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FreqTables

Build Status Coverage Status FreqTables

This package allows computing one- or multi-way frequency tables (a.k.a. contingency or pivot tables) from any type of vector or array. It includes support for CategoricalArray and DataFrame, as well as for weighted counts.

Tables are represented as NamedArray objects.

julia> using FreqTables

julia> x = repeat(["a", "b", "c", "d"], outer=[100]);

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

julia> tbl = freqtable(x)
4-element Named Array{Int64,1}
Dim1  │
──────┼────
a     │ 100
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
────────────┼───────────────
a           │ 30  20  30  20
b           │ 30  20  30  20
c           │ 20  30  20  30
d           │ 20  30  20  30

julia> tbl2 = freqtable(x, y, subset=1:20)
4×2 Named Array{Int64,2}
Dim1 ╲ Dim2 │ A  B
────────────┼─────
a           │ 3  2
b           │ 3  2
c           │ 2  3
d           │ 2  3

julia> prop(tbl2, 2)
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
────────────┼─────────
a           │ 3.0  2.0
b           │ 1.5  1.0
c           │ 2.0  3.0
d           │ 1.0  1.5

For convenience, when working with a data frame, one can also pass a DataFrame object and columns as symbols:

julia> using DataFrames, CSV

julia> iris = CSV.read(joinpath(Pkg.dir("DataFrames"), "test/data/iris.csv"));

julia> iris[:LongSepal] = iris[:SepalLength] .> 5.0;

julia> freqtable(iris, :Species, :LongSepal)
3×2 Named Array{Int64,2}
Species ╲ LongSepal │ false   true
────────────────────┼─────────────
setosa              │    28     22
versicolor          │     3     47
virginica           │     1     49

julia> freqtable(iris, :Species, :LongSepal, subset=iris[:PetalLength] .< 4.0)
2×2 Named Array{Int64,2}
Species ╲ LongSepal │ false   true
────────────────────┼─────────────
setosa              │    28     22
versicolor          │     3      8

Note that when one of the input variables contains integers, Name(i) has to be used when indexing into the table to prevent i to be interpreted as a numeric index:

julia> df = DataFrame(A = 101:103, B = ["x","y","y"]);

julia> ft = freqtable(df, :A, :B)
3×2 Named Array{Int64,2}
Dim1 ╲ Dim2 │ x  y
────────────┼─────
1011  0
1020  1
1030  1

julia> ft[Name(101), "x"]
1

julia> ft[101,"x"]
ERROR: BoundsError: attempt to access 10×2 Array{Int64,2} at index [101, 1]