🔤 Letter Frequency Counter
By ToolNimba Text Tools Team · Updated 2026-06-19
Each letter that appears at least once, with its share of all letters.
| # | Letter | Count | Percent | Bar |
|---|
Enter some text above to build the letter frequency table.
Letter frequency analysis tells you how often each letter of the alphabet shows up in a piece of text. Paste or type anything below and this tool counts every letter from A to Z (case-insensitive), then sorts them so you can instantly see which letters dominate and which barely appear. It reports the total letter count, the number of distinct letters, and the single most and least common letters, alongside a full table of counts and percentages. Spaces, digits, and punctuation are ignored, so the percentages always add up across the letters alone.
What is the Letter Frequency Counter?
Letter frequency is the count of how many times each letter appears in a body of text, usually shown as both a raw count and a percentage of all the letters present. In English, the distribution is famously uneven: E, T, A, O, I, and N together make up a large share of typical writing, while J, Q, X, and Z are rare. Because this pattern is so stable across normal English prose, frequency counts are a quick fingerprint of a text and a classic starting point for codebreaking.
The most well-known use is in cryptanalysis. A simple substitution cipher (where each letter is consistently swapped for another) preserves the frequency pattern of the original language, it just relabels the letters. By counting the ciphertext letters and comparing the shape of the distribution to the known frequencies of English, an analyst can guess that the most common ciphertext symbol probably stands for E, the next for T, and so on. This is exactly the technique that breaks Caesar shifts and other monoalphabetic ciphers without a key.
This tool restricts itself to the 26 Latin letters A to Z and folds uppercase and lowercase together, so A and a are counted as the same letter. Everything else (spaces, line breaks, numbers, and punctuation) is excluded from both the count and the percentage base. That keeps the percentages clean: each figure is the share of that letter out of all letters, not out of all characters, which is the convention used in frequency tables and cipher work.
When to use it
- Breaking or analysing simple substitution and Caesar ciphers by matching the ciphertext distribution to known English letter frequencies.
- Checking a pangram or constrained-writing piece to confirm which letters are present and how balanced the usage is.
- Teaching cryptography, statistics, or linguistics with a clear, hands-on demonstration of how uneven letter usage really is.
- Auditing a sample of text to spot an unusually high or low count for a specific letter before designing a font, keyboard layout, or word game.
How to use the Letter Frequency Counter
- Paste or type your text into the box, or click Load sample text to try it with three pangrams.
- Read the summary cards for the total letter count, distinct letters used, and the most and least common letters.
- Scroll the table to see every letter that appears, with its count, percentage, and a comparison bar.
- Switch the Sort by menu between frequency order and alphabetical order to view the data either way.
Formula & method
Worked examples
You analyse the word "mississippi" to find its letter frequencies.
- Lowercase the text and keep only a-z letters: m, i, s, s, i, s, s, i, p, p, i
- Total letters = 11
- Count each: i = 4, s = 4, p = 2, m = 1
- i percentage = 4 ÷ 11 x 100 = 36.36%
- s percentage = 4 ÷ 11 x 100 = 36.36%
- p percentage = 2 ÷ 11 x 100 = 18.18%, m percentage = 1 ÷ 11 x 100 = 9.09%
Result: Most common: i and s (4 each, 36.36%) · Least common: m (1, 9.09%) · 4 distinct letters
You count letters in the phrase "the lazy cat" (spaces ignored).
- Keep only a-z letters: t, h, e, l, a, z, y, c, a, t
- Total letters = 10
- Count each: a = 2, t = 2, then c, e, h, l, y, z = 1 each
- a percentage = 2 ÷ 10 x 100 = 20.00%
- t percentage = 2 ÷ 10 x 100 = 20.00%
- Every single-count letter = 1 ÷ 10 x 100 = 10.00%
Result: Most common: a and t (2 each, 20.00%) · 8 distinct letters out of 10 total
Approximate frequency of letters in typical English text (used as a baseline in frequency analysis)
| Letter | Approx. frequency | Rank |
|---|---|---|
| E | 12.7% | 1 (most common) |
| T | 9.1% | 2 |
| A | 8.2% | 3 |
| O | 7.5% | 4 |
| I | 7.0% | 5 |
| N | 6.7% | 6 |
| Q | 0.10% | 25 |
| Z | 0.07% | 26 (least common) |
What this tool counts and what it ignores
| Character type | Counted? | Example |
|---|---|---|
| Letters A to Z | Yes (case-insensitive) | A and a both count as a |
| Digits | No | 0 1 2 3 are skipped |
| Spaces and line breaks | No | word gaps do not count |
| Punctuation and symbols | No | . , ! ? @ # are skipped |
| Accented or non-Latin letters | No | e with accent, Greek, Cyrillic skipped |
Common mistakes to avoid
- Expecting percentages to add up out of all characters. The percentages here are each letter as a share of total letters, not total characters. Spaces, digits, and punctuation are excluded from the base, so a 12% figure means 12% of the letters, not 12% of everything you typed.
- Treating uppercase and lowercase as different letters. This tool is case-insensitive: A and a are merged into one letter. If you need a case-sensitive count, that is a different analysis and is not what frequency analysis usually means.
- Assuming a short text matches the standard English table. The famous E, T, A, O ordering holds for long, ordinary English passages. A short sentence, a pangram, or specialised jargon can have a very different shape, so do not read too much into a small sample.
- Forgetting that accented and non-Latin letters are skipped. Only the 26 plain A to Z letters are counted. Characters like an accented e, or letters from Greek or Cyrillic scripts, are ignored entirely, which can undercount text in other languages.
Glossary
- Letter frequency
- How often a given letter appears in a text, shown as a count and as a percentage of all letters present.
- Frequency analysis
- The technique of counting how often symbols occur in a text, used to break substitution ciphers by matching the pattern to a known language.
- Substitution cipher
- A code where each letter is consistently replaced by another letter or symbol, leaving the underlying frequency pattern intact.
- Pangram
- A sentence that uses every letter of the alphabet at least once, such as the quick brown fox phrase.
- Distinct letters
- The number of different letters of the alphabet that appear at least once in the text.
Frequently asked questions
How does the letter frequency counter work?
It reads your text, converts it to lowercase, and counts every character from a to z. It then shows each letter with its raw count and its percentage of the total letters, plus the single most and least common letters. Spaces, digits, and punctuation are ignored.
Is the count case-sensitive?
No. Uppercase and lowercase versions of a letter are merged, so A and a are counted together as one letter. This matches the standard convention used in frequency analysis and cipher work.
Are spaces, numbers, and punctuation included?
No. Only the 26 letters A to Z are counted. Spaces, line breaks, digits, and punctuation are excluded from both the total and the percentage base, so every percentage is a share of the letters alone.
How is this useful for breaking ciphers?
Simple substitution and Caesar ciphers keep the frequency pattern of the original language. By comparing the most common letters in your ciphertext to known English frequencies (E, T, A, O lead the list), you can guess which cipher letter stands for which real letter.
What is the most common letter in English?
In typical English text the letter E is the most common, at roughly 12.7%, followed by T and A. The rarest are Q and Z, each well under 1%. Short or unusual texts can differ, which is why a single sentence may not match the standard table.
Does this tool send my text anywhere?
No. All counting happens in your browser using plain JavaScript. Your text is never uploaded or stored, so you can safely analyse private or sensitive content offline.