R Data Science Quick Reference: A Pocket Guide to APIs, Libraries, and Packages - Tapa blanda

Mailund, Thomas

 
9781484248935: R Data Science Quick Reference: A Pocket Guide to APIs, Libraries, and Packages
Tapa blanda
ISBN 10: 1484248937 ISBN 13: 9781484248935
Editorial: Apress, 2019

Sinopsis

1. Introduction
2. Importing Data: readr
3. Representing Tables: tibble
4. Reformatting Tables: tidyr
5. Pipelines: magrittr
6. Functional Programming: purrr
7. Manipulating Data Frames: dplyr
8. Working with Strings: stringr
9. Working with Factors: forcats
10. Working with Dates: lubridate
11. Working with Models: broom and modelr
12. Plotting: ggplot2
13. Conclusions

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del 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.

De la contraportada

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.  


You will:
  • 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

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Apress
Año de publicación
2019
Idioma
Inglés
ISBN 10 
1484248937
ISBN 13 
9781484248935
Encuadernación
Tapa blanda
Número de páginas
256
Contacto del fabricante
no disponible
Persona responsable
no disponible