Books [Edzer Pebesma, Roger Bivand] Spatial Data Science: With Applications in R
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Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are represented, coordinate reference systems (projections, datums), the fact that the Earth is round and its consequences for analysis, and how attributes of geometries can relate to geometries. In the second part of the book, these concepts are illustrated with data science examples using the R language. In the third part, statistical modelling approaches are demonstrated using real world data examples. After reading this book, the reader will be...
Books [Michael C. Wimberly] Geographic Data Science with R: Visualizing and Analyzing Environmental Change
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The burgeoning field of data science has provided a wealth of techniques for analysing large and complex geospatial datasets, including descriptive, explanatory, and predictive analytics. However, applying these methods is just one part of the overall process of geographic data science. Other critical steps include screening for suspect data values, handling missing data, harmonizing data from multiple sources, summarizing the data, and visualizing data and analysis results. Although there are many books available on statistical and machine learning methods, few encompass the broader topic of scientific workflows for geospatial data...
Books [Robin Lovelace, Jakub Nowosad, Jannes Muenchow] Geocomputation with R
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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...
Books [Yihui Xie] bookdown: Authoring Books and Technical Documents with R Markdown
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bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown, and extends R Markdown for technical writing, so that you can make better use of document elements such as figures, tables, equations, theorems, citations, and references. Similar to LaTeX, you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the...
Books [Yihui Xie, Amber Thomas, Alison Presmanes Hill] blogdown: Creating Websites with R Markdown
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blogdown: Creating Websites with R Markdown provides a practical guide for creating websites using the blogdown package in R. In this book, we show you how to use dynamic R Markdown documents to build static websites featuring R code (or other programming languages) with automatically rendered output such as graphics, tables, analysis results, and HTML widgets. The blogdown package is also suitable for technical writing with elements such as citations, footnotes, and LaTeX math. This makes blogdown an ideal platform for any website designed to communicate information about data science, data analysis, data visualization, or R...
Books [Yihui Xie, J. J. Allaire, Garrett Grolemund] R Markdown: The Definitive Guide
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This is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem.
With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages.
About the Authors
- Yihui Xie is a software engineer at RStudio.
- J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE.
- Garrett Grolemund is the co-author of R for Data Science...
Books [Chester Ismay, Albert Y. Kim] Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on...
Books [Norman Matloff] The Art of R Programming: A Tour of Statistical Software Design
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R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.
The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro.
Along the way, you'll learn about functional and...
Books [Emmanuel Paradis] R for Beginners
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Books [Emmanuel Paradis] A Step-by-Step R Tutorial: An Introduction into R Applications and Programming
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ОПИСАНИЕ:
A Step-by-Step Tutorial in R has a two-fold aim: to learn the basics of R and to acquire basic skills for programming efficiently in R. Emphasis is on converting ideas about analysing data into useful R programs. It is stressed throughout that programming starts first by getting a clear understanding of the problem. Once the problem is well formulated the next phase is to write step-by-step code for execution by the R evaluator.
Although A Step-by-Step Tutorial in R is primarily intended as a course directed by an instructor, it can also be used with a little more effort as a self-teaching option. The first 11 chapters form the core...
Books [Patrick Burns] The R Inferno
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ОПИСАНИЕ:
An essential guide to the trouble spots and oddities of R. In spite of the quirks exposed here, R is the best computing environment for most data analysis tasks. R is free, open-source, and has thousands of contributed packages. It is used in such diverse fields as ecology, finance, genomics and music. If you are using spreadsheets to understand data, switch to R. You will have safer - and ultimately, more convenient - computations.
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Books [Sasha D. Hafner] The Book of R: A First Course in Programming and Statistics
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ОПИСАНИЕ:
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis.
You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools...
Books [Sasha D. Hafner] R for Beginners
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The objective of this book is to introduce participants to the use of R for data manipulation and analysis. It is intended for individuals with little or no prior experience in R. The topics that are covered are those that author thinks are the most important for getting started with R. By the end of the book, you should be able to complete all steps reguired for data analysis and visualization using R, including the use of some relatively sophisticated methods.
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Books [Hadley Wickham] Advanced R Programming
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ОПИСАНИЕ:
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...
Books [Julia Silge, David Robinson] Text Mining with R: A Tidy Approach
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ОПИСАНИЕ:
Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.
The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate...
Books [Winston Chang] Cookbook for R: Best R Programming TIPs
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The goal of this cookbook is to provide solutions to common tasks and problems in analyzing data. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.
Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you're a beginner, this book will help get you started. If you're an intermediate user, this book will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.
R is a powerful tool for statistics...
Books [Colin Gillespie, Robin Lovelace] Efficient R Programming: A Practical Guide to Smarter Programming
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ОПИСАНИЕ:
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code.
Drawing 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 any R user’s bookshelf. Academics...
Books [Malte Grosser, Henning Bumann, Hadley Wickham] Advanced R Solutions
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ОПИСАНИЕ:
This book offers solutions to all 284 exercises in Advanced R, Second Edition. All the solutions have been carefully documented and made to be as clear and accessible as possible. Working through the exercises and their solutions will give you a deeper understanding of a variety of programming challenges, many of which are relevant to everyday work. This will expand your set of tools on a technical and conceptual level. You will be able to transfer many of the specific programming schemes directly and will discover far more elegant solutions to everyday problems.
Features:
- When R creates copies, and how it affects memory...
Books [Hadley Wickham] Advanced R, Second Edition
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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...
Books [W. N. Venables, D. M. Smith] An Introduction to R
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Books [Alex Douglas, Deon Roos, Francesca Mancini, Ana Couto, David Lusseau] An Introduction to R
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The aim of this book is to introduce you to using R, a powerful and flexible interactive environment for statistical computing and research. R in itself is not difficult to learn, but as with learning any new language (spoken or computer) the initial learning curve can be a little steep and somewhat daunting.
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Books [Winston Chang] R Graphics Cookbook: Practical Recipes for Visualizing Data
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This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.
Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started.
- Use R’s default graphics for quick exploration of data
- Create a variety of bar graphs, line graphs, and scatter plots
- Summarize...
Books [James (JD) Long, Paul Teetor] R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics
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ОПИСАНИЕ:
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression.
Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this...
Books [Roger D. Peng] R Programming for Data Science
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ОПИСАНИЕ:
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to...
Books [Hadley Wickham] R Packages: Organize, Test, Document, and Share Your Code
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ОПИСАНИЕ:
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 Wickhamâ??s package development philosophy. In the process, youâ??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...
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