Designing Charts: Choosing Fonts

Fonts and font styles play an important role in creating effective and engaging data visualizations.  Here are things to consider: 

  • Understand the context: Before choosing a font, it’s essential to know the context in which your chart will be presented. Consider whether it will be used in a professional report, a blog post, or a presentation. This helps you determine the appropriate font style and size. 
  • Typography: When selecting a font for your chart, consider two primary factors: legibility and compatibility. You’d want to choose a font that is easy to read and complements the content of your visualization. 
    • Serif vs. Sans-serif: Serif fonts have small lines or strokes attached to the ends of letters, while sans-serif fonts don’t have these embellishments. Serif fonts like Times New Roman tend to give a traditional and formal feel, while sans-serif fonts like Arial or Helvetica often convey a more modern and clean appearance. Sans-serif fonts are generally recommended for data visualizations due to their better legibility, especially in smaller sizes. 
  • Font sizes: To ensure greater readability of your chart, always think about the audience and the viewing distance. You should choose a font size that is comfortable to read for your intended audience. For example, a font size of 10-12 points would be suitable for a printed report or a blog post. However, for a presentation, you might want to go with a larger size, such as 18-24 points, to make it easy to read from a distance. 
  • Tabular vs. Proportional fonts: Tabular fonts have uniform character widths, which makes them ideal for displaying numerical data in tables and charts, whereas proportional fonts have varying character widths. Tabular fonts, such as Courier New, ensure that all numbers align perfectly, making the data easier to read and compare. 
  • Lining vs. Old style numbers: Lining numbers share a consistent height and align well with capital letters, while old-style numbers have varying heights and better align with lowercase letters. In data visualizations, lining numbers are generally preferred as they offer better readability and uniformity, especially when dealing with numerical values. 
  • Color and contrast: Choosing appropriate color and contrast for your text plays a crucial role in readability. Always opt for high contrast between the text and the background. For instance, use dark text on a light background or vice versa.