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Applied Math with Python
A step-by-step guide for using Python to transform abstract mathematical concepts into effective, on-the-ground scripts that solve real-world business problems Applied Math with Python: Solve Real-World Problems with Python-Based Solutions is a detailed, step-by-step guide for business professionals, analysts, and data scientists interested in using Python to perform crucial organizational tasks: optimizing inefficient supply chains, calculating probabilities, forecasting financial performance, mining customer data for new insights, and more. Author, researcher, and Assistant Professor of Finance at the University of North Florida, Blake Rayfield uses practical examples and hands-on exercises to explain how to combine concepts from optimization, probability, statistics, and other branches of mathematics with the Python language to solve difficult, common business problems. You’ll discover how marketing managers can use Python to create useful customer segments, how to model revenue growth, and how to allocate limited resources in a product launch or expansion. Inside the book: Modular, plug-and-play strategies for solving hard problems in Python in situations where a spreadsheet is inadequateInstructions for building effective, scalable Python scripts incorporating many of the most powerful Python libraries, including pandas, NumPy, matplotlib, seaborn, scikit-learn, and PlotlyStart-to-finish coverage for business professionals – from building a Python scripting environment on your local computer or in a cloud environment to designing, writing, testing, and running a functional script Perfect for entrepreneurs, analysts, managers, and professionals working in AI, data science, and finance, Applied Math with Python is an expert guide for transforming abstract mathematical concepts into useful, repeatable, scalable solutions you can put to work immediately in your team and in your organization.
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Hands-On Blockchain for Python Developers
Write popular DeFi and NFT smart contracts with Vyper, a Pythonic programming language, and integrate blockchain with real-world applications using Python Key FeaturesUse the world's easiest programming language to build web3 applicationsWrite common smart contracts like decentralized exchanges, NFT marketplaces, and lending applicationsUnlock deeper levels of insights with technologies relating to blockchain, such as IPFS and Layer 2Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionWe are living in the age of decentralized fi nance and NFTs. People swap tokens on Uniswap, borrow assets from Aave, send payments with stablecoins, trade art NFTs on OpenSea, and more. To build applications of this kind, you need to know how to write smart contracts.This comprehensive guide will help you explore all the features of Vyper, a programming language designed to write smart contracts. You’ll also explore the web3.py library. As you progress, you’ll learn how to connect to smart contracts, read values, and create transactions. To make sure your foundational knowledge is strong enough, the book guides you through Ape Framework, which can help you create decentralized exchanges, NFT marketplaces, voting applications, and more. Each project provides invaluable insights and hands-on experience, equipping you with the skills you need to build real-world blockchain solutions.By the end of this book, you’ll be well versed with writing common Web3 applications such as a decentralized exchange, an NFT marketplace, a voting application, and more.What you will learnUnderstand blockchain and smart contractsLearn how to write smart contracts with VyperExplore how to use the web3.py library and Ape FrameworkDiscover related technologies such as Layer 2 and IPFSGain a step-by-step guide to writing an automated market maker (AMM) decentralized exchange (DEX) smart contractBuild innovative, interactive, and token-gated Web3 NFT applicationsWho this book is forThis blockchain book is for developers interested in understanding blockchain and smart contracts. It is suitable for both technology enthusiasts looking to explore blockchain technology and programmers who aspire to become smart contract engineers. Basic knowledge of GNU/Linux and Python programming is mandatory to get started with this book.
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Python for Accounting and Finance
This book is a comprehensive guide to the application of Python in accounting, finance, and other business disciplines. This book is more than a Python tutorial; it is an integrative approach to using Python for practical research in these fields. The book begins with an introduction to Python and its key libraries. It then covers real-world applications of Python, covering data acquisition, cleaning, exploratory data analysis, visualization, and advanced topics like natural language processing, machine learning, predictive analytics, and deep learning. What sets this book apart is its unique blend of theoretical knowledge and real-world examples, supplemented with ready-to-use code. It doesn't stop at the syntax; it shows how to apply Python to tackle actual analytical problems. The book uses case studies to illustrate how Python can enhance traditional research methods in accounting and finance, not only allowing the reader to gain a firm understanding of Python programming but also equipping them with the skills to apply Python to accounting, finance, and broader business research. Whether you are a PhD student, a professor, an industry professional, or a financial researcher, this book provides the key to unlocking the full potential of Python in research.
