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Letter Frequency Analyzer

Free letter and character frequency counter. Shows each letter's count and percentage, with comparison against expected English frequencies (E ~12.7%, T ~9.3%).

When to use this

Use the letter frequency analyzer for cryptography puzzles (frequency analysis is the classic substitution-cipher attack), Wordle / Scrabble strategy, linguistic teaching, or for detecting unusual content distributions.

How it compares

Letter frequency is character-level analysis; Word Frequency is word-level. The two reveal very different things — letter frequency exposes the language; word frequency exposes the content.

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How it works

Each character in the text is counted. The tool reports counts and percentages, sorted by frequency.

For English baseline mode, the table includes expected frequencies (E ~12.7%, T ~9.3%, A ~8.0%) and the deviation.

Letters with disproportionately high deviations may indicate non-English text, technical vocabulary, or unusual content.

FAQs

What is letter frequency analysis for?

Cryptography (breaking substitution ciphers), Wordle/Scrabble strategy, linguistic teaching, content-type detection.

Why English baseline?

English letter frequencies are stable (E ~12.7%, T ~9.3%, A ~8.0%). Deviations from baseline suggest unusual content or non-English text.

Should I include punctuation?

Off by default — punctuation and digits can swamp letter counts. Toggle on for a complete character analysis.

Worked example

Input

A short English passage.

Output

E: 12.4% (expected 12.7%) · T: 9.0% (9.3%) · A: 8.5% (8.0%) — normal English distribution.

English letter frequencies are remarkably consistent: E is always around 12-13%, T around 9%, A around 8%. Deviations suggest unusual content (technical jargon, proper nouns, or non-English text).

Common pitfalls

  • Expected frequencies are language-specific — change the baseline for non-English text.
  • Short samples (< 200 chars) deviate widely from expected.
  • Punctuation and digits can swamp letter counts — toggle them off for a clean letter analysis.
  • Case-insensitive comparison is appropriate for most analyses.

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