View source for Letter frequency

{{Short description|How often each letter appears in written language}}
{|class="wikitable sortable floatright"
|-
!rowspan="2"|Letter
!colspan="4"|Relative frequency in the English language<ref name=micka>{{cite web |last=Mička |first=Pavel |title=Letter frequency (English) |url=http://en.algoritmy.net/article/40379/Letter-frequency-English |website=Algoritmy.net |access-date=14 June 2022 |archive-date=4 March 2021 |archive-url=https://web.archive.org/web/20210304152631/http://en.algoritmy.net/article/40379/Letter-frequency-English |url-status=live|quote=Source is Leland, Robert. Cryptological mathematics. [s.l.] : The Mathematical Association of America, 2000. 199 p. ISBN 0-88385-719-7 }}</ref>
|-
!colspan="2" data-sort-type=number|Texts
!colspan="2" data-sort-type=number|Dictionaries
|-
|align="center"|'''A'''||align="right"|{{bartable| 8.2|%|10||background:blue}} || align="right"|{{bartable| 7.8|%|10||background:blue}}
|-
|align="center"|'''B'''||align="right"|{{bartable| 1.5|%|10}} || align="right"|{{bartable| 2.0|%|10}}
|-
|align="center"|'''C'''||align="right"|{{bartable| 2.8|%|10}} || align="right"|{{bartable| 4.0|%|10}}
|-
|align="center"|'''D'''||align="right"|{{bartable| 4.3|%|10}} || align="right"|{{bartable| 3.8|%|10}}
|-
|align="center"|'''E'''||align="right"|{{bartable| 12.7|%|10||background:blue}} || align="right"|{{bartable| 11.0|%|10||background:blue}}
|-
|align="center"|'''F'''||align="right"|{{bartable| 2.2|%|10}} || align="right"|{{bartable| 1.4|%|10}}
|-
|align="center"|'''G'''||align="right"|{{bartable| 2.0|%|10}} || align="right"|{{bartable| 3.0|%|10}}
|-
|align="center"|'''H'''||align="right"|{{bartable| 6.1|%|10}} || align="right"|{{bartable| 2.3|%|10}}
|-
|align="center"|'''I'''||align="right"|{{bartable| 7.0|%|10||background:blue}} || align="right"|{{bartable| 8.6|%|10||background:blue}}
|-
|align="center"|'''J'''||align="right"|{{bartable| 0.15|%|10}} || align="right"|{{bartable| 0.21|%|10}}
|-
|align="center"|'''K'''||align="right"|{{bartable| 0.77|%|10}} || align="right"|{{bartable| 0.97|%|10}}
|-
|align="center"|'''L'''||align="right"|{{bartable| 4.0|%|10}} || align="right"|{{bartable| 5.3|%|10}}
|-
|align="center"|'''M'''||align="right"|{{bartable| 2.4|%|10}} || align="right"|{{bartable| 2.7|%|10}}
|-
|align="center"|'''N'''||align="right"|{{bartable| 6.7|%|10}} || align="right"|{{bartable| 7.2|%|10}}
|-
|align="center"|'''O'''||align="right"|{{bartable| 7.5|%|10||background:blue}} || align="right"|{{bartable| 6.1|%|10||background:blue}}
|-
|align="center"|'''P'''||align="right"|{{bartable| 1.9|%|10}} || align="right"|{{bartable| 2.8|%|10}}
|-
|align="center"|'''Q'''||align="right"|{{bartable| 0.095|%|10}} || align="right"|{{bartable| 0.19|%|10}}
|-
|align="center"|'''R'''||align="right"|{{bartable| 6.0|%|10}} || align="right"|{{bartable| 7.3|%|10}}
|-
|align="center"|'''S'''||align="right"|{{bartable| 6.3|%|10}} || align="right"|{{bartable| 8.7|%|10}}
|-
|align="center"|'''T'''||align="right"|{{bartable| 9.1|%|10}} || align="right"|{{bartable| 6.7|%|10}}
|-
|align="center"|'''U'''||align="right"|{{bartable| 2.8|%|10||background:blue}} || align="right"|{{bartable| 3.3|%|10||background:blue}}
|-
|align="center"|'''V'''||align="right"|{{bartable| 0.98|%|10}} || align="right"|{{bartable| 1.0|%|10}}
|-
|align="center"|'''W'''||align="right"|{{bartable| 2.4|%|10}} || align="right"|{{bartable| 0.91|%|10}}
|-
|align="center"|'''X'''||align="right"|{{bartable| 0.15|%|10}} || align="right"|{{bartable| 0.27|%|10}}
|-
|align="center"|'''Y'''||align="right"|{{bartable| 2.0|%|10}} || align="right"|{{bartable| 1.6|%|10}}
|-
|align="center"|'''Z'''||align="right"|{{bartable| 0.074|%|10}} || align="right"|{{bartable| 0.44|%|10}}
|}

'''Letter frequency''' is the number of times [[Social:Letter (alphabet)|letters]] of the [[Social:Alphabet|alphabet]] appear on average in [[Social:Written language|written language]]. Letter frequency analysis dates back to the Arab mathematician [[Biography:Al-Kindi|Al-Kindi]] ({{c.|801}}–873&nbsp;AD), who formally developed the method to break [[Cipher|ciphers]]. Letter frequency analysis gained importance in [[Earth:Europe|Europe]] with the development of movable type in 1450 AD, where one must estimate the amount of type required for each letterform. Linguists use letter frequency analysis as a rudimentary technique for [[Language identification|language identification]], where it is particularly effective as an indication of whether an unknown [[Social:Writing system|writing system]] is alphabetic, syllabic, or [[Ideogram|ideographic]].

