Search icon Close icon
Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.

Change country

Modal Close icon
Country selected Country selected
country flag United States
Country selected
country flag United Kingdom
Country selected
country flag India
Country selected
country flag Germany
Country selected
country flag France
Country selected
country flag Canada
Country selected
country flag Russia
Country selected
country flag Spain
Country selected
country flag Brazil
Country selected
country flag Australia
Country selected
country flag Argentina
Country selected
country flag Austria
Country selected
country flag Belgium
Country selected
country flag Bulgaria
Country selected
country flag Chile
Country selected
country flag Colombia
Country selected
country flag Cyprus
Country selected
country flag Czechia
Country selected
country flag Denmark
Country selected
country flag Ecuador
Country selected
country flag Egypt
Country selected
country flag Estonia
Country selected
country flag Finland
Country selected
country flag Greece
Country selected
country flag Hungary
Country selected
country flag Indonesia
Country selected
country flag Ireland
Country selected
country flag Italy
Country selected
country flag Japan
Country selected
country flag Latvia
Country selected
country flag Lithuania
Country selected
country flag Luxembourg
Country selected
country flag Malaysia
Country selected
country flag Malta
Country selected
country flag Mexico
Country selected
country flag Netherlands
Country selected
country flag New Zealand
Country selected
country flag Norway
Country selected
country flag Philippines
Country selected
country flag Poland
Country selected
country flag Portugal
Country selected
country flag Romania
Country selected
country flag Singapore
Country selected
country flag Slovakia
Country selected
country flag Slovenia
Country selected
country flag South Africa
Country selected
country flag South Korea
Country selected
country flag Sweden
Country selected
country flag Switzerland
Country selected
country flag Taiwan
Country selected
country flag Thailand
Country selected
country flag Turkey
Country selected
country flag Ukraine
Country selected
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Home > Data > Data Analysis > Learning Jupyter
Learning Jupyter
Learning Jupyter

Learning Jupyter: Select, Share, Interact and Integrate with Jupyter Notebook

Arrow left icon
Profile Icon Toomey
Arrow right icon
$29.99 $43.99
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1 (3 Ratings)
eBook Nov 2016 238 pages 1st Edition
eBook
$29.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Toomey
Arrow right icon
$29.99 $43.99
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1 (3 Ratings)
eBook Nov 2016 238 pages 1st Edition
eBook
$29.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$29.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Table of content icon View table of contents Preview book icon Preview Book

Learning Jupyter

Chapter 2. Jupyter Python Scripting

Jupyter was originally IPython-an interactive version of Python to be used as a development environment. As such, most of the features of Python are available to you when developing your notebook.

In this chapter, we will cover the following topics:

  • Basic Python scripting
  • Python dataset access (from a library)
  • Python pandas
  • Python graphics
  • Python random numbers

Basic Python in Jupyter

In this chapter, we will be using Python scripts in a Jupyter Notebook. Jupyter does not interact with your scripts as much as it executes your script and records results. I think this is how Jupyter Notebooks have been extended to use other languages besides Python-the notebook just takes a script, runs it against a language engine, and records the output from the engine-all the while not really knowing what kind of script is being executed.

Similarly, I have not noticed any particular limitations when using Python in Jupyter. Some of the scripts I have run have taken a lot of time to run, used a lot of memory, opened new windows, and so on, all without failing. There are known issues running Python scripts that contain a __main__ execution loop and multithreaded applications.

We must open a Python section to our notebook to use Python coding. So, start your notebook, then, in the upper-right menu, select Python 2.

Note

I installed Jupyter in the Spring of 2016 on...

Python data access in Jupyter

Now that we have seen how Python works in Jupyter, including the underlying encoding, then how does Python accessing a large dataset work in Jupyter?

I started another view for pandas using Python Data Access as the name. From here, we will read in a large dataset and compute some standard statistics on the data. We are interested in seeing how we use pandas in Jupyter, how well the script performs, and what information is stored in the metadata (especially if it is a larger dataset).

