Iterative, looping split-apply-combines in Julia

General Usage
4

Okay. The hard part is generating the names. This should do what you want

julia> using Statistics, DataFrames;

julia> test=DataFrame(x1=rand(1000), x2=rand(1000), x3=rand(1000), x4=rand(1000));

julia> test.subject="a"
       test[501:1000,5]= "b";

julia> function getproduct(names)
           collect.( (vec ∘ collect ∘ Iterators.product)(names, names))
       end;

julia> function dostuff(x, y)
           mean(x) - mean(y)
       end;

julia> combine(groupby(test, "subject"), getproduct(names(test, Not("subject"))) .=> dostuff)
2×17 DataFrame. Omitted printing of 8 columns
│ Row │ subject │ x1_x1_dostuff │ x2_x1_dostuff │ x3_x1_dostuff │ x4_x1_dostuff │ x1_x2_dostuff │ x2_x2_dostuff │ x3_x2_dostuff │ x4_x2_dostuff │
│     │ String  │ Float64       │ Float64       │ Float64       │ Float64       │ Float64       │ Float64       │ Float64       │ Float64       │
├─────┼─────────┼───────────────┼───────────────┼───────────────┼───────────────┼───────────────┼───────────────┼───────────────┼───────────────┤
│ 1   │ a       │ 0.0           │ 0.000719563   │ 2.31758e-5    │ -0.00244945   │ -0.000719563  │ 0.0           │ -0.000696388  │ -0.00316901   │
│ 2   │ b       │ 0.0           │ 0.0272609     │ 0.0261707     │ 0.0326415     │ -0.0272609    │ 0.0           │ -0.00109015   │ 0.00538059    │

(side note, I invite the reader to think about how hard this would be in dplyr)

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