using CSV, DataFrames, AlgebraOfGraphics, CairoMakiebegin
cancer_filepath = "data//archive//cancer.csv"
cancer_data = CSV.read(cancer_filepath, DataFrame)
end;first(cancer_data, 5)| Id | Diagnosis | Radius (mean) | Texture (mean) | Perimeter (mean) | Area (mean) | Smoothness (mean) | Compactness (mean) | ... | |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 8510426 | "B" | 13.54 | 14.36 | 87.46 | 566.3 | 0.09779 | 0.08129 | |
| 2 | 8510653 | "B" | 13.08 | 15.71 | 85.63 | 520.0 | 0.1075 | 0.127 | |
| 3 | 8510824 | "B" | 9.504 | 12.44 | 60.34 | 273.9 | 0.1024 | 0.06492 | |
| 4 | 854941 | "B" | 13.03 | 18.42 | 82.61 | 523.8 | 0.08983 | 0.03766 | |
| 5 | 85713702 | "B" | 8.196 | 16.84 | 51.71 | 201.9 | 0.086 | 0.05943 |
draw(data(cancer_data) * mapping("Area (mean)", color=:Diagnosis) * histogram(bins=30) * visual(alpha=0.7))
draw(data(cancer_data) * mapping("Radius (worst)", color=:Diagnosis) * AlgebraOfGraphics.density())
Built with Julia 1.9.1 and
AlgebraOfGraphics 0.6.14CSV 0.10.9
CairoMakie 0.10.4
DataFrames 1.5.0
To run this tutorial locally, download [this file](/tutorials/distributions03x07.jl) and open it with Pluto.jl._