessible data visualizations (WCAG, colorblind-safe palettes, alt text for charts). Tools: matplotlib, plotly, seaborn, D3, Dash, p5.js, openpyxl, Pillow, Folium, NetworkX, bokeh.

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Software DevelopersComputer and Mathematical Occupations·SOC 15-1252

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SKILL.md

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data-visualization

description

Data Visualization

Master skill for static plots, interactive charts, dashboards, infographics, and generative art. Routes to specialized references by task type.

Task Router

Need	Tool	Reference
Static plots, publication figures, subplots	Matplotlib	references/matplotlib.md
Statistical plots (distributions, regressions)	Seaborn + Matplotlib	references/matplotlib.md
Deep statistical: pairplot, QQ, forest, survival	Seaborn + lifelines	references/statistical-plots.md
Interactive charts, hover/zoom/pan	Plotly Express / GO	references/plotly.md
Dashboards with callbacks, multi-page apps	Plotly Dash	references/plotly.md
Real-time / live dashboards, streaming	Plotly Dash	references/realtime-dashboards.md
Geographic maps, choropleth, GIS	Plotly / Folium	references/geographic-maps.md
Network graphs, Sankey, treemap, sunburst	Plotly + NetworkX	references/network-graphs.md
WCAG accessibility, color blindness, alt text	Best practices	references/accessibility-compliance.md
Custom web viz, D3 force layout, React + D3	D3.js	references/d3-custom-viz.md
AI-generated infographics, data storytelling	Gemini MCP	references/infographics.md
Generative art, flow fields, particle systems	p5.js	references/generative-art.md
Excel charts, pivot tables, conditional formatting	openpyxl	references/excel-charts.md
Color themes, palette selection, styling	Theme factory	references/color-themes.md
Animated GIFs, PIL animation, easing	Pillow / matplotlib	references/animated-visualizations.md

Decision Tree

Output type?
  ART (generative, algorithmic) --> p5.js (references/generative-art.md)
  INFOGRAPHIC (visual storytelling) --> Gemini MCP (references/infographics.md)
  ANIMATED GIF --> PIL + easing (references/animated-visualizations.md)
  EXCEL FILE --> openpyxl (references/excel-charts.md)
  COLOR THEME --> references/color-themes.md
  DATA CHART -->
    Interactivity needed?
      YES + dashboard --> Plotly Dash
      YES + standalone --> Plotly Express
      NO + statistical --> Seaborn
      NO + general --> Matplotlib OO API
    3D? --> Plotly (interactive) or mplot3d (static)
    Maps? --> references/geographic-maps.md
    Networks? --> references/network-graphs.md
    Live data? --> references/realtime-dashboards.md
    Accessibility? --> references/accessibility-compliance.md

Quick Reference

Matplotlib: Always OO interface: fig, ax = plt.subplots(figsize=(10,6), constrained_layout=True). Save: plt.savefig('fig.png', dpi=300, bbox_inches='tight'). Close: plt.close(fig).

Plotly: Two APIs — px (high-level) and go (fine control). Export: write_html() (interactive) or write_image() (static, needs kaleido).

Colormaps: viridis (default), cividis (colorblind-safe), coolwarm (diverging). Avoid jet.

Accessibility: Colorblind-safe palettes always. Never encode meaning with color alone. Add patterns/markers alongside color. Min contrast 4.5:1 text, 3:1 graphical. Alt text for every saved image.

Performance: >100k points → rasterized=True (mpl) or scattergl (Plotly). Always plt.close(fig) after saving.

Layer 3 Skills

Skill	Use when
`matplotlib`	Static plots, publication figures, animations
`plotly`	Interactive charts, Dash dashboards
`statistical-plots`	Pairplot, QQ, forest plot, survival analysis
`generative-art`	p5.js algorithmic art, flow fields
`infographics`	AI-generated visual data storytelling
`geographic-maps`	Choropleth, scatter maps, Folium, GIS
`network-graphs`	Sankey, treemap, force-directed, NetworkX
`realtime-dashboards`	Live/streaming data, dcc.Interval
`d3-custom-viz`	Custom D3.js, React + D3
`excel-charts`	openpyxl charts, pivot tables
`color-themes`	Palette selection, professional styling
`animated-visualizations`	GIFs, PIL animation, easing functions
`accessibility-compliance`	WCAG, color blindness, ARIA

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name

data-visualization

description

Data Visualization

Master skill for static plots, interactive charts, dashboards, infographics, and generative art. Routes to specialized references by task type.

