A student's guide to python for physical modeling
Kinder, Jesse M., 1978-
A student's guide to python for physical modeling Jesse M. Kinder, Philip Nelson - Second ed. - 223 p. il. 25 cm
"Python is an open-source computer programming language that is popular in the sciences. This second edition of A Student's Guide to Python for Physical Modeling offers an up-to-date primer aimed to help students (without previous programming experience) form a enough of a foundation in the Python programming language to get started with physical modeling. Students will learn how to install a Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. The text is applicable to all fields of science, but focuses on the physical sciences. It can be used as a textbook to cover a 2-3 week introductory tutorial on Python within any course in the physical sciences, or it can be used for self-study by individuals wanting to quickly learn Python for use in their own research. Numerous code samples and exercises - with solutions-illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. ** 2nd Edition includes the following** - Retains the short, focused format that has been successful for the 1st edition. - Retains the focus on novice readers who need basic skills. - Retain the focus on the needs of physical-science students. - Updated to reflect changes in the Python language (current with Python 3.9) and common practice in plotting and numerical methods. - Updated to reflect changes in the Anaconda software distribution. - Concepts and instructions clarified throughout, based on classroom experience. - Reduced emphasis on the decreasingly popular Spyder platform. Increased coverage of the popular Jupyter Notebook platform. - Additional new appendix on command line tools and version control with Git. - Additional new material on symbolic calculations with SymPy. - Additional new material to introduce basic Python libraries for data science and machine learning (pandas, sklearn)"--
9780691219288 9780691223650
2021934834
Python (Lenguaje de programación)
QA76.73 .P98 / K56 2021
A student's guide to python for physical modeling Jesse M. Kinder, Philip Nelson - Second ed. - 223 p. il. 25 cm
"Python is an open-source computer programming language that is popular in the sciences. This second edition of A Student's Guide to Python for Physical Modeling offers an up-to-date primer aimed to help students (without previous programming experience) form a enough of a foundation in the Python programming language to get started with physical modeling. Students will learn how to install a Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. The text is applicable to all fields of science, but focuses on the physical sciences. It can be used as a textbook to cover a 2-3 week introductory tutorial on Python within any course in the physical sciences, or it can be used for self-study by individuals wanting to quickly learn Python for use in their own research. Numerous code samples and exercises - with solutions-illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. ** 2nd Edition includes the following** - Retains the short, focused format that has been successful for the 1st edition. - Retains the focus on novice readers who need basic skills. - Retain the focus on the needs of physical-science students. - Updated to reflect changes in the Python language (current with Python 3.9) and common practice in plotting and numerical methods. - Updated to reflect changes in the Anaconda software distribution. - Concepts and instructions clarified throughout, based on classroom experience. - Reduced emphasis on the decreasingly popular Spyder platform. Increased coverage of the popular Jupyter Notebook platform. - Additional new appendix on command line tools and version control with Git. - Additional new material on symbolic calculations with SymPy. - Additional new material to introduce basic Python libraries for data science and machine learning (pandas, sklearn)"--
9780691219288 9780691223650
2021934834
Python (Lenguaje de programación)
QA76.73 .P98 / K56 2021