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! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
NumPy Essentials
NumPy Essentials

NumPy Essentials: Boost your scientific and analytic capabilities in no time at all by discovering how to build real-world applications with NumPy

Arrow left icon
Profile Icon Jaidev Deshpande Profile Icon Chin Profile Icon Tanmay Dutta Profile Icon Shane Holloway
Arrow right icon
$32.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3 (3 Ratings)
Paperback Apr 2016 156 pages 1st Edition
eBook
$23.39 $25.99
Paperback
$32.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Jaidev Deshpande Profile Icon Chin Profile Icon Tanmay Dutta Profile Icon Shane Holloway
Arrow right icon
$32.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3 (3 Ratings)
Paperback Apr 2016 156 pages 1st Edition
eBook
$23.39 $25.99
Paperback
$32.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$23.39 $25.99
Paperback
$32.99
Subscription
Free Trial
Renews at $19.99p/m

What do you get with Print?

Product feature icon Instant access to your digital copy whilst your Print order is Shipped
Product feature icon Paperback book shipped to your preferred address
Product feature icon Redeem a companion digital copy on all Print orders
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
Modal Close icon
Payment Processing...
tick Completed

Shipping Address

Billing Address

Shipping Methods
Table of content icon View table of contents Preview book icon Preview Book

NumPy Essentials

Chapter 2. The NumPy ndarray Object

Array-oriented computing is the very heart of computational sciences. It is something that most Python programmers are not accustomed to. Though list or dictionary comprehension is relative to an array and sometimes used similarly to an array, there is a huge difference between a list/dictionary and an array in terms of performance and manipulation. This chapter introduces a basic array object in NumPy. It covers the information that can be gleaned from the intrinsic characteristics of NumPy arrays without performing any external operations on the array.

The topics that will be covered in the chapter are as follows:

  • numpy.ndarray and how to use it-basic array-oriented computing
  • Performance of numpy.ndarray-memory access, storage, and retrieval
  • Indexing, slicing, views, and copies
  • Array data types

Getting started with numpy.ndarray

In this section, we will go over some of the internals of numpy ndarray, including its structure and behavior. Let's start. Type in the following statements in the IPython prompt:

In [1]: import numpy as np 
 
In [2]: x = np.array([[1,2,3],[2,3,4]]) 
 
In [3]: print(x)

NumPy shares the names of its functions with functions in other modules, such as the math module in the Python standard library. Using imports like the following there is not recommended:

from numpy import * 

As it may overwrite many functions that are already in the global namespace, which is not recommended. This may lead to unexpected behavior from your code and may introduce very subtle bugs in it . This may also create conflicts in the code itself, (example numPy has any and will cause conflicts with the system any keyword) and may cause confusion when reviewing or debugging a piece of code. Therefore, it is important and recommended to always follow the import numPy...

Array indexing and slicing

NumPy provides powerful indexing capabilities for arrays. Indexing capabilities in NumPy became so popular that many of them were added back to Python.

Indexing NumPy arrays, in many ways, is very similar to indexing lists or tuples. There are some differences, which will become apparent as we proceed. To start with, let's create an array that has 100 x 100 dimensions:

In [9]: x = np.random.random((100, 100)) 

Simple integer indexing works by typing indices within a pair of square brackets and placing this next to the array variable. This is a widely used Python construct. Any object that has a __getitem__ method will respond to such indexing. Thus, to access the element in the 42nd row and 87th column, just type this:

In [10]: y = x[42, 87] 

Like lists and other Python sequences, the use of a colon to index a range of values is also supported. The following statement will print the k th row of the x matrix.

In [11]: print(x[k, :]) 

The colon can be thought of...

Memory layout of ndarray

A particularly interesting attribute of the ndarray object is flags. Type the following code:

In [12]: x.flags 

It should produce something like this:

Out[12]: 
  C_CONTIGUOUS : True 
  F_CONTIGUOUS : False 
  OWNDATA : True 
  WRITEABLE : True 
  ALIGNED : True 
  UPDATEIFCOPY : False 

The flags attribute holds information about the memory layout of the array. The C_CONTIGUOUS field in the output indicates whether the array was a C-style array. This means that the indexing of this array is done like a C array. This is also called row-major indexing in the case of 2D arrays. This means that, when moving through the array, the row index is incremented first, and then the column index is incremented. In the case of a multidimensional C-style array, the last dimension is incremented first, followed by the last but one, and so on.

Similarly, the F_CONTIGUOUS attribute indicates whether the array is a Fortran-style array. Such an array is said to have column-major indexing...

