4 ways to make charts that tell your story

How can we make charts that convey our messages and are more than decoration? Here is a brief intro to data visualization and 4 things you can do to make clearer charts.

Charts, graphs and other data visualizations can be powerful tools to convey our messages. But too often, we make charts that don’t contribute to our storytelling. So here is a quick intro to data visualization for those of us who have to create charts but need guidance on how to make them more than just decoration.

This post was inspired by Cole Nussbaumer Knaflic’s article “5 easy ways to make your data visualization more accessible” (Storytelling with Data) and the positive feedback I got on a 40-minute mini-training I held on this topic with UN colleagues.

What is data visualization?

This section summarizes what you can learn about in the excellent and free Data visualisation e-learning modules offered by the UK Government Analysis Function. Highly recommended!

Data visualisation is the visual presentation of numbers.

Data visualisation e-learning modules, UK Government Analysis Function

Data visualizations (or dataviz) can include …

• charts
• tables (here, referring only to “short tables” used in publications, not extensive spreadsheets)
• maps
• infographics

Good data visualizations help you communicate because they let you

• present complex info simply
• improve engagement by making the page more interesting to readers/viewers
• highlight features in your data

But if done poorly, data visualizations can damage your reputation or lead to a loss of trust. (For example, if you use misleading labels or present the data in inappropriate ways.)

So how can we do it right? Let’s focus on charts.

How do I pick the right chart type?

When choosing your chart type, think first what you are trying to show with your data. What’s your message/story? Pick the chart type that will best convey your message. You can start with the simple table below or try the more complex interactive tool Visual vocabulary: Designing with data.

Type	Used for
Tables (referring here only simple tables)	Look up and compare values
Bar graph	Compare size of different categories
Line charts	Show data over time
Pie charts	Show how parts make up a whole

Crafting meaningful charts is all part of plain language—using design is as important as the words you choose and how you organize them.

How do I make my charts clearer and more accessible?

Charts don’t need to be complex. In fact, in most cases the simpler the chart, the better for your readers (just like simpler sentences). Here are four things you can do to make your charts clearer and more accessible.

Again, this content is heavily inspired by “5 easy ways to make your data visualization more accessible.” Please see their post for more details.

1. Make the title into the takeaway message

Give readers the takeaway message in the chart title. This will prime (prepare) your readers to see your message in the chart.¹

Compare the following two titles for the same chart. Does it affect how you understand the chart?

Similar to informative headings, a statement as a title helps people understand the chart. It also helps them to scan the page (especially online) and still get your point.

2. Directly label the data points

Label the data points directly, in the chart. Get rid of the legends.

Readers can see immediately what each bar or line represents. That’s much easier than looking back and forth between the legend and the bar/line to read the chart.

It’s also helpful for people who are colorblind, have a cognitive impairment, or are seeing the chart on a B&W printout or e-ink device.

Here’s a nice example, where you can see how the labels let you understand the chart even in grey scale.

One more example, this one of (what I learned is called) a slope graph. It’s a nice way to show change over two points of time. Note how the labels lets you read the chart even in grey scale (but some colors are just too faint—see my point below on contrast).

3. Consider contrast and colors and use white space

I’ve written about 3 simple principles for readability but to recap:

• Don’t rely only on color to convey meaning. Keep in mind people who are colorblind or reading your content as a B&W printout. (Are all parts of the chart readable without the color?)
• Use a font that is strong and big enough to be legible.
• In charts, make the bars thicker.
• Be strategic on what you put in. Don’t cram every little detail you have. Use white space.

Here’s an example based on a real chart I’ve seen. Don’t do this.

Also: Use a consistent color scheme in your document. Using different sets of colors for each chart only make people pause to decide if the differences mean something.

4. Add alt text

Alternative text (alt text) allows people who use assistive devices like screen readers or have low internet speed to “see” the content. (If you need it, here’s a refresher on alt text.)

Making data visualizations truly accessible is more complicated than for simple images. Please see Amy Cesal’s Writing Alt Text for Data Visualization for more, as I’m still learning about this. I’m starting with the template:

[Type of chart] that shows [what].

Remember that alt text works together with surrounding text and captions. Don’t repeat information that’s already in the text or captions.

Also: Make each chart stand on its own

And remember: Each chart should be able to stand on its own. That means if someone looks only at the chart (and people will), they will still understand what you are trying to say.

Make sure that

• the title, axes, labels, units etc. can be understood on their own (don’t use variable names that you used to run your data analysis or any other cryptic shorthand that readers don’t know)
• all acronyms are spelled out (even if you’ve already done so in the running text)
• other information needed for a reader to understand the chart is in the caption (cite sources too)

I hope this helps you create better charts.

Let’s practice! I’ve made/collected a few charts from the real world. See how you might improve them.

Feel free to share your thoughts and other recommendations in the comments!

A few resources to get you started…

I leave you with a few resources.

• Data visualization e-learning (GOV.UK): Short online lessons about data visualization
• Accessible data viz is better data viz: 5 easy ways to make your data visualization more accessible (Cole Nussbaumer Knaflic): Great starting point

Picking the right chart

• Visual vocabulary: Designing with data: Interactive chart to help you pick the right type of visualization

Designing good data visualizations

• Data visualization checklist (Stephanie Evergreen): An excellent checklist (you must register to get the download)
• How to build data visualizations in Excel (Evergreen Data): Instructions!

For dataviz ideas and inspiration

• Beyond the bar (Ama Nyame-Mensah) and When a bar is boring (Stephanie Evergreen): Bar charts are great but if you want to try something else…
• Visual Capitalist

Cover image created by Ema@The Clarity Editor.