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I have a data set as I've shown below:

It shows which book is sold by which shop. Also, every book_id has a type.

df <- tribble(
 ~shop,  ~book_id,  ~type,
  "A",       1,      'X', 
  "B",       1,      'X', 
  "C",       2,      'Y', 
  "D",       3,      'Z', 
  "E",       3,      'Z', 
  "A",       3,      'Z', 
  "B",       4,      'X', 
  "C",       5,      'Y', 
  "D",       1,      'X', 
)

In the data set,

  • shop A sells 1, 3
  • shop B sells 1, 4
  • shop C sells 2, 5
  • shop D sells 3, 1
  • shop E sells only 3

I want to see the similarity among shops based on the book_id. In other words, I want to see the intersection/overlapping among the shops.

First, I thought it is a manipulation problem. But it seems that I should need more than manipulation to get my desired data that I've shown below:

df <- tribble(
  ~shop_1, ~shop_2, ~similarity,  
    'A',      'B',       '?',                
    'A',      'C',       '?', 
    'A',      'D',       '?', 
    'A',      'E',       '?', 
    'B',      'C',       '?', 
    'B',      'D',       '?', 
    'B',      'E',       '?', 
    'C',      'D',       '?', 
    'C',      'E',       '?', 
    'D',      'E',       '?', 
)

Any comments/assistance really appreciated! Thanks in advance.

Note: Question mark (?) in similarity column in the desired data was used because I don't how to calculate the similarity.

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For comparison, you should create a contingency matrix with table(df$shop, df$book_id) (but you may want to use a tool like xtabs instead, to create a sparse matrix from package Matrix). Then, you can compute similarities between rows of that matrix (every row is a shop).

A suitable, notorious similarity measure is Jaccard index, but many more exist. Anyway, I see an R package exists for Jaccard measure alone, fittingly called jaccard.

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