The use of letter frequencies and [[Frequency analysis|frequency analysis]] plays a fundamental role in cryptograms and several word puzzle games, including Hangman, ''[[Engineering:Scrabble|Scrabble]]'', ''Wordle''<ref>{{Cite magazine|last=Guinness|first=Harry|title=The Best Starting Words to Win at Wordle|language=en-US|magazine=Wired|url=https://www.wired.com/story/best-wordle-tips/|access-date=2022-02-12|issn=1059-1028}}</ref> and the television game show ''Wheel of Fortune''. One of the earliest descriptions in classical literature of applying the knowledge of English letter frequency to solving a cryptogram is found in [[Biography:Edgar Allan Poe|Edgar Allan Poe]]'s famous story ''The Gold-Bug'', where the method is successfully applied to decipher a message giving the location of a treasure hidden by Captain Kidd.<ref>{{cite web|title=The works of Edgar Allan Poe in five volumes|url=http://www.gutenberg.org/catalog/world/readfile?fk_files=1977099|author=Poe, Edgar Allan|publisher=Project Gutenberg}}</ref>{{Citation needed|date=February 2023|reason=Given cite supports Poe plot, not 'earliest description' claim}}

Herbert S. Zim, in his classic introductory cryptography text "Codes and Secret Writing", gives the English letter frequency sequence as "'''ETAON RISHD LFCMU GYPWB VKJXZQ'''", the most common letter pairs as "TH HE AN RE ER IN ON AT ND ST ES EN OF TE ED OR TI HI AS TO", and the most common doubled letters as "LL EE SS OO TT FF RR NN PP CC".<ref>{{cite book |last=Zim |first=Herbert Spencer |title=Codes & Secret Writing: Authorized Abridgement |publisher=Scholastic Book Services |year=1961 |oclc=317853773}}</ref> Different ways of counting can produce somewhat different orders.

Letter frequencies also have a strong effect on the design of some keyboard layouts. The most frequent letters are placed on the home row of the Blickensderfer typewriter, the [[Engineering:Dvorak keyboard layout|Dvorak keyboard layout]], Colemak and other optimized layouts.

== Background ==
[[File:CaliforniaJobCaseLayout.png|thumb|right|400px|The California Job Case was a compartmentalized box for printing in the 19th century, sizes corresponding to the commonality of letters]]
The frequency of letters in text has been studied for use in [[Cryptanalysis|cryptanalysis]], and [[Frequency analysis|frequency analysis]] in particular, dating back to the Arab mathematician [[Biography:Al-Kindi|al-Kindi]] (c.&nbsp;801–873&nbsp;AD), who formally developed the method (the ciphers breakable by this technique go back at least to the [[Caesar cipher]] invented by Julius Caesar{{Citation needed|date=January 2024}}, so this method could have been explored in classical times). Letter frequency analysis gained additional importance in Europe with the development of movable type in 1450 AD, where one must estimate the amount of type required for each letterform, as evidenced by the variations in letter compartment size in typographer's type cases.

No exact letter frequency distribution underlies a given language, since all writers write slightly differently. However, most languages have a characteristic distribution which is strongly apparent in longer texts. Even language changes as extreme as from [[Social:Old English|Old English]] to modern English (regarded as mutually unintelligible) show strong trends in related letter frequencies: over a small sample of Biblical passages, from most frequent to least frequent, '''{{not a typo|enaid sorhm tgþlwu æcfy ðbpxz}}''' of Old English compares to '''{{not a typo|eotha sinrd luymw fgcbp kvjqxz}}''' of modern English, with the most extreme differences concerning letterforms not shared.<ref>{{cite web |url=http://www.math.ucsd.edu/~crypto/Projects/MarshaMoreno/TimeComparisonFrequency.pdf |title=Frequency Analysis in Light of Language Innovation |last1=Moreno |first1=Marsha Lynn |date=Spring 2005 |department=Math |publisher=University of California – San Diego |access-date=19 February 2015}}</ref>

[[Engineering:Linotype machine|Linotype machine]]s for the English language assumed the letter order, from most to least common, to be '''{{not a typo|etaoin shrdlu cmfwyp vbgkjq xz}}''' based on the experience and custom of manual compositors. The equivalent for the French language was '''{{not a typo|elaoin sdrétu cmfhyp vbgwqj xz}}'''.

Arranging the alphabet in Morse into groups of letters that require equal amounts of time to transmit, and then sorting these groups in increasing order, yields '''{{not a typo|e it san hurdm wgvlfbk opxcz jyq}}'''.<ref group=lower-alpha>[[Engineering:Morse code|American Morse code]] was developed in the 1830s by Alfred Vail, based on English-language letter frequencies, to encode the most frequent letters with the shortest symbols. Some efficiency was lost in the reformed version now used: the International Morse Code.</ref> Letter frequency was used by other telegraph systems, such as the Murray Code.

Similar ideas are used in modern [[Data compression|data-compression]] techniques such as [[Huffman coding]].

Letter frequencies, like word frequencies, tend to vary, both by writer and by subject. For instance, {{Vr|d}} occurs with greater frequency in fiction, as most fiction is written in past tense and thus most verbs will end in the inflectional suffix -ed / -d. One cannot write an essay about x-rays without using {{Vr|x}} frequently. Different authors have habits which can be reflected in their use of letters. [[Biography:Ernest Hemingway|Hemingway]]'s writing style, for example, is visibly different from [[Biography:William Faulkner|Faulkner]]'s. Letter, [[Bigram|bigram]], [[Trigram|trigram]], word frequencies, word length, and sentence length can be calculated for specific authors, and used to prove or disprove authorship of texts, even for authors whose styles are not so divergent.

Accurate average letter frequencies can only be gleaned by analyzing a large amount of representative text. With the availability of modern computing and collections of large [[Social:Corpus linguistics|text corpora]], such calculations are easily made. Examples can be drawn from a variety of sources (press reporting, religious texts, scientific texts and general fiction) and there are differences especially for general fiction with the position of {{Vr|h}} and {{Vr|i}}, with {{Vr|h}} becoming more common.

