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Esri Advanced Guide to Python in ArcGIS
Solving complex geospatial problems and delivering solutions has never been easier.Ready to take your Python knowledge to the next level? Esri Advanced Guide to Python in ArcGIS guides working GIS professionals through integrating Python with ArcGIS capabilities with increasing complexity through each consecutive chapter. Every chapter includes a project that teaches technical skills and problem-solving applicable to practical, job-focused assignments, including understanding client needs, performing market analytics, and managing ArcGIS Online organizations. Esri Advanced Guide to Python in ArcGIS uses step-by-step tutorials with an informal, conversational style of writing so you can easily follow and immediately apply the skills explained. Topics include: Designing effective GIS Python solutions ArcPy and ArcGIS API for Python basics Using imagery and GeoAI for advanced analysis Object-oriented programming Delivering work in various formats: Python scripts, Jupyter Notebook, ArcGIS Pro tools, geoprocessing services, and web applications Data engineering and manipulation techniques Managing ArcGIS Enterprise, ArcGIS Online, and other portal administration Perfect for intermediate to advanced programmers looking to enhance their GIS capabilities, Esri Advanced Guide to Python in ArcGIS will quickly help you become skilled at using Python for geospatial solutions and become more proficient and capable in your work.
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Object-oriented Python
Object-Oriented Python is an intuitive and thorough guide to mastering object-oriented programming from the ground up. You'll cover the basics of building classes and creating objects, and put theory into practice using the pygame package with clear examples that help visualize the object-oriented style. You'll explore the key concepts of object-oriented programming - encapsulation, polymorphism, and inheritance - and learn not just how to code with objects, but the absolute best practices for doing so. Finally, you'll bring it all together by building a complex video game, complete with full animations and sounds. The book covers two fully functional Python code packages that will speed up development of graphical user interface (GUI) programs in Python.
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Introduction to Python and Computer Programming
This book introduces Python programming language and fundamental concepts in algorithms and computing. Its target audience includes students and engineers with little or no background in programming, who need to master a practical programming language and learn the basic thinking in computer science/programming. The main contents come from lecture notes for engineering students from all disciplines, and has received high ratings. Its materials and ordering have been adjusted repeatedly according to classroom reception. Compared to alternative textbooks in the market, this book introduces the underlying Python implementation of number, string, list, tuple, dict, function, class, instance and module objects in a consistent and easy-to-understand way, making assignment, function definition, function call, mutability and binding environments understandable inside-out. By giving the abstraction of implementation mechanisms, this book builds a solid understanding of the Python programming language.
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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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Object-Oriented Approach to Problem Solving and Machine Learning with Python
This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.Start by solidifying your OOP foundation with clear explanations of core concepts such as use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.This book doesn’t stop at the basics. Explore how OOP empowers fields such as data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.Each chapter is designed for hands-on learning. You’ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.
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Python für Dummies Alles-in-einem-Band
Python programmieren lernen lohnt sich. Es ist eine moderne sich ständig weiterentwickelnde Programmiersprache. Dieses Buch hilft Ihnen, wenn Sie Python von der Pike auf lernen wollen, aber auch mehr als nur die Grundlagen verstehen wollen. Johannes Hofmeister erklärt Ihnen Grundlagen wie Syntax, Module und Basic-Funktionen und schreitet dann zu fort zu höheren Konzepten wie Funktionen und Objekte. Er zeigt Ihnen auch, wie Sie diese testen können, um fehlerfrei Software zu schreiben. Danach widmet sich der Autor Internettechnologien wie E-Mail, Apis und Browsing und erklärt Ihnen, wie Sie mit Django eine Webanwendung bauen. Sie erfahren, wie Sie mithilfe von Python komplexe Datensätze analysieren und zuletzt beweist Ihnen der Autor, wie vielseitig nutzbar Python ist.
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Programming with Python
Based on the latest version of the language, this book offers a self-contained, concise and coherent introduction to programming with Python. The book’s primary focus is on realistic case study applications of Python. Each practical example is accompanied by a brief explanation of the problem-terminology and concepts, followed by necessary program development in Python using its constructs, and simulated testing. Given the open and participatory nature of development, Python has a variety of incorporated data structures, which has made it difficult to present it in a coherent manner. Further, some advanced concepts (super, yield, generator, decorator, etc.) are not easy to explain. The book specially addresses these challenges; starting with a minimal subset of the core, it offers users a step-by-step guide to achieving proficiency.
