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
Dedication
About Packt
Contributors
Preface
Index

Rounding of dates


There might be situations where we have a date/time and a need to compute the previous, or next complete time interval, for example, the next hour, or the previous day. The Dates API exposes a few methods for rounding Date and DateTime objects—floor, ceil, and time. They are quite intuitive and very powerful:

julia> now() 
2018-11-08T21:13:20.605 

# round down to the nearest hour 
julia> floor(now(), Hour) 
2018-11-08T21:00:00 

# or to the nearest 30 minutes increment 
julia> floor(now(), Minute(30))  
2018-11-08T21:00:00 

# it also works with dates  
julia> floor(today(), Month) # today() is the 8th of Nov 2018 
2018-11-01

The ceil function works similarly, but instead of rounding down, it rounds up. As for the round function, it will round up or down, depending on whichever is the closest value:

julia> round(today(), Month) 
2018-11-01 # today is the 11th so beginning of month is closer 
 
julia> round(today() + Day(10), Month) 
2018-12-01 # end of month...