Also, to note that different dialects of a language will also affect a letter's frequency. For example, an author in the United States would produce something in which {{Vr|z}} is more common than an author in the United Kingdom writing on the same topic: words like "analyze", "apologize", and "recognize" contain the letter in American English, whereas the same words are spelled "analyse", "apologise", and "recognise" in British English. This would highly affect the frequency of the letter {{Vr|z}} as it is a rarely used letter by British speakers in the English language.<ref>{{cite web |url=http://www.oxforddictionaries.com/words/british-and-american-spelling |archive-url=https://web.archive.org/web/20111228045450/http://oxforddictionaries.com/words/british-and-american-spelling |url-status=dead |archive-date=December 28, 2011 |title=British and American spelling - Oxford Dictionaries |website=Oxford Dictionaries - English |access-date=18 April 2018}}</ref>

The "top twelve" letters constitute about 80% of the total usage. The "top eight" letters constitute about 65% of the total usage. Letter frequency as a function of rank can be fitted well by several rank functions, with the two-parameter [[Beta function|Cocho/Beta rank function]] being the best.<ref>{{cite journal |author1=Li, Wentian |author2=Miramontes, Pedro |title=Fitting ranked English and Spanish letter frequency distribution in US and Mexican presidential speeches |journal=Journal of Quantitative Linguistics |volume=18 |issue=4 |year=2011 |doi=10.1080/09296174.2011.608606 |pages=359 |arxiv=1103.2950|s2cid=1716455 }}</ref> Another rank function with no adjustable free parameter also fits the letter frequency distribution reasonably well<ref>{{cite journal |author=Gusein-Zade, S.M.|title=Frequency distribution of letters in the Russian language |journal=Probl. Peredachi Inf. |volume=24 |issue=4 |pages=102–107 |year=1988}}</ref> (the same function has been used to fit the amino acid frequency in protein sequences.<ref>{{cite journal |author1=Gamow, George |author2=Ycas, Martynas |title=Statistical correlation of protein and ribonucleic acid composition |journal=Proc. Natl. Acad. Sci. |volume=41 |issue=12 |pages=1011–1019 |year=1955 |pmc=528190 |doi=10.1073/pnas.41.12.1011 |pmid=16589789|bibcode=1955PNAS...41.1011G|doi-access=free }}</ref>) A spy using the VIC cipher or some other cipher based on a straddling checkerboard typically uses a mnemonic such as "a sin to err" (dropping the second "r")<ref>{{cite book |first=Friedrich L. |last=Bauer |url=https://books.google.com/books?id=hfWTDr_bvMwC |title=Decrypted Secrets: Methods and maxims of cryptology |year=2006 |page=57 |isbn=9783540481218 |via=Google Books}}</ref><ref>{{cite book |first=Greg |last=Goebel |url=http://www.vectorsite.net/ttcode_03.html |title=The Rise Of Field Ciphers: straddling checkerboard ciphers |year=2009}}</ref> or "at one sir"<ref>{{cite web |first=Dirk |last=Rijmenants |url=https://www.ciphermachinesandcryptology.com/en/onetimepad.htm |title=One-time Pad}}</ref> to remember the top eight characters.

==Relative frequencies of letters in the English language==
[[File:Worn keyboard of English speaker.jpg|thumb|Keyboard used for a long period by an English speaker: the letters E, O, T, H, A, S, I, N, and R show substantial wear; some wear is visible on D, L, U, Y, M, W, F, G, C, B, and P; and little or no wear is visible on K, V, J, Q, X, or Z.]]
There are three ways to count letter frequency that result in very different charts for common letters. The first method, used in the chart below, is to count letter frequency in root words of a dictionary. The second is to include all word variants when counting, such as "abstracts", "abstracted" and "abstracting" and not just the root word of "abstract". This system results in letters like {{Vr|s}} appearing much more frequently, such as when counting letters from lists of the most used English words on the Internet. A final variant is to count letters based on their frequency of use in actual texts, resulting in certain letter combinations like {{Vr|th}} becoming more common due to the frequent use of common words like "the", "then", "both", "this", etc. Absolute usage frequency measures like this are used when creating keyboard layouts or letter frequencies in old fashioned printing presses.

An analysis of entries in the Concise Oxford dictionary, ignoring frequency of word use, gives an order of "EARIOTNSLCUDPMHGBFYWKVXZJQ".<ref>{{cite web |title=What is the frequency of the letters of the alphabet in English? |url=http://oxforddictionaries.com/words/what-is-the-frequency-of-the-letters-of-the-alphabet-in-english |archive-url=https://web.archive.org/web/20111224230632/http://oxforddictionaries.com/words/what-is-the-frequency-of-the-letters-of-the-alphabet-in-english |url-status=dead |archive-date=December 24, 2011 |work=Oxford Dictionary |publisher=Oxford University Press |access-date=29 December 2012}}</ref>

The letter-frequency table below is taken from Pavel Mička's website, which cites Robert Lewand's ''Cryptological Mathematics''.<ref>{{cite web |last=Mička |first=Pavel |title=Letter frequency (English) |url=http://en.algoritmy.net/article/40379/Letter-frequency-English|publisher=Algoritmy.net}}</ref>

According to Lewand, arranged from most to least common in appearance, the letters are: '''etaoinshrdlcumwfgypbvkjxqz'''. Lewand's ordering differs slightly from others, such as Cornell University Math Explorer's Project, which produced a table after measuring 40,000&nbsp;words.<ref>{{cite web |last= |first= |date= |title=English Letter Frequency (based on a sample of 40,000 words) |url=http://pi.math.cornell.edu/~mec/2003-2004/cryptography/subs/frequencies.html |access-date=2021-01-24 |work=cornell.edu}}</ref>

