Search results for "introduction to python programming"
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Programming with Python for Social Scientists
As data become ′big′, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of - and control over - how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including:the fundamentals of why and how to do your own programming in social scientific research,questions of ethics and research design,a clear, easy to follow ′how-to′ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more.Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis.
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Introduction to Python for Engineers and Scientists
Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation. In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you’ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts. What You'll Learn Understand the fundamentals of the Python programming languageApply Python to numerical computational programming projects in engineering and scienceDiscover the Pythonic way of lifeApply data types, operators, and arrays Carry out plotting for visualizationWork with functions and loops Who This Book Is For Engineers, scientists, researchers, and students who are new to Python. Some prior programming experience would be helpful but not required.
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Programming for Computations - Python
This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.
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Introduction to Python for Science and Engineering
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 “bottom up,” 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 engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.
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Python Programming Professional Made Easy
Python Programming Professional Made Easy 2nd Edition! Sam Key back at it again with his upgraded version of Python Going from beginner to professional? Want to skip the learning curve? Need the jargon removed so you can understand in your terms? From various programming languages to statements and Basic Operators Everything you need to know with functions and flow controls! Don't waste anytime and jump on board of Python! Start your programming right now!
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Introduction to Python for Kids
Want to create cool games and apps to impress your friends (or yourself), but not sure where to start? Or, have you tried your hand at programming, but got utterly bored after combing through hundreds of pages of dry text? Then you’ve come to the right place! This book is the perfect blend of education and fun for kids 8 years and above looking to learn the magic of Python, one of the easiest and most powerful programming languages around, all while solving fun puzzles and building your own projects on the way. Yes, there’ll be chapters on the fundamentals of Python, such as variables, numbers, strings, automation with conditions, loops and functions, objects, and files. But, early on in the book you’ll get started with Turtle, a Python package that was custom-made for kids like you. It lets you literally draw and animate on your computer! Every concept will be interspersed with a fun mini project with Turtle, so you’ll never get bored. Once you get the fundamentals down, you’ll dive right into Tkinter and Pygame, more fun Python packages (goodbye theory!) and you’ll learn all about creating apps and games like the ones you see and use every day (bouncing ball, temperature converter, calculator, rock-paper-scissors, and so much more!). There are also four capstone projects at the end of the book that convert everything you’ve learned so far into full-blown apps and games that you can show off to your friends, parents, and even teachers! You’ll be creating a snake game with Turtle, a tic tac toe game with Tkinter, a full-fledged paint app, again with Tkinter, and finally, a classic space shooters game with Pygame (the cherry on top). Every project chapter will be accompanied with the logic behind the game/app and an explanation on how you’ve arrived at the logic. You’ll develop strong problem solving skills that’ll help you create future projects on your own.There are also two chapters dedicated to just creating fun mini projects and puzzles, one of them placed in the middle of the book to give you a welcome break from all the learning. The book ends with an overview on web development with Python and ideas for more fun projects and puzzles you can solve on your own. Become the “most likely to succeed” kid in your grade while having the most fun getting there! What You'll LearnGain a gentle, but thorough introduction into the world of programming and PythonCreate programs and solve problems with core Python conceptsBuild mini projects and capstone projects (showcase worthy) with Turtle, Tkinter, and Pygame Develop programming skills while doing the puzzles and activities described in the book Who This Book Is ForKids 8 years and above.
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Modular Programming with Python
Introducing modular techniques for building sophisticated programs using PythonAbout This Book• The book would help you develop succinct, expressive programs using modular deign• The book would explain best practices and common idioms through carefully explained and structured examples• It will have broad appeal as far as target audience is concerned and there would be take away for all beginners to PythonWho This Book Is ForThis book is intended for beginner to intermediate level Python programmers who wish to learn how to use modules and packages within their programs. While readers must understand the basics of Python programming, no knowledge of modular programming techniques is required.What You Will Learn• Learn how to use modules and packages to organize your Python code• Understand how to use the import statement to load modules and packages into your program• Use common module patterns such as abstraction and encapsulation to write better programs• Discover how to create self-testing Python packages• Create reusable modules that other programmers can use• Learn how to use GitHub and the Python Package Index to share your code with other people• Make use of modules and packages that others have written• Use modular techniques to build robust systems that can handle complexity and changing requirements over timeIn DetailPython has evolved over the years and has become the primary choice of developers in various fields. The purpose of this book is to help readers develop readable, reliable, and maintainable programs in Python.Starting with an introduction to the concept of modules and packages, this book shows how you can use these building blocks to organize a complex program into logical parts and make sure those parts are working correctly together.Using clearly written, real-world examples, this book demonstrates how you can use modular techniques to build better programs. A number of common modular programming patterns are covered, including divide-and-conquer, abstraction, encapsulation, wrappers and extensibility. You will also learn how to test your modules and packages, how to prepare your code for sharing with other people, and how to publish your modules and packages on GitHub and the Python Package Index so that other people can use them. Finally, you will learn how to use modular design techniques to be a more effective programmer.Style and approachThis book will be simple and straightforward, focusing on imparting learning through a wide array of examples that the readers can put into use as they read through the book. They should not only be able to understand the way modules help in improving development, but they should also be able to improvise on their techniques of writing concise and effective code.
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Python Object-Oriented Programming
A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniquesKey FeaturesBuild an intuitive understanding of object-oriented design, from introductory to mature programsLearn the ins and outs of Python syntax, libraries, and best practicesExamine a machine-learning case study at the end of each chapterBook DescriptionObject-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python’s classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python’s exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs.What you will learnImplement objects in Python by creating classes and defining methodsExtend class functionality using inheritanceUse exceptions to handle unusual situations cleanlyUnderstand when to use object-oriented features, and more importantly, when not to use themDiscover several widely used design patterns and how they are implemented in PythonUncover the simplicity of unit and integration testing and understand why they are so importantLearn to statically type check your dynamic codeUnderstand concurrency with asyncio and how it speeds up programsWho this book is forIf you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary.
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Introduction to Python for Science and Engineering
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 “bottom up,” 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 engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.
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