⌘ K
case · stopwords · top-N · CSV

Count word frequency across any text

Tokenizes Unicode words, optionally lowercases and drops stopwords, then ranks by count.

Word Frequency
Tokens
34
185 B
Unique shown
25
top 50
Top word
the
7×
Filters
lower
applied
Top
input · text
output · frequency
WordBarCount · %
the
7 · 20.59%
fox
2 · 5.88%
dog
2 · 5.88%
forest
2 · 5.88%
quick
1 · 2.94%
brown
1 · 2.94%
jumps
1 · 2.94%
over
1 · 2.94%
lazy
1 · 2.94%
was
1 · 2.94%
not
1 · 2.94%
amused
1 · 2.94%
kept
1 · 2.94%
running
1 · 2.94%
through
1 · 2.94%
grew
1 · 2.94%
darker
1 · 2.94%
as
1 · 2.94%
evening
1 · 2.94%
approached
1 · 2.94%
and
1 · 2.94%
animals
1 · 2.94%
began
1 · 2.94%
to
1 · 2.94%
stir
1 · 2.94%
Quick Start

How to count word frequency

Splits into Unicode tokens, applies the case/stopword options, then groups and ranks.

  1. 01

    Paste text

    Any length — long docs work fine in the browser.

    Tokenisation is Unicode-aware via \p{L}\p{N} property classes — so accented letters, ideographs, and emoji code points all count correctly.

    textUTF-8Unicodecode pointslive
    input · textraw · UTF-8
    The quick brown fox…
    loaded · UTF-8UTF-8 · ready
  2. 02

    Pick options

    Case-insensitive merges 'The' and 'the'. Stopwords strip removes 50 common words.

    Live re-counts run on every keystroke through a memoised reducer, so even multi-megabyte inputs stay smooth in the editor.

    optslivememoisedoptionssnappy
    mode · optionscase-i · live
    The === the
    options applied · livelive
  3. 03

    Top N

    Default 50. Bump for larger samples.

    Output preserves the original line endings (\n vs \r\n) and trailing whitespace is reported separately so you can spot diff-only changes.

    limitline endingswhitespacediff-cleanreproducible
    topN · counted50 · ready
    50 rows
    counted · livecounted
  4. 04

    Copy CSV

    Two-column word,count CSV pastes into any spreadsheet.

    Copy writes via the Async Clipboard API; downloads ship as text/plain; charset=utf-8 — nothing leaves your tab.

    copyclipboardtext/plainblobclient-side
    out · copiedcsv · done
    ✓ Copied CSV
    shipped · ready to shipsuccess
Pro tips

Text-processing fundamentals worth knowing

Tokenise with Unicode classes

Use \p{L}\p{N} with the u flag so accents, ideographs, and emoji count properly.

Normalise line endings

Convert \r\n to \n before diffing or hashing — Windows-vs-Unix endings produce phantom changes.

Mind invisible characters

Zero-width joiners, BOMs, and non-breaking spaces look identical to ASCII space. Strip them before comparison or storage.

Stream don’t slurp

For multi-megabyte text, iterate line-by-line rather than loading everything to memory — keeps the tab responsive.

Choose collation deliberately

Default JS sort is code-point order, not human alphabetical. Use Intl.Collator for locale-aware sorting.

Re-run after normalisation

NFC vs NFD changes byte length but not visible glyphs. String.prototype.normalize() before counts and comparisons.

Related toolsKeyword DensityN-gram GeneratorText StatisticsWord CounterCharacter CounterSort Lines
Use Cases

When to count words

Editing, NLP, learning.

Lexical analysis

Quick vocabulary profile of any text. Tokenisation uses Unicode property classes (\p{L}, \p{N}) with the u flag so accents, ideographs, and emoji code points all count correctly. Surrogate-pair-aware counts mean 🚀 weighs 1, not 2.

Unicode-correct

Vocabulary lists

Build study lists from real texts. Result updates as you type — paste and watch totals settle in milliseconds even on multi-megabyte inputs. Heavy work runs through a memoised reducer so the editor never janks.

diff-clean

NLP prep

Inspect token distribution before training. Output normalises line endings to LF for clean diffs across platforms. Windows-vs-Unix CRLF mismatches disappear, which keeps git blame honest and review comments focused on real changes.

instant counts

Editing pass

Catch overused words at a glance. Code-point counts are stable across NFC/NFD normalisation. Pair with the Reading Time Calculator to layer scan-time on top of raw counts, useful for editorial budgets and SEO meta-description limits.

platform-aware

Search index audit

Confirm important terms have enough mass. All processing runs client-side — paste sensitive or pre-publish copy without it leaving the tab. The clipboard API writes UTF-8 text/plain so it survives transit to any editor or CMS.

code-point-accurate

Style fingerprint

Compare two authors via their top words. Same input plus same options always produces identical output, so the tool is safe to embed in CI scripts or doc-generation pipelines without race conditions.

lossless
FAQ

Frequently asked questions

Unicode letter + digit groups via \p{L}\p{N}. Apostrophes are kept within words.
50 common English function words. Toggle off to include them.
Browser memory is the limit. Tens of megabytes of text usually work.
Stable insertion order — first occurrence wins on ties.
No. All counting runs locally.
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