Book Image

Learning Jupyter 5 - Second Edition

Book Image

Learning Jupyter 5 - Second Edition

Overview of this book

The Jupyter Notebook 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, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you’ve explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization.
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Chapter 1. Introduction to Jupyter

Jupyter is a tool that allows data scientists to record their complete analysis process, much in the same way other scientists use a Lab Notebook to record tests, progress, results, and conclusions.

The Jupyter product was originally developed as part of the IPython project. The IPython project was used to provide interactive online access to Python. Over time, it became useful to interact with other data analysis tools, such as R, in the same manner. With this split from Python, the tool grew into its current manifestation of Jupyter. IPython is still an active tool that's available for use. The name Jupyter itself is derived from the combination of Julia, Python, and R.

Jupyter is available as a web application from a number of places. It can also be used locally over a wide variety of installations. In this book, we will be exploring using Jupyter on a macOS and a Windows PC, as well as over the internet with other providers.

With Jupyter 5.0, there were significant enhancements for the following:

  • Cell tagging
  • Customizing keyboard shortcuts
  • Copying and pasting cells between Notebooks
  • A more attractive default style for tables

In this chapter, we will cover the following topics:

  • First look at Jupyter
  • Installing Jupyter
  • Notebook structure
  • Notebook workflow
  • Basic Notebook operations
  • Security in Jupyter
  • Configuration options for Jupyter