Book Image

Learning Jupyter

By : Dan Toomey
Book Image

Learning Jupyter

By: Dan Toomey

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
About the Author
About the Reviewer

Scala data access in Jupyter

There is a copy of the iris dataset on the University of California, Irvine website at . We will access this data and perform some simpler statistics on the same.

The Scala code is as follows:

//copied file locally
val filename = ""

//DEBUGGING Uncomment this line to display more information -
println("SepalLength, SepalWidth, PetalLength, PetalWidth, Class");
val array = scala.collection.mutable.ArrayBuffer.empty[Float]
for (line <- Source.fromFile(filename).getLines) {
    var cols = line.split(",").map(_.trim);
          ${cols(3)} |${cols(4)}");
    val i = cols(0).toFloat
    array += i;
val count = array.length;
var min:Double = 9999.0;
var max:Double = 0.0;
var total:Double = 0.0;
for ( x <- array ) {
    if (x...