Plotting Library for Online Tutorial / Book

General Usage
1

I am part of the effort to recreate “Causal Inference: The Mixtape” in Julia and therefore tried a couple of plotting libraries to recreate the first plot in the book (https://mixtape.scunning.com/probability-and-regression.html#ordinary-least-squares). There are of course different trade-offs with code length and possibilities. I would appreciate some input on which library would be best to recreate the book. Gadfly and VegaLite are very nice to read but I could not manage to implement everything (maybe this is not necessary though?), Plots and Makie are extremely flexible but result in longer code and with AlgebraOfGraphics I had a hard time actually showing the plot. Here is what I tried so far:

using DataFrames,
    GLM,
    Gadfly,
    VegaLite,
    Plots,
    GLMakie,
    AlgebraOfGraphics,
    Random
Random.seed!(1);

df = DataFrame(
    x = randn(10000),
    u = randn(10000)
);
df.y = 5.5 .* df.x .+ 12 .* df.u;

reg_df = lm(@formula(y~x), df)
df.fitted = predict(reg_df)
slope = "Slope = $(round(coef(reg_df)[2],digits = 7))"
intercept = "y-intercept = $(round(coef(reg_df)[1],digits = 7))"

Gadfly.plot(df,
    x = :x, y = :y,
    Guide.title("OLS Regression Line"),
    Geom.smooth(method=:lm,),
    Geom.point,
    size=[1.2pt],alpha=[0.5],
    color = [colorant"grey0"],
    Gadfly.Guide.manual_discrete_key(
        "",
        ["Fitted Values", "y"],
        shape = [Gadfly.Shape.hline, Gadfly.Shape.circle],
        color = [colorant"grey0"],
        size = [3pt, 1.2pt],
        pos = [2.7, 15])
    )

df |>
    @vlplot(x=:x, y=:y,
        title="OLS Regression Line",
        width=300,height=300) +
    @vlplot(
        mark = {:point, filled = true,
                color = "black",
                size = 1.2,alpha = 0.5}
        ) +
    @vlplot(
        mark = {:line,
                color = "black"},
        transform = [{regression = :y, on = :x}],
    )

Plots.scatter(
  df.x, df.y,
  markersize = 0.05,
  label = "y",
  title = "OLS Regression Line",
  color = :black,
  legend = :outerbottom
)
Plots.plot!(
  df.x, df.fitted,
  label = "Fitted values",
  color = :black)
Plots.quiver!(
  [2],[-20], quiver=([-1], [25]),
  color = :blue
)
annotate!(2.1, -24,
  Plots.text(slope,
    :blue)
)
Plots.quiver!(
  [-2],[20], quiver=([2], [-20+coef(reg_df)[1]]),
  color = :red
)
annotate!(-1.5, 24.5,
  Plots.text(intercept,
    :red)
)

fig = Figure(resolution = (800,600))
ax = fig[1,1] = Axis(fig, title = "OLS Regression Line")
Makie.scatter!(ax,
  df.x,df.y,
  markersize = 1,
  label = "y",
  color = :black
)
Makie.lines!(ax,
  df.x, df.fitted,
  label = "Fitted values",
  color = :black
)
annotations!(ax,
  [slope,intercept],
  position = [(1.5,-25),(-3.5, 21)], color = [:blue, :red])
arrows!(ax,
  [2, -2], [-20, 20],
  [-1, 2], [25, -20+coef(reg_df)[1]],
  color = [:blue, :red])
fig[2,1] = Legend(fig, ax,
  orientation = :horizontal,
  tellwidth = false, tellheight = true)
fig

fig = Figure(resolution = (800,600))
plt = data(df) *( 
    mapping(:x, :y) * 
    visual(Scatter, markersize=1, label = "y") +
    mapping(:x, :fitted=>"y") *
    visual(Lines, label = "Fitted values") )+
  data((x = [2, -2], y = [-20, 20], u = [-1, 2], v=[25,-20+coef(reg_df)[1]] ) )*
  mapping(:x, :y, :u, :v) *
  visual(Arrows, color = [:blue, :red])
ax = AlgebraOfGraphics.draw!(fig[1,1], plt)[1].axis
annotations!(ax,
  [slope,intercept],
  position = [(1.5,-25),(-3.5, 21)], color = [:blue, :red])
fig[2,1] = Legend(fig, ax,
  orientation = :horizontal, tellheight = true, tellwidth=false
  )
Label(fig[0,:],
  "OLS Regression Line",
  tellwidth=false)

fig

Also tagging @epogrebnyak and https://github.com/danielw2904/mixtape/issues/2 (hope that is ok :slight_smile: )