Task Router

Need	Tool	Reference
Static plots, publication figures, subplots	Matplotlib	references/matplotlib.md
Statistical plots (distributions, regressions)	Seaborn + Matplotlib	references/matplotlib.md
Deep statistical: pairplot, QQ, forest, survival	Seaborn + lifelines	references/statistical-plots.md
Interactive charts, hover/zoom/pan	Plotly Express / GO	references/plotly.md
Dashboards with callbacks, multi-page apps	Plotly Dash	references/plotly.md
Real-time / live dashboards, streaming	Plotly Dash	references/realtime-dashboards.md
Geographic maps, choropleth, GIS	Plotly / Folium	references/geographic-maps.md
Network graphs, Sankey, treemap, sunburst	Plotly + NetworkX	references/network-graphs.md
WCAG accessibility, color blindness, alt text	Best practices	references/accessibility-compliance.md
Custom web viz, D3 force layout, React + D3	D3.js	references/d3-custom-viz.md
AI-generated infographics, data storytelling	Gemini MCP	references/infographics.md
Generative art, flow fields, particle systems	p5.js	references/generative-art.md
Excel charts, pivot tables, conditional formatting	openpyxl	references/excel-charts.md
Color themes, palette selection, styling	Theme factory	references/color-themes.md
Animated GIFs, PIL animation, easing	Pillow / matplotlib	references/animated-visualizations.md

Decision Tree

Output type?
  ART (generative, algorithmic) --> p5.js (references/generative-art.md)
  INFOGRAPHIC (visual storytelling) --> Gemini MCP (references/infographics.md)
  ANIMATED GIF --> PIL + easing (references/animated-visualizations.md)
  EXCEL FILE --> openpyxl (references/excel-charts.md)
  COLOR THEME --> references/color-themes.md
  DATA CHART -->
    Interactivity needed?
      YES + dashboard --> Plotly Dash
      YES + standalone --> Plotly Express
      NO + statistical --> Seaborn
      NO + general --> Matplotlib OO API
    3D? --> Plotly (interactive) or mplot3d (static)
    Maps? --> references/geographic-maps.md
    Networks? --> references/network-graphs.md
    Live data? --> references/realtime-dashboards.md
    Accessibility? --> references/accessibility-compliance.md

Quick Reference

Matplotlib: Always OO interface: fig, ax = plt.subplots(figsize=(10,6), constrained_layout=True). Save: plt.savefig('fig.png', dpi=300, bbox_inches='tight'). Close: plt.close(fig).

Plotly: Two APIs — px (high-level) and go (fine control). Export: write_html() (interactive) or write_image() (static, needs kaleido).

Colormaps: viridis (default), cividis (colorblind-safe), coolwarm (diverging). Avoid jet.

Performance: >100k points → rasterized=True (mpl) or scattergl (Plotly). Always plt.close(fig) after saving.

Layer 3 Skills

Skill	Use when
`matplotlib`	Static plots, publication figures, animations
`plotly`	Interactive charts, Dash dashboards
`statistical-plots`	Pairplot, QQ, forest plot, survival analysis
`generative-art`	p5.js algorithmic art, flow fields
`infographics`	AI-generated visual data storytelling
`geographic-maps`	Choropleth, scatter maps, Folium, GIS
`network-graphs`	Sankey, treemap, force-directed, NetworkX
`realtime-dashboards`	Live/streaming data, dcc.Interval
`d3-custom-viz`	Custom D3.js, React + D3
`excel-charts`	openpyxl charts, pivot tables
`color-themes`	Palette selection, professional styling
`animated-visualizations`	GIFs, PIL animation, easing functions
`accessibility-compliance`	WCAG, color blindness, ARIA