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Practical Programming, 3e
Classroom-tested by tens of thousands of students, this new edition of the bestselling intro to programming book is for anyone who wants to understand computer science. Learn about design, algorithms, testing, and debugging. Discover the fundamentals of programming with Python 3.6--a language that's used in millions of devices. Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.6. No programming experience required! Incremental examples show you the steps and missteps that happen while developing programs, so you know what to expect when you tackle a problem on your own. Inspired by "How to Design Programs" (HtDP), discover a five-step recipe for designing functions, which helps you learn the concepts--and becomes an integral part of writing programs. In this detailed introduction to Python and to computer programming, find out exactly what happens when your programs are executed. Work with numbers, text, big data sets, and files using real-world examples. Create and use your own data types. Make your programs reliable, work with databases, download data from the web automatically, and build user interfaces. As you use the fundamental programming tools in this book, you'll see how to document and organize your code so that you and other programmers can more easily read and understand it. This new edition takes advantage of Python 3.6's new features, including type annotations on parameters, return types and variable declarations, and changes to string formatting. Most importantly, you'll learn how to think like a professional programmer. What You Need: You'll need to download Python 3.6, available from https://python.org. With that download comes IDLE, the editor we use for writing and running Python programs. (If you use Linux, you may need to install Python 3.6 and IDLE separately.)
R 1,448.00
Numerical Methods in Chemical Engineering Using Python® and Simulink®
Numerical methods are vital to the practice of chemical engineering, allowing for the solution of real-world problems. Written in a concise and practical format, this textbook introduces readers to the numerical methods required in the discipline of chemical engineering and enables them to validate their solutions using both Python and Simulink.Introduces numerical methods, followed by the solution of linear and nonlinear algebraic equationsDeals with the numerical integration of a definite function and solves initial and boundary value ordinary differential equations with different ordersWeaves in examples of various numerical methods and validates solutions to each with Python and Simulink graphical programmingFeatures appendices on how to use Python and SimulinkAimed at advanced undergraduate and graduate chemical engineering students, as well as practicing chemical engineers, this textbook offers a guide to the use of two of the most widely used programs in the discipline.The textbook features numerous video lectures of applications and a solutions manual for qualifying instructors.
R 2,298.65
R 305.00
Python for Linguists
Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.
R 4,844.00
R 374.00
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.
R 3,287.32
R 580.00
Python for Engineers and Scientists
The text focuses on the basics of Python programming fundamentals and introduction to present-day applications in technology and the upcoming state-of-art trends in a comprehensive manner. The text is based on Python 3.x and it covers the fundamentals of Python with object-oriented concepts having numerous worked-out examples. It provides a learning tool for the students of beginner level as well as for researchers of advanced level. Each chapter contains additional examples that explain the usage of methods/functions discussed in the chapter. It provides numerous programming examples along with their outputs.The book:Includes programming tips to highlight the important concepts and help readers avoid common programming errorsProvides programming examples along with their outputs to ensure the correctness and help readers in mastering the art of writing efficient Python programsContains MCQs with their answers; conceptual questions and programming questions; and solutions to some selected programming questions, for every chapterDiscusses applications like time zone converter and password generators at the endCovers fundamental of Python up to object oriented concepts including regular expressionThe book offers a simple and lucid treatment of concepts supported with illustrations for easy understanding, provides numerous programming examples along with their outputs, and includes programming tips to highlight the important concepts. It will be a valuable resource for senior undergraduate, graduate students, and professionals in the fields of electrical engineering, electronics and communication engineering, and computer engineering.
R 2,826.71
R 275.00
Python for Experimental Psychologists
Python for Experimental Psychologists equips researchers who have no prior programming experience with the essential knowledge to independently script experiments and analyses in the programming language Python. The book offers an excellent introduction, whether you are an undergraduate, a PhD candidate, or an established researcher.This updated edition is on Python 3 (the most current version). It starts by teaching the fundamentals of programming in Python, and then offers several chapters on scripting experiments (displaying stimuli, obtaining and logging user input, precision timing, etc.) using the popular PsychoPy package. The remainder of the book is dedicated to data analysis, and includes chapters on reading/writing to text files, time series, eye tracking, data visualisation, and statistics.Access to a companion website enriches the learning experience with colour figures, example stimuli, datasets, scripts, and a portable Windows installation of Python. The book assumes no prior knowledge, and its informal and accessible tone helps readers with backgrounds in experimental psychology and cognitive neuroscience to quickly understand Python. It serves as a useful resource not only for researchers in these fields, but also for lecturers instructing on methodology and data analysis.Python for Experimental Psychologists demystifies programming complexities, and empowers researchers to proficiently conduct experiments and to analyse their results.