In English, the space character occurs almost twice as frequently as the top letter ({{Vr|e}})<ref>{{cite web |url=http://www.data-compression.com/english.html |title=Statistical Distributions of English Text |website=data-compression.com |archive-url=https://web.archive.org/web/20170918020907/http://www.data-compression.com/english.html |archive-date=2017-09-18 |url-status=dead}}</ref> and the non-alphabetic characters (digits, punctuation, etc.) collectively occupy the fourth position (having already included the space) between {{Vr|t}} and {{Vr|a}}.<ref>{{cite web |last=Lee |first=E. Stewart |title=Essays about Computer Security |publisher=University of Cambridge Computer Laboratory |url=http://www.cl.cam.ac.uk/~mgk25/lee-essays.pdf |page=181}}</ref>

==Relative frequencies of the first letters of a word in English language==
{|class="wikitable sortable floatright"
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!rowspan="2"|Letter
!colspan="4"|Relative frequency as the first letter of an English word{{Citation needed|reason=The article does not reference a source for this data. Can someone who is aware of where this data came from add a reference?|date=January 2022}}
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!colspan="2" data-sort-type=number|Texts
!colspan="2" data-sort-type=number|Dictionaries
|-
|align="center"|'''A'''||align="right"|{{bartable|11.7|%|10||background:blue}} || align="right"|{{bartable|5.7|%|10||background:blue}}
|-
|align="center"|'''B'''||align="right"|{{bartable|4.4|%|10}} || align="right"|{{bartable|6|%|10}}
|-
|align="center"|'''C'''||align="right"|{{bartable|5.2|%|10}} || align="right"|{{bartable|9.4|%|10}}
|-
|align="center"|'''D'''||align="right"|{{bartable|3.2|%|10}} || align="right"|{{bartable|6.1|%|10}}
|-
|align="center"|'''E'''||align="right"|{{bartable|2.8|%|10||background:blue}} || align="right"|{{bartable|3.9|%|10||background:blue}}
|-
|align="center"|'''F'''||align="right"|{{bartable|4|%|10}} || align="right"|{{bartable|4.1|%|10}}
|-
|align="center"|'''G'''||align="right"|{{bartable|1.6|%|10}} || align="right"|{{bartable|3.3|%|10}}
|-
|align="center"|'''H'''||align="right"|{{bartable|4.2|%|10}} || align="right"|{{bartable|3.7|%|10}}
|-
|align="center"|'''I'''||align="right"|{{bartable|7.3|%|10||background:blue}} || align="right"|{{bartable|3.9|%|10||background:blue}}
|-
|align="center"|'''J'''||align="right"|{{bartable|0.51|%|10}} || align="right"|{{bartable|1.1|%|10}}
|-
|align="center"|'''K'''||align="right"|{{bartable|0.86|%|10}} || align="right"|{{bartable|1|%|10}}
|-
|align="center"|'''L'''||align="right"|{{bartable|2.4|%|10}} || align="right"|{{bartable|3.1|%|10}}
|-
|align="center"|'''M'''||align="right"|{{bartable|3.8|%|10}} || align="right"|{{bartable|5.6|%|10}}
|-
|align="center"|'''N'''||align="right"|{{bartable|2.3|%|10}} || align="right"|{{bartable|2.2|%|10}}
|-
|align="center"|'''O'''||align="right"|{{bartable|7.6|%|10||background:blue}} || align="right"|{{bartable|2.5|%|10||background:blue}}
|-
|align="center"|'''P'''||align="right"|{{bartable|4.3|%|10}} || align="right"|{{bartable|7.7|%|10}}
|-
|align="center"|'''Q'''||align="right"|{{bartable|0.22|%|10}} || align="right"|{{bartable|0.49|%|10}}
|-
|align="center"|'''R'''||align="right"|{{bartable|2.8|%|10}} || align="right"|{{bartable|6|%|10}}
|-
|align="center"|'''S'''||align="right"|{{bartable|6.7|%|10}} || align="right"|{{bartable|11|%|10}}
|-
|align="center"|'''T'''||align="right"|{{bartable|16|%|10}} || align="right"|{{bartable|5|%|10}}
|-
|align="center"|'''U'''||align="right"|{{bartable|1.2|%|10||background:blue}} || align="right"|{{bartable|2.9|%|10||background:blue}}
|-
|align="center"|'''V'''||align="right"|{{bartable|0.82|%|10}} || align="right"|{{bartable|1.5|%|10}}
|-
|align="center"|'''W'''||align="right"|{{bartable|5.5|%|10}} || align="right"|{{bartable|2.7|%|10}}
|-
|align="center"|'''X'''||align="right"|{{bartable|0.045|%|10}} || align="right"|{{bartable|0.05|%|10}}
|-
|align="center"|'''Y'''||align="right"|{{bartable|0.76|%|10}} || align="right"|{{bartable|0.36|%|10}}
|-
|align="center"|'''Z'''||align="right"|{{bartable|0.045|%|10}} || align="right"|{{bartable|0.24|%|10}}
|}
The frequency of the first letters of words or names is helpful in pre-assigning space in physical files and indexes.<ref name="ohlman">{{cite book |author=Ohlman, Herbert Marvin |title=Subject-Word Letter Frequencies with Applications to Superimposed Coding |url=http://books.nap.edu/openbook.php?record_id=10866&page=903 |publisher=Proceedings of the International Conference on Scientific Information |year=1959|doi=10.17226/10866 |isbn=978-0-309-57421-1 }}</ref> Given 26&nbsp;[[Engineering:Filing cabinet|filing cabinet]] drawers, rather than a 1:1 assignment of one drawer to one letter of the alphabet, it is often useful to use a more equal-frequency-letter code by assigning several low-frequency letters to the same drawer (often one drawer is labeled VWXYZ), and to split up the most-frequent initial letters ({{Vr|s, a, c}}) into several drawers (often 6&nbsp;drawers Aa-An, Ao-Az, Ca-Cj, Ck-Cz, Sa-Si, Sj-Sz). The same system is used in some multi-volume works such as some encyclopedias. Cutter numbers, another mapping of names to a more equal-frequency code, are used in some libraries.

