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First Steps #1: Installing Julia

This is post #1 in our First Steps series. Want to learn Julia but don't know where to start? Start here!

💻 Installing Julia

The recommended method of installing Julia is through the official binaries available at https://julialang.org/downloads/. Simply choose the proper link for your platform.

My Platform is...

Note: If your mac has an M-series processor, you may want to consider downloading both the Intel/Rosetta and the M-series releases of Julia. If you run into a package that doesn't work on your M-series processor, you can then switch to the Intel/Rosetta version.

4. Optional for M-series macs: Add juliarosetta to your PATH. First, rename the Julia-1.8 (Intel version) Application to Julia-1.8-Rosetta.

rm -f /usr/local/bin/juliarosetta

ln -s /Applications/Julia-1.8-Rosetta.app/Contents/Resources/julia/bin/julia /usr/local/bin/julia

Adding juliarosetta to macOS PATH

🪟 Windows

Double-click the .exe file and follow the instructions.
Find Julia via the start menu or double-click the Desktop shortcut (if you chose to add one during step 1) and voila 🎉!
Optional: Add julia to your PATH environmental variable. This means you can start Julia by typing julia in a terminal (it is recommended to use a modern terminal such as Windows Terminal from the Microsoft App Store. The easiest method is to check the "Add Julia to PATH" option in the installer. If you skipped that, the instructions slightly differ for Windows 7 and 8 vs. Windows 10.

🐧 Linux/FreeBSD

Odds are you expect less hand-holding 😄. See available versions here: https://julialang.org/downloads/.

🎁 Packages for Data Science

Installing Packages

Julia comes with an amazing package manager. Pkg will be covered in a different post. For now we'll just say that to add a package (StatsBase, for example), you'll use:

julia> using Pkg

julia> Pkg.add("StatsBase")

Installing StatsBase

Core Data Science Packages

There are many fantastic data science tools in Julia's package ecosystem. Many of them will be covered in future posts. For now, we recommend getting started with the following:

StatsBase: Basic Statistics for Julia.
DataFrames: In-memory tabular data in Julia.
Plots: Powerful convenience for Julia visualizations and data analysis.
Pluto: Simple reactive notebooks for Julia.

To install these packages, run the following in Julia:

using Pkg

for pkg in ["StatsBase", "DataFrames", "Plots", "Pluto"]
    Pkg.add(pkg)
end

Installing Core Data Science Packages

🚀 That's It!

Next up is First Steps #2: The REPL

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First Steps #1: Installing Julia

Josh Day