The right technique for data visualization: Part 1 — Data Across Time and Categories

By October 2, 2018 July 27th, 2019 Design Tips, Visual Communication
Data visualization Part 1 Header

You’ve got a credible statistic or 2, and you’re ready to share the information with your audience. Do you write it out? Draw a picture? Use a chart? To make sure your audience understands and retains the information, it needs to be compelling and accurate.

But the choice of what type of visualization to use isn’t purely aesthetic, nor is it entirely personal. The wrong choice can can lead your viewer to boredom, confusion, or both. Learn to pick the right technique in our 2-part series.

We start with looking at graphs and charts — excellent approaches for showing data sets that evolve over time or cover multiple categories. In part 2 of our series on data visualization best practices, we’ll look at how to handle standalone data points that aren’t easily represented on a graph.

Bar Graphs

For data sets that evolve over time or are grouped by multiple categories (like different industries or different foods), or both, a bar graph is a solid choice. A few tips will help ensure your bar graph is easy to read.

If your data set evolves over time, make sure to order your bars chronologically. Use 1 axis to label the time frames, and use the other to label the quantities. Never order the data from most to least or least to most if it’s time-bound; chronology is the better measurement for your viewer.

For chronological graphs with multiple categories, you can either make individual graphs for every category, or keep it as one by including multiple bars (one for each category) at each time label.

If your data set is grouped into multiple categories and isn’t bound by time, you should organize the bars from most to least, or least to most. This type of organization helps viewers to draw conclusions quickly. However, if it adds up to a whole (such as total revenue by category), that won’t be apparent in a bar chart. For this type of information you should use a circle chart instead. We’ll get to those shortly.

Data visualization Part 1 Bar Graphs-01

Line Graphs

Much like bar graphs, line graphs are useful for showing data over time or grouped by category. But a line graph allows for nuance. They are a great choice for showing information over very long periods, because the organic nature of a line allows it to bend and change with more detail in a smaller space than full bars.

In fact, you should be careful when using line graphs to show only a few points in time. Without knowing the data in between (whether minutes, days, years, or decades), you’ll presumably draw a straight line. However, the rate of growth or decline between those times may not have been so linear. For this reason, line graphs should be used carefully and with complete data sets to avoid distorting data.

If you aren’t showing data over time or by category, a line graph is not for you. Categorical data has many helpful graph applications, though. The following is another option that works well for this — if you’re showing portions of a whole.

Data visualization how to Part 1 Line Graphs

Pie and Donut Charts (Circle Charts)

The circle chart is one of the most commonly used forms of data visualization. There are pie charts (filled in) and donut charts (hollow, with a circular bar containing the data). Unfortunately, it’s so popular that it’s also one of the most misused tools we see.

A circular chart can only be used when you are showing portions that add up to a whole. For example, “75% of all caterpillars like apples” could be shown with this because it’s referring to 75% out of a total 100% of all caterpillars. You can also convert proportions to percentages for this goal. If your data point is 3 out of 4 caterpillars, that’s equal to 75% of caterpillars.

Unlike bar and line graphs, pie charts cannot be used to show an increase or decrease on their own. Let’s say in 2018, 20% more caterpillars liked apples compared to those in 2017. A circular chart showing 20% would be incorrect. That would make it appear that 20% of all caterpillars liked apples, which is wrong. Instead, 20% more liked them this year than last year.

The only way you could show this using circular charts would be if you knew the total percentage of caterpillars that liked apples in each year. Then you could have a 2017 pie chart showing that 60% of caterpillars liked apples, and a 2018 pie chart next to it showing that 72% of caterpillars liked apples — a 20% increase. (If you thought at first that that’s only a 12% increase, you’re not alone. Percentage changes can be tricky if you don’t work with them all the time. Here’s a cheat sheet!)

To use pie charts to show changing data over time, you’d create a new chart for every time period you’re measuring, and display them together for comparison.

Data visualization Part 1 pie charts

That’s all for graphs and charts! Check out part 2 in our series, where we examine some non-graph techniques for data sets that don’t quite fit as described above.

Lucy Todd

Author Lucy Todd

Lucy Todd is the Chief Process Officer at Killer Visual Strategies. She is a Seattle native and Western Washington University graduate. Her degree in Creative Writing and her customer service background both inform her work daily. A Killer employee since 2011 and executive since 2014, Lucy has researched for, written, and/or project-managed over 4,000 projects for the company, affording her key insight into our processes and projects. This experience is invaluable in allowing her to lead and empower Killer’s content and project management teams to success. Lucy enjoys managing the day-to-day at the office, offering a unique perspective when a team or colleague feels stuck, and learning from her peers and clients each day.

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