Categorical heatmap

Specific Domains Visualization
,
1

Can I use AoG for a categorical heatmap?

using RDatasets
let
  diamonds = dataset("ggplot2", "diamonds")
  p = data(diamonds) * mapping(:Cut => categorical, :Color => categorical, color=:Price) * visual(Heatmap)
  draw(p)
end
ERROR: LoadError: There was no `AbstractPlotting.convert_arguments` overload found for
the plot type Combined{AbstractPlotting.heatmap,Tuple{Array{Int16,1},Array{Int16,1}}}, or its conversion trait AbstractPlotting.SurfaceLike().
The arguments were:
(Array{Int16,1}, Array{Int16,1})

To fix this, define `AbstractPlotting.convert_arguments(::Combined{AbstractPlotting.heatmap,Tuple{Array{Int16,1},Array{Int16,1}}}, ::Array{Int16,1}, ::Array{Int16,1})`.
2

Do not know about AlgebraOfGraphics.jl but in case it helps, VegaLite.jl can be used for this interesting task:

using VegaLite, RDatasets

diamonds = RDatasets.dataset("ggplot2", "diamonds")

diamonds |>
    @vlplot(
        :rect, width=300, height=200,
        x="Cut:n", y="Color:n",
        color={"mean(Price)", title="Mean price", scale={scheme="blueorange"}},
        config={view={stroke="transparent"}}
    )

vegalite_categorical_heatmap
vegalite_categorical_heatmap1238×828 27.2 KB

julia> diamonds
53940×10 DataFrame
   Row │ Carat    Cut        Color  Clarity  Depth    Table    Price  X        Y        Z       
       │ Float64  Cat…       Cat…   Cat…     Float64  Float64  Int32  Float64  Float64  Float64 
───────┼────────────────────────────────────────────────────────────────────────────────────────
     1 │    0.23  Ideal      E      SI2         61.5     55.0    326     3.95     3.98     2.43
     2 │    0.21  Premium    E      SI1         59.8     61.0    326     3.89     3.84     2.31
     3 │    0.23  Good       E      VS1         56.9     65.0    327     4.05     4.07     2.31
   ⋮   │    ⋮         ⋮        ⋮       ⋮        ⋮        ⋮       ⋮       ⋮        ⋮        ⋮
 53938 │    0.7   Very Good  D      SI1         62.8     60.0   2757     5.66     5.68     3.56
 53939 │    0.86  Premium    H      SI2         61.0     58.0   2757     6.15     6.12     3.74
 53940 │    0.75  Ideal      D      SI2         62.2     55.0   2757     5.83     5.87     3.64
                                                                              53923 rows omitted
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3

If I understand correctly you want to basically create a table with as x and y axes Cut and Color and content the mean Price, and then draw a heatmap of that. Creating this objects is done with the analysis reducer.

However here this won’t quite work, because this would then call a heatmap with 3 vectors (which is essentially a “non-full” heatmap). I wonder if this, ie heatmap(x::Vector, y::Vector, z::Vector) is something Makie can support out of the box (using some default value for missing x, y combinations), or whether it needs to be handled on the side of AlgebraOfGraphics.

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4

@piever Can you say why the code I tried doesn’t work?

5

AlgebraOfGraphics is essentially a way to do some preprocessing before sending data to Makie for the plot. In your case, you end up calling heatmap with the following signature:

heatmap(diamonds.cut::Vector, diamonds.color::Vector, color::Vector=diamonds.Price)

but heatmap(x, y, color=z) is not supported in Makie. Beyond that, there is no way to guess that you actually want the mean price given the x and y variable. Taking the mean value can be handled by AoG with reducer. For example, here is the 1D case:

using AlgebraOfGraphics, CairoMakie, RDatasets
using AlgebraOfGraphics: reducer

diamonds = dataset("ggplot2", "diamonds")
p = data(diamonds) *
    mapping(:Cut => categorical, :Price) *
    reducer() *
    visual(BarPlot)
draw(p)

bar
bar960×540 4.79 KB

I was imagining that the following

diamonds = dataset("ggplot2", "diamonds")
p = data(diamonds) *
    mapping(:Cut => categorical, :Color => categorical, :Price) *
    reducer() *
    visual(Heatmap)
draw(p)

would just work, but unfortunately it looks like heatmap(x::Vector, y::Vector, z::Vector) is not supported out of the box in Makie. I can check over at Makie if it makes sense to add it there, otherwise the small reshape necessary (from the “long” to the “matrix” format) can be handled in AoG.

UPDATE: the syntax

diamonds = dataset("ggplot2", "diamonds")
p = data(diamonds) *  mapping(:Cut => categorical, :Color => categorical, :Price) * reducer
draw(p)

now works on AlgebraOfGraphics master branch.

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