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The Python Workshop
Learn the fundamentals of clean, effective Python coding and build the practical skills to tackle your own software development or data science projectsKey FeaturesBuild key Python skills with engaging development tasks and challenging activitiesImplement useful algorithms and write programs to solve real-world problemsApply Python in realistic data science projects and create simple machine learning modelsBook DescriptionHave you always wanted to learn Python, but never quite known how to start? More applications than we realize are being developed using Python because it is easy to learn, read, and write. You can now start learning the language quickly and effectively with the help of this interactive tutorial. The Python Workshop starts by showing you how to correctly apply Python syntax to write simple programs, and how to use appropriate Python structures to store and retrieve data. You'll see how to handle files, deal with errors, and use classes and methods to write concise, reusable, and efficient code. As you advance, you'll understand how to use the standard library, debug code to troubleshoot problems, and write unit tests to validate application behavior. You'll gain insights into using the pandas and NumPy libraries for analyzing data, and the graphical libraries of Matplotlib and Seaborn to create impactful data visualizations. By focusing on entry-level data science, you'll build your practical Python skills in a way that mirrors real-world development. Finally, you'll discover the key steps in building and using simple machine learning algorithms. By the end of this Python book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Python.What you will learnWrite clean and well-commented code that is easy to maintainAutomate essential day-to-day tasks with Python scriptsDebug logical errors and handle exceptions in your programsExplore data science fundamentals and create engaging visualizationsGet started with predictive machine learningKeep your development process bug-free with automated testingWho this book is forThis book is designed for anyone who is new to the Python programming language. Whether you're an aspiring software engineer or data scientist, or are just curious about learning how to code with Python, this book is for you. No prior programming experience is required.
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Intuitive Biostatistics with Python
Intuitive Biostatistics with Python is a comprehensive guide intended for a broad audience in the life sciences including laboratory scientists, students, technical staff, and physicians wishing to deepen their knowledge of data analysis. The goal of this book is to make biostatistics accessible and practical by integrating its concepts with Python, a powerful and easy-to-learn programming language. This dual approach enables life science professionals to better understand their own data, critically evaluate published work, and acquire highly sought-after computational skills.The choice of Python is deliberate, offering significant advantages over traditional point-and-click software. It ensures transparency and reproducibility through auditable code, offers unparalleled flexibility for custom analyses, and fosters deep computational thinking by revealing the mechanics of statistical tests. Moreover, Python is free, open source, and increasingly integrated into scientific and educational workflows, particularly with the use of artificial intelligence.This book offers original and practical explanations of fundamental statistical principles such as calculating P values and confidence intervals, bootstrapping, and simulation, using visualization to make abstract concepts tangible. Readers are encouraged to actively engage in learning through fully shared and well-documented code snippets, easily adaptable to their own research and publications. To reinforce learning, each chapter concludes with a cheat sheet summarizing the newly acquired functions and methods. The book also offers detailed, step-by-step demonstrations of how Python's statistical packages work, including the underlying mathematical equations. Ultimately, this book represents a commitment to improving scientific rigor and solving challenges such as reproducibility in the biomedical sciences.
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Python: Data Analytics and Visualization
Understand, evaluate, and visualize dataAbout This Book* Learn basic steps of data analysis and how to use Python and its packages* A step-by-step guide to predictive modeling including tips, tricks, and best practices* Effectively visualize a broad set of analyzed data and generate effective resultsWho This Book Is ForThis book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner.What You Will Learn* Get acquainted with NumPy and use arrays and array-oriented computing in data analysis* Process and analyze data using the time-series capabilities of Pandas* Understand the statistical and mathematical concepts behind predictive analytics algorithms* Data visualization with Matplotlib* Interactive plotting with NumPy, Scipy, and MKL functions* Build financial models using Monte-Carlo simulations* Create directed graphs and multi-graphs* Advanced visualization with D3In DetailYou will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn.After this, you will move on to a data analytics specialization-predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling.After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examplesThis Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Getting Started with Python Data Analysis, Phuong Vo.T
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Python for Software Design
A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.
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wxPython Application Development Cookbook
Over 80 step-by-step recipes to get you up to speed with building your own wxPython applicationsAbout This Book• This book empowers you to create rich cross-platform graphical user interfaces using Python• It helps you develop applications that can be deployed on Windows, OSX, and Linux• The recipes in the book involve real-world applications, giving you a first-hand experience of the practical scenariosWho This Book Is ForFor those who are familiar with programming in Python and want to start building applications with graphical user interfaces, this book will get you up and running quickly. A basic understanding of the Python programming language and object-oriented concepts are all that is needed.What You Will Learn• Create full featured user interfaces• Design and develop custom controls• Deploy and distribute wxPython applications to Windows, Macintosh OS X, Linux, and other UNIX-like environments• Handle and respond to application events• Manage and display data using grids• Interact with web services from your GUI• Use Paint events to draw custom displays• Support the display of user interfaces in multiple languagesIn DetailwxPython is a GUI toolkit for the Python programming language built on top of the cross-platform wxWidgets GUI libraries. wxPython provides a powerful set of tools that allow you to quickly and efficiently building applications that can run on a variety of different platforms. Since wxWidgets provides a wrapper around each platform's native GUI toolkit, the applications built with wxPython will have a native look and feel wherever they are deployed.This book will provide you with the skills to build highly functional and native looking user interfaces for Python applications on multiple operating system environments. By working through the recipes, you will gain insights into and exposure to creating applications using wxPython. With a wide range of topics covered in the book, there are recipes to get the most basic of beginners started in GUI programming as well as tips to help experienced users get more out of their applications. The recipes will take you from the most basic application constructs all the way through to the deployment of complete applications.Style and approach This book is a collection of step-by-step recipes that introduce the various components and concepts of wxPython in a conversational and easy-to-follow way. Each recipe contains coded examples along with detailed explanations about the key points of each topic. Each topic is designed to introduce and show you how to use a single feature from the wxPython library.
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