Our script accesses the iris dataset that's built into one of the Python packages. All we are looking to do is to read in a slightly large number of items and calculate some basic operations on the dataset. We are really interested to see how much of the data is cached in the IPYNB file

The Python code is as follows:

# import the datasets package
from sklearn import datasets
# pull in the iris data
iris_dataset = datasets.load_iris()
# grab the first two columns of data
X = iris_dataset...

Python pandas in Jupyter

One of the most widely used features of Python is pandas. It is a third-party library of data analysis packages that can be used freely. In this example, we will develop a Python script that uses pandas to see if there is any effect to using it in Jupyter.

I am using the Titanic dataset from http://www.kaggle.com/c/titanic-gettingStarted/download/train.csv. I am sure the same data is available from a variety of sources.

Here is the Python script that we want to run in Jupyter:

from pandas import *
training_set = read_csv('train.csv')
training_set.head()
male = training_set[training_set.sex == 'male']
female = training_set[training_set.sex =='female']
womens_survival_rate = float(sum(female.survived))/len(female)
mens_survival_rate = float(sum(male.survived))/len(male)

The result is we calculate the survival rates of the Titanic's passengers based on their sex.

We create a new notebook, enter the script into appropriate cells, include...

Python graphics in Jupyter

How does Python graphics work in Jupyter?

I started another view for this named Python Graphics so as to distinguish the work from the previous work.

If we were to build a sample dataset of baby names and the number of births in a year of that name, we could then plot the data.

The Python coding is simple:

import pandas
import matplotlib
%matplotlib inline
baby_name = ['Alice','Charles','Diane','Edward']
number_births = [96, 155, 66, 272]
dataset = list(zip(baby_name,number_births))
df = pandas.DataFrame(data = dataset, columns=['Name', 'Number'])
df['Number'].plot()

The steps of the script are as follows:

  1. Import the graphics library (and data library) that we need.
  2. Define our data.
  3. Convert the data into a format that allows easy graphical display.
  4. Plot the data.

We would expect a graph of the number of births by baby name.

If we take the preceding script and place it into cells of our Jupyter ...

Basic Python in Jupyter

In this chapter, we will be using Python scripts in a Jupyter Notebook. Jupyter does not interact with your scripts as much as it executes your script and records results. I think this is how Jupyter Notebooks have been extended to use other languages besides Python-the notebook just takes a script, runs it against a language engine, and records the output from the engine-all the while not really knowing what kind of script is being executed.

Similarly, I have not noticed any particular limitations when using Python in Jupyter. Some of the scripts I have run have taken a lot of time to run, used a lot of memory, opened new windows, and so on, all without failing. There are known issues running Python scripts that contain a __main__ execution loop and multithreaded applications.

We must open a Python section to our notebook to use Python coding. So, start your notebook, then, in the upper-right menu, select Python 2.

Note

I installed Jupyter in the Spring of 2016 on a...

Python data access in Jupyter

Now that we have seen how Python works in Jupyter, including the underlying encoding, then how does Python accessing a large dataset work in Jupyter?

I started another view for pandas using Python Data Access as the name. From here, we will read in a large dataset and compute some standard statistics on the data. We are interested in seeing how we use pandas in Jupyter, how well the script performs, and what information is stored in the metadata (especially if it is a larger dataset).

Our script accesses the iris dataset that's built into one of the Python packages. All we are looking to do is to read in a slightly large number of items and calculate some basic operations on the dataset. We are really interested to see how much of the data is cached in the IPYNB file

The Python code is as follows:

# import the datasets package
from sklearn import datasets
# pull in the iris data
iris_dataset = datasets.load_iris()
# grab the first two columns of data
X = iris_dataset...
Left arrow icon

Page 1 of 7

Right arrow icon
Download code icon Download Code

Key benefits

  • Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide
  • This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease
  • This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc

Description

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.

