#### Overview of this book

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more. This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we’ll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode. Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.
Table of Contents (16 chapters)
Learning Jupyter
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Free Chapter
Introduction to Jupyter
Jupyter Python Scripting
Jupyter R Scripting
Jupyter Julia Scripting
Jupyter JavaScript Coding
Interactive Widgets
Sharing and Converting Jupyter Notebooks
Multiuser Jupyter Notebooks
Jupyter Scala
Jupyter and Big Data

## Scala random numbers in Jupyter

In this example, we simulate a rolling dice and count how many times each combination appears. We then present a simple histogram for illustrative purposes.

The script is as follows:

```val r = new scala.util.Random
r.setSeed(113L)
val samples = 1000
var dice = new Array[Int](12)
for( i <- 1 to samples){
var total = r.nextInt(6) + r.nextInt(6)
dice(total) = dice(total) + 1
}
val max = dice.reduceLeft(_ max _)
for( i <- 0 to 11) {
var str = ""
for( j <- 1 to dice(i)/3) {
str = str + "X"
}
print(i+1, str, "\n")
}
```

We first pull in the Scala random library. We set the seed (in order to have repeatable results). We are drawing 1,000 rolls. For each roll, we increment a counter of how many times the total of pips on die 1 and die 2 appear. Then we present an abbreviated histogram of the results.

Scala has a number of shortcut methods for quick scanning through a list/collection, as seen in the `reduceLeft(_ max _)` statement. We...