Overview of the Exploration Canvas
The Exploration Canvas houses the tools users need to explore data, shape it, and create derived views.
It consists of two primary components: The Data Table (displays your dataset rows and columns) and the Visual Query Editor (provides tools for filtering and shaping data).
The Visual Query Editor (VQE) provides a visual data shaping interface made up of three tabs:
- Filters: Apply conditions to narrow down your data
- Group: Aggregate and group data by specific columns
- Column Manager: Manage which columns to display and their order
For more information about the Exploration Canvas, see Exploration Canvas for the Open Data Platform
Accessing the Exploration Canvas
From the Primer Page on any dataset or SoQL Derived View:
- Click the Actions button in the top right corner.
- Then select Query Data to access the Exploration Canvas
The Exploration Canvas will now open with your dataset loaded. You can adjust the amount of space these tabs take up on the page by dragging the divider between the data table and the Visual Query Editor.
At the bottom of the page, you'll see the Visual Query Editor with three tabs containing data shaping tools: Filters, Group, and Column Manager.
Click the kebab menu (3 horizontal lines) in a column's header to access quick action options:
- Filter: Opens the Filters tab with this column pre-selected
- Sort Ascending/Descending: Sorts the column in ascending or descending order
- Column Order: Open Column Manager
- Group & Aggregate: Open Group tab
- Exclude Column from Query: Removes the column from this view, but does not affect source data
- Column Description: Displays metadata and information about the column
Filter Tab
This tab allows you to filter the data in your data table. When filtering data in the Exploration Canvas, different operators become available depending on the data type of the column you select. To get started:
Click the Filter tab at the bottom of the page
Select the column dropdown menu to see a scrollable list of available columns, or type to search for a specific column.
Then select the desired column to begin filtering.
Once you've selected a column, choose an operator from the dropdown menu, then enter your filter value.
If needed, you can add more filter conditions (using AND or OR). Click Apply to view the data table with the applied filter(s).
Filter Operators
**Note** The operators available in the dropdown may vary based on the data type of the column you've selected.
Common Operators
| Operator | Description | Example |
|---|---|---|
| Contains | Returns rows where the column value includes the inputted text. |
arrival_city "contains" San → returns rows containing San Francisco, San Antonio, Santiago, etc |
| is | Returns rows where the column value exactly matches the inputted text. |
airline_name "is" United Airlines → returns rows where airline name is exactly United Airlines |
| is not | Returns rows where the column value does not exactly match the text you specify. |
departure_country "is not" USA → returns all flights except flights departing from USA |
| is not one of | Returns rows not matching any value in the list provided |
airline_name "is not one of" Delta, United Airlines → returns rows excluding those airlines |
| is one of | Returns rows that match any value(s) in your list. This is useful when you want to filter for multiple specific values. |
arrival_country "is one of" USA, UK, Japan → returns flights to any of these countries |
| starts with | Filters rows based on the beginning of the text you specify. |
departure_airport "starts with" CH → returns rows like Charles, Chattanooga, Charleston, etc |
Complex Operators
These operators provide advanced filtering options for specialized use cases, including pattern matching, range filtering, and null value handling.
**Note** When using Complex Operators, the text input fields are case-sensitive.
| Operator | Description | Example |
|---|---|---|
| as boolean | Converts values to true/false. Useful for columns with yes/no, true/false, or 1/0 values. |
flight_completed "as boolean" → converts "yes"/"no" or 1/0 values to true/false for further filtering |
| is between | Returns rows where the value falls within a range (inclusive). |
flight_number "is between" 1000, 5000 → returns flight numbers between 1000 and 5000 |
| is greater than | Returns rows where the value is larger than specified. |
flight_number "is greater than" 400 → returns rows with numbers above 400 |
| is greater than or equal to | Returns rows where the value is larger than or equal to specified. |
flight_number "is greater than or equal to" 5000 → returns flight numbers 5000 or higher |
| is less than | Returns rows where the value is smaller than specified. |
flight_number "is less than" 100 → returns flight numbers below 100 |
| is less than or equal to | Returns rows where the value is smaller than or equal to specified. |
flight_number "is less than or equal to" 3000 → returns flight numbers 3000 or lower |
| is like | Pattern matching with wildcards. Use % to represent any number of characters. |
airline_name "is like" %Airlines → matches flights ending with "Airlines" (United Airlines, Southwest Airlines) |
| is not between | Returns rows where the value falls outside of the specified range. |
distance_miles "is not between" 500, 2000 → returns flights shorter than 500 miles or longer than 2000 miles |
| is not like | Does not match the pattern specified. Use % to represent any number of characters. |
airline_name "is not like" %Airways → returns airlines not ending with Airways |
| is null | Returns rows with no value (empty cells). |
arrival_time "is null" → returns flights with missing arrival times |
| is not null | Returns rows with any value (non-empty cells). |
arrival_time "is not null" → returns flights with recorded arrival times |
Once you are done applying filters, you can click the 'Save As' button in the top right corner to save the filtered view of the dataset.
For more information on Filtered Views, see: Creating a Filtered View
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