Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Hands-On Data Analysis with NumPy and pandas
Hands-On Data Analysis with NumPy and pandas

Hands-On Data Analysis with NumPy and pandas: Implement Python packages from data manipulation to processing

Arrow left icon
Profile Icon Miller
Arrow right icon
NZ$26.99 NZ$38.99
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.9 (7 Ratings)
eBook Jun 2018 168 pages 1st Edition
eBook
NZ$26.99 NZ$38.99
Paperback
NZ$48.99
Subscription
Free Trial
Arrow left icon
Profile Icon Miller
Arrow right icon
NZ$26.99 NZ$38.99
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.9 (7 Ratings)
eBook Jun 2018 168 pages 1st Edition
eBook
NZ$26.99 NZ$38.99
Paperback
NZ$48.99
Subscription
Free Trial
eBook
NZ$26.99 NZ$38.99
Paperback
NZ$48.99
Subscription
Free Trial

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

Hands-On Data Analysis with NumPy and pandas

Diving into NumPY

By now you should have installed everything you need to use Python for data analysis. Let's now begin discussing NumPy, an important package for managing data and performing calculations. Without NumPy, there would not be any data analysis using Python, so understanding NumPy is critical. Our key objective in this chapter is learning to use the tools provided in NumPy.

In this chapter, the following topics will be covered:

  • NumPy data types
  • Creating arrays
  • Slicing arrays
  • Mathematics
  • Methods and functions

We begin by discussing data types, which are conceptually important when handling NumPy arrays. In this chapter, we will discuss NumPy data types controlled by dtype objects, which are the way NumPy stores and manages data. We'll also briefly introduce NumPy arrays called ndarray and discuss what they do.

...

NumPy arrays

Let's now talk about NumPy arrays, which are called ndarray. These are not the arrays you may encounter in C or C++. A better analog is matrices in MATLAB or R; that is, they behave like a mathematical object resembling a mathematical vector, matrix, or tensor. While they can store non-mathematical information such as strings, they exist mainly to manage and facilitate operations with data that is numeric in nature. ndarray are assigned a particular data type or dtype upon creation, and all current and future data in the array must be of that dtype. They also have more than one-dimension, referred to as axes.

A one-dimensional ndarray is a line of data; this would be a vector. A two-dimensional ndarray would be a square of data, effectively a matrix. A three-dimensional ndarray would be key book data, like a tensor. Any number of dimensions is permitted...

Special numeric values

In addition to dtype objects, NumPy introduces special numeric values: nan and inf. These can arise in mathematical computations. Not A Number (nan). It indicates that a value that should be numeric is, in fact, not defined mathematically. For example, 0/0 yields nan. Sometimes, nan is also used to signify missing information; for example, pandas uses this. inf indicates a quantity that is arbitrarily large, so in practice, it means larger than any number the computer can conceive of. -inf is also defined and it means arbitrarily small. This could occur if a numeric operation blows up, that is, grows rapidly without bounds.

Nothing is ever equal to nan; it makes no sense for something undefined to be equal to something else. You need to use the NumPy function isnan to identify nan. While the == sign does not work for nan, it does work for inf....

Creating NumPy arrays

Now that we have discussed NumPy data types and have been briefly introduced to NumPy arrays, let's talk about how we can create NumPy arrays. In this section, we will create NumPy arrays using various functions. There are functions that create what are known as empty ndarray; functions for creating ndarray filled with 0s, 1s, or random numbers; and functions for creating ndarray using data. We will discuss all of these, along with saving and loading NumPy arrays from disk. There are a few ways to create arrays. One way is to use the array function, where we give an iterable object or a list of iterable objects, from which an array will be generated.

We will do this using lists of lists, but these could be lists of tuples, tuples of tuples, or even other arrays. There are ways to automatically create arrays filled with data as well. For example...

Summary

In this chapter, we started by introducing NumPy data types. We then quickly moved on to discuss NumPy arrays, called ndarray objects, which are the main objects of interest in NumPy. We discussed how to create these arrays from programmer input, from other Python objects, from files, and even from functions. We proceeded to discuss how mathematical operations are performed on ndarray objects, from basic arithmetic to full-blown linear algebra.

In the next chapter, we will discuss some important topics: slicing ndarray objects arithmetic and linear algebra with arrays, and employing array methods and functions.

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Explore the tools you need to become a data analyst
  • Discover practical examples to help you grasp data processing concepts
  • Walk through hierarchical indexing and grouping for data analysis

Description

Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.

Who is this book for?

Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book.

What you will learn

  • Understand how to install and manage Anaconda
  • Read, sort, and map data using NumPy and pandas
  • Find out how to create and slice data arrays using NumPy
  • Discover how to subset your DataFrames using pandas
  • Handle missing data in a pandas DataFrame
  • Explore hierarchical indexing and plotting with pandas

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 29, 2018
Length: 168 pages
Edition : 1st
Language : English
ISBN-13 : 9781789534245
Category :
Languages :
Concepts :
Tools :

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 : Jun 29, 2018
Length: 168 pages
Edition : 1st
Language : English
ISBN-13 : 9781789534245
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 NZ$7 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 NZ$7 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total NZ$ 162.97
SciPy Recipes
NZ$56.99
Hands-On Data Analysis with NumPy and pandas
NZ$48.99
Mastering Numerical Computing with NumPy
NZ$56.99
Total NZ$ 162.97 Stars icon

Table of Contents

7 Chapters
Setting Up a Python Data Analysis Environment Chevron down icon Chevron up icon
Diving into NumPY Chevron down icon Chevron up icon
Operations on NumPy Arrays Chevron down icon Chevron up icon
pandas are Fun! What is pandas? Chevron down icon Chevron up icon
Arithmetic, Function Application, and Mapping with pandas Chevron down icon Chevron up icon
Managing, Indexing, and Plotting Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.9
(7 Ratings)
5 star 28.6%
4 star 14.3%
3 star 0%
2 star 28.6%
1 star 28.6%
Filter icon Filter
Top Reviews

Filter reviews by




Akshay Jan 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent book that gets down to the basics!
Subscriber review Packt
S. Sankara Subramanian Sep 10, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
no specific comments
Amazon Verified review Amazon
Amazon Customer Aug 27, 2018
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Would recommend this book to those with a background in data analysis and are untrained in using Python.Pros - This book delivers exactly what is written in the title, no more, no less. The writing style is introductory and there are plenty of examples. The book addresses how to clean data using Python which is mandatory when performing data analysis. Examples discussed in this book could be used to supplement references which are less practical.Cons - The editing uses incorrect fonts on words that refer to technical terms. For example, some Python functions in this book are type-font, but the editor frequently omits this formatting. Many screenshots include cursors. Some sections, such as the linear algebra section, explain how to implement code but do not explain the context or give references.
Amazon Verified review Amazon
BBCReview Sep 30, 2021
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
The books has good content on Numpy and Pandas, but you can't read the code snippets without a magnifying glass, or worse yet, zooming each one. Not the fault of the author, but it's darn hard to follow when it take 10 seconds to read each each snippet.
Amazon Verified review Amazon
Philip H Sep 15, 2018
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
The explanations are reasonable although the book could have been written much more concisely. The examples are written in tiny fonts
Amazon Verified review Amazon
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.