Who is this book for?

This book caters to all developers, students, or educators who want to execute code, see output, and comment all in the same document, in the browser. Data science professionals will also find this book very useful to perform technical and scientific computing in a graphical, agile manner.

What you will learn

  • Install and run the Jupyter Notebook system on your machine
  • Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook
  • Use interactive widgets to manipulate and visualize data in real time
  • Start sharing your Notebook with colleagues
  • Invite your colleagues to work with you in the same Notebook
  • Organize your Notebook using Jupyter namespaces
  • Access big data in Jupyter

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 30, 2016
Length: 238 pages
Edition : 1st
Language : English
ISBN-13 : 9781785889455
Category :
Data
Languages :
Python
Concepts :
Data Analysis
Tools :
Jupyter

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Nov 30, 2016
Length: 238 pages
Edition : 1st
Language : English
ISBN-13 : 9781785889455
Category :
Data
Languages :
Python
Concepts :
Data Analysis
Tools :
Jupyter

Packt Subscriptions

See our plans and pricing
Modal Close icon
$19.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
START FREE TRIAL
BUY NOW
$199.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts
START FREE TRIAL
BUY NOW
$279.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts
START FREE TRIAL
BUY NOW

Frequently bought together

Modern Python Cookbook
Modern Python Cookbook
Read more
Nov 2016 692 pages
Full star icon 2.7 (3)
eBook
eBook
  • eBook eBook $28.99
  • Paperback Paperback $35.99
$28.99 $41.99
$35.99 $51.99
Learning Jupyter
Learning Jupyter
Read more
Nov 2016 238 pages
Full star icon 1 (3)
eBook
eBook
  • eBook eBook $29.99
  • Paperback Paperback $54.99
$29.99 $43.99
$54.99
Jupyter for Data Science
Jupyter for Data Science
Read more
Oct 2017 242 pages
Full star icon 1 (2)
eBook
eBook
  • eBook eBook $24.99
  • Paperback Paperback $43.99
$24.99 $35.99
$43.99
Stars icon
Total $ 134.97 150.97 16.00 saved
Modern Python Cookbook
$35.99 $51.99
Learning Jupyter
$54.99
Jupyter for Data Science
$43.99
Total $ 134.97 150.97 16.00 saved Stars icon

Table of Contents

10 Chapters
1. Introduction to Jupyter Chevron down icon Chevron up icon
1. Introduction to Jupyter
First look at Jupyter
Installing Jupyter on Windows
Installing Jupyter on Mac
Notebook structure
Notebook workflow
Basic notebook operations
Security in Jupyter
Configuration options for Jupyter
Summary
2. Jupyter Python Scripting Chevron down icon Chevron up icon
2. Jupyter Python Scripting
Basic Python in Jupyter
Python data access in Jupyter
Python pandas in Jupyter
Python graphics in Jupyter
Python random numbers in Jupyter
Summary
3. Jupyter R Scripting Chevron down icon Chevron up icon
3. Jupyter R Scripting
Adding R scripting to your installation
Basic R in Jupyter
R dataset access
R visualizations in Jupyter
R cluster analysis
R forecasting
Summary
4. Jupyter Julia Scripting Chevron down icon Chevron up icon
4. Jupyter Julia Scripting
Adding Julia scripting to your installation
Basic Julia in Jupyter
Julia limitations in Jupyter
Standard Julia capabilities
Julia visualizations in Jupyter
Julia Vega plotting
Julia parallel processing
Julia control flow
Julia regular expressions
Julia unit testing
Summary
5. Jupyter JavaScript Coding Chevron down icon Chevron up icon
5. Jupyter JavaScript Coding
Adding JavaScript scripting to your installation
JavaScript Hello World Jupyter Notebook
Basic JavaScript in Jupyter
JavaScript limitations in Jupyter
Node.js d3 package
Node.js stats-analysis package
Node.js JSON handling
Node.js canvas package
Node.js plotly package
Node.js asynchronous threads
Node.js decision-tree package
Summary
6. Interactive Widgets Chevron down icon Chevron up icon
6. Interactive Widgets
Installing widgets
Widget basics
Interact widget
Interactive widget
Widgets
Summary
7. Sharing and Converting Jupyter Notebooks Chevron down icon Chevron up icon
7. Sharing and Converting Jupyter Notebooks
Sharing notebooks
Converting notebooks
Summary
8. Multiuser Jupyter Notebooks Chevron down icon Chevron up icon
8. Multiuser Jupyter Notebooks
Sample interactive notebook
JupyterHub
Docker
Summary
9. Jupyter Scala Chevron down icon Chevron up icon
9. Jupyter Scala
Installing the Scala kernel
Scala data access in Jupyter
Scala array operations
Scala random numbers in Jupyter
Scala closures
Scala higher-order functions
Scala pattern matching
Scala case classes
Scala immutability
Scala collections
Named arguments
Scala traits
Summary
10. Jupyter and Big Data Chevron down icon Chevron up icon
10. Jupyter and Big Data
Apache Spark
Our first Spark script
Spark word count
Sorted word count
Estimate Pi
Log file examination
Spark primes
Spark text file analysis
Spark - evaluating history data
Summary

