What are the most effective colors for data visualization?

1 Know your audience

The first step to choosing the right colors for your data visualization is to understand who you are designing for. Different cultures, industries, and contexts may have different associations and preferences for colors. For example, red can signify danger, urgency, or error in some settings, but it can also represent success, prosperity, or happiness in others. Similarly, green can indicate growth, health, or environmentalism, but it can also be associated with sickness, envy, or inexperience. You should also consider the accessibility and diversity of your audience, and avoid colors that are hard to see, distinguish, or interpret for people with color vision deficiencies or other impairments.

3 Apply color principles

The final step in creating an effective data visualization is to apply some color principles. Use color sparingly and strategically, such as highlighting the most important or relevant information and using neutral colors for the background or less important elements. Color should also be used consistently and logically, with the same color for the same data category or variable across different charts or graphs. When choosing colors, make sure they match the tone and mood of your data visualization and message, but avoid using colors that are too bright, dark, or saturated as they can strain the eyes. Additionally, be respectful when choosing colors and avoid those that are offensive, insensitive, or misleading to your audience or your data. By following these tips and best practices, you can create a compelling and memorable story with your data.

4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?