How to efficiently find columns of the matrix which are the same?

New to Julia
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7

The question is a little vague on the desired output, but I think the following will succintly include the OP’s desired information
(just noticed this is pretty similar to stevengj’s answer):

julia> using StatsBase

julia> M = permutedims(reshape([[1, 1, 1, 1, 0, 0]
       [1, 1, 1, 0, 1, 0]
       [0, 0, 0, 0, 0, 0]
       [0, 0, 0, 0, 0, 0]
       [0, 0, 0, 0, 0, 0]
       [0, 0, 0, 0, 0, 0]], (6,6)))
6×6 Matrix{Int64}:
 1  1  1  1  0  0
 1  1  1  0  1  0
 0  0  0  0  0  0
 0  0  0  0  0  0
 0  0  0  0  0  0
 0  0  0  0  0  0

julia> countmap(eachcol(M))
Dict{SubArray{Int64, 1, Matrix{Int64}, Tuple{...} with 4 entries:
  [1, 1, 0, 0, 0, 0] => 3
  [1, 0, 0, 0, 0, 0] => 1
  [0, 1, 0, 0, 0, 0] => 1
  [0, 0, 0, 0, 0, 0] => 1

julia> sort(values(countmap(eachcol(M))); rev = true)
4-element Vector{Int64}:
 3
 1
 1
 1

The last expression’s first element is the count of the most popular column in the matrix. If several columns appear multiple times, the vector will reflect this.

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