This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. 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, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools--useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on text, CSV, HTML, XML, and JSON files Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow Create your own tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines Model data with dimensionality reduction, regression, and classification algorithms Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark

Discover the ultimate guide to Tableau 2019.x that offers over 115 practical recipes to tackle business intelligence and data analysis challenges. This book takes you from the basics to advanced techniques, empowering you to create insightful dashboards, leverage powerful analytics, and seamlessly integrate with modern cloud data platforms. What this Book will help me do Master both basic and advanced functionalities of Tableau Desktop to effectively analyze and visualize data. Understand how to create impactful dashboards and compelling data stories for drive decision-making. Deploy advanced analytical tools including R-based forecasting and statistical techniques with Tableau. Set up and utilize Tableau Server in multi-node environments on Linux and Windows. Utilize Tableau Prep to efficiently clean, shape, and transform data for seamless integration into Tableau workflows. Author(s) The authors of the Tableau 2019.x Cookbook are recognized industry professionals with rich expertise in business intelligence, data analytics, and Tableau's ecosystem. Dmitry Anoshin and his co-authors bring hands-on experience from various industries to provide actionable insights. They focus on delivering practical solutions through structured learning paths. Who is it for? This book is tailored for data analysts, BI developers, and professionals equipped with some knowledge of Tableau wanting to enhance their skills. If you're aiming to solve complex analytics challenges or want to fully utilize the capabilities of Tableau products, this book offers the guidance and knowledge you need.

Have you ever wanted to transform your data analysis in R into interactive, web-based dashboards and applications? "Learning Shiny" is your guide to mastering R's Shiny framework to create dynamic, visual, and engaging web applications. With its step-by-step approach, this book enables you to harness Shiny's features effectively. What this Book will help me do Understand the core principles of R and data processing using tools like apply and lapply, empowering you to handle data programmatically. Learn the Shiny framework fundamentals, including structuring an interactive application using UI and server scripts. Create stunning visualizations and dashboards using libraries like ggplot2 and integrate Shiny seamlessly. Deploy and host Shiny web applications on Linux servers for effective sharing and collaboration. Enhance your applications with JavaScript integrations, using tools like D3.js, for advanced customization. Author(s) Hernan Resnizky is a renowned data scientist and educator with extensive experience in R programming and Shiny application development. Known for his clear teaching style, he has guided numerous professionals in using R for real-world applications. His practical approach ensures readers not only learn techniques but understand how to apply them effectively. Who is it for? "Learning Shiny" is ideal for data scientists looking to showcase their work through interactive web apps and visualizations, and for web developers curious about leveraging the Shiny framework in R. Beginners as well as those with some R experience will find tailored guidance to suit their level. If you aim to expand your toolkit with web-focused R capabilities, this book is for you.

This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. 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 spreadsheets Perform scrub operations on plain text, CSV, HTML/XML, and JSON Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow using Drake Create reusable tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines using GNU Parallel Model data with dimensionality reduction, clustering, regression, and classification algorithms

Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap. Starting with the basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics such as CUDA libraries. The authors share their experience developing algorithms using MATLAB, C++ and GPUs for huge datasets, modifying MATLAB codes to better utilize the computational power of GPUs, and integrating them into commercial software products. Throughout the book, they demonstrate many example codes that can be used as templates of C-MEX and CUDA codes for readers’ projects. Download example codes from the publisher's website: http://booksite.elsevier.com/9780124080805/ Shows how to accelerate MATLAB codes through the GPU for parallel processing, with minimal hardware knowledge Explains the related background on hardware, architecture and programming for ease of use Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects

