R 4 Data Science Quick Reference

Dekorationsartikel gehören nicht zum Leistungsumfang.

Sprache: Englisch

37,44 €*

inkl. MwSt.

Versandkostenfrei per Post / DHL

Aktuell nicht verfügbar

Kategorien:

Der Artikel ist nicht in deutscher Sprache verfasst.
Die Sprache der Produktbeschreibung und Details kann in Englisch angegeben sein. Sollten Sie Verständnisprobleme haben, wenden Sie sich gerne an uns.

Beschreibung

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.

What You'll Learn

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.

Über den Autor

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.

Zusammenfassung

Focuses on data science using R version 4 release

Covers the specific APIs and packages that let you build R-based data science applications

Includes how to use these packages to do data, statistical analysis using R

Inhaltsverzeichnis

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.

Details

Erscheinungsjahr:	2022
Fachbereich:	Programmiersprachen
Genre:	Informatik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Inhalt:	ix 232 S. 13 s/w Illustr. 232 p. 13 illus.
ISBN-13:	9781484287798
ISBN-10:	1484287797
Sprache:	Englisch
Ausstattung / Beilage:	Paperback
Einband:	Kartoniert / Broschiert
Autor:	Mailund, Thomas
Auflage:	2nd ed.
Hersteller:	Apress Apress L.P.
Maße:	254 x 178 x 14 mm
Von/Mit:	Thomas Mailund
Erscheinungsdatum:	29.10.2022
Gewicht:	0,467 kg

Artikel-ID: 122979142