Book Image

SciPy Recipes

By : V Kishore Ayyadevara, Ruben Oliva Ramos
Book Image

SciPy Recipes

By: V Kishore Ayyadevara, Ruben Oliva Ramos

Overview of this book

With the SciPy Stack, you get the power to effectively process, manipulate, and visualize your data using the popular Python language. Utilizing SciPy correctly can sometimes be a very tricky proposition. This book provides the right techniques so you can use SciPy to perform different data science tasks with ease. This book includes hands-on recipes for using the different components of the SciPy Stack such as NumPy, SciPy, matplotlib, and pandas, among others. You will use these libraries to solve real-world problems in linear algebra, numerical analysis, data visualization, and much more. The recipes included in the book will ensure you get a practical understanding not only of how a particular feature in SciPy Stack works, but also of its application to real-world problems. The independent nature of the recipes also ensure that you can pick up any one and learn about a particular feature of SciPy without reading through the other recipes, thus making the book a very handy and useful guide.
Table of Contents (11 chapters)

Creating NumPy arrays

There are several ways to create objects of ndarray type. The recipes in this chapter provide a comprehensive list of the possibilities.

How to do it…

Let's move on to learn how an array can be created from a list.

Creating an array from a list

To create an array from an explicit list, use the following code:

x = np.array([2, 3.5, 5.2, 7.3])

This will assign to x the following array object:

array([ 2. , 3.5, -1. , 7.3, 0. ])

Notice that integer array entries are converted to floating point values. NumPy arrays are homogeneous, that is...