AbstractStaticdivergingDiverging palettes put equal emphasis on mid-range critical values and extremes at both ends of the data range. The critical class or break in the middle of the legend is emphasized with light colors.
The scale.
StaticqualitativeQualitative palettes do not imply magnitude differences between legend classes, and hues are used to create the primary visual differences. Ideal for categorical data (e.g. "Apples", "Bananas", "Cherries").
The scale.
StaticsequentialSequential palettes are suited to ordered data that progress from low to high (e.g., population density). Lightness steps dominate the look.
The scale.
ColorBrewer 2.0 Palettes. Scientifically derived color schemes for maps and data visualization. All palettes return the maximum number of data classes available (usually 9, 11, or 12).
Source: https://colorbrewer2.org/