The use of color can influence the way data is perceived. The primary goal is to ensure that the viewer sees something that he or she understands and relates to, without being distracted or confused.
The color wheel is the basis of color theory. This system organizes colors in a circle. The primary colors—red, blue, and yellow—are the starting point. When these colors are mixed, secondary colors such as green, orange, and purple are created. Mixing these colors again results in tertiary colors. By laying out the colors in the shape of a wheel, you can more easily see complementary, analogous, and triadic relationships between colors. Complementary colors lie opposite one another and create a striking contrast. Analogous colors are next to one another and create a sort of visual harmony. These types of relationships are essential when selecting palettes that don’t clash and preserve the visual integrity of your data.
Diverging color schemes work really well if you need to show deviation around a midpoint in your data. This is the case in situations where you have two contrasting colors that blend through a neutral center. The idea here is to accentuate differences from the center point, so such schemes are well suited for showing data such as changes in temperature or economic indicators.
Choosing the Right Color Schemes
The right color scheme for your data visualization with Clip can make all the difference in the clarity and effectiveness of your message. Think about the purpose of your visualization and what kind of response you hope to get from your audience.
Identify what type of data you are dealing with. Is it quantitative or qualitative? For quantitative data, think about sequential color schemes, which use different shades of one color to show data changes over time. Qualitative data can be better represented with a categorical color scheme where different colors illustrate different categories—without ranking them or suggesting a progression. A clear line can be drawn between data sets.
For displaying variations around a midpoint in your data, consider using diverging color schemes. This approach usually employs two contrasting colors that merge through a neutral center color, and its purpose is to draw attention to such variations. It’s well-suited for data such as changes in temperature or economic indicators—data like this might have some central point around which variations occur.
Creating Color Palettes in Clip
The clip is a strong weapon in your arsenal, but knowing how to use it correctly for color customization in your visuals will take them to the next level. Mastery of creating custom color palettes would enable your charts to tell the story of your data in a compelling way.
You can define custom color palettes with hex codes in Clip scripts. By creating a unified palette, you can ensure that your visualizations are consistent across various projects. Clip lets you change some colors through scripts. You can change hue, saturation, and brightness according to your needs.
Clip lets you use color maps created previously in other visualization software. Integrating these well-known color maps may help save some time and get solid visual results. You must ensure the selected maps mesh well with the perceptual needs of your data, delivering clarity and distinction where appropriate.
Ensuring Accessibility and Contrast
The main purpose of data visualization is to communicate information. When choosing colors for your charts, accessibility is vital so every viewer—this includes people with color vision deficiencies—will correctly understand your visuals. Some form of color vision deficiency affects more than 5% of men and about 0.5% of women. Given the numerically significant segment of the population that stands to be affected, your choice of colors must make the visualization accessible.
Think about using color palettes that are friendly to colorblind viewers, so that your charts are accessible to everyone. You might consider using tools like Coblis (Color Blindness Simulator) to see how your charts will look to people with different types of color vision deficiencies.
If the contrast between text and background or data elements is low, your charts may suffer readability issues. Good contrast allows important information to be seen quickly. Always pair your colors with maximum readability in mind—getting help from contrast calculators, for instance, to ensure that recommended standards are met.
Testing and Iterating Your Designs
After you establish the basic design, test it. Collect opinions from co-workers or potential users about your color decisions. Their responses may reveal places in your design where color use is not very clear or may even be somewhat distasteful.
Make improvements to the design through iterations using this feedback. What is clear to a designer may be confusing to an audience that does not know the backstory or details about the data. Be willing to go back and change your color decisions if they do not seem to help the viewer grasp the intended meaning.
Make gradual changes in different things, such as the hues and contrasts, until the visualization seems perfect. Testing variability ensures that the final output is visually beautiful and clearly functional.
Leveraging Tools and Resources
Leverage tools and resources at your disposal to help you pick and test colors. Clip itself provides a good starting point, but incorporating outside tools would greatly enhance your workflow.
The software Adobe Color allows you to create and test color schemes effortlessly. Different color schemes like analogous, monochromatic, triad, complementary, compound, and shades will be shown visually in various ways. Users can even look at trends in different areas of design and find some inspiration in them with Adobe Color.
Coolors and other online sites speed up random palette generation. This is a great thing to do when you need a quick burst of creativity. Many of these tools also have community palettes or feature palettes based on existing projects, which can trigger new ideas and provide fresh angles for your work with Clip.