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Numpy Beginner's Guide (Update)

You're reading from Numpy Beginner's Guide (Update) Build efficient, high-speed programs using the high-performance NumPy mathematical library

Product type Paperback

Published in Jun 2015

Publisher

ISBN-13 9781785281969

Length 348 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Author (1):

Ivan Idris

View More author details

Table of Contents (16) Chapters

Preface

1. NumPy Quick Start

2. Beginning with NumPy Fundamentals FREE CHAPTER

3. Getting Familiar with Commonly Used Functions

4. Convenience Functions for Your Convenience

5. Working with Matrices and ufuncs

6. Moving Further with NumPy Modules

7. Peeking into Special Routines

8. Assuring Quality with Testing

9. Plotting with matplotlib

10. When NumPy Is Not Enough – SciPy and Beyond

11. Playing with Pygame

A. Pop Quiz Answers

B. Additional Online Resources

C. NumPy Functions' References

Index

Fancy indexing

The at() method was added in NumPy 1.8. This method allows fancy indexing in-place. Fancy indexing is indexing that does not involve integers or slices, which is normal indexing. In-place means that the array we operate on will be modified.

The signature for the at() method is ufunc.at(a, indices[, b]). The indices array specifies the elements to operate on. We need the b array only for universal functions with two operands. The following Time for action section gives examples of the at() method.

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Authors (1)

Ivan Idris

Ivan Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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