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

9.1 The for statement

The primary aim of the for statement is to traverse a list, that is, to apply the same sequence of commands to each element of a given list:

for s in ['a', 'b', 'c']:
    print(s) # a b c

In this example, the loop variables, is successively assigned to one element of the list. Notice that the loop variable is available after the loop has terminated. This may sometimes be useful; see, for instance, the example in Section 9.2: Controlling the flow inside the loop.

One of the most frequent uses of a for loop is to repeat, that is, to apply the same sequence of commands to each element of a given list: a given task a defined number of times, using the function range, see Section 1.3.1Lists.

for iteration in range(n): # repeat the following code n times
    ...

If the purpose of a loop is to go through a list, many languages (including Python) offer the following pattern:

for...