The 18 revised full papers and 6 short papers presented were carefully reviewed and selected from 55 submissions. The papers presented at DAIS 2011 address key challenges of modern distributed services and applications, including pervasiveness and peer-to-peer environments, and tackle issues related to adaptation, interoperability, availability and performance, as well as dependability and security.
An audacious, irreverent investigation of human behavior—and a first look at a revolution in the making
Our personal data has been used to spy on us, hire and fire us, and sell us stuff we don’t need. In Dataclysm, Christian Rudder uses it to show us who we truly are.
For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.
In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.
Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.
From the Hardcover edition.
The book begins with a summary of the nontechnical aspects of interviewing, such as common mistakes, strategies for a great interview, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI.
The technical core of EPI is a sequence of chapters on basic and advanced data structures, searching, sorting, broad algorithmic principles, concurrency, and system design. Each chapter consists of a brief review, followed by a broad and thought-provoking series of problems. We include a summary of data structure, algorithm, and problem solving patterns.
Inside, you'll learn about:
Interaction design and physical computingThe Arduino hardware and software development environmentBasics of electricity and electronicsPrototyping on a solderless breadboardDrawing a schematic diagram
And more. With inexpensive hardware and open-source software components that you can download free, getting started with Arduino is a snap. To use the introductory examples in this book, all you need is a USB Arduino, USB A-B cable, and an LED.
Join the tens of thousands of hobbyists who have discovered this incredible (and educational) platform. Written by the co-founder of the Arduino project, with illustrations by Elisa Canducci, Getting Started with Arduino gets you in on the fun! This 128-page book is a greatly expanded follow-up to the author's original short PDF that's available on the Arduino website.
The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.
The companion web site, algs4.cs.princeton.edu, containsAn online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material
The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.
Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.
This book supersedes ISBN 9780596550066, from O'Reilly.
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.Get a crash course in PythonLearn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data scienceCollect, explore, clean, munge, and manipulate dataDive into the fundamentals of machine learningImplement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clusteringExplore recommender systems, natural language processing, network analysis, MapReduce, and databases
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates
An Introduction to Numerical Methods and Analysis, Second Edition reflects the latest trends in the field, includes new material and revised exercises, and offers a unique emphasis on applications. The author clearly explains how to both construct and evaluate approximations for accuracy and performance, which are key skills in a variety of fields. A wide range of higher-level methods and solutions, including new topics such as the roots of polynomials, spectral collocation, finite element ideas, and Clenshaw-Curtis quadrature, are presented from an introductory perspective, and theSecond Edition also features: Chapters and sections that begin with basic, elementary material followed by gradual coverage of more advanced material Exercises ranging from simple hand computations to challenging derivations and minor proofs to programming exercises Widespread exposure and utilization of MATLAB® An appendix that contains proofs of various theorems and other material
This book covers:Arrays and lists: the most common data structuresStacks and queues: more complex list-like data structuresLinked lists: how they overcome the shortcomings of arraysDictionaries: storing data as key-value pairsHashing: good for quick insertion and retrievalSets: useful for storing unique elements that appear only onceBinary Trees: storing data in a hierarchical mannerGraphs and graph algorithms: ideal for modeling networksAlgorithms: including those that help you sort or search dataAdvanced algorithms: dynamic programming and greedy algorithms
The CWNA: Certified Wireless Network Administrator Official Study Guide: Exam CWNA-106 is the officially endorsed CWNA test prep for the leading wireless certification. Expert authors and CWNEs David D. Coleman and David A. Westcott guide readers through the skills and concepts candidates need to know for the exam, using hands-on methods to convey an in-depth understanding of wireless network administration. Readers should have a basic knowledge of Radio Frequency behavior, experience with WLAN hardware peripherals and protocols, and an interest in designing, installing, and managing wireless networks.
