Book Image

Julia 1.0 Programming Cookbook

By : Bogumił Kamiński, Przemysław Szufel
Book Image

Julia 1.0 Programming Cookbook

By: Bogumił Kamiński, Przemysław Szufel

Overview of this book

Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia. By the end of the book, you will have acquired the skills to work more effectively with your data
Table of Contents (18 chapters)
Title Page
Copyright and Credits
About Packt

Working with categorical data

In Julia, the type of data often carries important information about how the information stored should be interpreted. However, in some cases, working with categorical data can be tricky. In this recipe, we explain how you can refer to an order defined in a categorical vector to filter its contents.

Getting ready

Start the Julia command line. Make sure that you have the DataFrames.jl package installed. If it is missing, then install it by running the commands using Pkg; Pkg.add("DataFrames") in the Julia command line.


In the GitHub repository for this recipe, you will find the commands.txt file, which contains the presented sequence of shell and Julia commands.

Now, open your favorite terminal to execute the commands.

How to do it...

In this recipe, we create a simple data frame containing categorical data, which we will later filter. Here is a list of steps to be followed:

  1. Firstly, load the DataFrames.jl package and define a vector of possible grades from FtoA...