A Julia package for generating visualizations in Vega
Getting Started
Visualization Primitives
Creating A Visualization From Scratch
Required Arguments:
v::VegaVisualization
palette::Union(Tuple{AbstractString,Int64}, AbstractString, Array)
reversePalette::Bool = falseThis function mutates :VegaVisualization, modifying the colors for the group or fill properties of the visualization. The palette argument supports:
* Tuple{AbstractString,Int64}: A ColorBrewer theme and number of color levels desired
* AbstractString: A string representing a color the browser understands (i.e. "Pink", "#FFF")
* Array: An array of colors (i.e. ["Red", "Green"])
using Vega
ab = barplot(x = collect(1:20), y = rand(20), group = vcat([1 for i in 1:10], [2 for i in 1:10]))
colorscheme!(ab, palette = ("Purples", 3))using Vega
ab = barplot(x = collect(1:20), y = rand(20), group = vcat([1 for i in 1:10], [2 for i in 1:10]))
colorscheme!(ab, palette = ("Purples", 3), reversePalette = true)using Vega
srand(1)
a = barplot(x = [1:20], y = rand(20))
colorscheme!(a, palette = "Violet")using DataFrames, JSON, Vega
df = DataFrame()
for p in JSON.parse(readall(Pkg.dir("Vega", "vega-datasets/population.json")))
df = vcat(df, DataFrame(;[symbol(k)=>v for (k,v) in p]...))
end
pop1900 = df[df[:year] .== 1900, :];
x = pop1900[:people]
y = pop1900[:age]
group = pop1900[:sex]
pc1 = popchart(x = x, y = y, group = group)
colorscheme!(pc1, palette = ["Green", "Red"])