This page includes instructions for getting started with DATA 1010.
We’re going to use Julia in the course, and I recommend that you get it installed locally. You can also the web-based Prismia version, but there is some delay in starting up your instance, and you will likely find that you prefer the experience of a locally installed version.
Download the latest version of Julia from https://julialang.org/downloads. Note that you should use the standard download link you see on that page, rather than JuliaPro or the Conda distribution or whatever.
Once you’ve downloaded and installed the Julia application, you’ll want to make the
julia executable visible to your system. To do this, follow the platform-specific instructions here. (For macOS users, there’s a chance you might not already have a
/usr/local/bin directory; if that’s the case, then you’ll get an error when you run the
ln -s command suggested on the Julia website. If that’s the case, do
mkdir -p /usr/local/bin and then run the
ln -s command again. If you get a permissions error, re-run the same command but with
sudo prepended. You’ll be able to enter your password to override the permissions restriction. To avoid similar problems in the future, you might also want to change your permissions on your
/usr/local directory by doing
sudo chown -R $(whoami) /usr/local).
We’re primarily going to interact with Julia through JupyterLab. To get started with JupyterLab, type
julia at your command line (after installation and setup) to open a Julia REPL. Then run
using Pkg; Pkg.add("IJulia") using IJulia jupyterlab()
to install the Julia-Jupyter interface and open a Jupyter Lab session in your browser. After the first time you do this, you can either run the last two lines above in a Julia REPL, or you can run
jupyter lab from the command line if you have Anaconda installed (which you will for DATA 1030 or DATA 1050).
If you have any trouble with package installations, here are some tips:
- If you’re having trouble with a package, you can try rebuilding
it by doing
Pkg.build("PackageName"), and you can also
Pkg.rm("PackageName"); Pkg.add("PackageName")to remove it and add it back.
- You can do
using PyCall; PyCall.pythonto see which Python executable your installation is using.
- If your error message includes something about GR, you might need to rebuild your GR package or use PyPlot instead (these are both backends for Plots, meaning that they are used to generate the figures corresponding to your Plots commands). To rebuild GR, try
Pkg.update(); ENV["GRDIR"] = ""; Pkg.build("GR"). To switch to PyPlot, try
Pkg.add("PyPlot"); Pkg.add("LaTeXStrings"); using Plots; pyplot().
- Try googling the error message. Other folks have probably had similar issues, and sometimes the fix is pretty easy.
If you don’t want to have to run
using Statistics, LinearAlgebra in
every session, you can put these lines in your
startup.jl file. The
code in this file is loaded every time you run Julia.
The instructions below are for macOS/Linux. The same idea applies if
you’re using Windows, but the navigation commands are different. The
basic idea is to put a
startup.jl file in
~ represents whatever the home directory is on your system.
- Open a Terminal session
lsto see if there is a
configfolder already there. If not, make one with
vi startup.jlto create a
startup.jlfile and open an editor to put content into it.
ito insert text, and then type
using Statistics, LinearAlgebra.
- Save the file by pressing escape, then
:wq, and then enter.