Description
The Extract Numbers activity scans a text column and extracts numeric values using various extraction modes. It supports multiple formats such as plain numbers, currency amounts, scientific notation, and even expanded notations (e.g., 5K → 5000).
Use case:
Extracting invoice amounts, order IDs, and numeric metrics from unstructured strings such as “Order #1234, Amount: $45.67” or “Salary: 120K”.
| Type | Description |
|---|
| Data | Dataset containing a text column |
Output
| Type | Description |
|---|
| Transformed Data | Original or enhanced data with numeric values extracted from text |
Configuration Fields
| Field Name | Required | Description |
|---|
| Column | Yes | Name of the text column from which to extract numbers |
| Extract Mode | Yes | Extraction strategy:- Several – Extract all numbers separately
- JSON Array – Store as an array
- Expand Notation – Convert notation like 1K to 1000
- Decimal Separator – Handle regional decimal formats
|
| Output Column | Yes | Name of the column to store the extracted numbers |
| Include Original | No | Whether to keep the original column in the final output |
| Separator | Conditional | Character used to split values (only shown when Extract Mode is Decimal Separator) |
| Transaction Details |
|---|
| Order #1234, Amount: $45.67 |
| Invoice 56789 - $120.50 |
| Product ID: 998, Price: $30.00 |
Sample Configuration
| Field | Value |
|---|
| Column | Transaction Details |
| Extract Mode | Several |
| Output Column | Extracted Numbers |
| Include Original | Yes |
| Separator | Not Applicable |
Sample Output
| Transaction Details | Extracted Numbers_1 | Extracted Numbers_2 |
|---|
| Order #1234, Amount: $45.67 | 1234 | 45.67 |
| Invoice 56789 - $120.50 | 56789 | 120.50 |
| Product ID: 998, Price: $30.00 | 998 | 30.00 |
