R 4 Data Science Quick Reference - Thomas Mailund

R 4 Data Science Quick Reference

A Pocket Guide to APIs, Libraries, and Packages

(Autor)

Buch | Softcover
232 Seiten
2022 | 2nd ed.
Apress (Verlag)
978-1-4842-8779-8 (ISBN)
37,44 inkl. MwSt
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

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

Who This Book Is For
Programmers new to R's data science, data mining, and analytics packages.  Some prior coding experience with R in general is recommended.  

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.

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.

Erscheinungsdatum
Zusatzinfo 13 Illustrations, black and white; IX, 232 p. 13 illus.
Verlagsort Berkley
Sprache englisch
Maße 178 x 254 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Mathematik / Informatik Informatik Theorie / Studium
Schlagworte Analytics • Data Science • dplyr • forcats • ggplot • knitr • lubridate • magrittr • markdown • modelr • Programming language • purrr • R • r 4 • readr • Shiny • stingr • tibble • tidyr
ISBN-10 1-4842-8779-7 / 1484287797
ISBN-13 978-1-4842-8779-8 / 9781484287798
Zustand Neuware
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