Description

Book Synopsis

Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and âœbottom up,â which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.

Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.

Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.

All the major Python libraries for science and e

Introduction to Python for Science and

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Order before 4pm today for delivery by Fri 9 Jan 2026.

A Paperback by David J. Pine

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    View other formats and editions of Introduction to Python for Science and by David J. Pine

    Publisher: CRC Press
    Publication Date: 9/23/2024
    ISBN13: 9781032673905, 978-1032673905
    ISBN10: 1032673907

    Description

    Book Synopsis

    Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and âœbottom up,â which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.

    Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.

    Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.

    All the major Python libraries for science and e

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