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

Basic Julia in Jupyter

In this example we will use the Iris dataset for some standard analysis. So, start a new Julia notebook and call it Julia Iris. We can enter a small script to see how the steps progress for a Julia script.

This script uses another package for plotting, Gadfly. You would have to go through similar steps as before to install the package before operating the script.

Enter the following script into separate cells of your notebook:

using RDatasets, DataFrames, Gadfly
set_default_plot_size(5inch, 5inch/golden);
plot(dataset("datasets","iris"), x="SepalWidth",
        y="SepalLength", color="Species")

RDataSets is a library containing several of the commonly used R datasets, such as Iris. This is a simple script-we define our libraries that we are going to use, set the size of the plot area, and plot out the Iris data points (color coded to species).

So, you would end up with a starting screen that looks like the following screenshot:

We should take note of a few aspects...