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

Time for action – determining future value


The future value gives the value of a financial instrument at a future date, based on certain assumptions. The future value depends on four parameters—the interest rate, the number of periods, a periodic payment, and the present value. In this tutorial, let's take an interest rate of three percent, quarterly payments of 10 for 5 years and present value of 1,000.

Call the fv function with the appropriate values to calculate the future value.

print "Future value", np.fv(0.03/4, 5 * 4, -10, -1000)

The future value is as follows:

Future value 1376.09633204

This corresponds with saving for 10 years, with quarterly additional savings of 10 at an interest rate of three percent. If we vary the number of years and if we save and keep the other parameters constant, we will get following plot:

What just happened?

We calculated the future value using the NumPy fv function starting with a present value of 1,000; interest rate of three percent; and quarterly payments...