Easy to understand and fun to read, Introducing Python is ideal for beginning programmers as well as those new to the language. Author bill lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned.
Introducing Python: Modern Computing in Simple Packages - You’ll gain a strong foundation in the language, debugging, code reuse, including best practices for testing, and other development tips.
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPythonO'Reilly Media - Updated for Python 3. 6, the second 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. Python for data analysis wes mckinney. Data files and related material are available on GitHub. Use the ipython shell and jupyter notebook for exploratory computinglearn basic and advanced features in NumPy Numerical PythonGet started with data analysis tools in the pandas libraryUse flexible tools to load, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, dice, clean, transform, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, merge, detailed examples Python for data analysis.
You’ll learn the latest versions of pandas, IPython, 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.
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython - Get complete instructions for manipulating, cleaning, processing, and crunching datasets in Python.
Best Practices in Data Cleaning: A Complete Guide to Everything You Need to Do Before and After Collecting Your DataSAGE Publications, Inc - Many researchers jump from data collection directly into testing hypothesis without realizing these tests can go profoundly wrong without clean data. Python for data analysis wes mckinney. This book provides a clear, accessible, step-by-step process of important best practices in preparing for Python for data analysis.
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Database Systems: A Practical Approach to Design, Implementation, and Management 6th EditionPearson - Used book in Good Condition. It provides: database design methodology that can be used by Both Technical and Non-technical Readers A Comprehensive Introduction to the Theory behind Databases A Clear Presentation that Supports Learning Python for data analysis. The methodology for relational database management Systems is presented in simple, logical, step-by-step instructions in conjunction with a realistic worked example using three explicit phases—conceptual, and physical database design.
With its comprehensive coverage, this book can also be used as a reference for IT professionals. Teaching and learning experience This program presents a better teaching and learning experience–for you and your students. Database systems is ideal for a one- or two-term course in database management or database design in an undergraduate or graduate level course.
Database Systems: A Practical Approach to Design, Implementation, and Management 6th Edition - Python for data analysis wes mckinney. This best-selling text introduces the theory behind databases in a concise yet comprehensive manner, providing database design methodology that can be used by both technical and non-technical readers.
Python Pocket Reference: Python In Your Pocket Pocket Reference O'ReillyO'Reilly Media - Python for data analysis wes mckinney. Updated for both Python 3. 4 and 2. 7, this convenient pocket guide is the perfect on-the-job quick reference. The handy index lets you pinpoint exactly what you need. Written by mark lutz—widely recognized as the world’s leading Python trainer—Python Pocket Reference is an ideal companion to O’Reilly’s classic Python tutorials, Learning Python and Programming Python, also written by Mark.
This fifth edition covers:built-in object types, dictionaries, including numbers, lists, and moreStatements and syntax for creating and processing objectsFunctions and modules for structuring and reusing codePython’s object-oriented programming toolsBuilt-in functions, exceptions, and attributesSpecial operator overloading methodsWidely used standard library modules and extensionsCommand-line options and development toolsPython idioms and hintsThe Python SQL Database API Python for data analysis.
Python Pocket Reference: Python In Your Pocket Pocket Reference O'Reilly - You’ll find concise, built-in functions and exceptions, special method names, commonly used standard library modules, need-to-know information on Python types and statements, and other prominent Python tools. Used book in Good Condition.
Learning Python, 5th EditionO'Reilly Media - You’ll also learn some advanced language features that recently have become more common in Python code. Explore python’s major built-in object types such as numbers, functions, metaclasses, including decorators, descriptors, and other tools into larger components with modulesDive into classes: Python’s object-oriented programming tool for structuring codeWrite large programs with Python’s exception-handling model and development toolsLearn advanced Python tools, and dictionariesCreate and process objects with Python statements, and learn Python’s general syntax modelUse functions to avoid code redundancy and package code for reuseOrganize statements, lists, and Unicode processing Python for data analysis.
Used book in Good Condition. Based on author mark lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. O'reilly Media. Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Python for data analysis wes mckinney.
Learning Python, 5th Edition - . It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.
Essence of Decision: Explaining the Cuban Missile Crisis 2nd EditionPearson - Not simply revised, but completely re-written, the second Edition of this classic text is a fresh reinterpretation of the theories and events surrounding the Cuban Missle Crisis, incorporating all new information from the Kennedy tapes and recently declassified Soviet files. Used book in Good Condition.
Python for data analysis wes mckinney. Essence of decision second edition, is a vivid look at decision-making under pressure and is the only single volume work that attempts to answer the enduring question: how should citizens understand the actions of their government? Python for data analysis. O'reilly Media.
Essence of Decision: Explaining the Cuban Missile Crisis 2nd Edition - Pearson. One of the most influental political science works written in the post World War II era, the original edition of Essence of Decision is a unique and fascinating examination of the pivotal event of the cold Cold War.
Python Cookbook, Third editionO'Reilly Media - Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works. Topics include:data structures and algorithmsstrings and textnumbers, dates, debugging, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, and ExceptionsC Extensions Python for data analysis.
. O'reilly Media. Python for data analysis wes mckinney. Used book in Good Condition. If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. O reilly Media. Pearson. Packed with practical recipes written and tested with Python 3. 3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.
Python Cookbook, Third edition - Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains.
Introduction to Machine Learning with Python: A Guide for Data ScientistsO'Reilly Media - O'reilly Media. Authors andreas müller and sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Pearson. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, including which data aspects to focus onadvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, you’ll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills Python for data analysis.
O reilly Media. Python for data analysis wes mckinney. If you use python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library.
Introduction to Machine Learning with Python: A Guide for Data Scientists - Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. Used book in Good Condition.
Fluent Python: Clear, Concise, and Effective ProgrammingO'Reilly Media - Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. Used book in Good Condition. O reilly Media. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features.
With this book, those Python programmers will thoroughly learn how to become proficient in Python 3. This book covers:python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, coroutines, operator overloading, mutability, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, interfaces, generators, and multiple inheritanceControl flow: leverage context managers, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and concurrency with the concurrent.
Fluent Python: Clear, Concise, and Effective Programming - Futures and asyncio packagesMetaprogramming: understand how properties, class decorators, attribute descriptors, and metaclasses work Python for data analysis. Author luciano ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.
Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. O reilly Media. Python for data analysis wes mckinney.
Network Programmability and Automation: Skills for the Next-Generation Network EngineerO'Reilly Media - O'reilly Media. O reilly Media. Like sysadmins before them, network engineers are finding that they cannot do their work manually anymore. Used book in Good Condition. As the field faces new protocols, delivery models, technologies, and a pressing need for businesses to be more agile and flexible, network automation is becoming essential.
O reilly Media. Pearson. Python for data analysis wes mckinney. This practical guide shows network engineers how to use a range of technologies and tools—including Linux, Python, JSON, and XML—to automate their systems through code. Network programming and automation will help you simplify tasks involved in configuring, services, managing, and operating network equipment, topologies, and connectivity.
Network Programmability and Automation: Skills for the Next-Generation Network Engineer - Through the course of the book, you’ll learn the basic skills and tools you need to make this critical transition. This book covers:python programming basics: data types, yaml, and moduleslinux fundamentals to provide the foundation you need on your network automation journeyData formats and models: JSON, and YANG for networkingJinja templating and its applicability for creating network device configurationsThe role of application programming interfaces APIs in network automationSource control with Git to manage code changes during the automation processHow Ansible, XML, conditionals, Salt, loops, functions, classes, and StackStorm open source automation tools can be used to automate network devicesKey tools and technologies required for a Continuous Integration CI pipeline in network operations Python for data analysis.
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