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
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

R visualizations in Jupyter


A common use of R is to use several visualizations, which are available depending on the underlying data. In this section, we will go over some of them to see how R interacts with Jupyter.

R 3D graphics in Jupyter

One of the packages available for 3D graphics is persp. The persp package draws perspective plots over a 2D space.

We can enter a basic persp command in a new notebook and have something like this:

Once we run the step (Cell | Run All), we can see the display in the following screenshot. The first part is the script involved to generate the graphic (this is part of the example code):

Then we see the following graphic display:

R 3D scatterplot in Jupyter

The R lattice package has a cloud function that will produce 3D scatterplots.

The script we will use is as follows:

# make sure lattice package is installed
install.package("lattice")
# in a standalone R script you would have a command to download the lattice library - this is not needed in Jupyter
library...