06.04.2016 by Marisa Krystian
We spend a lot of time thinking about how people can best visualize their data here at Infogram. And, the reality is you don’t always need to present your information in colorful bars, columns, lines, or bubbles. Sometimes all you need is a table. That’s why in this article, we are going to discuss when to use tables vs. charts, and how to know what’s the best option for you in any scenario.
What is a Table?
A table is structured for organizing and displaying information, with data arranged in columns and rows. Information is displayed as text, using words and numbers, and grid lines may be present or not. Sometimes it is best to remove the grid lines to ensure your table is easy to read and effective at communicating your message.
Tables make it easy to compare pairs of corresponding values (e.g., quarterly sales over several years).
Tables are not exclusively used to display quantitative information! Whenever you have more than one set of values that have a direct relationship, you may use a table to organize the data. For example, people often use tables to display meeting agendas with certain times, topics, locations, and speakers.
A bonus? Tables have been used for centuries. They are easily understood and almost everybody can read them.
When to Use Tables vs. Charts
There are multiple reasons you might be driven to select a table, over a graph, as the right way to visualize your data.
Are you, or others, planning to use the table to look up one or more particular values? Or maybe the information will be used to examine a set of quantitative values as a whole to spot patterns. If so, a table might be right for you.
Data visualization expert and author Stephen Few explains in his book, Show Me the Numbers: Designing Tables and Graphs to Enlighten – Second Edition, the times when a table makes the most sense:
- The display will be used to look up individual values.
- It will be used to compare individual values but not entire series of values to one another.
- Precise values are required.
- The quantitative information to be communicated involves more than one unit of measure.
- Both summary and detail values are included.
The table below is fairly complex because it displays quantitative values that are simultaneously associated with multiple sets of categorical items. In this case, we are looking at sales dollars and particular salespeople.
Side Note: Embed the interactive tables you make with Infogram to help your viewer sort the data and draw better conclusions faster. For example, you can sort numbers from highest to lowest and names alphabetically.
Tables vs. Charts
When using a graph or a table to communicate your data-driven message, always ask yourself how the information will be used.
Charts are essentially a visual display of quantitative information along two axes. Visuals are used as a way for our brains to quickly understand information, which is a powerful tool if used correctly. Charts can show a large amount of data quickly in a way that is easy to process, without distracting people with a bunch of numbers.
According to Stephen Few, charts reveal more than a collection of individual values. Because of their visual nature, they show the overall shape of your data. This is when you should use charts instead of tables:
- The message is contained in the shape of the values (e.g. patterns, trends, exceptions).
- The display will be used to reveal relationships among whole sets of values.
The bar chart below is a fictional visual representation of Influenza cases last year.
When debating table vs. graph, ask yourself how the data will be used, consider your target audience, and decide the best way to map out your information. Think about the utility of your visual and let that help drive your decision-making.
Ready to make a table with Infogram? It’s simple! You can also easily switch between our 35+ different chart types to see if a table or graph is best for you and your data.
Get data visualization tips every week:
New features, special offers, and exciting news about the world of data visualization.