data-visualizationlisted

# Data Visualization Use these principles when designing, reviewing, or implementing data visualizations. Source rationale and extended examples live in `references/chart-principles.md` — read it when a decision needs more justification than the checklist below gives. ## 1. Choose a familiar chart type Prefer chart types users already know how to read: bar/column, line, area, pie/donut. Don't invent a novel chart type (streamgraphs, etc.) unless there's a clear, specific usability win over a familiar one. ## 2. Limit pie charts to 5 slices If a pie chart is the right call, cap it at 5 slices. Past that, switch to a bar chart — it handles more categories and comparison is easier than eyeballing angles. ## 3. Order categorical data Sort bar/column data ascending or descending unless there's an inherent order (e.g. time). Time-series data stays chronological — never re-sorted by value. ## 4. No 3D charts 3D effects distort area/angle perception and add nothing. Never use them for decoration. ## 5. Use an intentional color palette Don't rely on auto-generated/random series colors. Pick a deliberate palette that fits the product's visual language, keeps series distinguishable, holds contrast, and is consistent in meaning across the app (e.g. the same category is always the same color). Never make color the only channel carrying essential information — pair it with position, label, or pattern. ## 6. Don't depend on tooltips Tooltips are supplementary. Primary values an