Cleaning
Find & Replace
Replaces literal text inside one column using an ordered list of find and replace rules.
When to use it
Reach for it when a column holds a handful of known bad spellings, codes or labels that need to become standard values, and no pattern matching is involved.
In a pipeline
File InputFind & ReplaceExport CSV
Settings
| Setting | Type | Required | Default or hint |
|---|---|---|---|
| Column | select | Yes | — |
| Replace Rules (JSON) | textarea | — | [{"find":"old","replace":"new"}] |
Example
Standardise a country label
- Column=Country
- Replace Rules=find "U.S.A." → replace "United States"
| Order | Country |
|---|---|
| A-1 | U.S.A. |
| A-2 | Canada |
| Order | Country |
|---|---|
| A-1 | United States |
| A-2 | Canada |
Only the Country column is touched; rows with no match pass through unchanged.
Worth knowing
- Matching is literal and case-sensitive, so acme and Acme need separate rules.
- Rules run in order on the same value, so a later rule can rewrite what an earlier one produced.
- Every match in the cell is replaced, not only the first one.
- The column is written back as text, so numeric cells become strings after this node.