Count word occurrences and percentages in text

How it works

Cleaned tokens enter a map under their original or lowercased spelling, then rows sort by descending count and stop at the chosen limit. Each percentage divides the token count by every cleaned token before optional English stop-word removal.

• One-character tokens and the first 50 frequency rows are included by default.
• The English stop list is disabled initially because it is an editorial filter rather than a language-neutral rule.

Worked example

											the cat sat on the mat and the cat slept
										

												Word   Count  Percentage
-----  -----  ----------
the    3      30
cat    2      20
sat    1      10
on     1      10
mat    1      10
and    1      10
slept  1      10
											

When to use this

Copy editors spot repeated terms in articles, qualitative researchers inspect interview transcripts, and search analysts review keyword concentration in landing-page paragraphs.

Edge cases

• don't and state-of-the-art each remain one token because apostrophes and hyphens survive cleaning.
• café loses é under the ASCII word pattern, so its resulting token is caf rather than the full French spelling.
• With stop words excluded, a retained count still uses the pre-filter token total as its percentage denominator.