Fonts for Data Visualizations

Professor Cairo has a voracious appetite for reading and he thankfully likes to share books and articles. One article he included, Finding the Best Free Fonts for Numbers was an interesting read as I have a thing for type and fonts. I get picky and can spend probably too much time selecting a font that I feel works well. I’ve also taught typography classes so while I am not a type expert, I am knowledgeable about typography.

In general, I agree with the list Samantha recommends. Not everyone can afford some of the best designed super families out in the wild. I also agree that free fonts aren’t always the best choice. Most are poorly designed and more importantly were probably created for the most generic of applications. So, again, she has compiled a thoughtful list.

Old Standard TT

I disagree about one typeface: Old Standard TT.

I do not think it would function well for data visualizations where type sizes are below possibly 14 points and that might be generous. Why? Old Standard TT can be quite interesting at large sizes; however, at smaller sizes, it starts to fall apart.

I need reading glasses to be able to read Old Standard TT at 14 pts. Even with it set in black on a white background (great contrast between figure and ground), it is quite challenging to read. Imagine if it is set in a color also on a colored background. Personally, if it is hard to read, I won’t. In my mind, that is the worst possible user experience.

My recommendation: If you want to use Old Standard TT, use it for display copy—headlines, subheads, or instances where you want to set a numeral in a particularly large size.

Oldstyle or Lining

Samantha’s recommendation for lining and tabular is a good base; however, this should not be a hard and fast rule. Why? Because there is a purpose for Oldstyle figures. Oldstyle figures work well when used with running text. They don’t interrupt the flow of reading because they share the same x-height as their lowercase character companions. Lining numbers in contrast stand out when sharing the same baseline as lowercase characters in running text.

Oldstyle figures can be used for data visualizations especially in places where numbers share the same baseline as text. For example, annotations. They are also readable in tables and other data visualizations purposes. Oldstyle figures can also be tabular so please, don’t rule out a typeface because they have oldstyle figures.

OpenType and Investing in Typefaces

With OpenType fonts, you get the best of all worlds, usually. For figures, OpenType give you the flexibility of setting figures in tabular and lining and tabular and oldstyle. Usually a designer can also set type as proportional as well. This is one of the perks of OpenType fonts and investing in building a library of high-quality typefaces. (Use a font manager such as Extensis’s Suitcase Fusion). Many free fonts are not OpenType.

My Favorite Fonts for Data Visualizations So Far…

Below is a short list of sans serif typefaces I use over and over again. Many are large families so you also have a choice of many styles: thin, light, italic, regular, bold, etc.

Benton Sans

Fira Sans

Gotham

Whitney

Interstate

Poynter Gothic Text

PT Sans

Nimbus Sans

Myriad

News Gothic

FF Meta

Soleil

If you have an Adobe CC subscription …

Many of the fonts above are available through fonts.adobe.com (formerly TypeKit). It’s one of the perks of having an Adobe Creative Cloud subscription. If you are interested in others, try a search for sans serif with a large x-height. (A larger x-height usually means greater readability at smaller sizes.)

If you want to learn more about typography, I highly recommend Ellen Lupton’s website and book, Thinking with Type. I also have plenty of books which I’ll try to share soon. The great part about owning high-quality typefaces: you don’t need many. This is what makes OpenType super families so appealing.

2 thoughts on “Fonts for Data Visualizations”

  1. What a gorgeous post and in general beautiful blog. I completely agree about Myriad and Meta. So readable and so architectural.

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