If I have a DataFrame and want to get `unique` columns but treat each column as a

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#1

if I have a DataFrame and want to get unique columns but treat each column as a separate entity, what is the best way to do it?
MATLAB has a convenience argument unique(A(:,1:2),'rows') (yuk!) … but I can’t find an equivalent way to do it in Julia

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#2

unique in DataFrames works by row. You could do


julia> df = DataFrame(a = [1, 2], b = [3, 4], c = [1, 2]);

julia> unique_cols = unique(i -> i[2], pairs(eachcol(df)))
2-element Array{Pair{Symbol,AbstractArray{T,1} where T},1}:
 :a => [1, 2]
 :b => [3, 4]

julia> DataFrame(unique_cols)
2×2 DataFrame
 Row │ a      b     
     │ Int64  Int64 
─────┼──────────────
   1 │     1      3
   2 │     2      4

unique has a version which applies a function to each element of the iterator and finds unique inputs for after the function has been applied.

pairs(eachcol(df)) is an iterator of colname => vector pairs.

You apply the function i -> i[2] to each of these colname => vector pairs because you only want to compare the vectors. Obviously each column has a unique name.

you are left with a vector of pairs. The DataFrame constructor can work with a vector of colname => vector pairs. And you are done

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