Master the rules - then break them

Master the rules — then break them. Learn to make functional choices in data visualization | Blog | Datylon
Meteorite landings between 1990 and 2012 — a data visualization submission for Storytelling With Data June 2022 challenge
My data visualization submission for #SWDchallenge in June 2022

Rules in data visualization

1. Axes rules

Don’t flip the vertical axis

The first rule I broke is to not flip the vertical axis. Normally, the vertical axis starts at the bottom and the horizontal axis starts at the left. This means that for the vertical axis larger values are placed above smaller values and for the horizontal axis larger values are placed on the right of smaller values.

Award-winning data visualization by Simon Scarr (left),
and a copy/remake of that visualization which follows the rules, created by
Andy Cotgreave (right).

Bar charts should always start at zero

Along these lines (pun intended), there are some more rules for axes in data visualization, which I actually did stick to in my submission for storytelling with data.

Put the data in order

Another rule for axes is to put them in natural order if there is a natural sequence in the data. For example, time-series data should always be presented in the natural order. This means that for left-to-right languages the lowest point in time should be on the left and the most recent point in time on the right. For right-to-left languages, it is the other way around. This holds for example also for education levels or age groups. If there is no natural order for the categories, order them by value to make it easier to consume the data. We think this is a very important rule that you should always stick to, in order to make your data visualization easy to understand.

2. Color rules

Use a light background

Let’s start with the dark background I used for my visualization. There is still an ongoing debate on whether using dark or light backgrounds is better for the perception of (data) visualizations. Last decade we started using more devices and applications, very frequently and using a light background became standard. Often it is recommended to use dark texts on a light background since the brain is better at processing it than the other way around. Though, you might have noticed that in the last couple of years a lot of companies and services introduced the dark mode for devices or websites. What’s up with that, you probably wonder.

Don’t use gradients to spice it up

One other thing I did with the color in my meteorite landing data visualization is the use of a gradient. It is generally recommended against using gradients for the simple reason of just making your bar chart less boring. Gradients should only be used to communicate values of continuous data, for example in bar charts or heatmaps. Though, I broke this rule and only added the gradient to mimic the fall of the meteorite.

Use color to communicate additional information or highlight information

The last color rule I will discuss in the article is to only use color if it adds additional information to the data visualization. For example for a bar chart, using one color should be enough. Don’t use a new color for every bar just to make it beautiful, it will only make it harder to read.

The Twisted Nature of Irish Whiskey Sales — A remake of a line chart visualization, originally designed by vizwiz, and recreated with Datylon for Illustrator plug-in.
A remake of a line chart visualization, originally designed by vizwiz, and recreated with Datylon for Illustrator.

3. Maximize data-ink ratio

The last section of this article I will devote to maximizing the data-ink ratio. This term was invented by Edward Tufte and means that you should get rid of all elements in the chart that do not add new information; in other words — chart junk.

  • Maximize the data-ink ratio
  • Erase non-data ink
  • Erase redundant data-ink
  • Revise and edit

Avoid using grid lines and remove tick marks

The first thing I did to maximize the data-ink ratio in the meteorite landing data visualization is to let go of (some) gridlines. For some charts, gridlines are not necessary to make them more understandable. For bar charts, they are easy to avoid by placing the data labels directly on the chart, instead of using gridlines and an axis.

Don’t do legends

Another rule I did stick to is to avoid using a legend. In data visualization, there are multiple ways to avoid using legends. First, it is possible to specify categories by using colors in text, just like I did in my design. You can mention categories in subtitles or annotations and highlight them with the same color as used for the categories in the data visualization. This is a very elegant way of maximizing the data-ink ratio by avoiding legends. See another example of such a color application here.

Avoid chart junk

The first thing I didn’t do to maximize the data-ink ratio is avoid chart junk. Examples of chart junk we recommend avoiding or minimizing as much as possible are unnecessary texts, gimmicky font types, frames around the chart, additional figures or pictures, 3D effects, and ornamental elements.

Monstrous Costs (1982) by Nigel Holmes
Monstrous Costs’ by Nigel Holmes (1982). An example of a design that makes use of chart junk.

Don’t use data marks

Lastly, a data visualization will really benefit from not having any data marks. With data marks, we mean the dots (or other shapes) that are placed on top of the data point. Especially in bar charts, data marks most of the time do not add anything to the data visualization. They can actually be bad, since the viewer doesn’t know if the data point is located on the top, middle, or bottom of the data mark.

Conclusion

In this article, I presented to you some of the general rules in data visualization and how you can thoughtfully break them by making functional (and creative) choices. The key take-out is to always consider the goal of your data visualization and make decisions accordingly. Sometimes it is better to break the general rules to make your visualization more memorable, evoke emotions, or convey the message in a better, more engaging way.

Further reading & resources

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