About this book
In this handy, practical book you will cover each concept concisely, with many illustrative examples. You'll be introduced to several R data science packages, with examples of how to use each of them.
In this book, you'll learn about the following APIs and packages that deal specifically with data science applications: readr, tibble, forcates, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, broom, knitr, shiny, and more.
After using this handy quick reference guide, you'll have the code, APIs, and insights to write data science-based applications in the R programming language. You'll also be able to carry out data analysis.
- Get started with RMarkdown and notebooks
- Import data with readr
- Work with categories using forcats, time and dates with lubridate, and strings with stringr
- Format data using tidyr and then transform that data using magrittr and dplyr
- Write functions with R for data science, data mining, and analytics-based applications
- Visualize data with ggplot 2 and data fit for models using modelr and broom
- Report results with markdown, knitr, shiny, and more
R data science tidyr analytics purrr ggplot modelr broom markdown knitr shiny tidyr stingr forcats lubridate magrittr dplyr tibble readr RMarkdown
- DOI https://doi.org/10.1007/978-1-4842-4894-2
- Copyright Information Thomas Mailund 2019
- Publisher Name Apress, Berkeley, CA
- eBook Packages Professional and Applied Computing Professional and Applied Computing (R0)
- Print ISBN 978-1-4842-4893-5
- Online ISBN 978-1-4842-4894-2
- Buy this book on publisher's site