Book Image

NumPy Beginner's Guide - Second Edition

By : Ivan Idris
Book Image

NumPy Beginner's Guide - Second Edition

By: Ivan Idris

Overview of this book

NumPy is an extension to, and the fundamental package for scientific computing with Python. In today's world of science and technology, it is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy Beginner's Guide will teach you about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, is free and open source. Write readable, efficient, and fast code, which is as close to the language of mathematics as is currently possible with the cutting edge open source NumPy software library. Learn all the ins and outs of NumPy that requires you to know basic Python only. Save thousands of dollars on expensive software, while keeping all the flexibility and power of your favourite programming language.You will learn about installing and using NumPy and related concepts. At the end of the book we will explore some related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. Through examples, you will also learn about plotting with Matplotlib and the related SciPy project. NumPy Beginner's Guide will help you be productive with NumPy and have you writing clean and fast code in no time at all.
Table of Contents (19 chapters)
Numpy Beginner's Guide Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


This chapter informed us about a great number of common NumPy functions. We read a file with loadtxt and wrote to a file with savetxt. We made an identity matrix with the eye function. We read a CSV file containing stock quotes with the loadtxt function. The NumPy average and mean functions allow one to calculate the weighted average and arithmetic mean of a data set.

A few common statistics functions were also mentioned – first, the min and max functions that we used to determine the range of the stock prices; second, the median function that gives the median of a data set; and finally, the std and var functions that return the standard deviation and variance of a set of numbers.

We calculated the simple stock returns with the diff function that returns back the differences between sequential elements. The log function computes the natural logarithms of array elements.

By default, loadtxt tries to convert all data into floats. The loadtxt function has a special parameter for this purpose...