Dopely Colors
Data Visualization

Multi-Variable Encoder

Encode complex datasets into color. Map different data variables (X, Y, Z) to color dimensions (Hue, Saturation, Lightness) to reveal hidden patterns.

Mapping Strategy

Best for categorical or primary linear data.

Use for confidence or magnitude.

Use for density or secondary magnitude.

Variables Plot (X vs Y)

X: HueY: Sat

Why encode data into color?

Standard charts typically use position (X/Y) to show relationships. By encoding a 3rd or 4th variable into Color (Hue) and Intensity (Saturation), you can visualize higher-dimensional data on a 2D screen. This is crucial for identifying clusters in complex datasets like user cohorts, scientific measurements, or financial portfolios.

Multi-Variable Encoder

Encode more data. Use Hue, Saturation, and Lightness to represent three different data dimensions simultaneously.

Bivariate & Trivariate Maps

Visualize complex relationships (e.g., Population Density vs. Income) by mixing two color scales. This tool helps you balance the scales so the resulting mixed colors are still decipherable and meaningful.