Introduction to Python for Engineers and Scientists

A quick, practical compact primer for learning and applying the Python programming language
Includes sample code with applications for engineers and scientists
Python is one of today's most popular, if not the most popular, programming languages with its flexibility and many applications

Autorentext
Sandeep Nagar, Ph.D. teaches and consults on the use of Python and other open source programming languages for for data science/analysis and numerical computing for engineering and science applications. In addition to teaching at universities, he frequently gives workshops covering open source software. Sandeep has a Ph.D. in Material Science from KTH, Sweden in May 2012. Prior to that degree, he obtained a M.Sc. in Physics with specialization in Electronics and Radio Physics and a B.Sc.B.Ed degrees in India.

Klappentext

Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.

In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you'll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts.

You will:

• Understand the fundamentals of the Python programming language
• Apply Python to numerical computational programming projects in engineering and science
• Discover the Pythonic way of life
• Apply data types, operators, and arraysCarry out plotting for visualization

• Work with functions and loops

  Inhalt

  1. Philosophy of Python.- 2. Introduction to the Basics of Python.- 3. Ipython.- 4. Data Types.- 5. Operators.- 6. Arrays.- 7. Plotting.- 8. Functions and Loops.- 9. Object-Oriented Programming.- 10. Numerical Computing Formalism.