| 书目名称 | R Data Science Quick Reference | | 副标题 | A Pocket Guide to AP | | 编辑 | Thomas Mailund | | 视频video | | | 概述 | The first quick reference of its kind dealing with data science using R.Covers the specific APIs and packages that let you build R-based data science applications.Also covers how to use these packages | | 图书封面 |  | | 描述 | In this handy, practical book you will cover each concept concisely, with many illustrative examples. You‘ll be introduced to several R data science packages, with examples of how to use each of them. .In this book, you’ll learn about the following APIs and packages that deal specifically with data science applications: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more..After using this handy quick reference guide, 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. .What You Will Learn.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. . | | 出版日期 | Book 20191st edition | | 关键词 | R; data science; tidyr; analytics; purrr; ggplot; modelr; broom; markdown; knitr; shiny; tidyr; stingr; forcats; l | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-4894-2 | | isbn_ebook | 978-1-4842-4894-2 | | copyright | Thomas Mailund 2019 |
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发表于 2025-3-21 19:04:32
