Diverging Color Palettes

Diverging color palettes are used to visualize data that has a central point of reference, often zero or another meaningful midpoint. These palettes are particularly useful for highlighting deviations from this central value. The colors diverge from the central point in two different directions, typically using contrasting hues or shades to represent positive and negative deviations.

Diverging color palette features:

• Central Color: This represents the central value or reference point in the dataset. It’s often a neutral color, such as white or gray, or a color that doesn’t carry much perceptual weight.
• Colors for Positive Deviations: These colors represent values above the central point and typically transition to darker shades or hues.
• Colors for Negative Deviations: These colors represent values below the central point and usually transition to lighter shades or hues.

The key feature of a diverging color palette is that it effectively shows both the direction and magnitude of deviations from the central value. This makes it useful for visualizing data where positive and negative deviations are equally important, such as comparing performance against a benchmark or showing changes from a baseline.

For example, in a choropleth map showing changes in unemployment rates, a diverging color palette might use shades of blue to represent decreases in unemployment rates below the national average (negative deviations) and shades of red to represent increases in unemployment rates above the national average (positive deviations), with white or gray representing areas where unemployment rates are close to the national average.

1. Blue to Red (Default)

Ideal for highlighting values around a midpoint, with cool blues and warm reds diverging from a neutral grey.

["#1984c5", "#22a7f0", "#63bff0", "#a7d5ed", "#e2e2e2", "#e1a692", "#de6e56", "#e14b31", "#c23728"]

2. Orange to Purple

Provides a stark contrast between warm orange and cool purple, suitable for emphasizing deviations from a central value.

["#ffb400", "#d2980d", "#a57c1b", "#786028", "#363445", "#48446e", "#5e569b", "#776bcd", "#9080ff"]

3. Pink Foam

Features a transition from teal to pink, offering a less conventional but visually appealing divergence.

["#54bebe", "#76c8c8", "#98d1d1", "#badbdb", "#dedad2", "#e4bcad", "#df979e", "#d7658b", "#c80064"]

4. Salmon to Aqua

Moves from salmon pink to aqua, effectively drawing attention to the extremes in data sets.

["#e27c7c", "#a86464", "#6d4b4b", "#503f3f", "#333333", "#3c4e4b", "#466964", "#599e94", "#6cd4c5"]

Data visualization is a powerful tool for presenting information in an effective manner. However, choosing the right colors for your visualizations can make a significant difference in how your audience interprets and understands the data. In this article, we’ll explore fantastic color palettes specifically designed for data visualization, covering a range of styles and purposes. paraphrase