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The R language is widely used by statisticians for data analysis, and the popularity of R programming has therefore increased substantially in recent years. The emerging Internet of Things (IoT) gathers increasing amounts of data that can be analyzed to gain useful insights into trends. R for Data Analysis in easy steps, 2nd edition has an easy-to-follow style that will appeal to anyone who wants to produce graphic visualizations to gain insights from gathered data. The book begins by explaining core programming principles of the R programming language, which stores data in “vectors” from which simple graphs can be plotted. Next, it describes how to create “matrices” to store and manipulate data from which graphs can be plotted to provide better insights. This book then demonstrates how to create “data frames” from imported data sets, and how to employ the “Grammar of Graphics” to produce advanced visualizations that can best illustrate useful insights from your data. R for Data Analysis in easy steps, 2nd edition contains separate chapters on the major features of the R programming language. There are complete example programs that demonstrate how to create Line graphs, Bar charts, Histograms, Scatter graphs, Box plots, and more. The code for each R script is listed, together with screenshots that illustrate the actual output when that script has been executed. The free, downloadable example R code is provided for clearer understanding. By the end of this book you will have gained a sound understanding of R programming, and be able to write your own scripts that can be executed to produce graphic visualizations for data analysis. You need have no previous knowledge of any programming language, so it's ideal for the newcomer to computer programming. Updated for the latest version of R. Contents: Getting started Storing values Performing operations Testing conditions Employing functions Building matrices Constructing data frames Producing quick plots Telling stories with data Plotting perfection
Learn how to use R to turn raw data into insight, knowledge, and understanding. 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
Photoshop CC in easy steps, 2nd edition helps the reader to master the essentials of Photoshop Creative Cloud 2018 edition, and then enjoy the full creative potential of this popular photo editing software. This book breaks down complex functions into easy-to-follow learning sequences. The continual expansion, refinement and development of Photoshop can make learning the software a daunting experience for the first time user. But there is no need to feel intimidated. The answer is simple, take it in easy steps. That's exactly what Photoshop CC in easy steps is designed to do. In clear, concise, simple language this book breaks down the complex and complicated into small easily digestible learning chunks. Photoshop CC in easy steps delivers a solid, secure and lasting foundation that you can build on as you explore Photoshop and develop more and more control over one the most creative pieces of software available today. The author’s extensive knowledge and understanding of the requirements and needs of the new user is distilled in this book which is written in simple, clear language with step-by-step instructions. Updated for Adobe Photoshop CC 2018
C# Programming in easy steps, 2nd edition will teach you to code applications, and demonstrates every aspect of the C# language you will need to produce professional programming results. Its examples provide clear syntax-highlighted code showing C# language basics including variables, arrays, logic, looping, methods, and classes. C# Programming in easy steps, 2nd edition begins by explaining how to install the free Visual Studio Community Edition, to create an environment in which you can quickly begin to create your own executable programs by copying the book's examples. It demonstrates all the C# language basics before moving on to provide examples of Object Oriented Programming. The book concludes by demonstrating how you can use your acquired knowledge to create graphic programs for traditional PC Desktop apps, and also as Universal apps for multiple devices. C# Programming in easy steps, 2nd edition has an easy-to-follow style that will appeal to: · Anyone who wants to begin programming in C# · The programmer who quickly wants to add C# to their skills set · The hobbyist who wants to begin creating apps for their own computer · The student, and to those seeking a career in computing, who need a fundamental understanding of C# programming Updated for Visual Studio 2019 Table of contents: 1. Getting started 2. Storing values 3. Performing operations 4. Making statements 5. Devising methods 6. Handling strings 7. Accessing files 8. Solving problems 9. Creating objects 10. Controlling events 11. Building an application 12. Targeting devices
Python in easy steps, 2nd edition instructs you how to program in the powerful Python language, giving complete examples that illustrate each aspect with colorized source code. Python in easy steps, 2nd edition begins by explaining how to install the free Python interpreter so you can quickly begin to create your own executable programs by copying the book's examples. It demonstrates all the Python language basics before moving on to provide examples of Object Oriented Programming (OOP) and CGI scripting to handle web form data. The book concludes by demonstrating how you can use your acquired knowledge to create and deploy graphical windowed applications. Python in easy steps, 2nd edition makes no assumption you have previous knowledge of any programming language so it's ideal for the newcomer to computer programming. It has an easy-to-follow style that will appeal to programmers moving from another programming language, and to the student who is studying Python programming at school or college, and to those seeking a career in computing who need a fundamental understanding of computer programming. The Python 3.x language is under active development so frequent new releases are made available as small improvements are added to the language and Python in easy steps, 2nd edition features the very latest versions of Python at the time of publication. Python development is one of evolution, rather than revolution, so the examples provided in the book can be used in subsequent releases – simply download the latest version of Python then follow the easy steps. Python is the language used to program the Raspberry Pi - covered by Raspberry Pi in easy steps and Raspberry Pi 3 in easy steps. This second edition is updated to cover Python 3.10.
