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add proptable #19

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merged 7 commits into from
Dec 22, 2017
Merged

add proptable #19

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961525e
add proptable
bkamins Dec 19, 2017
6268227
refactor arguments
bkamins Dec 19, 2017
f65d113
introduce prop
bkamins Dec 21, 2017
a9070ae
add docstring and change dims to margin
bkamins Dec 21, 2017
4e715b6
change prop signature and refactor docstrings
bkamins Dec 21, 2017
495ce57
improved tests and docs
bkamins Dec 21, 2017
a660551
patch NamedArrays
bkamins Dec 21, 2017
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22 changes: 20 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ julia> x = repeat(["a", "b", "c", "d"], outer=[100]);

julia> y = repeat(["A", "B", "C", "D"], inner=[10], outer=[10]);

julia> freqtable(x)
julia> tbl = freqtable(x)
4-element Named Array{Int64,1}
Dim1 │
──────┼────
Expand All @@ -26,6 +26,15 @@ b │ 100
c │ 100
d │ 100

julia> prop(tbl)
4-element Named Array{Float64,1}
Dim1 │
──────┼─────
a │ 0.25
b │ 0.25
c │ 0.25
d │ 0.25

julia> freqtable(x, y)
4×4 Named Array{Int64,2}
Dim1 ╲ Dim2 │ A B C D
Expand All @@ -35,7 +44,7 @@ b │ 30 20 30 20
c │ 20 30 20 30
d │ 20 30 20 30

julia> freqtable(x, y, subset=1:20)
julia> tbl2 = freqtable(x, y, subset=1:20)
4×2 Named Array{Int64,2}
Dim1 ╲ Dim2 │ A B
────────────┼─────
Expand All @@ -44,6 +53,15 @@ b │ 3 2
c │ 2 3
d │ 2 3

julia> prop(tbl2, 1)
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This behavior (inherited from sum) is the opposite of R's: the passed dimensions are those to collapse, while in R they are ones to retain. I wonder whether it's appropriate for computing proportions: it's probably more natural to think "I want to compute proportion by rows" than "I want to divide each row by the column sums", isn't it? After all, we say "row profiles/percents" and "column profiles/percents".

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I was thinking about it, initially I wanted to be consistent with sum.
But let us call the argument margin then and make it work like in R.

4×2 Named Array{Float64,2}
Dim1 ╲ Dim2 │ A B
────────────┼─────────
a │ 0.3 0.2
b │ 0.3 0.2
c │ 0.2 0.3
d │ 0.2 0.3

julia> freqtable(x, y, subset=1:20, weights=repeat([1, .5], outer=[10]))
4×2 Named Array{Float64,2}
Dim1 ╲ Dim2 │ A B
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2 changes: 1 addition & 1 deletion src/FreqTables.jl
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Expand Up @@ -5,5 +5,5 @@ module FreqTables

include("freqtable.jl")

export freqtable
export freqtable, prop
end # module
3 changes: 3 additions & 0 deletions src/freqtable.jl
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Expand Up @@ -131,3 +131,6 @@ function freqtable(d::AbstractDataFrame, x::Symbol...; args...)
setdimnames!(a, x)
a
end

prop(tbl::AbstractArray{<:Number}) = tbl / sum(tbl)
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Could you add a docstring?

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I wanted to add a docstring for freqtable and prop in a separate PR when we have settled the implementation.

prop(tbl::AbstractArray{<:Number}, dims) = tbl ./ sum(tbl, dims)
34 changes: 33 additions & 1 deletion test/freqtable.jl
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Expand Up @@ -8,6 +8,7 @@ y = repeat(["D", "C", "A", "B"], inner=[10], outer=[10]);
tab = @inferred freqtable(x)
@test tab == [100, 100, 100, 100]
@test names(tab) == [["a", "b", "c", "d"]]
@test prop(tab) == [0.25, 0.25, 0.25, 0.25]
tab = @inferred freqtable(y)
@test tab == [100, 100, 100, 100]
@test names(tab) == [["A", "B", "C", "D"]]
Expand All @@ -17,6 +18,31 @@ tab = @inferred freqtable(x, y)
20 30 30 20;
20 30 30 20]
@test names(tab) == [["a", "b", "c", "d"], ["A", "B", "C", "D"]]
@test prop(tab) == [0.075 0.05 0.05 0.075;
0.075 0.05 0.05 0.075;
0.05 0.075 0.075 0.05;
0.05 0.075 0.075 0.05]
@test prop(tab, (1,2)) == [0.075 0.05 0.05 0.075;
0.075 0.05 0.05 0.075;
0.05 0.075 0.075 0.05;
0.05 0.075 0.075 0.05]
@test prop(tab, 1) == [0.3 0.2 0.2 0.3;
0.3 0.2 0.2 0.3;
0.2 0.3 0.3 0.2;
0.2 0.3 0.3 0.2]
@test prop(tab, 2) == [0.3 0.2 0.2 0.3;
0.3 0.2 0.2 0.3;
0.2 0.3 0.3 0.2;
0.2 0.3 0.3 0.2]
@test prop(tab, ()) == [1.0 1.0 1.0 1.0;
1.0 1.0 1.0 1.0;
1.0 1.0 1.0 1.0;
1.0 1.0 1.0 1.0]

@test_throws MethodError prop()
@test_throws MethodError prop([1,2,3], ("a","b"))
@test_throws MethodError prop(("a","b"))
@test_throws MethodError prop((1, 2))

tab =freqtable(x, y,
subset=1:20,
Expand All @@ -26,7 +52,13 @@ tab =freqtable(x, y,
3.0 2.0
1.5 1.0]
@test names(tab) == [["a", "b", "c", "d"], ["C", "D"]]

@test prop(tab) == [4 6; 2 3; 6 4; 3 2] / 30.0
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Wouldn't hurt to have @inferred here too.

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done

@test prop(tab, 1) == [8 12; 4 6; 12 8; 6 4] / 30.0
@test prop(tab, (1,)) == [8 12; 4 6; 12 8; 6 4] / 30.0
@test prop(tab, 2) == [6 9; 6 9; 9 6; 9 6] / 15.0
@test prop(tab, (2,)) == [6 9; 6 9; 9 6; 9 6] / 15.0
@test prop(tab, ()) == [1.0 1.0; 1.0 1.0; 1.0 1.0; 1.0 1.0]
@test prop(tab, (1, 2)) == [4 6; 2 3; 6 4; 3 2] / 30.0

using CategoricalArrays
cx = CategoricalArray(x)
Expand Down