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Principles for Clear & Honest Data Visualizations
Good visualizations make patterns obvious and decisions easier. Bad ones confuse or mislead. This section focuses on the theory behind clear charts, not a specific plotting library.
Choosing the Right Chart Type
Your choice of chart should reflect the relationship you want to show:
- Comparison: bar chart, grouped bar, line chart for time series.
- Distribution: histogram, box plot, violin plot, density plot.
- Relationship: scatter plot, bubble chart, heatmap.
- Composition: stacked bar chart, 100% stacked bar (avoid pie charts for many categories).
Color & Human Perception
Colors should encode information, not distract. Use color sparingly to highlight important elements and respect accessibility (color‑blind safe palettes).
- Use a neutral base color and a strong accent color for highlights.
- Avoid using too many categorical colors; group or filter instead.
- Don’t rely on color alone to encode critical information; use shapes or labels as well.
Avoid Misleading Visualizations
Small formatting decisions can significantly change the message. Always aim for honest, reproducible charts that match the underlying data.
- Start axes at zero when comparing magnitudes in bar charts.
- Keep aspect ratios reasonable so slopes are not exaggerated.
- Label units, time ranges and filters clearly.