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letter-frequency

Letter frequency analysis counts how often each letter appears in a text. In English prose, E is the most common letter (~12.7%), followed by T (9.1%), A (8.2%), O (7.5%), I (7.0%) — the famous ETAOIN SHRDLU. Frequencies are foundational to classical cryptography (breaking Caesar / Vigenère ciphers), linguistic analysis (identifying language from a sample), word games (Scrabble strategy, Wordle openers), and typesetting. The ZTools Letter Frequency tool counts case-insensitive occurrences, ranks them, optionally compares to expected English frequencies, and shows a histogram chart.

Use cases​

Break a Caesar cipher​

In ciphertext where E was shifted, the most-frequent letter probably maps to E. Frequency analysis breaks Caesar in seconds.

Identify the language of a sample​

English vs Spanish vs French have distinct frequency profiles. Compare your sample's top letters to known profiles.

Scrabble / Wordle strategy​

Best Wordle starting words use ETAOIN letters — high information content per guess.

Linguistic analysis​

Compare letter frequencies across genres, time periods, authors. Anomalies signal stylistic shifts.

How it works​

  1. Paste text — Any length. Tool counts letters case-insensitively by default.
  2. Configure — Case-sensitive / case-insensitive, include digits, include punctuation, include whitespace.
  3. Compute — Walks once over the text. O(n).
  4. Display — Sorted table (letter, count, %), bar chart, comparison to standard English frequencies.

Examples​

Input: "The quick brown fox jumps over the lazy dog"

Output: O: 4 (10.5%), E: 3 (7.9%), H: 2, R: 2, T: 2, U: 2 — pangram contains every letter at least once.

Input: 500-word English essay

Output: E ~12-14%, T ~9%, A ~8% — close to standard English profile. Significant deviation suggests non-standard text (technical, poetry, etc.).

Input: Spanish text

Output: E and A dominate (~14% and 13%); R, S, N follow. Different from English profile.

Frequently asked questions​

How accurate is "standard English frequency"?

Source-dependent. The classic table (E 12.7%, T 9.1%, ...) comes from a 1939 sample by linguist Frederick Mosteller. Modern texts (especially with code, URLs) shift these numbers slightly.

Bigram and trigram frequencies?

Out of scope here — for n-gram analysis, use a dedicated linguistic tool. Single-letter frequency is the most-cited.

Does case matter for cryptanalysis?

Usually not — case-insensitive is standard for frequency-based attacks. Cipher implementations rarely preserve case meaningfully.

Privacy?

All in browser.

Tips​

  • For cryptanalysis, also note bigram patterns ("th", "he", "in" are top English bigrams) — single letters alone aren't always enough.
  • Compare your sample to a known reference distribution — the deviation pattern reveals language / cipher.
  • For Wordle openers, ADIEU / AUDIO / AROSE all hit ETAOIN-rich starts.
  • For real cryptanalysis, modern ciphers (AES, RSA) defeat frequency analysis — this tool is for classical ciphers, education, and curiosity.

Try it now​

The full letter-frequency runs in your browser at https://ztools.zaions.com/letter-frequency — no signup, no upload, no data leaves your device.

Open the tool ↗

Last updated: 2026-05-06 · Author: Ahsan Mahmood · Edit this page on GitHub