Storopoli J., Huijzer R., Alonso L. Julia Data Science

Independently published, 2024. - 259 p. - ISBN: 9798489859165.First edition published in 2021.Version: 19.8.2024.There are many programming languages 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 lives. And, probably, you want to use data science too! That is why this book has a focus on data science.Why Julia?
Julia Basics.
DataFrames.jl.
DataFramesMeta.jl.
Data Visualization with Makie. jl.
Data Visualization with AlgebraOfGraphics.jl.True PDF (A5).