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Englisch
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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
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.
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
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.
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 |
| Seiten: | 244 |
| 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 |
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 |
| Seiten: | 244 |
| 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 |
Warnhinweis