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R For Data Science

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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-12

R For Data Science written by Hadley Wickham and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-12 with Computers categories.

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

Advanced R

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Author : Hadley Wickham
language : en
Publisher: CRC Press
Release Date : 2015-09-15

Advanced R written by Hadley Wickham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Mathematics categories.

An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You 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-efficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.

Geocomputation With R

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Author : Robin Lovelace
language : en
Publisher: CRC Press
Release Date : 2019-03-22

Geocomputation With R written by Robin Lovelace and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-22 with Mathematics categories.

Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. 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 in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/.

Hands On Machine Learning With R

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Author : Brad Boehmke
language : en
Publisher: CRC Press
Release Date : 2019-11-07

Hands On Machine Learning With R written by Brad Boehmke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-07 with Business & Economics categories.

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.

R Packages

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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-03-26

R Packages written by Hadley Wickham and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-26 with Computers categories.

Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy. In the process, you’ll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language. Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You’ll learn to focus on what you want your package to do, rather than think about package structure. Learn about the most useful components of an R package, including vignettes and unit tests Automate anything you can, taking advantage of the years of development experience embodied in devtools Get tips on good style, such as organizing functions into files Streamline your development process with devtools Learn the best way to submit your package to the Comprehensive R Archive Network (CRAN) Learn from a well-respected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr

An Introduction To Statistical Learning

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Author : Gareth James
language : en
Publisher: Springer Nature
Release Date : 2023-06-30

An Introduction To Statistical Learning written by Gareth James and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Mathematics categories.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Advanced R Second Edition

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Author : Hadley Wickham
language : en
Publisher: CRC Press
Release Date : 2019-05-24

Advanced R Second Edition written by Hadley Wickham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-24 with Mathematics categories.

Advanced R helps you understand how R works at a fundamental level. It is designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages who want to understand what makes R different and special. This book will teach you the foundations of R; three fundamental programming paradigms (functional, object-oriented, and metaprogramming); and powerful techniques for debugging and optimising your code. By reading this book, you will learn: The difference between an object and its name, and why the distinction is important The important vector data structures, how they fit together, and how you can pull them apart using subsetting The fine details of functions and environments The condition system, which powers messages, warnings, and errors The powerful functional programming paradigm, which can replace many for loops The three most important OO systems: S3, S4, and R6 The tidy eval toolkit for metaprogramming, which allows you to manipulate code and control evaluation Effective debugging techniques that you can deploy, regardless of how your code is run How to find and remove performance bottlenecks The second edition is a comprehensive update: New foundational chapters: "Names and values," "Control flow," and "Conditions" comprehensive coverage of object oriented programming with chapters on S3, S4, R6, and how to choose between them Much deeper coverage of metaprogramming, including the new tidy evaluation framework use of new package like rlang (http://rlang.r-lib.org), which provides a clean interface to low-level operations, and purr (http://purrr.tidyverse.org/) for functional programming Use of color in code chunks and figures Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund), R Packages, and ggplot2: Elegant Graphics for Data Analysis.

Learning R

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Author : Richard Cotton
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-09-09

Learning R written by Richard Cotton and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-09 with Computers categories.

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youâ??ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what youâ??ve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code

R For Dummies

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Author : Andrie de Vries
language : en
Publisher: John Wiley & Sons
Release Date : 2015-07-07

R For Dummies written by Andrie de Vries and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-07 with Computers categories.

Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more. R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide. Covers downloading, installing, and configuring R Includes tips for getting data in and out of R Offers advice on fitting regression models and ANOVA Provides helpful hints for working with graphics R For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.

Learn R

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Author : Pedro J. Aphalo
language : en
Publisher: CRC Press
Release Date : 2020-07-28

Learn R written by Pedro J. Aphalo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-28 with Mathematics categories.

Learning a computer language like R can be either frustrating, fun, or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. This book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. Although rarely mentioned separately, fluency in a computer programming language involves both writing and reading. The parallels between natural and computer languages are many, but differences are also important. For students and professionals in the biological sciences, humanities, and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide, encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2020 and beyond. Features R as it is currently used Few prescriptive rules—mostly the author’s preferences together with alternatives Explanation of the R grammar emphasizing the "R way of doing things" Tutoring for "programming in the small" using scripts The grammar of graphics and the grammar of data described as grammars Examples of data exchange between R and the foreign world using common file formats Coaching for becoming an independent R user, capable of both writing original code and solving future challenges What makes this book different from others: Tries to break the ice and help readers from all disciplines feel at home with R Does not make assumptions about what the reader will use R for Attempts to do only one thing well: guide readers into becoming fluent in the R language Pedro J. Aphalo is a PhD graduate from the University of Edinburgh, and is currently a lecturer at the University of Helsinki. A plant biologist and agriculture scientist with a passion for data, electronics, computers, and photography, in addition to plants, Dr. Aphalo has been a user of R for 25 years. He first organized an R course for MSc students 18 years ago, and is the author of 13 R packages currently in CRAN.