T.I.L Pill | Different Color Palettes for Data Visualization

In Data Visualization, there are 3 main uses of color to effectively communicate content within a dashboard- Categorical, Sequential, and Diverging. There are also other common ways to utilize color for specific purposes. In this article, we will take a quick look at these color schemes to introduce the concept, or to serve as a refresher resource to anyone who needs a bit of review. Also, this is the start of a new series of short-form articles called T.I.L Pill!

Uniform

Uniform color palettes prioritize consistency and clarity, using a very limited set of colors throughout the visualization. They are suitable for maintaining a cohesive visual language and ensuring clarity in conveying information. Uniform palettes are commonly used for maintaining brand consistency and visual hierarchies. However, with using such a scheme where everything is the same color or colored in a way not related to the data, nothing about the data stands out.

Categorical

Categorical color palettes - also refereed to as qualitative palettes, assign distinct colors to different categories or groups without inherent ordering within a dataset. They help viewers quickly distinguish between categories and make comparisons. It's recommended to limit the maximum palette size to 10 or fewer colors to avoid trouble distinguishing between groups. If there are more possible values than colors, bundling values together or using an "other" category is suggested.

Sequential

Sequential color palettes consist of a range of colors that gradually transition from light to dark or vice versa. They are ideal for representing data that follows a progression or scale, like measure values such as population density or temperature. Sequential palettes help viewers understand the increasing or decreasing nature of the data. Remember to consider the background color of your visualization and adapt the palette accordingly to maintain optimal contrast.

Diverging

Diverging color palettes use colors that fork from a central color, representing positive and negative deviations from a midpoint or a neutral value. They are useful for highlighting contrasts and differences within a dataset. They are particularly useful when visualizing a critical value to focus on. Select two colors that are visually distinct and have a significant contrast to clearly represent the positive and negative aspects of the data.

Highlighting

Highlighting color palettes aim to draw attention to specific data points, patterns, or insights within a visualization. They consist of colors that emphasize without conveying immediate urgency or alarm. Highlighting palettes are effective when there is a need to guide viewers' attention and emphasize critical information without overpowering the overall visualization. Standard practice for highlighting palettes involve choosing a hue for the intended marks, and using a desaturated -or gray color for the other marks.

Alerting

Alerting color palettes are designed to immediately grab attention and specifically convey a sense of urgency or alarm. They often employ bold, vibrant, and intense colors that stand out from the rest of the visualization. Alerting palettes are suitable for highlighting critical or alarming information that requires immediate attention, such as error messages or warning signs. These colors are usually paired with contrasting -often uniform colors for the rest of the marks to ensure clarity of the urgency.

Remember, the right choice of colors can make a significant difference in the clarity and impact of your charts and graphs, facilitating a better understanding of the information you present. By using these guidelines, you can create visually appealing and informative visualizations that effectively communicate your data and insights!

Author:
Marc-Anthony Tucker
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