Tagging values unique to a group in a dataframe

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1

Say that I have a dataframe:

function exampl()
    grp = Int8[]
    for i in 1:5
        grp = append!(grp, fill(i, 7))
    end

    values = Int8[]
    for i in 1:7
        values = append!(values, rand(1:15, 5))
    end

    df = DataFrame(grp = grp, values = values)
    gdf = groupby(df, :grp)
    combine(gdf, :values => unique)
end

julia> exampl()
25×2 DataFrame
 Row │ grp   values_unique 
     │ Int8  Int8          
─────┼─────────────────────
   1 │    1             11
   2 │    1              3
   3 │    1              9
   4 │    1              6
   5 │    1              1
   6 │    1             15
   7 │    2              8
   8 │    2              2
   9 │    2             10
  10 │    2             11
  11 │    2              3
  12 │    3              5
  13 │    3             15
  14 │    3              1
  15 │    3              4
  16 │    3             14
  17 │    4             12
  18 │    4             15
  19 │    4             10
  20 │    4              4
  21 │    4             14
  22 │    5              3
  23 │    5              8
  24 │    5              1
  25 │    5              4

How would I create a third column unique_to_group, a Boolean value that shows if the value in each row is unique to only that group compared with other groups. Example: row 3, with value 9 would be flagged as true in the new column as it is unique to grp 1 only. I have been trying setdiff! approaches but haven’t been able to make it work.

2

If I understand correctly, turning the problem around should work:

using Chain

df = exampl()

@chain df begin
    groupby(:values_unique)
    transform(:grp => (x -> length(unique(x)) == 1) => :ha)
end
1 Like
3

Yes! Indeed, turning the problem around. Thank you so much.