{"product_id":"r-4-data-science-quick-reference-a-pocket-guide-to-apis-libraries-and-packages-paperback","title":"R 4 Data Science Quick Reference: A Pocket Guide to Apis, Libraries, and Packages - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eThomas Mailund\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eIn 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.\u003cbr\u003eWith \u003ci\u003eR 4 Data Science Quick Reference\u003c\/i\u003e, 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.. \u003cbr\u003e\u003cb\u003eWhat You'll Learn\u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eImplement applicable R 4 programming language specification features\u003c\/li\u003e\n\u003cli\u003eImport data with readr\u003c\/li\u003e\n\u003cli\u003eWork with categories using forcats, time and dates with lubridate, and strings with stringr\u003c\/li\u003e\n\u003cli\u003eFormat data using tidyr and then transform that data using magrittr and dplyr\u003c\/li\u003e\n\u003cli\u003eWrite functions with R for data science, data mining, and analytics-based applications\u003c\/li\u003e\n\u003cli\u003eVisualize data with ggplot2 and fit data to models using modelr\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003cbr\u003eProgrammers new to R's data science, data mining, and analytics packages. Some prior coding experience with R in general is recommended.\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eIn 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.\u003cbr\u003eWith \u003ci\u003eR 4 Data Science Quick Reference\u003c\/i\u003e, 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.. \u003cbr\u003eYou will: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eImplement applicable R 4 programming language specification features\u003c\/li\u003e\n\u003cli\u003eImport data with readr\u003c\/li\u003e\n\u003cli\u003eWork with categories using forcats, time and dates with lubridate, and strings with stringr\u003c\/li\u003e\n\u003cli\u003eFormat data using tidyr and then transform that data using magrittr and dplyr\u003c\/li\u003e\n\u003cli\u003eWrite functions with R for data science, data mining, and analytics-based applications\u003c\/li\u003e\n\u003cli\u003eVisualize data with ggplot2 and fit data to models using modelr\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003eThomas 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.\u003cbr\u003e\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 232\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.51 x 10 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e October 29, 2022\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":71512661065981,"sku":"9781484287798","price":48.02,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/3414\/0157\/files\/j8cWZ5qeyp9781484287798.webp?v=1791525070","url":"https:\/\/booktolia.com\/products\/r-4-data-science-quick-reference-a-pocket-guide-to-apis-libraries-and-packages-paperback","provider":"booktolia","version":"1.0","type":"link"}