The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R’s quirks and shows how some...
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This book assumes no prerequisites: no algebra, no calculus, and no prior programming/coding experience. This is intended to be a gentle introduction to the practice of analyzing data and answering questions using data the way data scientists,...
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In this document, you'll find many tips for a good coding style in R programming language.
Contents:
- Removing unneeded columns
- Re-ordering columns
- Renaming columns with rename()
- Selecting columns with a regexp
- Create new columns with mutate() and if_else()
- Apply a function to certain columns only,...
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With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently.
The tutorials on this site were created for the R courses taught by Paul Hiemstra.
The course is organized as follow:
Generic working with R
Using R with RStudio
Finding functionality you need in...
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This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data...
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R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods.
This book will teach you how to create an R package.
Contents:
1. Getting started
- Introduction
- Package structure
2. Package components
- Code (R/)
- Package metadata...
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