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Discover everything you need to know about Python to turn your passion of programming into a job you'll love. Fueled by fun and practical examples, this book gives high schoolers who want to learn an easy programming language ideas for how to leverage them in the workforce. Start with the basics and before you know it, you'll be building your own web sites, doing white-hat hacking, finding code bugs and errors, and creating games, including using Python to roll characters for RPGs. Every chapter is relaxed and informal, like learning with a cool teacher all the time.

In Coding with Python, you can talk with turtles, travel to South America, draw a flower, and create a caterpillar without paper, pencils, or paint. Easy-to-follow, step-by-step instructions will guide you through coding these fantastic projects. Once you've got the hang of it, there are different challenges you can choose to really test your coding skills and handy troubleshooting hints to help if you need them. With Ready, Set, Code!, you'll soon be ready for the world of coding.

\"Preface The book in your hands is the result of more than a decade of independent and collaborative effort by the two authors and their computer- music associates. Combining computers and music has a long and fruitful heritage. Moreover, the ideas which underpin the connection between calculating and composing date back centuries. In the 21st century, computers and music are more closely aligned than ever before. In particular, computers have become indispensable in music making, distribution, performance, and consumption. This book introduces important concepts and skills necessary to make music with computers. It interweaves computing pedagogy with musical concepts and creative activities. It does this while maintaining a natural, steady increase in computational skills that are always motivated by creative musical contexts. This book is mainly intended for introductory computer science courses and for courses in the intersection of computing and the arts. However, it is naturally suited for self-study. It assumes little musical and programming experience; it introduces topics and concepts as they arise through motivating, and hopefully inspiring examples. This book addresses two trends in computing education: (1) the growing use of the Python language for teaching introductory programming, and (2) the increasing infusion of computational thinking into liberal arts courses, especially interdisciplinary offerings in computing and the arts. It does so by presenting computer music topics in an accessible manner for our two main target audiences:\"-- Provided by publisher.

A one-stop guide to teach chemists how to use Python for coding and iterations in a hands-on and practical manner Key Features ? Understand the core Python functions and algorithms for the computation of chemical parameters. ? Learn how to use Cheminformatics modules to process and analyze elemental data and molecular structures. ? Get familiar with the algorithms for numerical and symbolic computations. Description Python is a versatile and powerful computer language without a steep learning curve. It can be deployed to simulate various physicochemical parameters or to analyze complex molecular, bio-molecular, and crystalline structures. The objective of this book is to give a gentle introduction to Python programming with relevant algorithms, iterations, and basic simulations from a chemist's perspective. This book outlines the fundamentals of Python coding through the built-in functions, libraries, and modules as well as with a few selected external packages for physical/materials/inorganic/analytical/organic/ nuclear chemistry in terms of numerical, symbolic, structural, and graphical data analysis using the default, Integrated Development and Learning Environment. You will also learn about the Structural Elucidation of organic molecules and inorganic complexes with specific Cheminformatics modules. In addition to this, the book covers chemical data analysis with Numpy and also includes topics such as SymPy and Matplotlib for Symbolic calculations and Plotting. By the end of the book, you will be able to use Python as a graphical tool or a calculator for numerical and symbolic computations in the interdisciplinary areas of chemistry. What you will learn ? To fetch elemental, nuclear, atomic or molecular data with list or dictionary functions. ? Understanding the algorithms for the computation of Thermodynamic, Electrochemical, Kinetics, Molecular and Spectral parameters. ? Stoichiometrical calculation of the reactant and product coefficients from Matrices. ? Symbolic computations with reference to Physical Chemistry. ? With Matplotlib package, interpretation and plotting of the analyzed data in the desired graphical format. ? With various cheminformatics modules, correlate the structure of complex and bulkier molecules. Who this book is for This book is for Chemists, Chemical Engineers, Material Scientists, Bio-chemists, Biotechnologists, and Physicists. Students of Chemistry, Chemical Engineering, Materials Chemistry, Biochemistry, Biotechnology, and Physics will find this book resourceful. Table of Contents 1. Understanding Python Functions for Chemistry 2. Computations in Chemistry with NumPy 3. Interpolation, Physico-chemical Constants, and Units with SciPy 4. SymPy for Symbolic Computations in Chemistry 5. Interactive Plotting of Physico-chemical Data with Matplotlib 6. Introduction to Cheminformatics with RDKit 7. ChemFormula for Atomic and Molecular Data 8. Chemlib for Physico-chemical Parameters 9. ChemPy for Computations in Chemistry 10. Mendeleev Package For Atomic and Ionic Data 11. Computations of Parameters of Electrolytes with PyEQL 12. STK Module for Molecular Structures

Python is a robust, procedural, object-oriented, and functional language. The features of the language make it valuable for web development, game development, business, and scientific programming. This book deals with problem-solving and programming in Python. It concentrates on the development of efficient algorithms, the syntax of the language, and the ability to design programs in order to solve problems. In addition to standard Python topics, the book has extensive coverage of NumPy, data visualization, and Matplotlib. Numerous types of exercises, including theoretical, programming, and multiple-choice, reinforce the concepts covered in each chapter.