Both the overall letter distribution and the word-initial letter distribution approximately match the Zipf distribution and even more closely match the Yule distribution.<ref name="pande">{{cite journal |author1=Pande, Hemlata |author2=Dhami, H.S. |url=http://www.skase.sk/Volumes/JTL16/pdf_doc/02.pdf |title=Mathematical Modelling of Occurrence of Letters and Word's Initials in Texts of Hindi Language |journal=JTL |volume=16}}</ref>

Often the frequency distribution of the first digit in each datum is significantly different from the overall frequency of all the digits in a set of numeric data, an observation known as [[Benford's law]].

An analysis by [[Biography:Peter Norvig|Peter Norvig]] on words that appear 100,000 times or more in Google Books data transcribed using [[Optical character recognition|optical character recognition]] (OCR) determined the frequency of first letters of English words, among other things.<ref>{{cite web |url=http://norvig.com/mayzner.html |title=English Letter Frequency Counts: Mayzner revisited or ETAOIN SRHLDCU |website=norvig.com |access-date=18 April 2018}}</ref>{{clear}}

==Relative frequencies of letters in other languages==
{{Cite check|section|date=July 2014}}
{|class="wikitable sortable"
|-
!Letter
!data-sort-type=number|[[Social:English language|English]]<br>{{Citation needed|reason=The article does not reference a source for this data. Can someone who is aware of where this data came from add a reference?|date=January 2022}}
!data-sort-type=number|[[Social:French language|French]]<ref>{{cite web |url=http://gpl.insa-lyon.fr/Dvorak-Fr/CorpusDeThomasTemp%C3%A9 |title=Corpus de Thomas Tempé |access-date=2007-06-15 |url-status=dead |archive-url=https://web.archive.org/web/20070930194046/http://gpl.insa-lyon.fr/Dvorak-Fr/CorpusDeThomasTemp%C3%A9 |archive-date=2007-09-30 |df=dmy-all}}</ref>
!data-sort-type=number|[[Social:German language|German]]<ref>{{cite book |first=Albrecht |last=Beutelspacher |title=Kryptologie |publisher=Vieweg |location=Wiesbaden |year=2005 |isbn=3-8348-0014-7 |page=10 |edition=7}}</ref>
!data-sort-type=number|[[Social:Spanish language|Spanish]]<ref>{{cite book|last=Pratt|first=Fletcher|title=Secret and Urgent: The story of codes and ciphers|publisher=Blue Ribbon Books|year=1942|location=Garden City, NY|pages=254–5|oclc=795065}}</ref>
!data-sort-type=number|[[Social:Portuguese language|Portuguese]]<ref>{{cite web |url=http://www.numaboa.com/criptografia/criptoanalise/310-Frequencia-no-Portugues |title=Frequência da ocorrência de letras no Português |access-date=2009-06-16 |df=dmy-all |archive-url=https://web.archive.org/web/20090803182254/http://www.numaboa.com/criptografia/criptoanalise/310-Frequencia-no-Portugues |archive-date=2009-08-03 |url-status=dead }}</ref>
!data-sort-type=number|[[Social:Italian language|Italian]]<ref>{{cite book |first1=Simon |last1=Singh |first2=Stefano |last2=Galli |title=Codici e Segreti |year=1999 |location=Milano |publisher=Rizzoli |isbn=978-8-817-86213-4 |oclc=535461359 |language=it}}</ref>
!data-sort-type=number|[[Social:Turkish language|Turkish]]<ref>{{cite conference |author1=Serengil, Sefik Ilkin |author2=Akin, Murat |url=http://www.wseas.us/e-library/conferences/2011/Cambridge/NEHIPISIC/NEHIPISIC-20.pdf |title=Attacking Turkish Texts Encrypted by Homophonic Cipher |conference=Proceedings of the 10th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications |pages=123–126 |location=Cambridge, UK |date=20–22 February 2011}}</ref>
!data-sort-type=number|[[Social:Swedish language|Swedish]]<ref>{{cite web |url=http://practicalcryptography.com/cryptanalysis/letter-frequencies-various-languages/swedish-letter-frequencies/ |title= Practical Cryptography |access-date=2013-10-30 |df=dmy-all}}</ref>
!data-sort-type=number|[[Social:Polish language|Polish]]<ref>{{Cite web|url=https://sjp.pwn.pl/poradnia/haslo/frekwencja-liter-w-polskich-tekstach;7072.html|title = Frekwencja liter w polskich tekstach - Poradnia językowa PWN}}</ref>
!data-sort-type=number|[[Social:Dutch language|Dutch]]<ref name=OnzeTaal>{{cite web |url=http://www.onzetaal.nl/advies/letterfreq.php |title=Letterfrequenties |access-date=2009-05-17 |df=dmy-all |work=Genootschap OnzeTaal}}</ref>
!data-sort-type=number|[[Social:Danish language|Danish]]<ref>{{cite web |url=http://practicalcryptography.com/cryptanalysis/letter-frequencies-various-languages/danish-letter-frequencies/ |title=Danish letter frequencies |website=Practical Cryptography |access-date=2013-10-24 |df=dmy-all}}</ref>