Wireless technology is taking over the tech industry, and the demand for competent, certified professionals is far outpacing the supply. A CWNA certification denotes advanced-level proficiency in the field, with a complete understanding of wireless LAN components, features, and function—but the only way to pass the exam is to truly understand the material, not just the talking points. The CWNA: Certified Wireless Network Administrator Official Study Guide thoroughly covers each exam objective, and includes review questions, assessment tests, and exercises to test your skills. Topics include:Radio Frequency technologies, regulations, and standards 802.11 protocols Network implementation and security 802.11 RF site surveying
Readers also get access to a suite of study tools including an electronic test engine with hundreds or practice test questions, electronic flashcards, exercise peripherals, and industry White Papers, which serve as valuable backup references. In preparing for the CWNA-106 exam, the ideal study guide should cover all of the exam topics in depth—CWNA: Certified Wireless Network Administrator Official Study Guide does just that, making it an excellent, comprehensive study guide.
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.Get started quickly with an R tutorial and hundreds of examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with R’s graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R
By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts.
New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.Develop an understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyImport data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data
Bradley Holt, co-founder of the creative services firm Found Line, is a web developer and entrepreneur ten years of PHP and MySQL experience. He began using CouchDB before the release of version 1.0. Bradley is an active member of the PHP community, and can be reached at bradley-holt.com.
This updated second edition provides guidance for database developers, advanced configuration for system administrators, and an overview of the concepts and use cases for other people on your project. Ideal for NoSQL newcomers and experienced MongoDB users alike, this guide provides numerous real-world schema design examples.Get started with MongoDB core concepts and vocabularyPerform basic write operations at different levels of safety and speedCreate complex queries, with options for limiting, skipping, and sorting resultsDesign an application that works well with MongoDBAggregate data, including counting, finding distinct values, grouping documents, and using MapReduceGather and interpret statistics about your collections and databasesSet up replica sets and automatic failover in MongoDBUse sharding to scale horizontally, and learn how it impacts applicationsDelve into monitoring, security and authentication, backup/restore, and other administrative tasks
The code-packed examples in this book will help you learn how to work with documents, populate a simple database, replicate data from one database to another, and a host of other tasks.Install CouchDB on Linux, Mac OS X, Windows, or (if you must) from the source codeInteract with data through CouchDB’s RESTful API, and use standard HTTP operations, such as PUT, GET, POST, and DELETEUse Futon—CouchDB’s web-based interface— to manage databases and documents, and to configure replicationsLearn how to create, update, and delete documents in JSON format, and how to create and delete databasesWork with design documents to get the formatting and indexing your application requires
Inside, you’ll learn about:Interaction design and physical computing The Arduino hardware and software development environment Basics of electricity and electronics Prototyping on a solderless breadboard Drawing a schematic diagram
Getting started with Arduino is a snap. To use the introductory examples in this guide, all you need an Arduino Uno or earlier model, along with USB A-B cable and an LED. The easy-to-use Arduino development environment is free to download.
Join hundreds of thousands of hobbyists who have discovered this incredible (and educational) platform. Written by the co-founder of the Arduino project, Getting Started with Arduino gets you in on all the fun!
"The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works." -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc.
Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume.Plan and implement enterprise-scale MDM and Data Governance solutions Develop master data model Identify, match, and link master records for various domains through entity resolution Improve efficiency and maximize integration using SOA and Web services Ensure compliance with local, state, federal, and international regulations Handle security using authentication, authorization, roles, entitlements, and encryption Defend against identity theft, data compromise, spyware attack, and worm infection Synchronize components and test data quality and system performance
This highly versatile text provides mathematical background used in a wide variety of disciplines, including mathematics and mathematics education, computer science, biology, chemistry, engineering, communications, and business.
Some of the major features and strengths of this textbook
More than 1,600 exercises, ranging from elementary to challenging, are included with hints/answers to all odd-numbered exercises.
Descriptions of proof techniques are accessible and lively.
Students benefit from the historical discussions throughout the textbook.
It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.
