What are the best typography practices for data visualizations?

2 Use sizes that balance readability and emphasis

The size of your text can affect how easily and quickly your audience can read and comprehend your data visualization. If your text is too small, it can strain the eyes and make your message unclear. If your text is too large, it can overpower your data and take up too much space. To find the right size for your text, consider the following factors: the medium and format of your visualization, the distance and angle of your audience, the amount and density of your text, and the importance and relevance of your text. Generally, you want to use larger sizes for titles, subtitles, and key points, and smaller sizes for labels, annotations, and sources. You can also use size to create contrast and hierarchy, such as using a larger size for the most important or interesting data points.

3 Use colors that enhance and harmonize your data

The color of your text can influence how your audience perceives and interprets your data visualization. Color can add meaning, emotion, and interest to your text, as well as highlight or differentiate your data. For example, you can use color to indicate categories, trends, or outliers in your data, or to match your text with your data points. You can also use color to create contrast and hierarchy, such as using a darker or brighter color for the most important or interesting text. However, be careful not to use too many colors, as this can create clutter and confusion. A good rule of thumb is to limit yourself to four or five colors per visualization. Also, make sure to choose colors that are legible, accessible, and consistent with your message and brand.

4 Use alignments that organize and align your data

The alignment of your text can affect how your audience navigates and scans your data visualization. Alignment can create order, structure, and balance in your text, as well as align your text with your data points. For example, you can use left alignment to create a vertical line that guides the eye from top to bottom, or center alignment to create a symmetrical and centered layout. You can also use alignment to create contrast and hierarchy, such as using right alignment for secondary or supplementary text. However, avoid using justified alignment, as this can create uneven spaces and gaps in your text. A good rule of thumb is to use the same alignment for the same type of text, such as using left alignment for all labels, or center alignment for all titles.

5 Use labels that clarify and explain your data

The labels of your text are the words and phrases that describe and identify your data points, such as axes, legends, titles, and captions. Labels can clarify and explain your data, as well as provide context and background for your audience. For example, you can use labels to define your variables, units, sources, and methods, or to summarize your main findings and insights. You can also use labels to create contrast and hierarchy, such as using uppercase or lowercase letters, or adding punctuation or symbols. However, avoid using labels that are too long, vague, or technical, as this can create confusion and boredom. A good rule of thumb is to use labels that are concise, accurate, and relevant.

6 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?