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


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

Progress bar widget

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

import ipywidgets as widgets

This would display our progress bar as shown here:

Listbox widget

We could also use the list box widget, called as Dropdown, in this script:

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

This script will display a list box to the user with the displayed values of Pen, Pencil, and Pad. When the user selects one of the values, the associated value is returned to the w variable, which we display: