Filter

Keep the rows you need. Remove the rows you do not.

What it does

Filter shows only the rows that match your conditions. A condition compares one column with a value. For example: category is Electronics, or quantity > 10. You build each condition with dropdowns. No code is needed.

Filter your data

  1. Type filter in the Search transforms box, in the Pipeline panel.
  2. Select Filter in the results. The Filter panel opens below the grid.
  3. Look at Action. Keep Keep matching rows selected, or select Remove matching rows.
  4. Click Add Condition. The condition window opens.
  5. Open Select a column… and pick a column.
  6. Pick a comparison from the second dropdown.
  7. Type or pick the value to compare with.
  8. Click Apply Condition, then click Apply.

The grid updates at once. The step appears in your pipeline, where you can edit or delete it later.

The comparisons you can pick

The list adapts to the column type:

  • Text columns: is, is not, contains, starts with, ends with, does NOT start with, does NOT end with, is Empty, is NOT Empty.
  • Number columns: =, !=, >, <, >=, <=, is Empty, is NOT Empty.
  • Date columns: is, before, after, on or before, on or after, is Empty, is NOT Empty.

Combine conditions

One condition is often not enough. In the condition window:

  • Click + And to add a condition that must ALSO match.
  • Click + Or to add an alternative condition.
  • Click Nested group to group conditions, like brackets in math.

Example: keep rows where category is Electronics AND quantity > 5. Two conditions, joined with And.

Tips

  • Not sure if a value exists? Click the small grid icon next to a column name first. It shows the column's values and counts.
  • Filters here become pipeline steps. The quick filters from the column explorer are different. They only change your current view.
  • To invert a whole filter later, edit the step and switch Action to Remove matching rows.

For SQL users

The condition window has a SQL Expression tab. Write any DuckDB WHERE expression there. The step runs as:

SELECT * FROM data WHERE category = 'Electronics' AND quantity > 5
Try Filter with sample data →

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