Handbook Of Mathematical Functions

Leverage this examplepacked comprehensive guide for all your Python computational needs Key FeaturesLearn the first steps within Python to highly specialized conceptsExplore examples and code snippets taken from typical programming situations within scientific computing.Delve into essential computer science concepts like iterating objectoriented programming testing and MPI presented in strong connection to applications within scientific computing.Book Description 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. Youll use pandas for basic data analysis to understand the modern needs of scientific computing and cover data module improvements and builtin features. Youll 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 youll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing. What you will learnUnderstand the building blocks of computational mathematics linear algebra and related Python objectsUse Matplotlib to create highquality figures and graphics to draw and visualize resultsApply objectoriented programming OOP to scientific computing in PythonDiscover how to use pandas to enter the world of data processingHandle exceptions for writing reliable and usable codeCover manual and automatic aspects of testing for scientific programmingGet to grips with parallel computing to increase computation speedWho this book is for This book is for students with a mathematical background university teachers designing modern courses in programming data scientists researchers developers and anyone who wants to perform scientific computation in Python.