cs448b-visualization

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	Choosing how to map data to visual properties, or evaluating if encodings are effective
chart-design.md	Deciding which chart type fits the data, or configuring axes/scales
d3-patterns.md	Writing D3.js code for bindings, scales, axes, transitions
interaction-animation.md	Adding brushing, filtering, tooltips, or animated transitions
color.md	Selecting color palettes or ensuring accessibility
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