The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.
WordPress is the most popular CMS (Content Management System) and is a fantastic tool for blogs and building websites. It is used by over 50% of the 100 top world blogs, and there are estimated to be over 75 million WordPress websites. Many bloggers/web developers are turning to WordPress to create great websites. It has the ability for people of a non-technical background to create their own website/blog in easy steps, all the way up to advanced web developers to create stunning professional designs. WordPress in easy steps, 2nd edition shows how to create stunning websites using WordPress, without having to learn programming. For anyone who may not be technically-minded but wants an affordable website for business or for blogging. WordPress in easy steps guides you through: • Setting Up WordPress • Working with the Dashboard • Creating Site Content • Adding Media • Appearance and Themes • Adding Plugins • Comments • Setting up Users and Privileges • Tools and Settings • WordPress Tricks WordPress in easy steps, 2nd edition is for: • Bloggers/Hobbyist web designers, or those looking to design a website who don’t want to learn technical language, or bloggers looking for a great platform to work with. • Web Developers: A lot of professional web design companies are using WordPress to build their websites for clients because it provides a great content management system so that the end user can add their own content once development is complete. • Anybody who has had a WordPress website built for them and wants guidance to help them update their own website. Covers WordPress 5.
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Summary Beyond Spreadsheets with R shows you how to take raw data and transform it for use in computations, tables, graphs, and more. You'll build on simple programming techniques like loops and conditionals to create your own custom functions. You'll come away with a toolkit of strategies for analyzing and visualizing data of all sorts using R and RStudio. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Spreadsheets are powerful tools for many tasks, but if you need to interpret, interrogate, and present data, they can feel like the wrong tools for the task. That's when R programming is the way to go. The R programming language provides a comfortable environment to properly handle all types of data. And within the open source RStudio development suite, you have at your fingertips easy-to-use ways to simplify complex manipulations and create reproducible processes for analysis and reporting. About the Book With Beyond Spreadsheets with R you'll learn how to go from raw data to meaningful insights using R and RStudio. Each carefully crafted chapter covers a unique way to wrangle data, from understanding individual values to interacting with complex collections of data, including data you scrape from the web. You'll build on simple programming techniques like loops and conditionals to create your own custom functions. You'll come away with a toolkit of strategies for analyzing and visualizing data of all sorts. What's inside How to start programming with R and RStudio Understanding and implementing important R structures and operators Installing and working with R packages Tidying, refining, and plotting your data About the Reader If you're comfortable writing formulas in Excel, you're ready for this book. About the Author Dr Jonathan Carroll is a data science consultant providing R programming services. He holds a PhD in theoretical physics. Table of Contents Introducing data and the R language Getting to know R data types Making new data values Understanding the tools you'll use: Functions Combining data values Selecting data values Doing things with lots of data Doing things conditionally: Control structures Visualizing data: Plotting Doing more with your data with extensions