Recommendations for you

Left arrow icon
Python Machine Learning By Example
Python Machine Learning By Example
Read more
Jul 2024 518 pages
Full star icon 4.9 (8)
eBook
eBook
  • eBook eBook $24.99
  • Paperback Paperback $31.99
$24.99 $36.99
$31.99 $45.99
Building AI Applications with OpenAI APIs
Building AI Applications with OpenAI APIs
Read more
Oct 2024 252 pages
eBook
eBook
  • eBook eBook $21.99
  • Paperback Paperback $39.99
$21.99 $31.99
$39.99
Unlocking Data with Generative AI and RAG
Unlocking Data with Generative AI and RAG
Read more
Sep 2024 346 pages
eBook
eBook
  • eBook eBook $21.99
  • Paperback Paperback $27.98
$21.99 $31.99
$27.98 $39.99
Building LLM Powered Applications
Building LLM Powered Applications
Read more
May 2024 342 pages
Full star icon 4.2 (22)
eBook
eBook
  • eBook eBook $27.98
  • Paperback Paperback $34.98
$27.98 $39.99
$34.98 $49.99
RAG-Driven Generative AI
RAG-Driven Generative AI
Read more
Sep 2024 334 pages
Full star icon 4.5 (13)
eBook
eBook
  • eBook eBook $24.99
  • Paperback Paperback $43.99
$24.99 $35.99
$43.99
Machine Learning with PyTorch and Scikit-Learn
Machine Learning with PyTorch and Scikit-Learn
Read more
Feb 2022 774 pages
Full star icon 4.4 (95)
eBook
eBook
  • eBook eBook $29.99
  • Paperback Paperback $54.99
$29.99 $43.99
$54.99
Python for Algorithmic Trading Cookbook
Python for Algorithmic Trading Cookbook
Read more
Aug 2024 404 pages
Full star icon 4.6 (15)
eBook
eBook
  • eBook eBook $32.99
  • Paperback Paperback $41.98
$32.99 $47.99
$41.98 $59.99
Microsoft Power BI - The Complete Masterclass [2023 EDITION]
Microsoft Power BI - The Complete Masterclass [2023 EDITION]
Read more
Jan 2023 14hrs 31mins
Video
Video
  • Video Video $109.99
$109.99
Principles of Data Science
Principles of Data Science
Read more
Jan 2024 326 pages
Full star icon 4.8 (4)
eBook
eBook
  • eBook eBook $21.99
  • Paperback Paperback $27.98
$21.99 $31.99
$27.98 $39.99
Mastering NLP from Foundations to LLMs
Mastering NLP from Foundations to LLMs
Read more
Apr 2024 340 pages
Full star icon 4.9 (24)
eBook
eBook
  • eBook eBook $29.99
  • Paperback Paperback $36.99
$29.99 $42.99
$36.99 $52.99
Right arrow icon

