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 and writing Microsoft Excel files

Microsoft Excel is a popular spreadsheet application. In this recipe, you will discover how to create files within Julia using the openpyxl Python library, as well as how to read Excel files. Specifically, we will look at how to handle Excel files in two different ways: firstly, by using Python's openpyxl library via PyCall.jl, and secondly, by using the XLSX.jl package.

Getting ready

For this recipe, you need the following packages: PyCall.jl, Conda.jl, DataFrames.jl, and XLSX.jl. Install them with the Julia package manager by going to the Julia command line (REPL), pressing the ] key, and running the following commands:

(v1.0) pkg> add PyCall
(v1.0) pkg> add Conda
(v1.0) pkg> add DataFrames 
(v1.0) pkg> add XLSX

This will install the required packages and their dependencies.


The openpyxl Python library can be installed with the following commands:

julia> using Conda
julia> Conda.add("openpyxl")


In the GitHub repository for this...