Book Image

Applying Math with Python

By : Sam Morley
Book Image

Applying Math with Python

By: Sam Morley

Overview of this book

Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain. The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python’s scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
Table of Contents (12 chapters)

Creating networks in Python

In order to solve the multitude of problems that can be expressed as network problems, we first need a way of creating networks in Python. For this, we will make use of the NetworkX package and the routines and classes it provides to create, manipulate, and analyze networks.

In this recipe, we'll create an object in Python that represents a network and add nodes and edges to this object.

Getting ready

As we mentioned in the Technical requirements section, we need the NetworkX package to be imported under the alias nx by using the following import statement:

import networkx as nx

How to do it...

Follow these steps to create a Python representation of a simple graph:

  1. We need to create a new Graphobject that will store the nodes and edges that constitute the graph:
G = nx.Graph()
  1. Next, we need to add the nodes for the network using the add_node...