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R 916.00
Python for Excel Users
Introduction: Elevate Your Analytics with PythonIn today’s data-driven world, the ability to efficiently analyze and interpret information is more crucial than ever, especially in the business sector. Python for Excel Users: A Beginner’s Guide is tailored for business students and professionals who are proficient in Microsoft Excel but are ready to embark on their Python journey. As a powerful and versatile programming language, Python has become indispensable in data analysis. This book bridges the gap between Excel and Python by providing parallel exercises that demonstrate how Python can amplify business analytics tasks with unmatched efficiency and flexibility.Through its side-by-side comparisons, interactive Python exercises, and a "teachable moment" approach, this guide offers a unique and intuitive learning experience. By translating familiar Excel tasks into Python’s dynamic and versatile ecosystem, you’ll not only enhance your data analysis skills but also gain confidence in programming.Why Python?Did you know that Python powers cutting-edge technologies like ChatGPT? Indeed, Python forms the foundation of many machine learning algorithms, including large language models (LLMs). Python is more than a programming language; it’s a tool for understanding and shaping the digital world. Despite its advanced capabilities, Python’s simple, readable syntax makes it accessible to everyone – from professional software developers to citizen developers like you. Dubbed the "language of the people," Python is revolutionizing how we approach problem-solving and automation in the modern world.Becoming Tomorrow’s Tech- Savvy LeadersThe leaders of tomorrow are not just visionaries – they are innovators who harness the power of technology to drive change and inspire others. This book guides you through different scenarios to help you understand the connections between business questions and analytics steps we are taking.As business students embracing Python, you’re positioning yourselves as future-ready leaders equipped to navigate and excel in the complexities of modern business.Welcome to a journey that will elevate your analytics, expand your technological fluency, and transform you into a tech-savvy leader of the future.
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Introduction to Python in Earth Science Data Analysis
This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.
R 2,624.51
Modern Python Cookbook
Enhance your Python skills with the third edition of Modern Python Cookbook with 130+ new and updated recipes covering Python 3.12, including new coverage on graphics, visualizations, dependencies, virtual environments, and more.Purchase of the print or Kindle book includes a free eBook in PDF formatKey FeaturesNew chapters on type matching, data visualization, dependency management, and moreComprehensive coverage of Python 3.12 with updated recipes and techniquesProvides practical examples and detailed explanations to solve real-world problems efficientlyBook DescriptionPython is the go-to language for developers, engineers, data scientists, and hobbyists worldwide. Known for its versatility, Python can efficiently power applications, offering remarkable speed, safety, and scalability. This book distills Python into a collection of straightforward recipes, providing insights into specific language features within various contexts, making it an indispensable resource for mastering Python and using it to handle real-world use cases.The third edition of Modern Python Cookbook provides an in-depth look into Python 3.12, offering more than 140 new and updated recipes that cater to both beginners and experienced developers. This edition introduces new chapters on documentation and style, data visualization with Matplotlib and Pyplot, and advanced dependency management techniques using tools like Poetry and Anaconda. With practical examples and detailed explanations, this cookbook helps developers solve real-world problems, optimize their code, and get up to date with the latest Python features.What you will learnMaster core Python data structures, algorithms, and design patternsImplement object-oriented designs and functional programming featuresUse type matching and annotations to make more expressive programsCreate useful data visualizations with Matplotlib and PyplotManage project dependencies and virtual environments effectivelyFollow best practices for code style and testingCreate clear and trustworthy documentation for your projectsWho this book is forThis Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book offers helpful details and design patterns for learning Python. If you are experienced, it will expand your knowledge base. Fundamental knowledge of Python programming and basic programming principles will be helpful
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Numerical Python
Learn how to leverage the scientific computing and data analysis capabilities of Python, its standard library, and popular open-source numerical Python packages like NumPy, SymPy, SciPy, matplotlib, and more. This book demonstrates how to work with mathematical modeling and solve problems with numerical, symbolic, and visualization techniques. It explores applications in science, engineering, data analytics, and more.Numerical Python, Third Edition, presents many case study examples of applications in fundamental scientific computing disciplines, as well as in data science and statistics. This fully revised edition, updated for each library's latest version, demonstrates Python's power for rapid development and exploratory computing due to its simple and high-level syntax and many powerful libraries and tools for computation and data analysis. After reading this book, readers will be familiar with many computing techniques, including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling, and machine learning.What You'll LearnWork with vectors and matrices using NumPyReview Symbolic computing with SymPyPlot and visualize data with MatplotlibPerform data analysis tasks with Pandas and SciPyUnderstand statistical modeling and machine learning with statsmodels and scikit-learnOptimize Python code using Numba and CythonWho This Book Is ForDevelopers who want to understand how to use Python and its ecosystem of libraries for scientific computing and data analysis.
