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

Investigating the contents of a data frame

Understanding how to check the contents of DataFrame after creating it is an essential aspect of working with data. In this recipe, we explain what features of the DataFrames.jl package make this task easy.

Getting ready

Make sure that you have the DataFrames.jl package installed. If it is missing, 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...

Here is a list of steps to be followed:

  1. Create a random DataFrame so that its contents can be inspected later:
julia> using DataFrames, Randomjulia> Random.seed!(1);julia> df = DataFrame(rand(1000, 100));
  1. Confirm the DataFrame that was created is too large to be displayed, as it contains 1000 rows and 100 columns by using the nrow,...