This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision.Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth EditionSolved examples in Matlab, including real-life data sets in imaging and audio recognitionAvailable separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)
The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases.
This book will teach you:the simple and familiar graphical notation of COMN with its three basic shapes and four line styles how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren’t tangled with confused techno-speak how to express logical data designs that are freer from implementation considerations than is possible in any other notation how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development
Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you. All example code in this book is available as working Heroku apps.Create analytics applications by using the agile big data development methodologyBuild value from your data in a series of agile sprints, using the data-value stackGain insight by using several data structures to extract multiple features from a single datasetVisualize data with charts, and expose different aspects through interactive reportsUse historical data to predict the future, and translate predictions into actionGet feedback from users after each sprint to keep your project on track
Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it’s specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
This book supersedes ISBN 9780596550066, from O'Reilly.
Written by Oracle ACE Director and MySQL expert Ronald Bradford, with coauthor Chris Schneider, Effective MySQL: Replication Techniques in Depth describes what is needed to understand and implement MySQL replication to build scalable solutions. This book includes detailed syntax examples to demonstrate the features, options, and limitations of native MySQL replication. Providing an evaluation of various new replication features and additional third-party product implementations, this Oracle Press guide helps to ensure your MySQL environment can support the various high-availability needs of your business.Master the strengths and limitations of native asynchronous replication in a MySQL topology Identify the important features to improve replication for growing business requirements Recognize the key business factors to determine your optimal highavailability needs Understand the benefits of using MySQL replication for failover scenarios Identify the key configuration variables and SQL commands affecting master/ slave replication Learn about the advancements in replication techniques provided by new products, including Tungsten Replicator and Galera Optimize your replication management with various utilities and toolkits
Find additional detailed information and presentations at EffectiveMySQL.com.
If you administer a DNS system or are thinking about running one, or if you need to upgrade to support IPv6 DNS, need to secure a DNS for zone transfer, dynamic update, or other reasons, or if you need to implement DNSSEC, or simply want to understand the DNS system, then this book provides you with a single point of reference. Pro DNS and BIND starts with simple concepts, then moves on to full security-aware DNSSEC configurations. Various features, parameters, and resource records are described and, in the majority of cases, illustrated with one or more examples.
The book contains a complete reference to zone files, Resource Records, and BINDs configuration file parameters. You can treat the book as as a simple paint-by-numbers guide to everything from a simple caching DNS, to the most complex secure DNS (DNSSEC) implementation. Background information is still included for when you need to know what to do and why you have to do it, and so that you can modify processes to meet your unique needs.
Implementing Splunk Second Edition is a learning guide that introduces you to all the latest features and improvements of Splunk 6.2. The book starts by introducing you to various concepts such as charting, reporting, clustering, and visualization. Every chapter is dedicated to enhancing your knowledge of a specific concept, including data models and pivots, speeding up your queries, backfilling, data replication, and so on. By the end of the book, you'll have a very good understanding of Splunk and be able to perform efficient data analysis.
· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems
· Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems
· Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
* Ample end-of-chapter problems and full Solutions Manual
* Includes CD with sample ARENA modeling programs
How to Cheat in Unity 5takes a no-nonsense approach to help you achieve fast and effective results with Unity 5. Geared towards the intermediate user, HTC in Unity 5 provides content beyond what an introductory book offers, and allows you to work more quickly and powerfully in Unity. Packed full with easy-to-follow methods to get the most from Unity, this book explores time-saving features for interface customization and scene management, along with productivity-enhancing ways to work with rendering and optimization. In addition, this book features a companion website at www.alanthorn.net, where you can download the book’s companion files and also watch bonus tutorial video content.
