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

Basic Python in Jupyter


We must open a Python section of our Notebook to use Python coding. So, start your Notebook, and then in the upper-right menu, select Python 3:

 

This will open a Python window to work in:

As mentioned in the previous chapter, the new window shows an empty cell so that you can enter Python code.

Let's give the new work area a name, Learning Jupyter 5, Chapter 2. Autosave should be on (as you can see next to the title). With an accurate name, we can find this section again easily from the Notebook home page. If you select your browser's Home tab and refresh it, you will see this new window name being displayed:

Note that it has an Notebook icon versus a folder icon. The extension that's automatically assigned is .ipynb (Python Notebook). And, since the item is in a browser in a Jupyter environment, it is marked as running. There is a file by that name in your directory on the disk as well:

 

If you open the .ipynb file in a text editor, you will see the basic contents of...