Views and copies

There are primarily two ways of accessing data by slicing and indexing. They are called copies and views: you can either access elements directly from an array, or create a copy of the array that contains only the accessed elements. Since a view is a reference of the original array (in Python, all variables are references), modifying a view modifies the original array too. This is not true for copies.

The may_share_memory function in NumPy miscellaneous routines can be used to determine whether two arrays are copies or views of each other. While this method does the job in most cases, it is not always reliable, since it uses heuristics. It may return incorrect results too. For introductory purposes, however, we shall take it for granted.

Generally, slicing an array creates a view and indexing it creates a copy. Let us study these differences through a few code snippets. First, let's create a random 100x10 array.

In [21]: x = np.random.rand(100,10) 

Now, let us extract...

Getting started with numpy.ndarray


In this section, we will go over some of the internals of numpy ndarray, including its structure and behavior. Let's start. Type in the following statements in the IPython prompt:

In [1]: import numpy as np 
 
In [2]: x = np.array([[1,2,3],[2,3,4]]) 
 
In [3]: print(x)

NumPy shares the names of its functions with functions in other modules, such as the math module in the Python standard library. Using imports like the following there is not recommended:

from numpy import * 

As it may overwrite many functions that are already in the global namespace, which is not recommended. This may lead to unexpected behavior from your code and may introduce very subtle bugs in it . This may also create conflicts in the code itself, (example numPy has any and will cause conflicts with the system any keyword) and may cause confusion when reviewing or debugging a piece of code. Therefore, it is important and recommended to always follow the import...

Array indexing and slicing


NumPy provides powerful indexing capabilities for arrays. Indexing capabilities in NumPy became so popular that many of them were added back to Python.

Indexing NumPy arrays, in many ways, is very similar to indexing lists or tuples. There are some differences, which will become apparent as we proceed. To start with, let's create an array that has 100 x 100 dimensions:

In [9]: x = np.random.random((100, 100)) 

Simple integer indexing works by typing indices within a pair of square brackets and placing this next to the array variable. This is a widely used Python construct. Any object that has a __getitem__ method will respond to such indexing. Thus, to access the element in the 42nd row and 87th column, just type this:

In [10]: y = x[42, 87] 

Like lists and other Python sequences, the use of a colon to index a range of values is also supported. The following statement will print the k th row of the x matrix.

In [11]: print(x[k, :]) 

The colon can be...

Memory layout of ndarray


A particularly interesting attribute of the ndarray object is flags. Type the following code:

In [12]: x.flags 

It should produce something like this:

Out[12]: 
  C_CONTIGUOUS : True 
  F_CONTIGUOUS : False 
  OWNDATA : True 
  WRITEABLE : True 
  ALIGNED : True 
  UPDATEIFCOPY : False 

The flags attribute holds information about the memory layout of the array. The C_CONTIGUOUS field in the output indicates whether the array was a C-style array. This means that the indexing of this array is done like a C array. This is also called row-major indexing in the case of 2D arrays. This means that, when moving through the array, the row index is incremented first, and then the column index is incremented. In the case of a multidimensional C-style array, the last dimension is incremented first, followed by the last but one, and so on.

Similarly, the F_CONTIGUOUS attribute indicates whether the array is a Fortran-style array. Such an array...

Left arrow icon Right arrow icon

Key benefits

  • Optimize your Python scripts with powerful NumPy modules
  • Explore the vast opportunities to build outstanding scientific/ analytical modules by yourself
  • Packed with rich examples to help you master NumPy arrays and universal functions

Description

In today’s world of science and technology, it’s all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy gives you both the speed and high productivity you need. This book will walk you through NumPy using clear, step-by-step examples and just the right amount of theory. We will guide you through wider applications of NumPy in scientific computing and will then focus on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier Transform; solving linear systems of equations, interpolation, extrapolation, regression, and curve fitting; and evaluating integrals and derivatives. We will also introduce you to using Cython with NumPy arrays and writing extension modules for NumPy code using the C API. This book will give you exposure to the vast NumPy library and help you build efficient, high-speed programs using a wide range of mathematical features.

Who is this book for?

If you are an experienced Python developer who intends to drive your numerical and scientific applications with NumPy, this book is for you. Prior experience or knowledge of working with the Python language is required.

What you will learn

  • * Manipulate the key attributes and universal functions of NumPy
  • * Utilize matrix and mathematical computation using linear algebra modules
  • * Implement regression and curve fitting for models
  • * Perform time frequency / spectral density analysis using the Fourier Transform modules
  • * Collate with the distutils and setuptools modules used by other Python libraries
  • * Establish Cython with NumPy arrays
  • * Write extension modules for NumPy code using the C API
  • * Build sophisticated data structures using NumPy array with libraries such as Panda and Scikits
Estimated delivery fee Deliver to United States

Economy delivery 10 - 13 business days

Free $6.95

Premium delivery 6 - 9 business days

$21.95
(Includes tracking information)

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 28, 2016
Length: 156 pages
Edition : 1st
Language : English
ISBN-13 : 9781784393670
Category :
Languages :
Concepts :
Tools :

What do you get with Print?

