Count
count.co
  • Getting Started
    • What is Count?
    • Count FAQ
    • Intro to your workspace
    • Example canvases
    • Getting started guides
      • Set up your workspace and projects
        • 1. Review workspace settings
        • 2. Create and organise your projects
      • Canvas orientation
      • Your first ad hoc analysis
        • 1. Examples and templates
        • 2. Build your first queries
        • 3. Create visuals
        • 4. Caching, local cells and scheduling
        • 5. Collaborating with a stakeholder
      • Your first report
        • 1. Examples and templates
        • 2. Filters and control cells
        • 3. Sharing your report
        • 4. Alerts
  • Connect your data
    • Database connection overview
      • Athena
      • Azure Synapse
      • BigQuery
      • Databricks
      • Microsoft SQL Server
      • MySQL
      • PostgreSQL
      • Redshift
      • Snowflake
    • Refresh database schema
    • Upload CSV files
    • dbt integration
      • ☁️dbt Cloud integration
      • 👩‍💻dbt Core integration
  • Import & Export
    • Import from other tools
      • Import Miro files
      • Import SQL files
      • Import Google Sheets
      • Import Jupyter notebooks
    • Export code and results
      • Export compiled SQL and Jinja-SQL
      • Export CSV files
      • Export images and PDF files
  • THE CANVAS
    • Navigating the canvas
      • Canvas tool bar
      • Data sidebar
      • Customizing the canvas
    • Canvas objects
      • Cells
      • Text and markdown
      • Shapes and tools
      • Sticky notes
      • Frames
      • Images
      • Embeds
      • Stamps
      • Grouping objects
      • Object order and alignment
      • Locking objects
      • Scaling objects
      • Shared styles
    • Overviews
    • Templates
    • Count AI
    • Alerts and subscriptions
      • Slack integration
    • Keyboard shortcuts
  • Querying data
    • Cells overview
      • Dynamic query compilation engine
    • SQL cells
      • Referencing other cells
      • Jinja templating
      • SQL formatting
    • Python cells
    • Visual and low-code cells
      • Calculations in visuals and low-code cells
      • Joins in visuals and low-code cells
    • Control cells
      • Single and multiple selects
      • Date controls
      • Text, number, and boolean controls
      • Custom control cells
    • Local DuckDB cells
      • DuckDB on the server
    • Query caching and scheduling
    • Manage queries and results
    • Troubleshooting
  • Visualizing data
    • Visualization overview
    • Templated visuals
    • Custom visuals
      • Marks
      • Facet
      • Subplots
      • Style
      • Filters
    • Formatting a visual
      • Axes
        • Secondary Axis
      • Colors and labels
      • Legends
      • Tooltips
    • Column summaries
    • Dynamic text
    • Every Visual Under the Sun
  • Presenting and Reporting
    • Reports and Slides
  • Count Metrics
    • Intro to Count Metrics
    • Build and edit a catalog
    • Views
      • Creating views
      • Customizing views
    • Datasets
      • Creating datasets
    • Save changes to the catalog
      • Catalog validation
      • Version control
    • Exposing catalogs to the workspace
    • Caching in Count Metrics
    • Using the catalog
      • Explore from cell
  • Sharing and Permissions
    • Real-time collaboration
    • Comments
    • Sharing permissions
    • Shared links
    • Embedding canvases
  • History and Versions
    • Version control
    • Duplicating and merging
    • Data snapshots
  • Settings and administration
    • Workspace settings
      • Workspace members
      • Groups
      • Tags
      • Billing
      • Single sign-on (SSO)
        • Okta
        • Entra ID
        • JumpCloud
        • Google
        • Generic OIDC
      • Brand
    • Connection settings
    • Project settings
    • User settings
    • Roles and permissions
  • Quick guides
    • Interactive control guides
      • Date ranges
      • Date groupings
      • Search
      • Select All
  • Resources
    • Join the Slack community
  • Blog
  • Security overview
  • Terms of use
  • Pricing FAQ
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On this page
  • How to edit legends
  • How to show legends
  • Set legend position
  • How to use legends with multiple marks
  1. Visualizing data
  2. Formatting a visual

Legends

Legends appear by default if there are any columns added to the Color or Size fields.

PreviousColors and labelsNextTooltips

Last updated 6 months ago

A data legend is a small key or guide that explains what the symbols, colours, or patterns in a chart or graph mean. It's like the map key you use to navigate a road trip — it tells you what everything stands for, making sure you don't get lost in the data.

How to edit legends

When you have configured your visualisation, if you right click on the legend you will have options to:

  • change legend location

  • hide legend

  • edit legend

How to show legends

Simply navigate the column you want to unhide the legend for and click the 3 little dots. Then jump to the 'display' option as shown in the screenshot.

Set legend position

After right-clicking on a legend title, choose a position from the Legend position menu:

How to use legends with multiple marks

When configuring a custom visual, you will have the option of adding multiple marks to the marks legend, this can be done by clicking the 3 dots within each individual mark.

Once you have added each of your chosen marks to the legend, you need to make it visible at a visual level. This is done by clicking the 3 dots just under the custom tab.