Color new - Data visualization - Foundations - Atlassian Design System (2024)

Data visualization is the representation of information in pictorial or graphical format, such as charts, graphs, maps, and diagrams. These visuals aid in the communication of complex data so that insights can be more easily drawn.

Because color can affect our perception of information, the appropriate use of color is critical in making a data visualization successful.

Applying color to data visualizations

Color in Atlassian product experiences are applied using design tokens. For data visualization, chart color tokens are available to ensure appropriate color contrasts can be met.Use chart tokens for lines, bars or other UI representing the data. For elements of the chart interface such as axes and text, use border and text tokens.

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  1. Title: color.text

  2. Tick label: color.text.subtle

  3. Threshold or reference line: color.chart.neutral

  4. Legend: color.text

  5. Gridline: color.border

  6. Mark: color.chart.brand

Types of chart colors

  1. Single-color charts

  2. Categorical

  3. Status and severity

  4. Custom charts

Sequential and divergent chart colors are not currently supported.

Single-color charts

For data visualization requiring only one color, use color.chart.brand as the default color choice. This ensures all data visualization embodies our brand’s visual language.

If the data represents status or severity, use the appropriate status or severity color token instead.

To highlight one piece of data from a data set, use color.chart.neutral for the less important information so that the important data can stand out.

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TokenDescription

color.chart.brand

Our primary color for data visualization. Use when only one color is required.

color.chart.neutral

A secondary color for data visualization. Use for the less important data when you want other data to stand out.

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Do

Use a single color as the default for data visualizations. Only add more colors when needing to differentiate between data categories.

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Don't

Don’t use more than one color in your data visualization if the additional colors don’t serve any communication purpose.

Categorical

Use categorical chart colors when you need to differentiate two or more unrelated data categories from each other.

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Follow the same sequence as the numbers in the token names. This ensures each color is visually distinct from its neighbors across all color deficiencies. If the display order can't be controlled (in line charts for example), provide additional visual indicators.

TokenDescription

color.chart.categorical.1

For data visualization only. Follow the numbered sequence.

color.chart.categorical.2

For data visualization only. Follow the numbered sequence.

color.chart.categorical.3

For data visualization only. Follow the numbered sequence.

color.chart.categorical.4

For data visualization only. Follow the numbered sequence.

color.chart.categorical.5

For data visualization only. Follow the numbered sequence.

color.chart.categorical.6

For data visualization only. Follow the numbered sequence.

color.chart.categorical.7

For data visualization only. Follow the numbered sequence.

color.chart.categorical.8

For data visualization only. Follow the numbered sequence.

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Do

Limit the number of colors presented in your data visualization to 5-6 by grouping additional categories together.

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Don't

Avoid using more than 5-6 colors in a data visualization. Too many colors can hinder comprehension.

Status and severity

These chart colors use established color associations for status and severity, such as in progress, at risk, or high priority. Use these when you want to reinforce meaning through color in your data visualization.

If more than one set of data exists for a given color association, use bold emphasis to represent the more extreme value. For example, High priority and Highest priority both use danger tokens, but Highest uses color.chart.danger.bold.

It’s important to note that status and severity colors may be hard for users with color deficiencies to tell apart. For this reason, use other visual indicators or consider categorical colors as a better option.

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TokenDescription

color.chart.success

color.chart.success.bold

For data visualization communicating positive information, such as 'on track' or done.

color.chart.warning

color.chart.warning.bold

For data visualization communicating caution, such as 'at risk' or 'medium priority'.

color.chart.danger

color.chart.danger.bold

For data visualization communicating negative or critical information, such as 'off track' or 'high priority'.

color.chart.information

color.chart.information.bold

For data visualization communicating low priority or in-progress statuses.

color.chart.discovery

color.chart.discovery.bold

For data visualization communicating 'new' statuses.

color.chart.neutral

For data visualization communicating 'to-do' statuses.

Custom charts

A generic set of chart color tokens is available to support data visualization experiences where end users can choose their own colors.

They can also be used to build custom categorical color schemes, although our predefined categorical tokens are recommended for better accessibility and consistency.

These tokens are available in every hue with three emphasis levels. See all custom chart tokens in our design token reference list or get guidance on color picker swatches.

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Interacting with chart data

Data visualization often allows users to drill into data by hovering or selecting a data point. Use chart hovered tokens to provide visual feedback for these interactions.

An alternative approach is to fade out data that isn’t being interacted with. Use our opacity.disabled token for this implementation.

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All chart color tokens

For the full list of chart design tokens and their values, see our design token reference list. Every token comes with a description to help you ensure you’re using the correct one.

Chart color accessibility

Our chart colors meet WCAG AA 3:1 contrast ratios when used on any of our elevation surfaces (WCAG 1.4.11).

The following sections provide more guidance to help you achieve better accessibility.

Apply a border or space between adjacent colors

While these chart colors pass 3:1 contrast ratios against surfaces, they don’t against each other. For this reason, apply a space or border (color.border.inverse) as a visual separator between data elements.

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Do

Apply a visual separator between chart colors

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Don't

Don’t place chart colors adjacent to each other

Don't place text on chart colors

Our chart colors don’t support accessible pairings with text, which need at least a 4.5:1 contrast. Consider placing text next to the chart element instead.