!data-sort-type=number|[[Social:Icelandic language|Icelandic]]<ref>{{cite web |url=http://practicalcryptography.com/cryptanalysis/letter-frequencies-various-languages/icelandic-letter-frequencies/ |title=Icelandic letter frequencies |website=Practical Cryptography |access-date=2013-10-24 |df=dmy-all}}</ref>
!data-sort-type=number|[[Social:Finnish language|Finnish]]<ref>{{cite web |url=http://practicalcryptography.com/cryptanalysis/letter-frequencies-various-languages/finnish-letter-frequencies/ |title=Finnish letter frequencies |website=Practical Cryptography |access-date=2013-10-24 |df=dmy-all}}</ref>
!data-sort-type=number|[[Social:Czech language|Czech]]<br>{{Citation needed|reason=The article does not reference a source for this data. Can someone who is aware of where this data came from add a reference?|date=January 2022}}
!data-sort-type=number|[[Social:Hungarian language|Hungarian]]<ref>{{WolframAlpha|title=Hungarian character frequencies|id=Hungarian+character+frequencies|access-date=March 25, 2023}}</ref>
|-
|'''a'''
|8.167%||7.636%||6.516%||11.525%||14.634%||11.745%||11.920%||9.383%||8.965%||7.49%||6.025%||10.110%||12.217%||8.421%||8.89%
|-
|'''b'''
|1.492%||0.901%||1.886%||2.215%||1.043%||0.927%||2.844%||1.535%||1.482%||1.58%||2.000%||1.043%||0.281%||0.822%||1.94%
|-
|'''c'''
|2.782%||3.260%||2.732%||4.019%||3.882%||4.501%||0.963%||1.486%||3.988%||1.24%||0.565%||~0%||0.281%||0.740%||0.646%
|-
|'''d'''
|4.253%||3.669%||5.076%||5.010%||4.992%||3.736%||4.706%||4.702%||3.293%||5.93%||5.858%||1.575%||1.043%||3.475%||1.92%
|-
|'''e'''
|12.702%||14.715%||16.396%||12.181%||12.570%||11.792%||8.912%||10.149%||7.921%||18.91%||15.453%||6.418%||7.968%||7.562%||11.6%
|-
|'''f'''
|2.228%||1.066%||1.656%||0.692%||1.023%||1.153%||0.461%||2.027%||0.312%||0.81%||2.406%||3.013%||0.194%||0.084%||0.548%
|-
|'''g'''
|2.015%||0.866%||3.009%||1.768%||1.303%||1.644%||1.253%||2.862%||1.377%||3.40%||4.077%||4.241%||0.392%||0.092%||3.79%
|-
|'''h'''
|6.094%||0.937%||4.577%||1.973%||1.281%||0.136%||1.212%||2.090%||1.072%||2.38%||1.621%||1.871%||1.851%||1.356%||1.26%
|-
|'''i'''
|6.966%||7.529%||6.550%||6.247%||6.186%||10.143%||8.600%*||5.817%||8.286%||6.50%||6.000%||7.578%||10.817%||6.073%||4.25%
|-
|'''j'''
|0.253%||0.813%||0.268%||2.493%||0.879%||0.011%||0.034%||0.614%||2.343%||1.46%||0.730%||1.144%||2.042%||1.433%||1.48%
|-
|'''k'''
|1.772%||0.074%||1.417%||0.026%||0.015%||0.009%||4.683%||3.140%||3.411%||2.25%||3.395%||3.314%||4.973%||2.894%||4.85%
|-
|'''l'''
|4.025%||5.456%||3.437%||4.967%||2.779%||6.510%||5.922%||5.275%||2.136%||3.57%||5.229%||4.532%||5.761%||3.802%||6.71%
|-
|'''m'''
|2.406%||2.968%||2.534%||3.157%||4.738%||2.512%||3.752%||3.471%||2.911%||2.21%||3.237%||4.041%||3.202%||2.446%||3.82%
|-
|'''n'''
|6.749%||7.095%||9.776%||6.712%||4.446%||6.883%||7.487%||8.542%||5.600%||10.03%||7.240%||7.711%||8.826%||6.468%||6.82%
|-
|'''o'''
|7.507%||5.796%||2.594%||8.683%||9.735%||9.832%||2.476%||4.482%||7.590%||6.06%||4.636%||2.166%||5.614%||6.695%||3.65%
|-
|'''p'''
|1.929%||2.521%||0.670%||2.510%||2.523%||3.056%||0.886%||1.839%||3.101%||1.57%||1.756%||0.789%||1.842%||1.906%||0.48%
|-
|'''q'''
|0.095%||1.362%||0.018%||0.877%||1.204%||0.505%||0||0.020%||0.003%||0.009%||0.007%||0||0.013%||0.001%||~0%
|-
|'''r'''
|5.987%||6.693%||7.003%||6.871%||6.530%||6.367%||6.722%||8.431%||4.571%||6.41%||8.956%||8.581%||2.872%||4.799%||2.65%
|-
|'''s'''
|6.327%||7.948%||7.270%||7.977%||6.805%||4.981%||3.014%||6.590%||4.263%||3.73%||5.805%||5.630%||7.862%||5.212%||6.99%
|-
|'''t'''
|9.056%||7.244%||6.154%||4.632%||4.336%||5.623%||3.314%||7.691%||3.966%||6.79%||6.862%||4.953%||8.750%||5.727%||6.96%
|-
|'''u'''
|2.758%||6.311%||4.166%||3.927%||3.639%||2.813%||3.235%||1.919%||2.347%||1.99%||1.979%||4.562%||5.008%||2.160%||0.392%
|-
|'''v'''
|0.978%||1.838%||0.846%||1.138%||1.575%||2.097%||0.959%||2.415%||0.034%||2.85%||2.332%||2.437%||2.250%||5.344%||2.31%
|-
|'''w'''
|2.360%||0.049%||1.921%||0.027%||0.037%||0.033%||0||0.142%||4.549%||1.52%||0.069%||0||0.094%||0.016%||~0%
|-
|'''x'''
|0.250%||0.427%||0.034%||0.515%||0.453%||0.008%||0||0.159%||0.019%||0.036%||0.028%||0.046%||0.031%||0.027%||~0%
|-
|'''y'''
|1.974%||0.708%||0.039%||1.433%||0.006%||0.020%||3.336%||0.708%||3.857%||0.035%||0.698%||0.900%||1.745%||1.043%||2.56%
|-
|'''z'''
|0.074%||0.326%||1.134%||0.467%||0.470%||1.181%||1.500%||0.070%||5.620%||1.39%||0.034%||0||0.051%||1.599%||4.3%
|-
|'''à'''
|~0%{{cn|date=May 2022}}<!-- vis-à-vis -->||0.486%||0||~0%<!-- vis-à-vis -->||0.072%||0.635%||0||0||0||0||0||0||0||0||0
|-
|'''â'''
|~0%<!-- papier-mâché -->||0.051%||0||0||0.562%||~0%||~0%<!-- kâğıt -->||0||0||0||0||0||0||0||0
|-
|'''á'''
|~0%<!-- háček -->||0||0||0.502%||0.118%||0||0||0||0||0||0||1.799%||0||0.867%||3.44%
