With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools. No prior experience with lattice is required to read the book, although basic familiarity with R is assumed. The book contains close to 150 figures produced with lattice. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved. It is both for learning and for reference. This revised edition reflects changes in R since 2003 and has new material on survival analysis, random coefficient models, and the handling of high-dimensional data. Found insideAbout the Book R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Found insideAfter introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. This book presents some of the most important modeling and prediction techniques, along with relevant applications. However, classical simulation methods such as Markov Chain Monte Carlo can become computationally unfeasible; this book presents the Integrated Nested Laplace Approximations (INLA) approach as a computationally effective and extremely ... Chapter 7. Found insideThis practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Found inside – Page 1Do you want to use R to tell stories? This book was written for you—whether you already know some R or have never coded before. Most R texts focus only on programming or statistical theory. Found inside – Page 1This 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. In this book, a founding member of the PostgreSQL development team introduces everything you need to know to succeed with PostgreSQL, from basic SQL commands through database administration and optimization. Found insideIn this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ... The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences. Found inside... read in .sav data file using haven package read.table() – read in .tab data file save() – save data as .RData file save.image() – save R workspace as . Found insideThis book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Found inside – Page iiThis second edition is intended for users of S-PLUS 3.3, or later, and covers both Windows and UNIX. "This book is about the fundamentals of R programming. Found insideOver 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature About This Book 54 useful and practical tasks to improve working systems Includes optimizing performance and ... This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested ... This book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data. Found insideThe first section of this chapter covers reading data into R, ... Not only will commands from the foreign package easily help read in a SAS *.xpt or ... This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. Found insideTable 5.6 Brief overview of R functions to read and write data. ... In addition to the R functions discussed above, which are included in the base package, ... What you will learn Use basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow control Import data to R from various formats such as CSV, Excel, and SQL Clean data by handling missing ... Requiring no prior programming experience and packed with practical examples, easy, step-by-step exercises, and sample code, this extremely accessible guide is the ideal introduction to R for complete beginners. Found insideYou can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub. In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: ... This book is a guide for conducting single-subject data analysis. It introduces readers to the various functions available in SSD for R, a free and innovative software package written in R, by the authors. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data ... All the datasets and R code used in the text are available online. New to the second edition are a systematic adoption of the tidyverse and incorporation of Statcast player tracking data (made available by Baseball Savant). Found inside – Page 1By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Found inside – Page 857.1.2 raster The raster package (R. J. Hijmans 2013) has functions for creating, reading, manipulating, and writing raster data. The package provides ... Found insideThis book can also be used as material for courses in both data cleaning and data analysis. This book has fundamental theoretical and practical aspects of data analysis, useful for beginners and experienced researchers that are looking for a recipe or an analysis approach. Found inside – Page 1If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and ... Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. Found inside – Page 49In this recipe, we covered how to read and write an Excel file containing world development indicators with the xlsx package. In the first step, ... Found inside – Page 1You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory ... Found insideThe second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. Found inside – Page 42814.1.1 The R Commander's interface – a guide to getting started To start the R ... interface. r Click on Data in packages, then on Read data from package, ... This tutorial manual provides a comprehensive introduction to R, a software package for statistical computing and graphics. "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"-- Found insideDrawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to ... This tutorial manual provides a comprehensive introduction to R, written by the author the. 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