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Julia has various packages for plotting and before starting making plots, we need to first download and install some of them as follows −
(@v1.5) pkg> add Plots PyPlot GR UnicodePlots
The package Plots is a high-level plotting package, also referred to as ‘back-ends’ interfaces with other plotting packages. To start using the Plots package, type the following command −
julia> using Plots [ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]
Plotting a function
For plotting a function, we need to switch back to PyPlot back-end as follows −
julia> pyplot() Plots.PyPlotBackend()
Here we will be plotting the equation of Time graph which can be modeled by the following function −
julia> eq(d) = -7.65 * sind(d) + 9.87 * sind(2d + 206); julia> plot(eq, 1:365) sys:1: MatplotlibDeprecationWarning: Passing the fontdict parameter of _set_ticklabels() positionally is deprecated since Matplotlib 3.3; the parameter will become keyword-only two minor releases later. sys:1: UserWarning: FixedFormatter should only be used together with FixedLocator
Packages
Everyone wants a package that helps them to draw quick plots by text rather than graphics.
UnicodePlots
Julia provides one such package called UnicodePlots which can produce the following −
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scatter plots
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line plots
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bar plots
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staircase plots
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histograms
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sparsity patterns
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density plots
We can add it to our Julia installation by the following command −
(@v1.5) pkg> add UnicodePlots
Once added, we can use this to plot a graph as follows:
julia> using UnicodePlots
Example
Following Julia example generates a line chart using UnicodePlots.
julia> FirstLinePlot = lineplot([1, 2, 3, 7], [1, 2, -5, 7], title="First Line Plot", border=:dotted) First Line Plot
Example
Following Julia example generates a density chart using UnicodePlots.
Julia> using UnicodePlots Julia> FirstDensityPlot = densityplot(collect(1:100), randn(100), border=:dotted)
VegaLite
This Julia package is a visualization grammar which allows us to create visualization in a web browser window. With this package, we can −
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describe data visualization in a JSON format
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generate interactive views using HTML5 Canvas or SVG
It can produce the following −
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Area plots
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Bar plots/Histograms
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Line plots
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Scatter plots
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Pie/Donut charts
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Waterfall charts
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Worldclouds
We can add it to our Julia installation by following command −
(@v1.5) pkg> add VegaLite
Once added we can use this to plot a graph as follows −
julia> using VegaLite
Example
Following Julia example generates a Pie chart using VegaLite.
julia> X = ["Monday", "Tuesday", "Wednesday", "Thrusday", "Friday","Saturday","Sunday"]; julia> Y = [11, 11, 15, 13, 12, 13, 10] 7-element Array{Int64,1}: 11 11 15 13 12 13 10 julia> P = pie(X,Y)
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