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[null,"1.","Record Nr.",null,"UNINA9910710761903321"]
[null,null,"Autore",null,"Theofanos Mary"]
[null,null,"Titolo",null,"Common industry specification for usability - requirements / / Mary Theofanos"]
[null,null,"Pubbl/distr/stampa",null,"Gaithersburg, MD : , : U.S. Dept. of Commerce, National Institute of Standards and Technology, , 2007"]
[null,null,"Descrizione fisica",null,"1 online resource"]
[null,null,"Collana",null,"NISTIR ; ; 7432"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","2007."]
[{"$nulls":4},"Contributed record: Metadata reviewed, not verified. Some fields updated by batch processes."]
[{"$nulls":4},"Title from PDF title page."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,"2.","Record Nr.",null,"UNINA9910624380503321"]
[null,null,"Autore",null,"Mailund Thomas"]
[null,null,"Titolo",null,"R 4 Data Science Quick Reference : A Pocket Guide to APIs, Libraries, and Packages / / by Thomas Mailund"]
[null,null,"Pubbl/distr/stampa",null,"Berkeley, CA : , : Apress : , : Imprint : Apress, , 2022"]
[null,null,"ISBN",null,"9781484287804"]
[{"$nulls":4},"1484287800"]
[null,null,"Edizione",null,"[2nd ed. 2022.]"]
[null,null,"Descrizione fisica",null,"1 online resource (231 pages)"]
[null,null,"Disciplina",null,"519.502855133"]
[null,null,"Soggetti",null,"Programming languages (Electronic computers)"]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Programming Language"]
[{"$nulls":4},"Big Data"]
[{"$nulls":4},"Computer Science"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"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."]
[null,null,null,"Sommario/riassunto","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, "]
[{"$nulls":4},"data mining, and analytics-based applications Visualize data with ggplot2 and fit data to models using modelr."]