Waffle and Gauge Chart

Key points

The waffle and the linear gauge provide a visually engaging way to display a data point in relationship to a whole, much like a pie chart.
Static Image of the example waffle chart

Best Practices

To create these chart types, you must specify a numerator and a denominator. The chart tool calculates the ratio and, depending on the chart type, represents the result as circles, squares, or person icons in a square grid or as a linear bar (a gauge).

The linear gauge is often used to show progress towards a goal while the waffle is used to show proportion (of a population, for example).

Due to the small size of these visualization types, leaving them in the standard width on DFE works well.

Do use:

  • To place emphasis on parts-to-whole contribution
  • To visualize whole number percentages. These charts can show the value of a single percentage point more clearly than a pie or donut chart.

Don't use:

  • If isolating one point of data tells an incomplete perspective
  • If there are many points of data contributing to a whole
  • For visualizing precise percentages with fractions of a percent
  • For values that exceed 100%

  • Reserve waffles and gauges for key data points. A data point may be interesting and merit pointing out somewhere on the page, but if doesn't support the primary public health messages you're trying to convey, don't highlight it.
  • You can use waffles and gauges singly or in groups. Grouped visualizations invite readers to compare data points, so you should make certain grouped data points are comparable in terms of public health messaging and presentation. While there may be exceptions to the rule, generally this means that all charts in the group are the same type — waffle or gauge — and that the numeric results are based on the same denominator.
  • When grouping linear gauges, stack them vertically if possible. This arrangement helps the reader scan the information more easily. (Remember to test your data visualizations in both small and large viewports.)
  • Good titles are invaluable. The chart title should be long enough so that your audience can make sense of the relationships between the elements. A glance at the title should clearly convey what the chart contains.
  • Chart supporting text can highlight key public health messages, but keep the text brief.
  • Providing a data source makes your graphic more reputable. It also allows those who are interested to dig deeper. (You can use the Citation / Subtext element to provide a data source for an individual waffle or gauge.)
  • Customizations exist for colors, font, and imagery in the Visualization Editor. If a series of visualizations is presented on a page or across related pages, we recommend that you use consistent visual settings.
  • Most inline styling can be applied to the text elements (such as boldface, italics, etc.).

Quick Build Notes

  1. Select a waffle or gauge as the Visualization Type.
  2. Upload your data.
  3. Type in the title and other text fields in the General panel.
  4. Set the Numerator and Denominator fields in the Data panel.

Configuration Options

The example visualizations below highlight options available for waffle and gauge charts. Key configuration selections are in the build notes section under each example.

For in-depth configuration information visit the Configuration Options section.

Count Comparison

This waffle chart shows the percentage of Federal inputs out of the total number of inputs. The chart designer achieved this result by setting the numerator as the sum of inputs where type = Federal and the denominator as the sum of all inputs. Note that the supporting text is short.

Sample Data: Waffle Chart Data

Data Format
  • Vertical
  • Multiple Series: No
General
  • Chart Type: Waffle
Data
Numerator
  • Data Column: Amount
  • Data Function: Count
  • Data Conditional: Type = Federal
Denominator
  • Select from Data
  • Data Column: Amount
  • Data Function: Count
Visual
  • Shape: Square
  • Layout: Horizontal
  • Data Point Font Size: 75
  • Display Border

Average Compared to Max Value

This waffle chart is calculating the average of all inputs and comparing the average against the maximum number in the data column. Vertical configuration was selected.

Sample Data: Waffle Chart Data

Data Format
  • Vertical
  • Multiple Series: No
General
  • Chart Type: Waffle
Data

Numerator
  • Data Column: Amount
  • Data Function: Mean (Average)
Denominator
  • Select from Data
  • Data Column: Amount
  • Data Function: Max
Visual
  • Shape: Circle
  • Layout: Vertical
  • Data Point Font Size: 75
  • Display Border
  • Use Theme Border Color

Filtered Minimum Compared to Total Amount

This waffle chart has been filtered within the Visualization Editor to reflect only data from California in the year 2019.

Sample Data: Waffle Chart Data

Data Format
  • Vertical
  • Multiple Series: No
General
  • Chart Type: Waffle
Data
Numerator
  • Data Column: Amount
  • Data Function: Min
Denominator
  • Select from Data
  • Data Column: Amount
  • Data Function: Sum
Add Filter
  • Column: Location
  • Column Value: California
Add Filter
  • Column: Year
  • Column Value: 2019
Visual
  • Shape: Person
  • Layout: Horizontal
  • Use Accent Style

Linear Gauge

The linear gauge can be used in place of the waffle chart to show proportion. The options are essentially the same, except for some visual settings. As with the numerator, you can have the tool calculate the denominator from the source data. Or you can enter a denominator.

Sample Data: Gauge Data

Data Format
  • Vertical
  • Multiple Series: No
General
  • Chart Type: Gauge
  • Chart Subtype: Linear
Data
Numerator
  • Data Column: Outreach Total
  • Data Function: Sum
  • Data Conditional: Month = December
Denominator
  • Select from Data
  • Data Column: Outreach Total
  • Data Function: Sum

  • Suffix: %
  • Round: 1
  • Show Percentage
Visual
  • Data Point Font Size: 32
  • Display Border
  • Use Theme Background Color

Linear Gauge without Message

The linear gauge is often used to show progress towards a goal. At times you may want to keep visual details to a minimum by omitting the message text. Just make certain that the context for the data visualization is clear. You can also control the size of the numeric result.

Sample Data: Gauge Year to Date Data

Data Format
  • Vertical
  • Multiple Series: No
General
  • Chart Type: Gauge
  • Chart Subtype: Linear
Data
Numerator
  • Data Column: Total YTD
  • Data Function: Sum
Denominator
  • Select from Data
  • Data Column: Goal
  • Data Function: Sum

  • Suffix: %
  • Value Descriptor: Of
  • Show Percentage
  • Show Denominator
Visual
  • Data Point Font Size: 45
  • Display Border
  • Use Theme Border Color
  • Use Accent Style
  • Use Theme Background Color
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Content Source:
Office of Communications