Julia tutorials for faster, easier data analysis
I love Julia. Just don’t tell my wife. Kidding! I’m talking about the Julia language from MIT. It’s a pleasure to use, and gaining popularity.
There is a Julia package that will encode strings for you, but it doesn’t handle url encoding properly. This code fixes that.
Learn how to add, delete and replace items in Julia arrays; how to find and remove duplicates in an array; how to join or intersect two arrays, and more.
Julia can be used for fast web scraping, not just data analysis.
Julia dataframes let you do anything you want: pivot tables, data cleaning, table joins, filtering, and more, all with a nice clean syntax.
You can’t do it in one line of Julia code, but you can do it!
If you’re going to learn a coding language for data science, Julia is the one. Here’s why.
It’s WAY easier than installing Python. You can install Julia like any other Mac app. You can even use a Homebrew Cask.