| Titre : |
R 4 data science quick reference : a pocket guide to APIs, libraries, and packages |
| Type de document : |
texte imprimé |
| Auteurs : |
Thomas Mailund, Auteur |
| Mention d'édition : |
Second edition |
| Editeur : |
New York : Apress |
| Année de publication : |
2022 |
| Importance : |
IX, 232 p. |
| Présentation : |
ill. |
| Format : |
25 cm |
| ISBN/ISSN/EAN : |
978-1-4842-8779-8 |
| Note générale : |
Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
R (Computer program language)
Statistics -- Data processing
R (Langage de programmation)
Statistique -- Informatique |
| Index. décimale : |
004.43 Langage de programmation |
| Résumé : |
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. |
| Note de contenu : |
Summary :
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 |
R 4 data science quick reference : a pocket guide to APIs, libraries, and packages [texte imprimé] / Thomas Mailund, Auteur . - Second edition . - New York : Apress, 2022 . - IX, 232 p. : ill. ; 25 cm. ISBN : 978-1-4842-8779-8 Index Langues : Anglais ( eng)
| Mots-clés : |
R (Computer program language)
Statistics -- Data processing
R (Langage de programmation)
Statistique -- Informatique |
| Index. décimale : |
004.43 Langage de programmation |
| Résumé : |
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. |
| Note de contenu : |
Summary :
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 |
|  |
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