You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms

    More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversity--and possibly dilution.This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhiker's Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

    This book is neither a step-by-step tutorial nor a reference book. Instead, our goal is to bring a diverse set of software engineering topics together into a single narrative, help readers understand the most important ideas through concrete examples and a learn-by-doing approach, and teach readers enough about each topic to get them started in the field. Courseware for doing the work in the book is available as a virtual machine image that can be downloaded or deployed in the cloud. A free MOOC (massively open online course) at saas-class.org follows the book's content and adds programming assignments and quizzes. See http://saasbook.info for details.

    Get an insider's tour of databases and client-server systems so you can understand the local customs. Then work your way up to sophisticated commands and statements, and check out the coverage of SQL-related products, such as Microsoft SQL server. You'll be able to communicate with your database like a native speaker in no time! Inside, find helpful advice on how to Get a complete overview of SQL components, such as Data Definition Language, Data Manipulation Language, and Data Control Language Use SQL to transfer and retrieve information on the Internet and intranets Uncover fundamental SQL commands and data types Extract data from many different data sources by using ODBC Master the basics of creating tables, views, schemas, and indexes for easy data access Manage databases by using SQL server Access a database over the Internet Get tips for making advanced queries

    Like many others, I feel like I have learned more in the last couple of years studying Bitcoin than I have during two decades of formal education. The following lessons are a distillation of what I’ve learned. First published as an article series titled “What I’ve Learned From Bitcoin,” what follows can be seen as a third edition of the original series. Like Bitcoin, these lessons aren’t a static thing. I plan to work on them periodically, releasing updated versions and additional material in the future.Bitcoin is an inexhaustible teacher, which is why I do not claim that these lessons are all-encompassing or complete. They are a reflection of my personal journey down the rabbit hole. There are many more lessons to be learned, and every person will learn something different from entering the world of Bitcoin. I hope that you will find these lessons useful and that the process of learning them by reading won’t be as arduous and painful as learning them firsthand.

    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!

    This classic guide—fully updated for Windows Server 2003, Windows XP, and Windows 2000, including 64-bit extensions—describes the architecture and internals of the Windows operating system. You’ll find hands-on experiments you can use to experience Windows internal behavior firsthand, along with advanced troubleshooting information to help you keep your systems running smoothly and efficiently. Whether you’re a developer or a system administrator, you’ll find critical architectural insights that you can quickly apply for better design, debugging, performance, and support.Get in-depth, inside knowledge of the Windows operating system: Understand the key mechanisms that configure and control Windows, including dispatching, startup and shutdown, and the registry Explore the Windows security model, including access, privileges, and auditing Investigate internal system architecture using the kernel debugger and other tools Examine the data structures and algorithms that deal with processes, threads, and jobs Observe how Windows manages virtual and physical memory Understand the operation and format of NTFS, and troubleshoot file system access problems View the Windows networking stack from top to bottom, including mapping, APIs, name resolution, and protocol drivers Troubleshoot boot problems and perform crash analysis

    Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python's implementation.How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more.Get a better grasp of NumPy, Cython, and profilersLearn how Python abstracts the underlying computer architectureUse profiling to find bottlenecks in CPU time and memory usageWrite efficient programs by choosing appropriate data structuresSpeed up matrix and vector computationsUse tools to compile Python down to machine codeManage multiple I/O and computational operations concurrentlyConvert multiprocessing code to run on local or remote clustersDeploy code faster using tools like Docker

    Why not learn to talk to your computer in its own language? Whether you want to write games, start a business, or you're just curious, learning to program is a great place to start. Plus, programming is fun!Hello World! provides a gentle but thorough introduction to the world of computer programming. It's written in language a 12-year-old can follow, but anyone who wants to learn how to program a computer can use it. Even adults. Written by Warren Sande and his son, Carter, and reviewed by professional educators, this book is kid-tested and parent-approved.You don't need to know anything about programming to use the book. But you should know the basics of using a computer--e-mail, surfing the web, listening to music, and so forth. If you can start a program and save a file, you should have no trouble using this book.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

     Data Structures and Algorithms in Python is the first mainstream object-oriented book available for the Python data structures course. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++.

    You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google

    Python is easy to learn, and it's perfect for exploring topics like statistics, geometry, probability, and calculus. You’ll learn to write programs to find derivatives, solve equations graphically, manipulate algebraic expressions, even examine projectile motion.Rather than crank through tedious calculations by hand, you'll learn how to use Python functions and modules to handle the number crunching while you focus on the principles behind the math. Exercises throughout teach fundamental programming concepts, like using functions, handling user input, and reading and manipulating data. As you learn to think computationally, you'll discover new ways to explore and think about math, and gain valuable programming skills that you can use to continue your study of math and computer science.If you’re interested in math but have yet to dip into programming, you’ll find that Python makes it easy to go deeper into the subject—let Python handle the tedious work while you spend more time on the math.

    

    Too often, lessons about requirements engineering processes lack the no-nonsense guidance that supports real-world solutions. Complementing the best practices presented in his book, Software Requirements, Second Edition, requirements engineering authority Karl Wiegers tackles even more of the real issues head-on in this book. With straightforward, professional advice and practical solutions based on actual project experiences, this book answers many of the tough questions raised by industry professionals. From strategies for estimating and working with customers to the nuts and bolts of documenting requirements, this essential companion gives developers, analysts, and managers the cosmic truths that apply to virtually every software development project. Discover how to: - Make the business case for investing in better requirements practices - Generate estimates using three specific techniques - Conduct inquiries to elicit meaningful business and user requirements - Clearly document project scope - Implement use cases, scenarios, and user stories effectively - Improve inspections and peer reviews - Write requirements that avoid ambiguity

    Jason Briggs, author of the popular online tutorial "Snake Wrangling for Kids," begins with the basics of how to install Python and write simple commands. In bite-sized chapters, he instructs readers on the essentials of Python, including how to use Python's extensive standard library, the difference between strings and lists, and using for-loops and while-loops. By the end of the book, readers have built a game and created drawings with Python's graphics library, Turtle. Each chapter closes with fun and relevant exercises that challenge the reader to put their newly acquired knowledge to the test.