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 values of inverse probabilities associated with a random variable

The inverse probability of a random variable is the inverse of the CDF associated with the distribution.

The percent point function (PPF) gives us the value of the continuous random variable that is associated with the percent value (quantile value).

How to do it...

In order to understand this better, let us consider the following:

  1. Import the relevant packages:
from scipy.stats import norm
  1. Extract the value associated with the 95% percentile (quantile) value:
norm.ppf(0.95)

The output of the preceding line of code is 1.6448536269514722.

  1. The inverse of the preceding output can be calculated as follows:
norm.cdf(1.6448)

The output of this is...