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Automate the Boring Stuff with Python Workbook
Al Sweigart's classic coding book Automate the Boring Stuff with Python, now in its third edition, has taught more than half a million readers how to dispense with tedious tasks using the Python programming language. In this hands-on companion workbook, Sweigart gives those readers - and any Python programming beginner - hundreds of new ways to practice what they've learned. Through a wide variety of exercises, readers will test their understanding of programming concepts, face down tricky challenges, and explore use cases of common techniques. The workbook's creative projects encourage readers to build games, animations, and digital tools, offering novel ways to think about Python's applications in their everyday life. Covers Python 3.x and its ecosystem of third-party libraries.
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Python for Data Analysis 3e
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the Jupyter notebook and IPython shell for exploratory computingLearn basic and advanced features in NumPyGet started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples
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Challenging Programming in Python: A Problem Solving Perspective
This book aims to strengthen programming skills and foster creative thinking by presenting and solving 90 challenging problems. The book is intended for individuals with elementary, intermediate, and advanced Python programming skills who aspire to take their abilities to the next level. Additionally, the book is valuable for individuals interested in enhancing their creative thinking and logical reasoning skills. It is a self-instructional book meant to provide readers with the ability to solve challenging problems independently. The presented challenges are lucidly and succinctly expressed, facilitating readers to follow along and comprehend the problem-solving process. The challenges cover various fields, making it suitable for a wide range of individuals. The book is divided into eight chapters, beginning with an introduction in chapter one. The second chapter presents essential Python basics for programming challenging problems, while the subsequent chapters focus on specific types of challenges. These include math-based challenges in chapter three, number-based challenges in chapter four, string-based challenges in chapter five, game-based challenges in chapter six, count-based challenges in chapter seven, and miscellaneous challenges in chapter eight. Each chapter comprises a set of challenges with examples, hints, algorithms, and Python code solutions. The target audience of the book includes computer science and engineering students, teachers, software developers, and participants in programming competitions.
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Python's Kiss
From Pulitzer Prize and National Book Award-winning author Louise Erdrich, a captivating collection of short stories It was as though I was chosen--marked out by the python's kiss for wisdom or maybe sorrow. Or perhaps, I think now, a sense of the ridiculous in extremes of experience. Also, I hoped for a long life. WRITTEN OVER THE PAST TWO DECADES, Louise Erdrich's magnificent story collection features a range of characters--a tribal newsletter editor whose son tells her a story that nothing in her experience can encompass, immigrant farmers whose tenuous hold on the earth, and sanity, is challenged, and ordinary people, bird lovers, artists, grade-school teachers, and romantics. A girl decides to spend her life with a stone. A man is confronted with a folk-singing thief. A woman enters a corporately owned afterlife to seek revenge on her father. Accompanied by specially commissioned artwork by Aza Erdrich Abe--an intimate and revelatory creative collaboration between mother and daughter--these stories offer an opportunity to celebrate the wisdom and brilliant, wide-ranging imagination of one of America's most important writers.
