Department of Statistics, Colorado State University, Fort Collins, Colorado, United States of America.
Department of Mathematics, Colorado State University, Fort Collins, Colorado, United States of America.
PLoS Comput Biol. 2022 Mar 24;18(3):e1009884. doi: 10.1371/journal.pcbi.1009884. eCollection 2022 Mar.
R is an increasingly preferred software environment for data analytics and statistical computing among scientists and practitioners. Packages markedly extend R's utility and ameliorate inefficient solutions to data science problems. We outline 10 simple rules for finding relevant packages and determining which package is best for your desired use. We begin in Rule 1 with tips on how to consider your purpose, which will guide your search to follow, where, in Rule 2, you'll learn best practices for finding and collecting options. Rules 3 and 4 will help you navigate packages' profiles and explore the extent of their online resources, so that you can be confident in the quality of the package you choose and assured that you'll be able to access support. In Rules 5 and 6, you'll become familiar with how the R Community evaluates packages and learn how to assess the popularity and utility of packages for yourself. Rules 7 and 8 will teach you how to investigate and track package development processes, so you can further evaluate their merit. We end in Rules 9 and 10 with more hands-on approaches, which involve digging into package code.
R 是科学家和从业者在数据分析和统计计算中越来越喜欢的软件环境。包极大地扩展了 R 的功能,并改善了数据科学问题的低效解决方案。我们概述了查找相关包并确定哪个包最适合您所需用途的 10 条简单规则。我们在第 1 条规则中首先介绍了如何考虑您的目的的提示,这将指导您的搜索方向,在第 2 条规则中,您将学习查找和收集选项的最佳实践。第 3 条和第 4 条规则将帮助您浏览包的简介并探索其在线资源的程度,以便您可以对所选择的包的质量有信心,并确保您能够获得支持。在第 5 条和第 6 条规则中,您将熟悉 R 社区如何评估包,并了解如何自行评估包的流行度和实用性。第 7 条和第 8 条规则将教您如何调查和跟踪包的开发过程,以便您可以进一步评估其价值。我们在第 9 条和第 10 条规则中以更实际的方法结束,其中涉及深入研究包代码。