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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 FREE CHAPTER

2. Beginning with NumPy Fundamentals

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

Exponential Moving Average

The Exponential Moving Average (EMA) is a popular alternative to the SMA. This method uses exponentially decreasing weights. The weights for points in the past decrease exponentially but never reach zero. We will learn about the exp() and linspace() functions while calculating the weights.

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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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