Customer reviews

Rating distribution
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
(3 Ratings)
5 star 0%
4 star 0%
3 star 0%
2 star 0%
1 star 100%
Drew Dec 04, 2018
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
There are things that could be useful theoretically. Starting with my first gripe - The book states that it is using Python 2. It is November, 2016 - and Python 2 is dead. I don't have a problem with using Python2, but I do have a problem with not identifying that you use Python 2. It just comes across as false advertising.Don't worry, that isn't my only gripe. There are a few things, like commands on how to use Jupyter that you may find useful, but a quick internet search may prove more useful. The word vomit continually shows little understanding of what is going on. That means this isn't even a language barrier, it is just plain bad. I included to screenshots. It shows commentary that conveys that he doesn't understand what is going on, while using built in datasets. I was using those datasets on day 1 of my exposure to the material. 'I understand that he doesn't understand why numbers don't add up to 100%. But he needs to follow it up with details on whether there is data actually missing (which represents an unaddressed category), whether there is an error in the math (like floating point error), or what is going on. As it is, I assume that this is his first exposure, and he just tells the readers that sometimes there are problems. Not that the writer will take any action to resolve them.The statistics one is a great expression of incompetence. If you are going to use a statistical methodology, at least understand statistics. The Standard Deviation won't drift a lot when rolling two six-sided dice. The theoretical odds of the sum are always between 2 and 12. The small domain limits the statistical data quite nicely. There are specific patterns which we don't need to go into, but needless to say, it makes the writer appear incompetent about his chosen content. I could read more, but why?
Amazon Verified review Amazon
Matt Mar 28, 2017
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Only Windows and Mac OS. No Linux. Not helpful.
Amazon Verified review Amazon
Axel Willy Jan 28, 2017
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Selbst für Einsteiger nicht zu gebrauchen. Ein paar Seiten Text kopiert aus Manpages, dazu sehr viele übergroße Screenshots. Informationsgehalt fast nicht vorhanden. Buch zurück geschickt.
Amazon Verified review Amazon

People who bought this also bought

Left arrow icon
Machine Learning Engineering with Python
Machine Learning Engineering with Python
Read more
Aug 2023 462 pages
Full star icon 4.6 (36)
eBook
eBook
  • eBook eBook $27.98
  • Paperback Paperback $49.99
$27.98 $39.99
$49.99
Deep Learning with TensorFlow and Keras – 3rd edition
Deep Learning with TensorFlow and Keras – 3rd edition
Read more
Oct 2022 698 pages
Full star icon 4.6 (45)
eBook
eBook
  • eBook eBook $27.98
  • Paperback Paperback $49.99
$27.98 $39.99
$49.99
Modern Generative AI with ChatGPT and OpenAI Models
Modern Generative AI with ChatGPT and OpenAI Models
Read more
May 2023 286 pages
Full star icon 4.2 (34)
eBook
eBook
  • eBook eBook $27.98
  • Paperback Paperback $49.99
$27.98 $39.99
$49.99
Generative AI with LangChain
Generative AI with LangChain
Read more
Dec 2023 368 pages
Full star icon 4 (34)
eBook
eBook
  • eBook eBook $27.98
  • Paperback Paperback $49.99
$27.98 $39.99
$49.99
Causal Inference and Discovery in Python
Causal Inference and Discovery in Python
Read more
May 2023 456 pages
Full star icon 4.5 (49)
eBook
eBook
  • eBook eBook $21.99
  • Paperback Paperback $27.98
$21.99 $31.99
$27.98 $39.99
Right arrow icon

About the author

Profile icon Toomey
Toomey
Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
Read more
See other products by Toomey
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.