Product feature icon Instant access to your digital copy whilst your Print order is Shipped
Product feature icon Paperback book shipped to your preferred address
Product feature icon Redeem a companion digital copy on all Print orders
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
Modal Close icon
Payment Processing...
tick Completed

Shipping Address

Billing Address

Shipping Methods
Estimated delivery fee Deliver to United States

Economy delivery 10 - 13 business days

Free $6.95

Premium delivery 6 - 9 business days

$21.95
(Includes tracking information)

Product Details

Publication date : Apr 28, 2016
Length: 156 pages
Edition : 1st
Language : English
ISBN-13 : 9781784393670
Category :
Languages :
Concepts :
Tools :

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
$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
$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

Frequently bought together


Stars icon
Total $ 126.97
Practical Data Analysis Cookbook
$54.99
Getting Started with Python Data Analysis
$38.99
NumPy Essentials
$32.99
Total $ 126.97 Stars icon

Table of Contents

10 Chapters
1. An Introduction to NumPy Chevron down icon Chevron up icon
2. The NumPy ndarray Object Chevron down icon Chevron up icon
3. Using NumPy Arrays Chevron down icon Chevron up icon
4. NumPy Core and Libs Submodules Chevron down icon Chevron up icon
5. Linear Algebra in NumPy Chevron down icon Chevron up icon
6. Fourier Analysis in NumPy Chevron down icon Chevron up icon
7. Building and Distributing NumPy Code Chevron down icon Chevron up icon
8. Speeding Up NumPy with Cython Chevron down icon Chevron up icon
9. Introduction to the NumPy C-API Chevron down icon Chevron up icon
10. Further Reading Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3
(3 Ratings)
5 star 33.3%
4 star 0%
3 star 33.3%
2 star 33.3%
1 star 0%
ABHIJIT Feb 28, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very GOOD book for scientific programmers.Requires some amount of background in mathematics .
Amazon Verified review Amazon
Salah Sep 27, 2021
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
I was surprised that there's no image processing or using numpy with pictures ,this book is very basic .
Amazon Verified review Amazon
A. Priest Feb 25, 2018
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
This book contains numerous typos, omissions, and some of the stuff in it either doesn't work outright or are obsolete. I read every chapter except the final one, and although I learned a lot from the stuff that do work, and learned a lot from trying to make the things that don't work, finally work, I can't honestly give this book more than 2 stars.Here are some examples of typos:Pg 121, PyMethodDefApi_methods is really PyMethodDef Api_methods. I thought the data type is missing, but couldn't figure out which part is the variable name and which part is the type. This is by no means the only mistake of its kind in this book. There are many, and you must figure out where to insert the spaces to make the codes work. If you're a newbie and want to type along and run the codes as you go, which is pretty much how everyone learns Python from the beginning, you'll spend a lot of time doing this.The is a part of the book that refers to colored graphs, but this book is black and white. I don't remember which part, but I was disappointed the editor didn't correct that.If you want to build a C API, Py_InitModule3( ) is no longer supported. (My C compiler flagged it as a warning and I looked it up.) Python 3+ uses PyModuleDef(). This book was published in 2016, but Python 3 came out in 2008.You'd find many typos, grammatical mistakes and codes that don't work along the way. It's just frustrating to read this book if you actually repeat all the exercises.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is the digital copy I get with my Print order? Chevron down icon Chevron up icon

When you buy any Print edition of our Books, you can redeem (for free) the eBook edition of the Print Book you’ve purchased. This gives you instant access to your book when you make an order via PDF, EPUB or our online Reader experience.

What is the delivery time and cost of print book? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
What is custom duty/charge? Chevron down icon Chevron up icon

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order? Chevron down icon Chevron up icon

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges? Chevron down icon Chevron up icon

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

  • If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
  • Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.
How can I cancel my order? Chevron down icon Chevron up icon

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy? Chevron down icon Chevron up icon

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

  1. If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
  2. Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
  3. You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
  4. Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
  5. If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
  6. Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged? Chevron down icon Chevron up icon

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use? Chevron down icon Chevron up icon

You can pay with the following card types:

  1. Visa Debit
  2. Visa Credit
  3. MasterCard
  4. PayPal
What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
Modal Close icon
Modal Close icon