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Learning Python with Raspberry Pi
The must-have companion guide to the Raspberry Pi User Guide! Raspberry Pi chose Python as its teaching language of choice to encourage a new generation of programmers to learn how to program. This approachable book serves as an ideal resource for anyone wanting to use Raspberry Pi to learn to program and helps you get started with the Python programming language. Aimed at first-time developers with no prior programming language assumed, this beginner book gets you up and running. Covers variables, loops, and functionsAddresses 3D graphics programmingWalks you through programming MinecraftZeroes in on Python for scripting Learning Python with Raspberry Pi proves itself to be a fantastic introduction to coding.
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Getting Started with Python
Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting informationKey FeaturesTurn your designs into working software by learning the Python syntaxWrite robust code with a solid understanding of Python data structuresUnderstand when to use the functional or the OOP approachBook DescriptionThis Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests.By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications.This Learning Path includes content from the following Packt products:Learn Python Programming - Second Edition by Fabrizio RomanoPython Data Structures and Algorithms by Benjamin BakaPython 3 Object-Oriented Programming by Dusty PhillipsWhat you will learnUse data structures and control flow to write codeUse functions to bundle together a sequence of instructionsImplement objects in Python by creating classes and defining methodsDesign public interfaces using abstraction, encapsulation and information hidingRaise, define, and manipulate exceptions using special error objectsCreate bulletproof and reliable software by writing unit testsLearn the common programming patterns and algorithms used in PythonWho this book is forIf you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.
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Learning Professional Python
Volume 2 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills.Learning Professional Python: Volume 2 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications
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Python Programming Fundamentals
This easy-to-follow and classroom-tested textbook guides the reader through the fundamentals of programming with Python, an accessible language which can be learned incrementally. Features: incudes numerous examples and practice exercises throughout the text, with additional exercises, solutions and review questions at the end of each chapter; highlights the patterns which frequently appear when writing programs, reinforcing the application of these patterns for problem-solving through practice exercises; introduces the use of a debugger tool to inspect a program, enabling students to discover for themselves how programs work and enhance their understanding; presents the Tkinter framework for building graphical user interface applications and event-driven programs; provides instructional videos and additional information for students, as well as support materials for instructors, at an associated website.
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Python for Teenagers
This book, which is designed for middle-school through college-aged students, will arm beginners with solid programming foundations they can carry throughout life. It uses fun and simple language (and programming examples) to teach the fundamentals needed to start the down path of becoming a programmer. Python is a highly flexible language, allowing developers to enter any number of technical fields and is a welcome addition to any resume. With its low learning curve, it makes a great introductory language, as new developers can take the coding fundamentals they learn in Python and apply them to any other language. The second edition builds upon the foundation of the first book, revising all the chapters where the language has changed, updating the commands, code, and examples to bring it up to date with the current version of Python. Since Python is the most popular programming language in the world and can be used in conjunction with other languages - across multiple platforms - it can increase the reader's ability to qualify for a wider range of jobs than other languages. Finally, Python is fun - something not every programming language can boast! What You Will LearnInstall and configure PythonGrasp basic software development principles and syntaxUnderstand the best practices for coding in PythonCreate applications and debug code Who This Book Is ForThe book’s target audience is primarily middle school to college aged students looking to learn how to program computers and develop software. Older individuals and computer programmers who know other languages and want to add Python to their repertoire can also benefit from the book.
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Python for Asset Management
The asset management industry is undergoing a paradigm shift toward automation, transparency, and data-driven decision-making. Traditional tools (Excel, Bloomberg) are being replaced by programmable, scalable solutions. Yet, most finance professionals lack accessible, practical training in applying Python to real portfolio problems.Python For Asset Management fills that gap. The book empowers non-programmers—portfolio managers, risk analysts, and students—to implement advanced models themselves. It responds to the growing demand for quantitative literacy in finance, especially in sustainable investing and smart beta strategies, areas of active research for both of the authors.Features31 hands-on Python exercises with real data and executable code.Complete GitHub repository (MIT License) with all scripts, data pipelines, and results.Step-by-step implementation of VaR (historical, parametric, Monte Carlo), bond immunization, and factor models.Real-world decision tools — e.g., build a bullet/barbell/ladder bond portfolio, run Brinson-Fachler attribution, or backtest smart beta vs. index.Immediate applicability — every exercise produces a deliverable (e.g., optimal weights, risk report, attribution table) ready for client meetings.Focus on practical asset management workflows, not just theory.
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