Remove Unwanted Chars
Remove specific characters or all non-alphanumeric characters from text.
💡 Common Use Cases
- Strip emojis and symbols from usernames or filenames
- Remove punctuation before counting or comparing words
- Delete digits from mixed alphanumeric strings
- Clean special characters from data before a database import
- Remove non-ASCII characters that break legacy systems
Strip unwanted characters from any text — fast and precise
Sometimes your text has exactly the wrong stuff in it: stray symbols, accidental punctuation, control characters from a bad copy-paste, emoji from a chat message that need to go before the text becomes a database key, or any number of other unwanted artefacts. The Remove Unwanted Characters tool lets you specify exactly what should be stripped — by character, by category, or by pattern — and gives you clean output in a single click.
How to use it
Drop your CSV data, scraped content, or symbol-cluttered text into the editor. Choose your removal mode:
- Remove specific characters — type the characters you want gone (e.g. "$#@%")
- Remove all punctuation — strips every standard punctuation mark
- Remove all digits — strips 0–9
- Remove all letters — strips a–z and A–Z (and accented letters)
- Remove non-alphanumeric — keeps only letters and digits
- Remove emoji — strips emoji characters and other decorative symbols
- Remove non-ASCII — strips anything outside the basic English character set (accents, non-Latin scripts, emoji, special punctuation)
Click Apply. The result appears immediately. Copy it and use it.
Real-world uses
Generating database-safe keys. A user-supplied string like "Customer's First Choice!" can become "CustomersFirstChoice" by stripping non-alphanumeric characters, ready for use as an identifier in URLs, file names, or database keys.
Phone number normalisation. Phone numbers arrive in countless formats: "(555) 123-4567", "+1 555-123-4567", "555.123.4567". Stripping every character except digits gives a single canonical form ("5551234567") that you can compare reliably.
Stripping emoji from chat exports. When you export a chat log to use the text content for analysis, emoji are usually noise. Stripping them produces a clean text-only version.
Cleaning OCR output. Optical character recognition often produces garbage characters where it could not read the source clearly. Stripping non-ASCII or non-alphanumeric content can clean up the result before further processing.
Removing accents and diacritics. Names from international sources often include accented characters that some systems cannot store. Stripping non-ASCII converts "Müller" to "Mller", which is admittedly ugly — for a better solution, use a transliteration tool that converts ü to u. But for quick cleanup, this tool will at least produce ASCII-only output.
Preparing slugs for URLs. A blog post title becomes a URL slug by stripping punctuation and special characters, then lowercasing and replacing spaces with hyphens. The first step is character removal.
Stripping markdown or HTML markup. Quick way to remove formatting characters like **, __, #, or angle brackets from a body of text.
The custom-character mode in detail
When you choose "remove specific characters", every character you enter in the field will be stripped from the input — wherever it appears. The field treats each character as a literal: typing "$#" will remove every dollar sign and every hash. There is no regex involved in custom mode (use Find & Replace for regex), so you can include characters like ., *, or ? directly without escaping.
Letters vs digits vs alphanumeric
"Letters" in this tool means alphabetic characters, including accented ones (é, ñ, ü, etc.). "Digits" means 0 through 9. "Alphanumeric" means both combined. "Non-alphanumeric" means everything else — punctuation, whitespace, emoji, symbols, and so on. Choose carefully: stripping "non-alphanumeric" will remove spaces, so words will run together. If you want to keep spaces, choose "remove punctuation" instead.
Privacy
All character stripping happens in your browser. The text is never uploaded, logged, or stored. This makes the tool safe for sensitive data — customer names, internal IDs, phone numbers, or anything else you would not paste into a server-side cleaner.
If you regularly clean and normalise text data, combine this tool with Remove Extra Spaces, Convert Case, and Remove Duplicates for a full data-cleaning pipeline that runs entirely in your browser.