Did you know that Julia is a phantastic tool for Data Science? 👇
I just published a new 🚨 article on "Why you should invest in Julia now, as a Data Scientist" 🧑💻
— Logan Kilpatrick (@OfficialLoganK) December 7, 2021
Link: https://t.co/Jp4kD9Tnr0
If you have ever considered picking up #JuliaLang but didn't go through with it, now is a great time to re-visit the language!
We will look at the DataFrames.jl package this time. This is a very powerful package to work with tabular data, similar to pandas or an R data.frame or R data.table.
We'll give a very quick intro to working with data in julia by going through the first steps with DataFrames.jl tutorial on the manual.
However, this will be too short to cover all important concepts. I will refer you to several additional sources:
The package manual is very well done and should be on your list of references.
This tutorial series is very good for the DataFrames.jl package: https://github.com/bkamins/Julia-DataFrames-Tutorial
The julia academy data science tutorial is full of excellent stuff
The Turing Institute's Data Sciences tutorials give a good intro to data structures and machine learning in julia.
After this, we will illustrate use of the FixedEffectsModels.jl package and how it compares to R competitors in this notebook
Last modified: July 14, 2022. Website built with Franklin.jl and the Julia programming language.
