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


Tuples are one of the simplest data types and data structures in Julia. They can have any length and can contain any kind of value—but they are immutable. Once created, a tuple cannot be modified. A tuple can be created using the literal tuple notation, by wrapping the comma-separated values within brackets (...):

(1, 2, 3)

julia> ("a", 4, 12.5) 
("a", 4, 12.5) 

In order to define a one-element tuple, we must not forget the trailing comma:

julia> (1,) 

But it's OK to leave off the parenthesis:

julia> 'e', 2 
('e', 2) 
julia> 1, 

We can index into tuples to access their elements:

julia> lang = ("Julia", v"1.0") 
("Julia", v"1.0.0") 
julia> lang[2] 

Vectorized dot operations also work with tuples:

julia> (3,4) .+ (1,1) (4, 5)



Named tuples

A named tuple represents a tuple with labeled items. We can access the individual components by label or by index:

julia> skills = (language = "Julia", version = v"1.0") 
(language = "Julia", version =...