Hi Ilya,

However I don't understand the data type which is returned from Counts function

Counts returns an Association. In other languages it is called a Hash, or HashMap or Map or Dictionary... It is a set of key -> value.

This

list = StringTake [#,2] &/@ DictionaryLookup[#~~ ___] &/@  Alphabet[];

does not work as expected because of precedence / associativity of operators. You need to parenthesize.

list = StringTake[#, 2] & /@ (DictionaryLookup[# ~~ ___] & /@ Alphabet[]);

The other problem is that # ~~ ___ will return single character words so StringTake will fail, so only consider words with two or more characters.

list = StringTake[#, 2] & /@ (DictionaryLookup[# ~~ __] & /@ Alphabet[]);

Finally, list is a list of lists so you need to Map the Counts function.

Map[Counts, list]
(* {<|"aa" -> 3, "ab" -> 335, "ac" -> 407, "ad" -> 373, "ae" -> 47, .... *)

I prefer to write these kinds of expressions in postfix form.

Alphabet[] // Map[DictionaryLookup[# ~~ __] &] // Map[StringTake[#, 2] &] // Map[Counts]

To generate the table, take a look at the Grid function. You will have to deal with combinations for which there are no counts. If you get stuck, post another question.

Since you are new to WL, a good learning resource is Stephen Wolfram's 'An Elementary Introduction to the Wolfram Language' which is available online.

Hi Ilya,

I tried a couple of ways of visualizing this data.

MatrixPlot. Vertical bands where the second letter is a vowel are clearly visible. a is the only first letter that has every letter as the second letter, e and o are close with only one missing second letter. re and co are the most frequent. z and j are the least frequent second letter.

Grid of Graph with vertex size and color based on frequency.

I can post the code if you are interested.

Hi Ilya,

Here is the code that I used. I generalized it to work with any language that WL has alphabet and dictionary data for. I verified it on English. Can you please verify that it works correctly for Russian. Thanks!

Two letter frequencies

Generate association of first two letters of words in the dictionary to frequency of occurrence. First and second letters are restricted to first and last letter in the alphabet. This eliminates words containing capitals or accented characters in the first two letters. For some reason DictionaryLookup[] for English has words which contain characters that are not part of Alphabet[] for English.

language = "Russian";
alphabet = Alphabet[language];
numLetters = alphabet // Length;

pairCounts = 
  alphabet // 
     Map[DictionaryLookup[{language, # ~~ 
          CharacterRange[First@alphabet, Last@alphabet] ..}] &] // 
    Map[StringTake[#, 2] &] // Map[Counts];

Matrix Plot

Several combinations do not occur so we need to add them to the association with a count of zero.

pairZeroCounts = 
  alphabet // Tuples[#, 2] & // Map[StringJoin] // 
   AssociationThread[#, ConstantArray[0, numLetters^2]] &;
allPairCounts = <|pairZeroCounts, pairCounts|>;

Generate matrix of frequencies and text strings of frequency values centered over matrix rows and columns.

matrixValues = allPairCounts // Values // Partition[#, numLetters] &;
epilog = MapIndexed[Text[Style[#, 10], #2 - 1/2] &, Transpose@Reverse@matrixValues, {2}];

Labels, ticks and MatrixPlot.

frameLabels = Style[#, 16, Black] & /@ {"Second Letter", "First Letter"};
ticks = Transpose[{Range@numLetters, alphabet // Map[Style[#, 14, Black] &]}];

matrixValues //
 MatrixPlot[
   #,
   Mesh -> All,
   FrameTicks -> {ticks, ticks, ticks, ticks},
   FrameLabel -> Transpose[{frameLabels, frameLabels}],
   PlotLegends -> 
    Placed[Style[language <> " Words", 20, Black, Bold], Above],
   ColorFunction -> "TemperatureMap",
   ColorRules -> {0 -> White},
   ImageSize -> 800,
   Epilog -> epilog] &

Graph

edges = pairCounts // Keys // Characters // Apply[DirectedEdge, #, {2}] &;

(* Association of second letter to frequency *)
weights = pairCounts // Map[KeyMap[StringTake[#, -1] &]];
(* Weight of 1 for second letters that do not occur *) 
defaultWeights = Thread[alphabet -> ConstantArray[1, numLetters]] // Map[Association];

vertexWeights = MapThread[Association, {defaultWeights, weights}];
weightRange = vertexWeights // MinMax;

(* Helper to set VertexSize and VertexStyle *)
setProperties[graph_, index_] := 
 Module[{scaledWeights = Rescale[vertexWeights[[First@index]], weightRange]},
  SetProperty[graph, 
   {VertexSize -> {v_ :> scaledWeights[v]}, 
    VertexStyle -> {v_ :> (ColorData[{"SolarColors", "Reversed"}]@scaledWeights[v])}}]]

G = edges // Map[Graph[#,
      VertexLabels -> Placed["Name", Below],
      VertexLabelStyle -> Directive[Black, 16],
      GraphLayout -> "RadialEmbedding"] &];

G // MapIndexed[setProperties] // Partition[#, UpTo[6]] & // Grid[#, Frame -> All] &

In order to get the contingency matrices you can use the Wolfram Function Repository function CrossTabulate.

ResourceFunction["CrossTabulate"]@
 Flatten[Map[Partition[Characters[#], 2, 1] &, 
   ToLowerCase[DictionaryLookup["*"]]], 1]

I don't know so many words starting with bb.

The code I posted makes overlapping pairs of all characters for a given word. (See: Partition[Characters[#], 2, 1] .)