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所在平台: Udemy |
课程主页: https://www.udemy.com/course/efficient-r-programming-with-the-tidyverse/
课程评论：没有评论
**课程名称：** 使用 R tidyverse 进行数据科学 **课程概述：** 本课程旨在帮助您将 R 编程技能提升至新高度，教授如何利用 R 的 tidyverse 系列包高效、优雅地处理日常数据科学任务。无论您身处商业、金融、科学研究还是工程领域，都能熟练运用 R 应对数据挑战。 **课程特色：** * **针对人群：** 适用于具备 R 基础知识，但希望掌握数据科学工具和信心来处理数据可视化、数据汇总、数据子集化和数据合并等日常任务的初学者和中级学习者。 * **解决痛点：** 如果您还在依赖 Excel 进行数据处理、格式化和可视化，本课程将为您提供 R 的强大替代方案。 * **核心内容：** * **数据操作 (dplyr)：** 学习如何过滤、排序、创建新变量、汇总数据、连接数据集以及选择列/行。 * **数据重塑 (tidyr)：** 掌握如何整理（gather）和扩展（spread）变量，以及如何在单元格中拆分（separate）数据。 * **数据可视化 (ggplot2)：** 学习绘制散点图、箱线图、条形图、线图、面板图，并能添加误差线。 * **代码效率提升：** 学习使用 magrittr 的前向管道符（forward pipe operator）来高效地链接代码。 * **学习成果：** 完成本课程后，您将自信地使用 R 来应对日常数据科学工作。
Take your R programming skills to the next level with this short course in data science using R's tidyverse packages! Learn to code efficiently and elegantly to tackle everyday data science challenges in business, finance, scientific research, engineering and more!Do you feel you have a basic knowledge of R but don't yet have the tools or confidence to tackle everyday data science problems like plotting, summarising, sub-setting and merging data? Still turning to MS Excel to manipulate, format, and visualize data? Then look no further.Aimed at beginners and intermediates who have a basic understanding of R, this course introduces some of the core tools of the tidyverse. It covers a step-by-step guide to the most important functions offered by some tidyverse packages, providing students with a comprehensive toolkit to address everyday data science tasks.The course covers the following areas:1) Data manipulation with dplyr (filtering, sorting, creating new variables, summarising data, joining data sets, selecting columns/rows)2) Data reformatting with tidyr (gathering variables, spreading out variables, separating data in cells)3) Data visualization with ggplot2 (scatterplots, boxplots, bar charts, line charts, panels, adding errorbars)4) Linking code efficiently using the magrittr forward pipe operatorAfter completing the course, you will be confident to use R for your everyday data science tasks!
