Glossary

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Programming in JuliaPlotting

Reading time: ~10 min

The main plotting package in Julia is called Plots. To create a figure, you supply data in the form of arrays as arguments to the plot function (x first, then y if appropriate, then z if appropriate). All other plot information (called attributes, in Plots lingo) is supplied using keyword arguments. For example:

using Plots
using Random
Random.seed!(123)
plot(rand(10), rand(10), seriestype = :scatter,
     group = rand(0:1,10), title = "Some random points")

Note that the group keyword argument partitioned the data into two series, one for each unique value in the array supplied to group. These series are automatically shown in different colors and labeled in the legend.

You can see all the main plot types and attributes on the Plots.jl cheatsheet.

To save a plot, use the savefig function:

P = plot(rand(0:10),rand(0:10), seriestype=:scatter)
savefig(P,"myfigure.pdf") # save figure as a PDF file

Exercise
Make a graph which looks as much as possible like the one shown below. You'll want to look at the Plots.jl cheatsheet for options.

using Plots
x = range(0, stop = 2π, length = 100)
y = sin.(x)
# add plotting code here

Solution. We change the line style and width, and we add labels for the axes:

using Plots
x = range(0, stop = 2π, length = 100)
y = sin.(x)
plot(x,y, linewidth = 3, linestyle = :dash,
     xlabel="x", ylabel="sin(x)", legend = :none)

To get a quick refresher on how to perform common tasks in Julia, check out the Julia-Python-R cheatsheet, also linked from browndsi.github.io.

Congratulations! You have finished the Data Gymnasia Programming with Julia course.

Bruno
Bruno Bruno