Book Image

Learning Julia

By : Anshul Joshi, Rahul Lakhanpal
Book Image

Learning Julia

By: Anshul Joshi, Rahul Lakhanpal

Overview of this book

Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
8
Data Visualization and Graphics

Summary


In this chapter, we saw how Julia proves its mettle in the field of numerical and statistical computations. We saw how data from various sources can be read and written using Julia's built-in features as well as how to use DataFrames for our own advantage. Next, we saw how linear algebra and differential equations can be solved using some of the most advanced mathematical packages. Later on, Statistics proved to be an area of deep interest for Julia developers, as we saw how easy it is for someone coming from a traditional language background to easily pick up stats in Julia. Lastly, we talked about some optimization problems and how they can be solved in Julia.

Coming up, in the next chapter, we will see how to make more sense out of data using graphs and what packages in Julia can be used to complete the job.