Book Image

Scientific Computing with Python - Second Edition

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python - Second Edition

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
20
About Packt
22
References

3.1 Lists

In this section, we introduce lists  the most frequently used container datatype in Python. With lists, we can refer to several, even totally different, Python objects together.

A list is, as the name hints, a list of objects of any kind:

L = ['a', 20.0, 5]
M = [3,['a', -3.0, 5]]

The first list in this example contains a string, a float, and an integer object. The second list in this example, M, contains another list as its second item.

The individual objects are enumerated by assigning each element an index. The first element in the list gets index . This zero-based indexing is frequently used in mathematical notation. Consider as an example for zero-based indexing the usual indexing of coefficients of a polynomial.

The index allows us to access the following objects from the two lists defined in the preceding example:

L[1] # returns 20.0
L[0] # returns 'a'
M[1] # returns ['a',-3.0,5]
M...