Data visualization in Julia
For the following Julia program, we use a package called Plots
. The command used to install the package is Pkg.add("Plots")
. Here, we run Julia programs via a Jupyter
notebook. The Julia program is presented in the following screenshot:

After clicking Kernel
on the menu bar, and then Restart and Run All
, we get the following:

Again, the srand(123)
command guarantees that any user who applies the same random seed will get the same set of random numbers. Because of this, he/she would get the same graph shown previously. The next example is a scatter plot using a Julia package called PyPlot
:
using PyPlot n=50 srand(333) x = 100*rand(n) y = 100*rand(n) areas = 800*rand(n) fig = figure("pyplot_scatterplot",figsize=(10,10)) ax = axes() scatter(x,y,s=areas,alpha=0.5) title("using PyPlot: Scatter Plot") xlabel("X") ylabel("Y") grid("on")
The related graph is shown here:

The next Julia program is borrowed from Sargent and Stachurski (2017):
using QuantEcon: meshgrid...