This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.
This fast-paced introduction to Python moves from the basics to advanced concepts, enabling readers to gain proficiency quickly.
F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer ...
Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and ...
Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality Contains methods for function evaluation, solving ...
This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn.
Series in Computational Physics Steven A. Gottlieb and Rubin H. Landau, Series Editors Introduction to Python for Science and Engineering This guide offers a quick and incisive introduction to Python programming for anyone.
This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python.
The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing.
Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets.
In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn.