03352nam 22006255 450 991062438050332120251009105818.09781484287804148428780010.1007/978-1-4842-8780-4(MiAaPQ)EBC7127626(Au-PeEL)EBL7127626(CKB)25219243200041(OCoLC)1349468003(OCoLC-P)1349468003(CaSebORM)9781484287804(DE-He213)978-1-4842-8780-4(PPN)265863988(Perlego)4514046(EXLCZ)992521924320004120221028d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierR 4 Data Science Quick Reference A Pocket Guide to APIs, Libraries, and Packages /by Thomas Mailund2nd ed. 2022.Berkeley, CA :Apress :Imprint: Apress,2022.1 online resource (231 pages)Includes index.Print version: Mailund, Thomas R 4 Data Science Quick Reference Berkeley, CA : Apress L. P.,c2022 9781484287798 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.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.. You will: 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.Programming languages (Electronic computers)Big dataComputer scienceProgramming LanguageBig DataComputer ScienceProgramming languages (Electronic computers)Big data.Computer science.Programming Language.Big Data.Computer Science.519.502855133Mailund Thomas846442MiAaPQMiAaPQMiAaPQBOOK9910624380503321R 4 Data Science Quick Reference2962674UNINA