Extract regex matches from a column into new columns, with a live match preview and three extraction modes.
Description
Applies a regular expression pattern to a text column and extracts matching content into new columns, with a live preview as you type. Three modes cover different needs: Smart Extract takes the first match per cell and, if your pattern has capture groups, also adds one column per group. Precision Capture outputs only the capture-group values (no whole-match column), packed left to right — ideal for structured multi-part extraction. Greedy Collect captures every match per cell, one column per match position, so the number of output columns is set by whichever row has the most matches.
Best For
Extracting dates, amounts, reference numbers, or codes from freeform text
Pulling several named parts out of a structured string in one pass with Precision Capture
Collecting every occurrence of a pattern from a long text field with Greedy Collect
How to Use
1Connect a table and pick the source column
Pass a table with a text column into the node, then choose the column to extract from.
2Write your pattern
Type a regular expression into the pattern field. The preview updates live to show what it matches.
3Choose an extraction mode
Smart Extract for a first-match column (plus one per group), Precision Capture for just the capture groups, or Greedy Collect for every match.
4Name the output column
Enter a base name for the new column(s) — in Greedy Collect mode, extra matches get a numbered suffix (Name_1, Name_2, ...).
Tips & Notes
Smart Extract keeps the whole match, plus its groups
If your pattern has capture groups, Smart Extract still gives you the full match in the first column and each group in its own column after it.
Greedy Collect's column count depends on your data
The number of output columns is set by the row with the most matches — if most rows have 1–2 matches but one has 10, you'll get 10 output columns, mostly blank.
