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)

Computing the probability mass function of a discrete random variable

A random variable is a variable whose value is unknown, or a variable for which the value changes over different iterations of the experiment.

For example, when we roll a die, the outcome of rolling the dice will vary over different iterations and hence the outcome becomes a random variable.

A random variable is discrete if the outcome of the random variable is limited to a few possible outcomes.

For example, the outcome of rolling a fair dice can only be 1, 2, 3, 4, 5, or 6; it cannot be a number beyond that. Thus, the outcome is limited to only a few possible values.

In the previous example, whenever a die is rolled, there is a probability associated with each outcome. For example, if a fair dice is rolled once, the probability that the outcome is 4 is 1/6, as all outcomes have an equal chance of being obtained...