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

Reading CSV data from the internet

Often, you need to fetch data in CSV format from the internet. In this recipe, you will discover a simple way of fetching such data and reading it into DataFrame using the CSV.jl package. Then, we will look at how you can save this data back to a CSV file.

Getting ready

We will use a classic dataset calledIris, which is available for download here:

The citation is as follows:

@misc{R.A. Fisher , author = "R.A. Fisher ", year = "2017", title = "{UCI} Machine Learning Repository", url = "", institution = "University of California, Irvine, School of Information and Computer Sciences" }

Start your Julia command line and make sure that you do not have a file namediris.csvin your working directory. Also, make sure that you have theDataFrames.jland theCSV.jlpackages installed. If they are missing, then install them by running the commands using Pkg; Pkg.add("DataFrames...