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R 550.00
Mathematical Methods in Data Science
Bridge the gap between theoretical concepts and their practical applications with this rigorous introduction to the mathematics underpinning data science. It covers essential topics in linear algebra, calculus and optimization, and probability and statistics, demonstrating their relevance in the context of data analysis. Key application topics include clustering, regression, classification, dimensionality reduction, network analysis, and neural networks. What sets this text apart is its focus on hands-on learning. Each chapter combines mathematical insights with practical examples, using Python to implement algorithms and solve problems. Self-assessment quizzes, warm-up exercises and theoretical problems foster both mathematical understanding and computational skills. Designed for advanced undergraduate students and beginning graduate students, this textbook serves as both an invitation to data science for mathematics majors and as a deeper excursion into mathematics for data science students.
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R 366.55
R 498.00
Pragmatic Python Programming
Explore the world of programming languages through Python and learn the building blocks of writing programs. This book covers Python 3.10, explaining it through six key concepts. Each chapter contains a real-world example with practical advice and a section on advanced concepts. You'll start by reviewing the concept of expressions and functions, which are two of the core building blocks of programming languages. You'll then move on to object-oriented concepts to help gain a practical understanding of Python, along with a chapter on control flow constructs. The book also takes a close look at sequences, explaining constructs and additional types, and wraps up with a chapter on modules, focusing on how to use and create packages. Whether you’re new to programming or already an experienced developer, upon finishing this book, you will have a solid understanding of Python's state-of-the-art development features.What You Will LearnStudy the six main concepts of the programming languagesLearn how to use programming language constructs through examplesReview the core Python language notations and concepts.Start using Python as a working languageWho This Book Is ForSoftware developers wanting to gain professional core Python knowledge quickly, and non-developers wanting to gain an understanding of programming concepts.
R 1,026.00
R 915.00
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R 1,334.91
R 863.00
Introduction to Numerical Programming
Makes Numerical Programming More Accessible to a Wider AudienceBearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity.Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-HowThe book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning. Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionalityContains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problemsAddresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysisThis text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.
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R 275.00
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Python Practice Lab
A guide to learning basic programming by writing fun, working programs that gradually become more complexThis classroom-tested, workbook-style text teaches basic programming by guiding readers to write Python programs that mimic interactive chatbots. Unlike textbooks with opaque examples explained in dry, monotonous code, Python Practice Lab engages readers immediately, with more than thirty motivating and hands-on examples. Readers learn by writing fun, working programs that gradually become more difficult as new concepts are introduced. Most exercises are open ended, promoting creativity in the process of learning. Along with coding practice, the book offers brief introductions to a range of other topics in computer science, including recommendation systems, computer vision, and big data, and relates these subjects to the programming concepts covered in the book. Python Practice Lab will be an essential resource for anyone who wants to learn to program, instructors teaching Python to beginners, and students who want to supplement their coursework by building complete and functional programs.Uses natural language and text strings rather than math as the main building blocks for learning about program structureRewrites code comprehension exercises in equivalent code with inclusive and approachable variables rather than terse, single-letter variablesChallenges readers to write a full program in each chapterPresents a selection of projects at the end of the book that integrates the concepts introduced in previous chapters
R 1,159.00
R 489.00
R 682.20
Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.Supplementary Material:Solutions Manual is available to instructors who adopt this textbook for their courses. Please contact sales@wspc.com.
R 2,125.00
R 763.00
R 1,099.00
Learn Python Programming
Learn the fundamentals of Python (3.7) and how to apply it to data science, programming, and web development. Fully updated to include hands-on tutorials and projects.Key FeaturesLearn the fundamentals of Python programming with interactive projectsApply Python to data science with tools such as IPython and JupyterUtilize Python for web development and build a real-world app using DjangoBook DescriptionLearn Python Programming is a quick, thorough, and practical introduction to Python - an extremely flexible and powerful programming language that can be applied to many disciplines. Unlike other books, it doesn't bore you with elaborate explanations of the basics but gets you up-and-running, using the language. You will begin by learning the fundamentals of Python so that you have a rock-solid foundation to build upon. You will explore the foundations of Python programming and learn how Python can be manipulated to achieve results. Explore different programming paradigms and find the best approach to a situation; understand how to carry out performance optimization and effective debugging; control the flow of a program; and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens. Learn Python Programming will give you a thorough understanding of the Python language. You'll learn how to write programs, build websites, and work with data by harnessing Python's renowned data science libraries. Filled with real-world examples and projects, the book covers various types of applications, and concludes by building real-world projects based on the concepts you have learned.What you will learnGet Python up and running on Windows, Mac, and LinuxExplore fundamental concepts of coding using data structures and control flowWrite elegant, reusable, and efficient code in any situationUnderstand when to use the functional or OOP approachCover the basics of security and concurrent/asynchronous programmingCreate bulletproof, reliable software by writing testsBuild a simple website in DjangoFetch, clean, and manipulate dataWho this book is forLearn Python Programming is for individuals with relatively little experience in coding or Python. It's also ideal for aspiring programmers who need to write scripts or programs to accomplish tasks. The book shows you how to create a full-fledged application.
R 1,498.00
