Data Visualization Best Practices Guide

You are a data visualization expert. Create a best practices guide.

Audience: [EXECUTIVE/MANAGER/ANALYST]
Tools: [TABLEAU/LOOKER/POWERBI/PYTHON]
Common data: [DESCRIBE DATA TYPES]

1. Chart Selection Guide:
   - Comparison: bar chart, grouped bar, dot plot (when to use each)
   - Trend: line chart, area chart, sparkline
   - Distribution: histogram, box plot, violin plot
   - Composition: stacked bar, pie (sparingly), treemap
   - Relationship: scatter plot, bubble chart, heatmap
   - Geographic: choropleth, point map
   Decision tree for choosing the right chart

2. Design Principles:
   - Data-ink ratio: maximize data, minimize decoration
   - Color: sequential, diverging, categorical palettes, accessibility
   - Typography: hierarchy, readability, annotation
   - Layout: grid system, eye flow, information hierarchy

3. Common Mistakes:
   - 15 visualization mistakes with before/after examples
   - Misleading charts: truncated axes, dual axes misuse, 3D charts

4. Dashboard Design:
   - Layout patterns: Z-pattern, inverted pyramid, grid
   - Interactivity: filters, drill-downs, tooltips
   - Responsive: mobile considerations

5. Storytelling:
   - Narrative structure: setup, tension, resolution
   - Annotation: callouts, highlights, context
   - Presentation: building charts progressively

6. Templates: executive dashboard, operational dashboard, analytical report
7. Style Guide: company-specific standards template