Название: Julia Data Science
Автор: Jose Storopoli, Rik Huijzer, Lazaro Alonso
Издательство: Independently published
Год: 2025-06-01
Страниц: 260
Язык: английский
Формат: pdf
Размер: 19.5 MB

This book describes the basics of the Julia programming language DataFrames.jl for data manipulation and Makie.jl for data visualization.

There are many programming languages and each and every one of them has its strengths and weaknesses. Some languages are very quick, but verbose. Other languages are very easy to write in, but slow. This is known as the two-language problem and Julia aims at circumventing this problem. Even though all three of us come from different fields, we all found the Julia language more effective for our research than languages that we’ve used before. We discuss some of our arguments in Section 2. However, compared to other languages, Julia is one of the newest languages around. This means that the ecosystem around the language is sometimes difficult to navigate through. It’s difficult to figure out where to start and how all the different packages fit together. That is why we decided to create this book! We wanted to make it easier for researchers, and especially our colleagues, to start using this awesome language.

As discussed above, each language has its strengths and weaknesses. In our opinion, Data Science is definitely a strength of Julia. At the same time, all three of us used Data Science tools in our day to day life. And, probably, you want to use Data Science too! That is why this book has a focus on Data Science.

Why should you dedicate your precious time into learning a language that is almost never mentioned in any job listing, lab position, postdoc offer, or academic job description? The answer is that Julia is a fresh approach to both programming and Data Science. Everything that you do in Python or in R, you can do it in Julia with the advantage of being able to write readable, fast, and powerful code. Therefore, the Julia language is gaining traction, and for good reasons. So, if you don’t have any programming background knowledge, we highly encourage you to take up Julia as a first programming language and Data Science framework.

You will learn to:
Read CSV and Excel data into Julia.
Process data in Julia, that is, learn how to answer data questions.
Filter and subset data.
Handle missing data.
Join multiple data sources together.
Group and summarize data.
Export data out of Julia to CSV and Excel files.
Plot data with different Makie.jl backends.
Save visualizations in several formats such as PNG or PDF.
Use different plotting functions to make diverse data visualizations.
Customize visualizations with attributes.
Use and create new plotting themes.
Add LaTeX elements to plots.
Manipulate color and palettes.
Create complex figure layouts.