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
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      • Microsoft SQL Server
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    • Refresh database schema
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    • dbt integration
      • ☁️dbt Cloud integration
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  • 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
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  • THE CANVAS
    • Navigating the canvas
      • Canvas tool bar
      • Data sidebar
      • Customizing the canvas
    • Canvas objects
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      • Shared styles
    • Overviews
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    • Count AI
    • Alerts and subscriptions
      • Slack integration
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  • 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
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      • Legends
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    • 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
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  • Settings and administration
    • Workspace settings
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  • Quick guides
    • Interactive control guides
      • Date ranges
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On this page
  • Create a visual cell
  • See the output table of a visual
  • Querying a visual
  • Execute visual queries locally
  • Creating a low-code cell
  • How low-code cells work
  1. Querying data

Visual and low-code cells

Making data pretty since 1160 BC*.

PreviousPython cellsNextCalculations in visuals and low-code cells

Last updated 8 months ago

Visual cells are where you create in Count. They can be built from other cells, or directly from database tables.

Create a visual cell

Check out the to see how to create a visual cell.

See the output table of a visual

In any visual, you can toggle between the visual and the table of results. This allows you to see the row-level detail of your visual.

Querying a visual

You can query a visualization to continue your analysis (think: pivot your data, then query the resulting pivot table).

Reference a visual cell by:

  • building a SQL cell that references the visual cell name in the FROM statement, or

  • selecting one of the Reference cell shortcuts near the edge of the selected visual

Execute visual queries locally

By default, your visuals will be executed as queries on your data warehouse. If you would prefer to instead perform these queries locally, you may select the Local database option from the cell controls in the right-hand sidebar.

If the visual is built directly from a database table, then this option will not be possible. In this case you should first create a cell that references the database table, then ensure the visual references that cell.

Low-code cells provide a quick and easy way to query data without the use of SQL or Python. They combine many of the controls of visual cells with the single-table output of a SQL cell.

Creating a low-code cell

Create a low-code cell by either:

  • Clicking on the + icon that appears when the cell is selected and then selecting Low-code cell

How low-code cells work

Low-code cells output a single table just like SQL cells, but their queries are controlled via a UI similar to that for visuals. You can chain low-code cells to each other or any other cell type, and they will update automatically when any of their dependencies change.

First select the base table you want to query, and then either:

  • Drag the columns you'd like to explore into the Columns section

  • Click on each column to add

You can add filters by dragging columns into the Filters section.

Visuals that contain have multiple queries (and therefore output tables) associated with them — one per mark. The output table that is referenced by another cell is that returned by the lowest non-empty mark.

Using the X to place a new cell

Selecting the Low-code cell option from the

You can add columns from multiple tables or cells by using .

more than one mark
keyboard shortcut
control bar
low-code joins
visualizations
Visualization Overview
Seeing visual results table
Querying a visual
First select the table you want to query.
Then click on or drag tokens to add them as columns in the query, or drag to the Filters section.