Method Signatures

#Array methods
area(x::AbstractVector, y::AbstractVector{<:Union{Missing, Real}})
area(x::AbstractVector, y::AbstractArray{<:Union{Missing, Real},2})

#Dataframe methods
area(df::AbstractDataFrame, x::Symbol, y::Symbol)
area(df::AbstractDataFrame, x::Symbol, y::Symbol, group::Symbol)

#Other methods
area(k::KernelDensity.UnivariateKDE)

Optional Arguments

mark::Union{String, AbstractVector} = "line"
fill::Union{Bool, AbstractVector} = true
stack::Union{Bool, AbstractVector, Void} = true
step::Union{String, Void} = nothing #choice of {"start", "middle", "end"}
legend::Bool = false
scale::Bool = false
kwargs... #modifies top-level EChart properties

Examples

Single Series

using ECharts
x = ["Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday"]
y = [11, 11, 15, 13, 12, 13, 10]
ar = area(x, y)

Multiple Series (Stacked Area)

The default when passed multiple series is to stack the series, i.e. showing the individual series contribution to the whole. If you want to overlay each series relative to zero on the Y-axis, use stack = false.

In order for the stacked charts to render properly, any missing values are set to 0 on render. If this is not the correct treatment, you need to remove missing values prior to calling area().

using ECharts
x = ["Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday"]
y = [11, 11, 15, 13, 12, 13, 10]
y2 = 3.7 .* y
as = area(x, hcat(y, y2))

Step Chart

using ECharts
x = ["Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday"]
y = [11, 11, 15, 13, 12, 13, 10]
y2 = 3.7 .* y
astep = area(x, hcat(y, y2), step = "middle")

DataFrame with group argument

using ECharts, DataFrames
x = [0,1,2,3,4,5,6,7,8,9,0,1,2,3,4,5,6,7,8,9]
y = [28, 43, 81, 19, 52, 24, 87, 17, 68, 49, 55, 91, 53, 87, 48, 49, 66, 27, 16, 15]
g = [0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1]
df_merged = DataFrame(x = x, y = y, g = g)
adfg = area(df_merged, :x, :y, :g)

UnivariateKDE

using ECharts
using KernelDensity, Distributions

#Set seed for repeatability
srand(1234)

#Generate Beta dist, calculate kernel density estimate
x = rand(Beta(3.0, 2.0), 10)
k = kde(x)

a = area(k)