Sequential vs Diverging Color Palettes in Data Visualization
When to use sequential vs diverging color palettes in charts. Covers use cases, example schemes, and tools for generating each type.
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Tags: color, data-visualization, design
Sequential vs Diverging Color Palettes in Data Visualization Choosing the wrong palette type doesn't just make a chart look bad — it encodes false information. A diverging palette on one-sided data implies a midpoint that doesn't exist. A sequential palette on deviation data hides whether values are above or below the baseline. This guide covers when each type applies, how to implement them in D3 and matplotlib, and examples from real dashboard design. --- The Core Question: Does Your Data Have a Meaningful Midpoint? That single question determines your palette choice 90% of the time. No meaningful midpoint → Sequential palette Yes, meaningful midpoint → Diverging palette A "meaningful midpoint" means zero, a target, an average, or any threshold where values on either side represent…
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