/visualization-skill

name: cs448b-visualization
description: "Data visualization design based on Stanford CS448B. Use for: (1) choosing chart types, (2) selecting visual encodings, (3) critiquing visualizations, (4) building D3.js visualizations, (5) designing interactions/animations, (6) choosing colors, (7) visualizing networks, (8) visualizing text. Covers Bertin, Mackinlay, Cleveland & McGill."

CS448B Visualization

When to Use Each Reference

| Reference | Use When | |-----------|----------| | [encoding-perception.md](references/encoding-perception.md) | Choosing how to map data to visual properties, or evaluating if encodings are effective | | [chart-design.md](references/chart-design.md) | Deciding which chart type fits the data, or configuring axes/scales | | [d3-patterns.md](references/d3-patterns.md) | Writing D3.js code for bindings, scales, axes, transitions | | [interaction-animation.md](references/interaction-animation.md) | Adding brushing, filtering, tooltips, or animated transitions | | [color.md](references/color.md) | Selecting color palettes or ensuring accessibility | | [networks-text.md](references/networks-text.md) | Visualizing graphs, hierarchies, or text/document data |

Critique Checklist

When reviewing any visualization:

1. **Expressiveness** - Does it show all the data? Only the data? No misleading elements? 2. **Effectiveness** - Is the most important data on the most accurate encoding (position > length > area > color)? 3. **Zero baseline** - Do bar charts start at zero? 4. **Accessibility** - Works for colorblind viewers (~8% of males)? 5. **Data-ink ratio** - Can any non-data elements be removed? 6. **Aspect ratio** - Are line charts banked so slopes are ~45°?

Encoding Decision Order

When mapping data fields to visual channels:

1. Most important quantitative → Position (x or y) 2. Second quantitative → Position (other axis) or Length 3. Categories (≤7) → Color hue 4. Categories (>7) → Position or small multiples 5. Magnitude/importance → Size (but expect ~30% underestimation)

Chart Selection Logic

• **One variable, distribution** → Histogram
• **One variable, categories** → Bar chart
• **Two variables, both quantitative** → Scatterplot
• **Two variables, time + quantitative** → Line chart
• **Two variables, both categorical** → Heatmap
• **Hierarchy** → Treemap or node-link tree
• **Network (sparse)** → Force-directed layout
• **Network (dense)** → Matrix diagram

Animation Decision

• **Presentation context** → Use animation (faster, engaging)
• **Analysis context** → Use small multiples (more accurate)
• **State transitions** → Animate to maintain object constancy
• **Duration**: 200-300ms quick feedback, 500-700ms standard, 1000ms+ complex