R 4 Data Science Quick Reference

A Pocket Guide to APIs, Libraries, and Packages

Thomas Mailund

  • Apress

  • Date de publication : 2022-10-28

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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.  

Détails
Auteur
Thomas  Mailund
Marque
Apress
Collection
n.c
Parution
2022-10-28
Pages
232 pages
EAN papier
9781484287798
Langue
Anglais
Informations ebook
EAN PDF
9781484287804
Prix
36,47 €
En savoir plus
Nb pages copiables 2
Nb pages imprimables 23
Taille du fichier 3645 Ko
Ce livre est accessible aux handicaps   Informations sur l'accessibilité
EAN EPUB
9781484287804
Prix
36,47 €
En savoir plus
Nb pages copiables 2
Nb pages imprimables 23
Taille du fichier 799 Ko
Ce livre est accessible aux handicaps   Informations sur l'accessibilité
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Auteur(s) du livre


Defaut-Illustration Thomas Mailund
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.
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