|-
|'''å'''
|~0%<!-- Åland -->||0||0||0||0||0||0||1.34%||0||0||1.190%||~0%||0.003%||0||0
|-
|'''ä'''
|~0%<!-- Häagen-Dazs -->||0||0.578%||0||0||0||0||1.80%||0||0||0||0||3.577%||0||0
|-
|'''ã'''
|0||0||0||0||0.733%||0||0||0||0||0||0||0||0||0||0
|-
|'''ą'''
|0||0||0||0||0||0||0||0||1.021%||0||0||0||0||0||0
|-
|'''æ'''
|~0%{{cn|date=May 2022}}||0||0||0||0||0||0||0||0||0||0.872%||0.867%||0||0||0
|-
|'''œ'''
|~0%||0.018%||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ç'''
|~0%<!-- façade -->||0.085%||0||~0%<!-- Barça -->||0.530%||0||1.156%||0||0||0||0||~0%||0||0||0
|-
|'''ĉ'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ć'''
|0||0||0||0||0||0||0||0||0.448%||0||0||0||0||0||0
|-
|'''č'''
|~0%<!-- háček -->||0||0||0||0||0||0||0||0||0||0||0||0||0.462%||0
|-
|'''ď'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0.015%||0
|-
|'''ð'''
|0||0||0||0||0||0||0||0||0||0||0||4.393%||0||0||0
|-
|'''è'''
|~0%{{cn|date=May 2022}}<!-- crème brûlée -->||0.271%||0||~0%<!-- crème brûlée -->||0||0.263%||0||0||0||0||0||0||0||0||0
|-
|'''é'''
|~0%{{cn|date=May 2022}}<!-- née -->||1.504%||0||0.433%||0.337%||0||0||0||~0%<!-- In texts prior to 1891 and in French loanwords -->||0||0||0.647%||0||0.633%||4.25%
|-
|'''ê'''
|0||0.218%||0||0||0.450%||~0%||0||0||0||0||0||0||0||0||0
|-
|'''ë'''
|~0%{{cn|date=May 2022}}<!-- Zoë -->||0.008%||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ę'''
|0||0||0||0||0||0||0||0||1.131%||0||0||0||0||0||0
|-
|'''ě'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||1.222%||0
|-
|'''ĝ'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ğ'''
|0||0||0||0||0||0||1.125%||0||0||0||0||0||0||0||0
|-
|'''ĥ'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''î'''
|0||0.045%||0||0||0||~0%||~0%<!-- millî -->||0||0||0||0||0||0||0||0
|-
|'''ì'''
|0||0||0||0||0||(0.030%)||0||0||0||0||0||0||0||0||0
|-
|'''í'''
|0{{cn|date=May 2022}}||0||0||0.725%||0.132%||0.030%||0||0||0||0||0||1.570%||0||1.643%||0.47%
|-
|'''ï'''
|~0%{{cn|date=May 2022}}<!-- naïve -->||0.005%||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ı'''
|0||0||0||0||0||0||5.114%*||0||0||0||0||0||0||0||0
|-
|'''ĵ'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ł'''
|0||0||0||0||0||0||0||0||1.746%||0||0||0||0||0||0
|-
|'''ľ'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||~0%<!-- Ľudovít Štúr -->||0
|-
|'''ñ'''
|~0%{{cn|date=May 2022}}<!-- jalapeño -->||0||0||0.311%||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ń'''
|0||0||0||0||0||0||0||0||0.185%||0||0||0||0||0||0
|-
|'''ň'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0.007%||0
|-
|'''ò'''
|0||0||0||0||0||0.002%||0||0||0||0||0||0||0||0||0
|-
|'''ö'''
|~0%<!-- Boötes -->||0||0.443%||0||0||0||0.777%||1.31%||0||0||0||0.777%||0.444%||0||0.784%
|-
|'''ô'''
|~0%<!-- entrepôt -->||0.023%||0||0||0.635%||~0%||0||0||0||0||0||0||0||0||0
|-
|'''ó'''
|0{{cn|date=May 2022}}||0||0||0.827%||0.296%||~0%||0||0||0.823%||0||0||0.994%||0||0.024%||0.597%
|-
|'''ő'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0.823%
|-
|'''õ'''
|0{{cn|date=May 2022}}||0||0||0||0.040%||0||0||0||0||0||0||0||0||0||0
|-
|'''ø'''
|~0%<!-- øre -->||0||0||0||0||0||0||0||0||0||0.939%||0||0||0||0
|-
|'''ř'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0.380%||0
|-
|'''ŝ'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ş'''
|0||0||0||0||0||0||1.780%||0||0||0||0||0||0||0||0
|-
|'''ś'''
|0{{cn|date=May 2022}}||0||0||0||0||0||0||0||0.683%||0||0||0||0||0||0
|-
|'''š'''
|0||0||0||0||0||0||0||0||0||0||0||0||~0%<!-- šakki -->||0.688%||0
|-
|'''ß'''
|0||0||0.307%||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ť'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0.006%||0
|-
|'''þ'''
|0||0||0||0||0||0||0||0||0||0||0||1.455%||0||0||0
|-
|'''ù'''
|0||0.058%||0||0||0||(0.166%)||0||0||0||0||0||0||0||0||0
|-
|'''ú'''
|0{{cn|date=May 2022}}||0||0||0.168%||0.207%||0.166%||0||0||0||0||0||0.613%||0||0.045%||0.098%
|-
|'''û'''
|~0%<!-- crème brûlée -->||0.060%||0||0||0||~0%||~0%<!-- mahkûm -->||0||0||0||0||0||0||0||0
|-
|'''ŭ'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0
|-
|'''ü'''
|~0%<!-- über -->||0||0.995%||0.012%||0.026%||0||1.854%||0||0||0||0||0||0||0||0.617%
|-
|'''ű'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0||0.117%
|-
|'''ů'''
|0||0||0||0||0||0||0||0||0||0||0||0||0||0.204%||0
|-
|'''ý'''
|0||0||0||~0%<!-- Aýna -->||0||0||0||0||0||0||0||0.228%||0||0.995%||0
|-
|'''ź'''
|0||0||0||0||0||0||0||0||0.061%||0||0||0||0||0||0
|-
|'''ż'''
|0||0||0||0||0||0||0||0||0.885%||0||0||0||0||0||0
|-
|'''ž'''
|0||0||0||0||0||0||0||0||0||0||0||0||~0%<!-- džonkki -->||0.721%||0
|}

