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https://github.com/nalimilan/FreqTables.jl
Frequency tables in Julia
https://github.com/nalimilan/FreqTables.jl
contingency-table frequency-table julia statistics
Last synced: 3 months ago
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Frequency tables in Julia
- Host: GitHub
- URL: https://github.com/nalimilan/FreqTables.jl
- Owner: nalimilan
- License: other
- Created: 2014-06-28T13:40:19.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2023-09-16T23:00:17.000Z (about 1 year ago)
- Last Synced: 2024-07-20T20:38:17.378Z (4 months ago)
- Topics: contingency-table, frequency-table, julia, statistics
- Language: Julia
- Homepage:
- Size: 85.9 KB
- Stars: 89
- Watchers: 5
- Forks: 19
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
- awesome-julia - Frequency tables in Julia
README
# FreqTables
[](https://github.com/nalimilan/FreqTables.jl/actions?query=workflow%3ACI+branch%3Amaster)
[](https://coveralls.io/github/nalimilan/FreqTables.jl?branch=master)
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`](https://github.com/JuliaData/CategoricalArrays.jl)
and [`Tables.jl`](https://github.com/JuliaData/Tables.jl) compliant objects, as well as for weighted counts.
Tables are represented as [`NamedArray`](https://github.com/davidavdav/NamedArrays.jl/) objects.
```julia
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, margins=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 tables (like e.g. a `DataFrame`) one can pass a table object and columns as symbols:
```julia
julia> using DataFrames, CSV
julia> iris = DataFrame(CSV.File(joinpath(dirname(pathof(DataFrames)), "../docs/src/assets/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
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
────────────┼─────
101 │ 1 0
102 │ 0 1
103 │ 0 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]
```