The fastest way to clean numeric data. Remove digits, strip phone numbers, and clean up mixed text instantly.
Data cleaning is a critical step in analysis and programming. Often, you might have text contaminated with unwanted digits, such as ID numbers mixed with names, page numbers in a document, or timestamps in logs. Manually deleting them is tedious; our tool automates it instantly.
This tool is ideal for:
| Scenario | Input Example | Result (Remove All) |
|---|---|---|
| Cleaning Names | John Doe 1990 | John Doe |
| Removing IDs | Product_5542 | Product_ |
| Cleaning Logs | Error 404 at 12:00 | Error at : |
Prepare your text for analysis or publication.
If you are working with scraped data or customer lists, numeric noise is common. Instead of writing a custom Python script or Regex formula every time, just paste your text here to sanitize it in seconds.
Uses advanced Regex to target digits.
Your data never leaves your browser.
Sometimes you want to keep version numbers (v2.0) but remove quantities (500 items). Our "Remove Standalone" feature helps you differentiate between numbers that are part of words and those that aren't.
The "Remove All Digits" button removes the digits 0-9 but leaves the period/dot (.) behind. This is generally safer for text, but you can check the output to be sure.
If you choose "Remove All Digits", it strips the numbers out of the word (e.g., "H3llo" becomes "Hllo"). If you choose "Remove Standalone", "H3llo" remains untouched.
No. We process everything locally in your browser using JavaScript. We do not see or store your data.