
R 4 Data Science Quick Reference
A Pocket Guide to APIs, Libraries, and Packages
Thomas Mailund(Author)
APress
2nd Edition
Published on 29. October 2022
Book
Paperback/Softback
IX, 232 pages
978-1-4842-8779-8 (ISBN)
Description
In this handy, quick reference book you'll be introduced to several R data science packages, with examples of how to use each of them. All concepts will be covered concisely, with many illustrative examples using the following APIs: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more.
With R 4 Data Science Quick Reference , 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. All source code used in the book is freely available on GitHub..
What You'll Learn
Programmers new to R's data science, data mining, and analytics packages. Some prior coding experience with R in general is recommended.
With R 4 Data Science Quick Reference , 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. All source code used in the book is freely available on GitHub..
What You'll Learn
- Implement applicable R 4 programming language specification features
- 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 ggplot2 and fit data to models using modelr
Programmers new to R's data science, data mining, and analytics packages. Some prior coding experience with R in general is recommended.
More details
Edition
Second Edition
Language
English
Place of publication
Berkeley
United States
Target group
Professional and scholarly
Illustrations
13 s/w Abbildungen
IX, 232 p. 13 illus.
Dimensions
Height: 254 mm
Width: 178 mm
Thickness: 14 mm
Weight
467 gr
ISBN-13
978-1-4842-8779-8 (9781484287798)
DOI
10.1007/978-1-4842-8780-4
Schweitzer Classification
Other editions
Additional editions

E-Book
10/2022
2nd Edition
APress
€36.99
Available for download
Previous edition

Book
08/2019
Apress
€40.65
Article exhausted; check for reprint
Person
Thomas Mailund is an associate professor at Aarhus University, Denmark. He has a background in math and computer science. For the last decade, his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species. He has published Beginning Data Science in R, Functional Programming in R, and Metaprogramming in R with Apress as well as other books on R and C programming.
Content
1. Introduction. - 2. Importing Data: readr.- 3. Representing Tables: tibble. - 4. Tidy+select, 5. Reformatting Tables: tidyr.- 6. Pipelines: magrittr.- 7. Functional Programming: purrr. - 8. Manipulating Data Frames: dplyr. - 9. Working with Strings: stringr.- 10. Working with Factors: forcats. - 11. Working with Dates: lubridate. - 12. Working with Models: broom and modelr. - 13. Plotting: ggplot2.- 14. Conclusions.