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)

Querying and changing the shape of an array

Since we have learnt various ways to create an array, we can now definitely learn how to query and change the shape of an array.

How to do it...

The shape of an array is stored in the shape field of the ndarray object, as shown in the following example:

x = np.array([[1,2,3,4,5,6],[7,8,9,10,11,12]])
x.shape

The shape field of an ndarray object contains a tuple with the size of each of the dimensions of the array, so the preceding code will produce the following output:

(2, 6)

It is possible to assign a to the field shape, which has the effect of reshaping the array, as shown in the following example:

x.shape = (4,3)

This statement will change the array to the following:

array...