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

Converting data between DataFrame and Matrix

The DataFrames.jl package provides a vast array of procedures that allow you to manipulate tabular data with rows of heterogeneous types. However, you often have your data stored initially in a matrix. In this recipe, we discuss how you can convert such data to DataFrame. We also show how you can perform the reverse procedure, that is, transform the data from DataFrame to a value of a standard Matrix type available in Julia.

Getting ready

Make sure that you have theDataFrames.jlpackage installed. You can check this by writing this in the Julia command line:

julia> using DataFrames

If this command fails, then add theDataFrames.jlpackage, in accordance with the instructions in the Managing packages recipe in Chapter 1Installing and Setting Up Julia:

julia> using Pkg; Pkg.add("DataFrames")


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...