4 Principles to Choose the Perfect Color Combination for Your Data Visualization

DZone 's Guide to

4 Principles to Choose the Perfect Color Combination for Your Data Visualization

A discussion on how to make your data visualizations easier to understand.

· Big Data Zone ·
Free Resource

1. Color Combination for Data Visualization

Even so, we often find that although we have data, we don't know what chart to use to express the value of data in the best form. We only use a few simple histograms, line charts, or pie charts. In terms of details such as the color and font, we have no idea how to make a more beautiful combination.

To build an excellent visual dashboard (a truly informative and action-oriented dashboard), it's not enough to just list all the information on it. In order for the dashboard to convey information to people completely and clearly, we must carefully consider the various elements of planning and design.

Next, this article will give you a detailed explanation from the aspect of picking the color combination for your data visualization. The color scheme sets the tone of anything that you've created. People can know the type of data you're displaying, its relationship and the differences between categories from the colors you use in your data visualizations.

Image title

From True Value Paint

If you don't know how to combine and present the completed report or don't know how to make a reasonable layout either, follow us to get through the process of choosing the perfect color combination.

2. Principles of Color Combination Consistency

Color is one of the most effective aesthetic features because it attracts attention. The first feature we notice is the color, which highlights specific insights and identifies outliers in a straightforward manner. In the argumentation, the use of color should be based on data instead of the personal preference or brand color.

In general, we can keep to the following principles of color combination consistency when choosing the color scheme.

2.1 Consistency of Numerical Index

When we perform color mapping based on the numerical value of a certain indicator, it is recommended to use the gradient color of the growing color system.

For example, as shown in the above figure, the statistics are the sales situation of a region in different years. The colors of the left image have no color system and growth law. It is difficult for users to understand the mapping meaning of the specific index value. At this time, if we use the expression of the growing color system on the right one, it will convey a sense of color measurability to the user. Then, according to such a gradient growth color, users can easily understand the distribution of sales in each region in that year.

2.2 Consistency of Indicator Color

When making a chart, we should use the same color scheme for the same metrics. And we need to avoid the excessive color interference to the user.

For example, when we do sales analysis, we usually analyze the indicators of sales and payment collection. Then, when we do data visualization analysis of different dimensions for the same indicator, we recommend using the same color system for sales and payment collection. It means that the sales amount can be indicated by the yellow-green color, and the return amount can be indicated by the blue color accordingly. After following the principle of consistency of indicator color, the user can quickly understand the meaning of the indicator expressed by the current data visualization chart according to the color distinction.

2.3 Consistency of Color System

In the same dashboard, we should try to choose a color scheme of the same color system to avoid color collisions.

When it comes to defining and selecting colors in the dashboard, many users may be very confused about how to match them. Actually, in terms of color combination, FineReport has built in a lot of beautiful color schemes. It allows users to choose colors in the same color system, which are very friendly for users. After all, the appearance also makes a difference.

From FineReport

If we are going to customize colors, we need to avoid some collisions. For example, if you match the colors such as yellow + white, blue + black, red + blue, yellow + purple, etc., the whole image is not aesthetically pleasing and it's easy to irritate the user's eyes.

2.4 Consistency of Semantic Color

The colors that match the semantics can help people process information faster. We ought to choose the color that suits our most intuitive feeling according to the meaning of the indicator.

Therefore, in the climate chart, red can be used to indicate the heat distribution. And brown can be used to indicate drought index, blue to indicate precipitation, and so on.

Image title

From hikersbay

The above are the main four principles of color combination consistency. Do you have a basic understanding of how to choose a color scheme for your data visualization?

In fact, we all know that creating a color scheme for data visualizations from scratch is a challenge. That is because you have to show the contrast or natural progressions through the colors you use. At this moment, we highly recommend finding a scheme that's already out there. That is, you can use a few reporting tools to help you find the color schemes that appeal to you. For example, FineReport can provide you with a wide range of color schemes. The HTML5 chart technology of FineReport supports various chart types, patterns and styles.

Now let's enjoy some excellent data visualizations!

Composite Chart

Bar Chart

Scatter Diagram

big data, data analysis, data visualization

Published at DZone with permission of Lewis Chou . See the original article here.

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}