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You're reading from Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Product type Paperback

Published in Apr 2018

Publisher Packt

ISBN-13 9781788839440

Length 238 pages

Edition 1st Edition

Languages

JavaScript

Tools

Jupyter

Concepts

Data Analysis

Author (1):

Toomey

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Table of Contents (17) Chapters

Title Page

Packt Upsell

Contributors

Preface

1. Installation and Setting up the Environment FREE CHAPTER

Introduction
Installing Jupyter on Windows
Installing Jupyter on the Mac
Installing Jupyter on Linux
Installing Jupyter on a server

2. Adding an Engine

Introduction
Adding the Python 3 engine
Adding the R engine
Adding the Julia engine
Adding the JavaScript engine
Adding the Scala engine
Adding the Spark engine

3. Accessing and Retrieving Data

Introduction
Reading CSV files
Reading JSON files
Accessing a database
Reading flat files
Reading text files

4. Visualizing Your Analytics

Introduction
Generating a line graph using Python
Generating a histogram using Python
Generating a density map using Python
Plotting 3D data using Python
Present a user-interactive graphic using Python
Visualizing with R
Generate a regression line of data using R
Generate an R lowess line graph
Producing a Scatter plot matrix using R
Producing a bar chart using R
Producing a word cloud using R
Visualizing with Julia
Drawing a Julia scatter diagram of Iris data using Gadfly
Drawing a Julia histogram using Gadfly
Drawing a Julia line graph using the Winston package

5. Working with Widgets

Introduction
What are widgets?
Using ipyleaflet widgets
Using ipywidgets
Using a widget container
Using an interactive widget
Using an interactive text widget
Linking widgets together
Another ipywidgets linking example
Using a cookie cutter widget
Developing an OPENGL widget
Creating a simple orbit of one object
Using a complex orbit of multiple objects

6. Jupyter Dashboards

Introduction
What is Jupyter dashboards?
Creating an R dashboard
Create a Python dashboard
Creating a Julia dashboard
Develop a JavaScript (Node.js) dashboard

7. Sharing Your Code

Introduction
Using a Notebook server
Using a web server
Sharing your Notebook through a public server
Sharing your Notebook through Docker
Sharing your Notebook using nbviewer
Converting your Notebook into a different format
Converting Notebooks to R
Converting Notebooks to HTML
Converting Notebooks to Markdown
Converting Notebooks to reStructedText
Converting Notebooks to Latex
Converting Notebooks to PDF

8. Multiuser Jupyter

Introduction
Why multiuser?
Providing multiuser with JupyterHub
Providing multiuser with Docker
Running your Notebook in Google Cloud Platform
Running your Notebook in AWS
Running your Notebook in Azure

9. Interacting with Big Data

Introduction
Obtaining a word count from a big-text data source
Obtaining a sorted word count from a big-text source
Examining big-text log file access
Computing prime numbers using parallel operations
Analyzing big-text data
Analyzing big data history files

10. Jupyter Security

Introduction
Security mechanisms built into Jupyter
Using SSL
The Jupyter trust model
Controlling network access
Additional practices

11. Jupyter Labs

Introduction
Installing and starting JupyterLab
JupyterLab display
JupyterLab menus
Starting a Notebook
Starting a console

Index

Chapter 10. Jupyter Security

In this chapter, we will cover the following recipes:

Security mechanisms built into Jupyter
Using SSL
The Jupyter trust model
Controlling network access
Additional practices

The rest of the chapter is locked

You're reading from Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Table of Contents (17) Chapters

Chapter 10. Jupyter Security

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You're reading from Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Table of Contents (17) Chapters

Chapter 10. Jupyter Security

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Authors (1)

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