For use cases where text is an essential feature (for example, calendar events), consider using our other color tokens instead.

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Do

Position text nearby chart data.

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Don't

Don’t apply text over chart colors.

Don't rely on color alone

Avoid using just color to communicate meaning in your data visualization. Incorporate other visual indicators such as shapes, line texture, patterns, or direct labels to support users in making sense of the data. Highcharts provide some good examples of these accessible chart experiences.

Additionally, providing the data in alternative formats, such as tables and text-based descriptions, will ensure all users can access the data in their preferred format.

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Do

Incorporate visual indicators other than color into your data visualization.

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Don't

Don’t rely on color alone to communicate meaning in your data visualization.

Data visualization in dark mode

Chart color tokens currently support two color themes: light and dark. Each token maps to a different value for each theme so their appearance differs depending on which theme is being used.

  • To learn the basics of tokens and themes, go to design tokens.

  • For detailed mappings from light to dark colors, see picking colors for dark mode. Note that if you are using design tokens, you shouldn’t have to map your own values.

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Color new - Data visualization - Foundations - Atlassian Design System (2024)

FAQs

What is the maximum number of colors in data visualization? ›

As a rule of thumb, you should try to limit the maximum palette size to ten or fewer colors.

What are the best 3 colors for data visualization? ›

There's a complementary color combination that is especially loved by data visualization designers: yellow/orange/red and blue.

How do you choose a color for data visualization? ›

Tips: - Use color meaningfully, e.g., only use color when needed to communicate something about the data. - For categorical data, avoid using too many different colors - no more than 6 colors is best; 12 colors max. - For sequential data, don't use rainbows, use white to highly saturated.

What are the alert colors for design systems? ›

Designers use semantic colors to announce specific messaging, such as warnings or other alerts. Some of the best examples of semantic colors are green, which has a positive connotation, so designers use it to communicate success. They also most often use red for warnings or yellow for general alerts.

What is the maximum number of colors possible? ›

If we use RGB, the range of colors is 0-255. Meaning there are 256 possible values for each Red, Green and Blue. 256^3 is 16,777,216. Therefore, the answer to your question is 16,777,216.

What is the maximum number of colours we would typically use in a design? ›

Many successful logos use only one or two colors and three at maximum. Why keep the color palette so simple when there is a world of infinite, prismatic options?

What are the 3 C's of data visualization? ›

The three Cs of data visualization are correlation, clustering, and color.

What are the 3 rules of data visualization? ›

To recap, here are the three most effective data visualization techniques you can use to deliver presentations that people understand and remember: compare to a real object, include a visual, and give context to your numbers.

What is the easiest color to visualize? ›

As you know, lights have specific wavelengths, and these wavelengths put each light on a level that is either easy or hard to see. Some wavelengths are easier for the human eye to recognize. And some others are not. In daylight, green is the most visible color from a distance for human eyes.

What is the common color usage mistake in data visualization? ›

Pitfall #1: Overwhelming with too many colors

Colors are great for distinguishing between categories in your data – but if you use too many colors it can have the opposite effect. Your visualization becomes hard to read. Only use different colors when they actually mean something important in the data.

Why color is important in data visualization? ›

Color selection in data visualization is not merely an aesthetic choice, it is a crucial tool to convey quantitative information. Properly selected colors convey the underlying data accurately, in contrast to many color schemes commonly used in visualization that distort relationships between data values.

What is color mapping in data visualization? ›

Color mapping is the process of mapping values in your data to colors in a plot. It allows you to increase the dimensionality of a graphic - for example, adding a third dimension to the two-dimensional x, y coordinates in a scatterplot.

What are the best practices for design system colors? ›

Typically, a design system doesn't need to offer many color options. For a good and effective system, five colors would be enough: one as a base, two as lighter tones, and two for shades. By limiting the number of swatches, you'll simplify the design process and ensure consistency throughout your projects.

What is color code list? ›

List of common HTML color codes
NameHex CodeRGB Code
Black#000000rgb(0, 0, 0)
Red#FF0000rgb(255, 0, 0)
Maroon#800000rgb(128, 0, 0)
Yellow#FFFF00rgb(255, 255, 0)
12 more rows

Does using more than 5 colors increase the impact of your visualization? ›

Pitfall #1: Overwhelming with too many colors

Your visualization becomes hard to read. Only use different colors when they actually mean something important in the data. While colors help the brain quickly identify differences, using lots of them makes this harder.

What is the maximum color palette in tableau? ›

About the preferences file

tps file, each with as many colors as you want. Although there isn't a limit to how many colors can be added to each custom palette, the Edit colors dialog box only shows 20 colors.

What is the max number of colors in an indexed image? ›

Most image file formats limit indexed images to 256 colors. If you write an indexed image with more than 256 colors (using imwrite ) to a format that does not support more than 256 colors, you will receive an error.

Is the maximum number of colors that are used in screen to display the image? ›

8-bit color graphics are a method of storing image information in a computer's memory or in an image file, so that each pixel is represented by 8 bits (1 byte). The maximum number of colors that can be displayed at any one time is 256 per pixel or 28.

References

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