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

Widgets


There is another package of widgets, called widgets, that has all of the standard controls you might want to use, with many optional parameters available to customize your display.

The progress bar widget

One of the widgets available in this package displays a progress bar to the user. We could have the following script:

import ipywidgets as widgets 
widgets.FloatProgress( 
    value=45, 
    min=0, 
    max=100, 
    step=5, 
    description='Percent:', 
) 

The preceding script would display our progress bar as follows:

We see a progress bar that looks to be 45%.

The listbox widget

We could also use the listbox widget, called a Dropdown, as in the following script:

import ipywidgets as widgets 
from IPython.display import display 
w = widgets.Dropdown( 
    options={'Pen': 7732, 'Pencil': 102, 'Pad': 33331}, 
    description='Item:', 
) 
display(w) 
w.value 

This script will display a listbox to the user with the values Pen, Pencil, and Pad. When the user selects one of the values, the associated...