Gnuplot in Action is the first comprehensive introduction to gnuplot—from the basics to the power features and beyond. Besides providing a tutorial on gnuplot itself, it demonstrates how to apply and use gnuplot to extract intelligence from data. Particular attention is paid to tricky or poorly-explained areas. You will learn how to apply gnuplot to actual data analysis problems. This book looks at different types of graphs that can be generated with gnuplot and will discuss when and how to use them to extract actual information from data. About the Technology Statistical data is only as valuable as your ability to analyze, interpret, and present it in a meaningful way. Gnuplot is the most widely used program to plot and visualize data for Unix/Linux systems and it is also popular for Windows and the Mac. It's open-source (as in free!), actively maintained, stable, and mature. It can deal with arbitrarily large data sets and is capable of producing high-quality, publication-ready graphics. So far, the only comprehensive documentation available about gnuplot is the online reference documentation, which makes it both hard to get started and almost impossible to get a complete overview over all of its features. If you've never tried gnuplot—or have found it tough to get your arms around—read on. About the Book One of gnuplot's main advantages is that it requires no programming skills nor knowledge of advanced mathematical or statistical concepts. Gnuplot in Action assumes you have no previous knowledge of either gnuplot or statistics and data analysis. The books starts out with basic gnuplot concepts, then describes in depth how to get a graph ready for final presentation and to make it look "just right" by including arrows, labels, and other decorations. Next the book looks at advanced concepts, such as multi-dimensional graphs and false-color plots—powerful features for special purposes. The author also describes advanced applications of gnuplot, such as how to script gnuplot so that it can run unattended as a batch job, and how to call gnuplot from within a CGI script to generate graphics for dynamic websites on demand. What's Inside Creating graphs with gnuplot Data transformations and filters Preparing/polishing graphs for final presentation Publishing graphs in print or on the Web Using gnuplot's power features Gnuplot scripting and programming Types of graphs and when to use them Techniques of graphical analysis How to build, install, and develop for gnuplot Command and Option reference organized by concept About the Reader Gnuplot in Action makes gnuplot easy for anyone who needs to do data analysis, but doesn't have an education in analytical tools and methods. It's perfect for DBAs, programmers, and performance engineers; business analysts and MBAs; and Six-Sigma Black Belts and process engineers. About the Author Philipp K. Janert is Chief Consultant at Principal Value, LLC. He has been a gnuplot user for more than 15 years and regards it as one of the indispensable tools in his toolbox. He has worked for small start-ups and in large corporate environments, both in the US and overseas, including several years at Amazon.com, where he initiated and led several projects to improve Amazon's order fulfillment processes. Philipp K. Janert has written about software and software development for the O'Reilly Network, IBM developerWorks, IEEE Software, and Linux Magazine. He holds a Ph.D. in Theoretical Physics from the University of Washington. Visit his website at www.principal-value.com. Quotes Knee-deep in data? This is your guidebook to exploring it with gnuplot. - Austin King, Mozilla Sparkles with insight about visualization, image perception, and data exploration. - Richard B. Kreckel, GiNaC.de Incredibly useful for beginners - indispensable for advanced users. - Mark Pruett, Systems Architect Dominion Bridges the gap between gnupolt's reference manual and real-world problems. - Mitchell Johnson, Border Stylo A Swiss Army knife for plotting data. - Nishanth Sastry, Computer Laboratory, University of Cambridge/IBM

The complete, easy-to-understand guide to IT—now and in the future! Computers, networks, and pervasive computing Hardware, operating systems, and software How networks work: LANs, WANs, and the Internet E-business, the Web, and security The guide for ANYONE who needs to understand the key technologies driving today's economy and high tech industries! You can't afford not to understand the information revolution that's sweeping the world-but who's got time for all the acronyms and hype most technology books give you? The Essential Guide to Computing demystifies the digital society we live in with an intelligent, thorough, and up-to-date explanation of computer, networking, and Internet technologies. It's perfect for smart professionals who want to get up to speed, but don't have computer science or engineering degrees! You'll find up-to-the-minute coverage on all of today's hottest technologies including: The evolution of computing: from the room-sized "monoliths" of the 1950s to today's global Internet Preview of the next revolution: "pervasive computing" Computer hardware: microprocessors, memory, storage, I/O, displays, and architecture Windows, Macintosh, UNIX/Linux, DOS, NetWare, Palm: what operating systems do, and how they compare Programming languages: from machine language to advanced object-oriented technologies Key software applications: databases, spreadsheets, word processing, voice recognition, and beyond Microsoft and the software industry: where they stand, where they're headed How networks work: LANs, WANs, packet switching, hardware, media, and more The Internet, e-commerce, and security Enterprise applications: data warehousing, Web-centered development, and groupware Whether you're a consumer, investor, marketer, or executive, this is your start-to-finish briefing on the information technologies that have changed the world-and the coming technologies that will transform it yet again!