Learn bite-sized tips and tricks for effective Unity workflows
Become a more powerful Unity user through interface customization
Enhance your productivity with rendering tricks, better scene organization and more
Better understand Unity asset and import workflows
Learn techniques to save you time and money during development
In this third edition of a widely acclaimed resource, three networking experts share their extensive experience, teaching you the cabling skills you need to build a reliable, efficient, and cost-effective network cabling infrastructure. As you master these techniques, you'll learn to avoid common pitfalls and troubleshoot problems as quickly as they arise. Coverage includes:Choosing the right cables and components for your network architecture and topology Avoiding unnecessary and unexpected costs Understanding the current limitations of data communications and network cabling Understanding how laws and building codes constrain cabling Understanding the function and importance of universal cabling standards Determining when you have a cabling-related network problem Assembling a complete cabling toolkit Integrating voice and data on the same cable system Setting up an infrastructure in which desktops, printers, copiers, and other nodes share cabling Understanding issues of bandwidth, impedance, resistance, attenuation, crosstalk, capacitance, propagation, delay, and delay skew Working effectively with USB and Firewire Knowing when to discard legacy cabling and begin anew Documenting your cabling Creating an RFP and selecting a vendor
This valuable handbook has attracted scores of contributors since the European Journalism Centre and the Open Knowledge Foundation launched the project at MozFest 2011. Through a collection of tips and techniques from leading journalists, professors, software developers, and data analysts, you’ll learn how data can be either the source of data journalism or a tool with which the story is told—or both.Examine the use of data journalism at the BBC, the Chicago Tribune, the Guardian, and other news organizationsExplore in-depth case studies on elections, riots, school performance, and corruptionLearn how to find data from the Web, through freedom of information laws, and by "crowd sourcing"Extract information from raw data with tips for working with numbers and statistics and using data visualizationDeliver data through infographics, news apps, open data platforms, and download links
It covers the topics traditionally treated in a first course, but also highlights new and emerging themes. Chapters are broken down into `lecture' sized pieces, motivated and illustrated by numerous theoretical and computational examples.
Over 200 exercises are provided and these are starred according to their degree of difficulty. Solutions to all exercises are available to authorized instructors.
The book covers key foundation topics:
o Taylor series methods
o Runge--Kutta methods
o Linear multistep methods
and a range of modern themes:
o Adaptive stepsize selection
o Long term dynamics
o Modified equations
o Geometric integration
o Stochastic differential equations
The prerequisite of a basic university-level calculus class is assumed, although appropriate background results are also summarized in appendices. A dedicated website for the book containing extra information can be found via www.springer.com
The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other.
Written by Oracle ACE Director and MySQL expert Ronald Bradford, Effective MySQL: Optimizing SQL Statements is filled with detailed explanations and practical examples that can be applied immediately to improve database and application performances. Featuring a step-by-step approach to SQL optimization, this Oracle Press book helps you to analyze and tune problematic SQL statements.Identify the essential analysis commands for gathering and diagnosing issues Learn how different index theories are applied and represented in MySQL Plan and execute informed SQL optimizations Create MySQL indexes to improve query performance Master the MySQL query execution plan Identify key configuration variables that impact SQL execution and performance Apply the SQL optimization lifecycle to capture, identify, confirm, analyze, and optimize SQL statements and verify the results Improve index utilization with covering indexes and partial indexes Learn hidden performance tips for improving index efficiency and simplifying SQL statements
The extensively revised second edition provides further clarification of matters that typically give rise to difficulty in the classroom and restructures the chapters on logic to emphasize the role of consequence relations and higher-level rules, as well as including more exercises and solutions.
Topics and features: teaches finite mathematics as a language for thinking, as much as knowledge and skills to be acquired; uses an intuitive approach with a focus on examples for all general concepts; brings out the interplay between the qualitative and the quantitative in all areas covered, particularly in the treatment of recursion and induction; balances carefully the abstract and concrete, principles and proofs, specific facts and general perspectives; includes highlight boxes that raise common queries and clear away confusions; provides numerous exercises, with selected solutions, to test and deepen the reader’s understanding.
This clearly-written text/reference is a must-read for first-year undergraduate students of computing. Assuming only minimal mathematical background, it is ideal for both the classroom and independent study.
Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your data
"Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author