With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    Service Design is a bit of a buzzword these days and has gained a lot of interest from various fields. This book, assembled to describe and illustrate the emerging field of service design, was brought together using exactly the same co-creative and user-centred approaches you can read and learn about inside. The boundaries between products and services are blurring and it is time for a different way of thinking: this is service design thinking.A set of 23 international authors and even more online contributors from the global service design community invested their knwoledge, experience and passion together to create this book. It introduces service design thinking in a manner accessible to beginners and students, it broadens the knowledge and can act as a resource for experienced design professionals.

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    How do you present large volumes of information to people who need to find what they're looking for quickly? This classic primer shows information architects, designers, and web site developers how to build large-scale and maintainable web sites that are appealing and easy to navigate. The new edition is thoroughly updated to address emerging technologies -- with recent examples, new scenarios, and information on best practices -- while maintaining its focus on fundamentals. With topics that range from aesthetics to mechanics, Information Architecture for the World Wide Web explains how to create interfaces that users can understand right away. Inside, you'll find:* An overview of information architecture for both newcomers and experienced practitioners* The fundamental components of an architecture, illustrating the interconnected nature of these systems. Updated, with updates for tagging, folksonomies, social classification, and guided navigation* Tools, techniques, and methods that take you from research to strategy and design to implementation. This edition discusses blueprints, wireframes and the role of diagrams in the design phase* A series of short essays that provide practical tips and philosophical advice for those who work on information architecture* The business context of practicing and promoting information architecture, including recent lessons on how to handle enterprise architecture* Case studies on the evolution of two large and very different information architectures, illustrating best practices along the way* How do you document the rich interfaces of web applications? How do you design for multiple platforms and mobile devices? With emphasis on goals and approaches over tactics or technologies, this enormously popular book gives you knowledge about information architecture with a framework that allows you to learn new approaches -- and unlearn outmoded ones.

    Users demand software that is well-behaved, good-looking, and easy to use. Your clients or managers demand originality and a short time to market. Your UI technology -- web applications, desktop software, even mobile devices -- may give you the tools you need, but little guidance on how to use them well.UI designers over the years have refined the art of interface design, evolving many best practices and reusable ideas. If you learn these, and understand why the best user interfaces work so well, you too can design engaging and usable interfaces with less guesswork and more confidence.Designing Interfaces captures those best practices as design patterns -- solutions to common design problems, tailored to the situation at hand. Each pattern contains practical advice that you can put to use immediately, plus a variety of examples illustrated in full color. You'll get recommendations, design alternatives, and warnings on when not to use them.Each chapter's introduction describes key design concepts that are often misunderstood, such as affordances, visual hierarchy, navigational distance, and the use of color. These give you a deeper understanding of why the patterns work, and how to apply them with more insight.A book can't design an interface for you -- no foolproof design process is given here -- but Designing Interfaces does give you concrete ideas that you can mix and recombine as you see fit. Experienced designers can use it as a sourcebook of ideas. Novice designers will find a roadmap to the world of interface and interaction design, with enough guidance to start using these patterns immediately.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    Yet information graphics is rarely taught in schools or is the focus of on-the-job training. Now, for the first time, Dona M. Wong, a student of the information graphics pioneer Edward Tufte, makes this material available for all of us. In this book, you will learn:to choose the best chart that fits your data;the most effective way to communicate with decision makers when you have five minutes of their time;how to chart currency fluctuations that affect global business;how to use color effectively;how to make a graphic “colorful” even if only black and white are available.The book is organized in a series of mini-workshops backed up with illustrated examples, so not only will you learn what works and what doesn’t but also you can see the dos and don’ts for yourself. This is an invaluable reference work for students and professional in all fields.

    Yet, ethical principles for working with data have been available for decades. The real issue today is how to put those principles into action. With this report, authors Mike Loukides, Hilary Mason, and DJ Patil examine practical ways for making ethical data standards part of your work every day. To help you consider all of possible ramifications of your work on data projects, this report includes: A sample checklist that you can adapt for your own procedures Five framing guidelines (the Five C’s) for building data products: consent, clarity, consistency, control, and consequences Suggestions for building ethics into your data-driven culture Now is the time to invest in a deliberate practice of data ethics, for better products, better teams, and better outcomes. Get a copy of this report and learn what it takes to do good data science today.

    But as the field evolves, designers enter the field from many disciplines. Practitioners today have enough experience in UI design that they have been exposed to design rules, but it is essential that they understand the psychology behind the rules in order to effectively apply them. In "Designing with the Mind in Mind," Jeff Johnson, author of the best selling "GUI Bloopers," provides designers with just enough background in perceptual and cognitive psychology that UI design guidelines make intuitive sense rather than being just a list of rules to follow. * The first practical, all-in-one source for practitioners on user interface design rules and why, when and how to apply them.* Provides just enough background into the reasoning behind interface design rules that practitioners can make informed decisions in every project.* Gives practitioners the insight they need to make educated design decisions when confronted with tradeoffs, including competing design rules, time constrictions, or limited resources.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    More than a series of fascinating case studies, To Engineer Is Human is a work that looks at our deepest notions of progress and perfection, tracing the fine connection between the quantifiable realm of science and the chaotic realities of everyday life."Alert, inquisitive, unspecialized, wholly human...refreshingly eclectic." --The Spectator"Henry Petroski is an ardent engineer, and if he writes more good books like this, he might find himself nominated to become the meistersinger of the guild. [This is] a refreshing plunge into the dynamics of the engineering ethos...as straightforward as an I-beam."--Science

    This innovative book presents the design process and the best software tools for creating infographics that communicate. Including a special section on how to construct the increasingly popular infographic resume, the book offers graphic designers, marketers, and business professionals vital information on the most effective ways to present data.Explains why infographics and data visualizations work Shares the tools and techniques for creating great infographics Covers online infographics used for marketing, including social media and search engine optimization (SEO) Shows how to market your skills with a visual, infographic resume Explores the many internal business uses of infographics, including board meeting presentations, annual reports, consumer research statistics, marketing strategies, business plans, and visual explanations of products and services to your customers With Cool Infographics, you'll learn to create infographics to successfully reach your target audience and tell clear stories with your data.

    With simple, creative guidance, this book teaches readers how to learn what they want to learn from the media and other communication sources.

    Whether you re a beginner, a student, or a career artist looking to be in the best museum shows, this book provides ways of advancing your plans on any level. Making It in the Art World is an invaluable resource for artists at every stage, offering readers a plethora of strategies and helpful tips to plan and execute a successful artistic career. Topics include how to evaluate your own work, how to submit art, how to present work to the public, how to avoid distractions in the studio, and much more.

    Nothing could be further from the truth. In Behind Every Good Decision, authors and analytics experts Piyanka Jain and Puneet Sharma demonstrate how professionals at any level can take the information at their disposal and leverage it to make better decisions. The authors’ streamlined frame work demystifies the process of business analytics and helps anyone move from data to decisions in just five steps…using only Excel as a tool. Readers will learn how to: Clarify the business question • Lay out a hypothesis-driven plan • Pull relevant data • Convert it to insights • Make decisions that make an impact Packed with examples and exercises, this refreshingly accessible book explains the four fundamental analytic techniques that can help solve a surprising 80% of all business problems. Business analytics isn’t rocket science—it’s a simple problem-solving tool that can help companies increase revenue, decrease costs, improve products, and delight customers. And who doesn’t want to do that?