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Python for Signal Processing
This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.
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Intuitive Python
Developers power their projects with Python because it emphasizes readability, ease of use, and access to a meticulously maintained set of packages and tools. The language itself continues to improve with every release: writing in Python is full of possibility. But to maintain a successful Python project, you need to know more than just the language. You need tooling and instincts to help you make the most out of what's available to you. Use this book as your guide to help you hone your skills and sculpt a Python project that can stand the test of time.No matter your experience level or background, Python's batteries-included standard library and rich third-party ecosystem provide a solid foundation to build your projects on. With the right intuition and background knowledge, you can take advantage of all the power Python offers. Take a guided tour of some of Python's high points to craft a project that you can sustain and build on for a long time.Run static analysis tools to detect and eliminate classes of bugs before you run code. Experiment with Python's concurrency model and develop patterns for using Python's thread and process abstractions to their full potential. Introduce yourself to Python's type hinting system: mypy. Download and run third-party Python packages and do so safely without compromising on security. Debug code using Python's built in debugger, and try procedures out in the interactive console. Run your code under new versions of the Python interpreter to unlock performance and usability improvements. All along the way, sharpen your Python instincts so you can keep your code clean and reduce the chance of bugs.Mine Python for all you can by playing to its strengths and embracing patterns that harness its potential.What You Need:The books assumes you have some experience programming in any language (not necessarily Python). To run the code presented in the book, you'll need a Python environment which you can download from https://www.python.org/downloads/.
R 933.00
R 608.00
Functional Python Programming
Python isn't all about object-oriented programming. Discover a valuable way of thinking about code design through a function-first approach – and learn when you need to use it. Now with detailed exercises at the end of every chapter!Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesLearn how, when, and why to adopt functional elements in your projectsExplore the Python modules essential to functional programming, like itertools and functoolsRevised to cover new features of Python 3.10, exercises at the end of every chapter, and moreBook DescriptionNot enough developers understand the benefits of functional programming, or even what it is. Author Steven Lott demystifies the approach, teaching you how to improve the way you code in Python and make gains in memory use and performance. Starting from the fundamentals, this book shows you how to apply functional thinking and techniques in a range of scenarios, with examples centered around data cleaning and exploratory data analysis. You'll learn how to use generator expressions, list comprehensions, and decorators to your advantage. You don't have to abandon object-oriented design completely, though – you'll also see how Python's native object-orientation is used in conjunction with functional programming techniques. By the end of this book, you'll be well versed in the essential functional programming features of Python, and understand why and when functional thinking helps. You'll also have all the tools you need to pursue any additional functional topics that are not part of the Python language.What you will learnUse Python's libraries to avoid the complexities of state-changing classesLeverage built-in higher-order functions to avoid rewriting common algorithmsWrite generator functions to create lazy processingDesign and implement decorators for functional compositionMake use of Python type annotations to describe parameters and results of functionsApply functional programming to concurrency and web servicesExplore the PyMonad library for stateful simulationsWho this book is forThe functional paradigm is very useful for programmers working in data science, but any Python developer who wants to create more reliable, succinct, and expressive code will have much to learn from this book.No prior knowledge of functional programming is required to get started, though Python programming knowledge is assumed. A running Python environment is essential.
R 1,596.00
Python Audio Cookbook
The Python Audio Cookbook offers an introduction to Python for sound and multimedia applications, with chapters that cover writing your first Python programs, controlling Pyo with physical computing, and writing your own GUI, among many others.Guiding the reader through a variety of audio synthesis techniques, the book empowers readers to combine their projects with popular platforms, from the Arduino to Twitter, and state-of-the-art practices such as AI. The Python Audio Cookbook balances accessible explanations for theoretical concepts, including Python syntax, audio processing and machine learning, with practical applications. This book is an essential introductory guide to Python for sound and multimedia practitioners, as well as programmers interested in audio applications.
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