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

Working with data


There are various ways and sources from which we can get data. We can get data directly from the user through the Terminal or using a script or from a source file (which can either be a binary file or structured files like CSV or XML files). To see how Julia accepts data from the user from any of these resources, let's dive right into these ways one by one.

When starting to play with data for the very first time, it's obvious to use the Julia REPL or a notebook environment such as the IJulia notebook. Now, Julia understands every incoming bit of data in a byte stream. So if we try to use the regular built-in functions such as read() and write(), they will basically be oriented toward a binary I/O. Let's see a simple example of a read() operation in action:

# usage of read with Char
julia> read(STDIN, Char)
j
'j': ASCII/Unicode U+006a (category Ll: Letter, lowercase)

# usage of read with Bool 
julia> read(STDIN, Bool)
true
true

# usage of read with Int8
julia> read...