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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    £49.99

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    Order before 4pm today for delivery by Mon 8 Jun 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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