Data Visualization

When to Use

• Choose chart types that match the analytical question and audience decision
• Apply design principles: honest axes, labels, color, hierarchy, small multiples
• Meet accessibility needs: colorblind-safe palettes, contrast, alt-text guidance
• Design executive summaries and operational monitoring dashboards (layout and viz layer)
• Build actuarial/insurance views: loss triangles, trend panels, distributions, scenario bands
• Audit or fix misleading charts (truncated axes, dual-axis abuse, cherry-picking)
• Write viz specs for engineers (data bindings, encodings) or slide narrative outlines
• Review matplotlib, plotly, ggplot, or BI tool outputs for clarity and integrity

When NOT to Use