Punctuation Remover: Free Online Tool
FREE TOOL · NO SIGN-UP
This punctuation remover strips full stops, commas, question marks, quotes, brackets and other punctuation marks from any text in one step. You can keep apostrophes so contractions like “don’t” stay intact, keep hyphens in words like “long-tail”, and optionally remove symbols such as $, +, =, currency signs and emoji too. It is useful for cleaning keyword lists, preparing text for NLP and word frequency analysis, and tidying data for spreadsheets. Paste your text and the clean version appears instantly, all inside your browser.
How to Use the Punctuation Remover
Paste, set three options, copy.
Step 1: Enter or paste your input
Paste your text into the Input text box: a paragraph, an article, survey answers, a keyword export or a column of data. Line breaks are kept. Clear empties the box.
Step 2: Choose your options
- Keep apostrophes (don’t): on by default. Straight (‘) and curly (’) apostrophes stay, so “it’s” and “we’re” are not turned into “its” and “were”.
- Keep hyphens: on by default. Normal hyphens stay, so “e-commerce” and “long-tail” remain one word.
- **Also remove symbols (@#$%&*)**: off by default. When ticked, the tool also removes symbol characters such as $, +, =, <, >, |, ~, ^, currency signs like € and £, and emoji.
Step 3: Copy, download or apply the result
The result updates as you type, with the number of characters removed and the input and output lengths. Double spaces left behind are collapsed to single spaces. Click Copy or Download to save it as a text file.
What Punctuation Removal Does
A punctuation remover deletes every character classed as punctuation in Unicode, which covers far more than the marks on your keyboard. That includes:
- Full stops, commas, colons, semicolons, question marks and exclamation marks.
- Straight and curly quotation marks, and guillemets (« »).
- Brackets of every kind: ( ) [ ] { }.
- Dashes, including en dashes and em dashes, plus underscores.
- Slashes, ellipses and bullet points.
- Characters like @, #, %, & and *, which Unicode classes as punctuation rather than symbols.
- Punctuation from other languages, such as the Spanish ¿ and ¡, Chinese and Japanese full stops and commas, and Arabic commas.
Letters, numbers, spaces and line breaks are never removed. Accented letters and non-Latin scripts stay as they are.
Because punctuation is removed rather than replaced, words joined only by punctuation will merge. “end.Next” becomes “endNext”, and “black/white” becomes “blackwhite”. In most text there is already a space after punctuation, so this is rare, but check slashes and dashes between words. If needed, replace them with spaces first using Find and Replace Text.
Choosing Which Marks to Keep
The right settings depend on what you will do with the text:
| Task | Keep apostrophes | Keep hyphens | Remove symbols |
|---|---|---|---|
| Word frequency or keyword analysis | Yes | Yes | Yes |
| NLP preprocessing (bag of words) | Your choice | Your choice | Yes |
| Cleaning keyword lists | Yes | Yes | No |
| Preparing slugs or IDs | No | Yes | Yes |
| Prices and data with currency | Yes | Yes | No |
Keep symbols (leave the option off) when the text contains prices, maths, code or emoji you need. A price like “$49” keeps its dollar sign by default. Remove symbols when you want only words and numbers, for example before counting words or comparing text.
Note that @, #, % and & are removed even when symbols are kept, because Unicode treats them as punctuation. If you need to keep hashtags or email addresses, protect them first or run the tool on the rest of the text.
Apostrophes, Hyphens and Contractions
Apostrophes and hyphens are the two marks that change meaning when removed.
Apostrophes. Removing them turns contractions and possessives into different words:
- “it’s” becomes “its”
- “we’re” becomes “were”
- “can’t” becomes “cant”
- “John’s” becomes “Johns”
For analysis that counts words, this can create false matches. Keeping apostrophes (the default) avoids it. Both the straight apostrophe and the curly ’ that word processors insert are kept.
Hyphens. Hyphenated compounds like “well-known”, “e-commerce” and “state-of-the-art” act as single words. Keeping hyphens keeps them together. Remove them if you want “well” and “known” counted separately, but note that “e-commerce” would then become “ecommerce”.
Only the standard hyphen (-) is kept. En dashes (U+2013) and em dashes (U+2014) are always removed, since they separate phrases rather than join words. If your text uses them between words without spaces, replace them with spaces first so words do not merge.
Punctuation Stripping for NLP and Data Cleaning
In natural language processing, removing punctuation is a common preprocessing step. It reduces the number of unique tokens, so “tools”, “tools,” and “tools.” are counted as the same word. That matters for:
- Word frequency and keyword density. Our Keyword Density Checker and Keyword Cloud Generator give cleaner results on stripped text.
- Bag-of-words and TF-IDF models, where punctuation adds noise.
- Text matching and deduplication, where “Hello!” and “Hello” should match.
- Survey and review analysis, where people use punctuation inconsistently.
It is not always right, though. Sentiment analysis can use “!” and “?” as signals, and modern language models are trained on punctuated text, so stripping it can hurt results. Sentence splitting also depends on full stops. Remove punctuation after you split sentences, not before.
For data cleaning, follow up with the Case Converter to lowercase everything, and the Extra Spaces Remover to tidy spacing.
Key Features of Our Punctuation Remover
- Free with no signup.
- Removes all Unicode punctuation, including curly quotes, dashes and non-English marks.
- Keep apostrophes and keep hyphens options.
- Optional symbol removal, including currency signs and emoji.
- Collapses leftover double spaces.
- Removed count and character counts.
- Copy and Download; runs in your browser.
Who Removes Punctuation
- SEOs cleaning keyword lists and analysing word frequency.
- Data scientists and analysts preprocessing text for NLP.
- Researchers coding survey responses and interviews.
- Developers normalizing input for search and matching.
- Teachers and puzzle makers preparing word lists.
Pro Tips and Mistakes to Avoid
Checklist of best practices
- Keep apostrophes for English text analysis.
- Replace slashes and dashes between words with spaces first.
- Split sentences before removing punctuation.
- Keep an original copy of the text.
Common mistakes and quick fixes
- Words merged together. Punctuation joined them, like “and/or”. Add spaces first.
- Hashtags and emails broken. @ and # count as punctuation. Process them separately.
- Prices lost their symbol. “Also remove symbols” was on. Untick it.
- Contractions changed. Keep apostrophes was off. Turn it back on.
Get Clean Text for Any Task
Paste your text above to strip punctuation in one click. Then lowercase it with the Case Converter, remove repeated words with the Duplicate Word Remover, and count terms with the Keyword Density Checker. Browse all free tools in the FHSEO Hub tools directory.