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Scientific Computing with Python

Scientific Computing with Python

By : Führer, Claus Fuhrer, Solem, Verdier
4.5 (15)
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Scientific Computing with Python

Scientific Computing with Python

4.5 (15)
By: Führer, Claus Fuhrer, Solem, 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)
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20
About Packt
22
References

3.5 Sets

The last container object we introduce in this section is defined by the data type set

Sets are containers that share properties and operations with sets in mathematics. A mathematical set is a collection of distinct objects. Like in mathematics, in Python the elements of a set are also listed within a pair of braces.

Here are some mathematical set expressions:

And here are their Python counterparts:

A = {1,2,3,4}
B = {5}
C = A.union(B)   # returns{1,2,3,4,5}
D = A.intersection(C)   # returns {1,2,3,4}
E = C.difference(A)   # returns {5}
5 in C   # returns True

Sets contain an element only once, corresponding to the aforementioned definition:

A = {1,2,3,3,3}
B = {1,2,3}
A == B # returns True

Moreover, a set is unordered; that is, the order of the elements in the set is not defined:

A = {1,2,3}
B = {1,3,2}
A == B # returns True

Sets in Python can contain all kinds of immutable objects, that is, numeric objects, strings...

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