Book Image

Julia Programming Projects

By : Adrian Salceanu
Book Image

Julia Programming Projects

By: Adrian Salceanu

Overview of this book

Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt

Defining variables

We have seen in the previous chapter how to use the REPL in order to execute computations and have the result displayed back to us. Julia even lends a helping hand by setting up the ans variable, which automatically holds the last computed value.


But, if we want to write anything but the most trivial programs, we need to learn how to define variables ourselves. In Julia, a variable is simply a name associated to a value. There are very few restrictions for naming variables, and the names themselves have no semantic meaning (the language will not treat variables differently based on their names, unlike say Ruby, where a name that is all caps is treated as a constant).

Let's see some examples:

julia> book = "Julia v1.0 By Example" 
julia> pi = 3.14 
julia> ANSWER = 42 
julia> my_first_name = "Adrian"


You can follow along through the examples in the chapter by loading the accompanying Jupyter/IJulia notebook provided with this chapter's support files.

The variables...