A Gauge Chart is a variation of a pie chart designed to represent data in a semi-circular format with segments indicating different ranges of values. Unlike traditional gauge charts with a needle, this gauge-style pie chart uses proportional segments to visualize data distribution within a defined range. It is particularly effective for visualizing performance indicators, comparisons between different categories.
Creating a Gauge Chart
To add a new chart:
Within the table, click on the "+" sign above the search bar.
From the drop-down menu, select Chart view.
A box will appear to enter a name for the view—choose a descriptive name that reflects its content.
Select who can edit:
Collaborative for team access and editing.
Personal for individual use. Note: You can't add it in dashboards.
Click "Add".
Click Chart type.
From the list, choose Gauge Chart.
Building a Gauge Chart
To create a Gauge chart, users must configure the following components:
Configuring a Gauge Chart: Example - Risk Impact Analysis
To illustrate how to create a Gauge chart, let's build one that categorizes risks based on their impact level.
For the x-axis (category): we will select "Impact" to show the distribution of risk levels.
For the y-axis (values): we will choose "Titles" with the Count measure to calculate the total number of risks per impact level.
1. Define the x-axis (Category/Slice)
From the drop-down list, choose a column to represent different sections of the Gauge.
In this example, we use "Impact" to categorize risks into different impact levels (e.g., Low, Medium, High).
2. Define the Values (Amounts)
From the drop-down list, choose a column to represent numerical values.
We select "Title", applying the Count measure to calculate the total number of risks within each impact level.
This setup ensures a structured and meaningful representation of risk distribution, making it easier to assess and mitigate high-impact risks.
Available Measures Based on Column Types
For Numeric Columns
Count – Counts the number of entries in the selected column.
Sum – Adds up all numerical values.
Avg – Calculates the average of the values.
Min/Max – Retrieves the smallest or largest value in the dataset.
For Non-Numeric Columns
Count ONLY – Non-numeric columns can only be counted.
Number formatting always follows the column setup within the table.
Customization & Features
Design Customization
Corner Radius:
Users can modify the corner radius to create rounded slice edges for a smoother appearance.
Gap:
Users can adjust the gap between slices to enhance visibility and separate sections more clearly.
Show Legend:
Displays a legend for better readability, especially useful when a breakdown is applied.
Inner Radius:
Users can modify the inner radius by adjusting the central empty space.
Color Customization:
Users can change the color palette or customize slice colors individually to match specific preferences.
Filtering a Gauge Chart
Within the view, click on the funnel icon in the view bar.
A box will appear; click on "Add filter."
Three fields will be displayed:
Choose a Column
Choose a Condition
Choose a Value to Filter by
The filter will be applied directly to the view, updating the displayed data based on the selected criteria.
Sharing a Gauge Chart
To share a chart internally with users who have access to the Charts table:
Click the Share Chart icon at the top corner of the view.
Copy the link.
Share it.
Note: Only people with access permission to this view can see it using this link.
Publishing a Gauge Chart (SOON)
Once your chart is designed and tested, publishing it involves making it accessible to an audience.
To Publish a Chart:
Click the Share Chart icon at the top corner of the view.
Go to the Publish tab.
Click Publish.
Copy the link.
Share it.
Note: There are options to Restrict Access with Password, Change the Link, or Unpublish the Link.
For more details, visit the public sharing article.
Field Availability & Limitations
Unavailable Fields for Both X-Axis & Y-Axis |
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Additional X-Axis Restrictions |
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By integrating these features, Gauge charts provide a structured and visually appealing way to represent categories, enabling users to analyze distributions and make data-driven decisions efficiently.