Julia Data Science

Welcome! This is an open source and open access book on how to do Data Science using Julia. Our target audience are researchers from all fields of applied sciences. Of course, we hope to be useful for industry too. You can navigate through the pages of the ebook by using the arrow keys (left/right) on your keyboard.

The book is also available as PDF.

The source code is available at GitHub.

Storopoli, Huijzer and Alonso (2021). Julia Data Science. https://juliadatascience.io. ISBN: 9798489859165.

1 Preface
1.1 What is Data Science?
1.2 Software Engineering
1.3 Acknowledgements
2 Why Julia?
2.1 For Non-Programmers
2.2 For Programmers
2.3 What Julia Aims to Accom..
2.4 Julia in the Wild
3 Julia Basics
3.1 Development Environments
3.2 Language Syntax
3.3 Native Data Structures
3.4 Filesystem
3.5 Julia Standard Library
4 DataFrames.jl
4.1 Load and Save Files
4.2 Index and Summarize
4.3 Filter and Subset
4.4 Select
4.5 Types and Categorical Da..
4.6 Join
4.7 Variable Transformations
4.8 Groupby and Combine
4.9 Missing Data
4.10 Performance
5 DataFramesMeta.jl
5.1 Macros
5.2 Column Selection
5.3 Column Transformation
5.4 Row Selection
5.5 Row Sorting
5.6 Data Summaries
5.7 Piping Operations
6 Data Visualization with Ma..
6.1 CairoMakie.jl
6.2 Attributes
6.3 Create Plot Figure
6.4 Cheat Sheets
6.5 Themes
6.6 Using LaTeXStrings.jl
6.7 Colors and Colormaps
6.8 Layouts
6.9 GLMakie.jl
6.10 A Makie recipe for a Da..
7 Data Visualization with Al..
7.1 Layers
7.2 Layouts
7.3 Statistical Visualizatio..
7.4 Plot Customizations
7.5 Makie.jl and AlgebraOfGr..
8 Appendix
8.1 Packages Versions
8.2 Notation
References