<nowiki>*</nowiki>See İ and dotless I.

The figure below illustrates the frequency distributions of the 26&nbsp;most common Latin letters across some languages. All of these languages use a similar 25+&nbsp;character alphabet.

Based on these tables, the 'etaoin shrdlu'-equivalent for each language is as follows:
*French: ' '; (Indo-European: Italic; traditionally, 'esartinulop' is used, in part for its ease of pronunciation<ref>Perec, Georges; ''Alphabets''; Éditions Galilée, 1976</ref>)
*Spanish: ' '; (Indo-European: Italic)
*Portuguese: ' ' (Indo-European: Italic)
*Italian: ' '; (Indo-European: Italic)
*German: ' '; (Indo-European: Germanic)
*Swedish: ' '; (Indo-European: Germanic)
*Turkish: ' '; (Turkic)
*Dutch: ' '; (Indo-European: Germanic)<ref name=OnzeTaal/>
*Polish: ' '; (Indo-European: Balto-Slavic)
*Danish: ' '; (Indo-European: Germanic)
*Icelandic: ' '; (Indo-European: Germanic)
*Finnish: ' '; (Uralic: Finnic)
*Czech: ' '; (Indo-European: Balto-Slavic)
*Hungarian: ' '; (Uralic: Finno-Ugric)

==See also==
*Arabic letter frequency
*[[Social:Corpus linguistics|Corpus linguistics]]
*[[Engineering:Dvorak keyboard layout|Dvorak keyboard layout]]
*English word frequency
*Etaoin shrdlu
*[[Social:Letter frequency effect|Letter frequency effect]]
*Lipogram
*RSTLNE (''Wheel of Fortune'')

== Explanatory notes==
{{notelist}}

== References ==
{{Reflist}}

==External links==
* {{cite web |url=http://pages.central.edu/emp/LintonT/ |title=Cryptographical Mathematics |author=Lewand, Robert Edward |publisher=pages.central.edu|archive-url=https://web.archive.org/web/20070402181401/http://pages.central.edu/emp/LintonT/ |archive-date=2007-04-02 }}
* {{cite web |url=https://www.bckelk.org.uk/words/etaoin.html |title=Some examples of letter frequency rankings in some common languages |publisher=www.bckelk.org.uk}}
* {{cite web |url=http://www.patrick-wied.at/projects/heatmap-keyboard/ |title=JavaScript Heatmap Visualization showing letter frequencies of texts on different keyboard layouts |publisher=www.patrick-wied.at}}
* {{cite web |url=http://norvig.com/mayzner.html |title=An updated version of Mayzner's work using Google books Ngrams data set |author=Norvig, Peter |publisher=norvig.com}}
* [http://simia.net/letters/ Letter frequency]—simia.net

===Useful tables===
Useful tables for single letter, digram, trigram, tetragram, and pentagram frequencies based on 20,000&nbsp;words that take into account word-length and letter-position combinations for words 3 to 7&nbsp;letters in length:

* {{cite journal |last1=Mayzner |first1=M.S. |last2=Tresselt |first2=M.E. |last3=Wolin |first3=B.R. |title=Tables of single-letter and digram frequency counts for various word-length and letter-position combinations |journal=Psychonomic Monograph Supplements |volume=1 |issue=2 |pages=13–32 |year=1965 |oclc=639975358}}
* {{cite journal |last1=Mayzner |first1=M.S. |last2=Tresselt |first2=M.E. |last3=Wolin |first3=B.R. |title=Tables of trigram frequency counts for various word-length and letter-position combinations |journal=Psychonomic Monograph Supplements |volume=1 |issue=3 |pages=33–78 |year=1965 }}
* {{cite journal |last1=Mayzner |first1=M.S. |last2=Tresselt |first2=M.E. |last3=Wolin |first3=B.R. |title=Tables of tetragram frequency counts for various word-length and letter-position combinations |journal=Psychonomic Monograph Supplements |volume=1 |issue=4 |pages=79–143 |year=1965 }}
* {{cite journal |last1=Mayzner |first1=M.S. |last2=Tresselt |first2=M.E. |last3=Wolin |first3=B.R. |title=Tables of pentagram frequency counts for various word-length and letter-position combinations |journal=Psychonomic Monograph Supplements |volume=1 |issue=5 |pages=144–190 |year=1965 }}

[[Category:Cryptography]]
[[Category:Frequency distribution]]

{{Sourceattribution|Letter frequency}}