Tables, a.k.a. “crosstabs” or “spreadsheets”, are one of the most common ways to present data. They may not be visualizations in themselves, but they can be a powerful tool for visual analysis. For this reason, we include Tables as a separate family within the glossary.

Inspiring examples of tables from the community

We’ve selected a few visualizations from the Tableau community to highlight how beautifully data can be portrayed. For more practical examples check out the different Analytical Functions or individual visualization types.


Tables and crosstabs in data visualization?

Analysts tend to use tables when they want to see individual values. They make it easy to identify measures across a set of intervals (Ex. what was the company’s profit in November 2018) or dimensions (Ex. How many sales did each person close in 2019). Additionally, a summary table can effectively describe a large data set, providing you subtotals and grand totals for each interval or dimension. The issue with tables is that they do not scale well. If the table has more than ten to fifteen rows and five columns it becomes hard to read, understand, and gain insight from. This is because a table activates the language systems within the brain while visualizing data activates the visual systems.

Adding visual elements to the table will help people gain insight from the data in short order. Color gradients (see Heat Maps) and size (see Proportional Area Tables) help viewers identify patterns and outliers. Icons help the viewer identify a change in measures between dimensions. Mixing and matching different marks will draw attention to relationships better than a table of raw data.

Tables and crosstabs are useful for performing comparative analysis between specific points of data. They are easy to create. They can show one key insight with ease. But you should consider whether a crosstab supports the goals of your project before building it into a data visualization.

Types of tables and crosstabs

The table below contains a tagline for some common table visualizations. As the glossary expands in depth and breadth more types will be added and each will have a page dedicated to showing practical examples and explaining when to use them.

Crosstab

Displays dimensions and measures in columns and rows.

Heat Map

Uses size to highlight patterns within the data of a table.

Highlight Table

Overlays a color gradient on top of a table to highlight patterns.

Should you use a table for your visualization?

Choosing to include a table in a data visualization starts with what you want the viewer to get from the data. If they should locate precise values within a data set a table may help them. It will also help them if they want to compare values for different dimensions or categories. Tables also provide details obfuscated by other families of visualizations. A line chart with monthly sales may show a trend, but you may not be able to see if March had more sales than August at a glance. Tables go with visualizations to provide an overview of the information within it. If a table provides extra context it’s worth building, otherwise there are likely more effective visualizations.

For more information on whether you should use a table read this blog on designing text tables.

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