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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practical-data-analysis-with-r-programming/
课程评论：没有评论
R语言数据整理与探索性数据分析课程 本课程将介绍R语言中的tidyverse数据集，该数据集是一系列专为数据科学设计的R包。课程将重点关注以下几个核心包： * **ggplot2**: 用于数据可视化 * **dplyr**: 用于数据操作 * **tidyr**: 用于数据整理 * **readr**: 用于读取数据 * **readxl**: 用于读取Excel文件 * **tibbles**: 现代化的数据框 课程共包含七个部分： **第一部分：引言** 介绍课程整体内容和将要使用的工具。 **第二部分：使用ggplot2进行数据可视化** 通过`diamonds`数据集，学习使用`ggplot2`创建各种可视化图表，包括条形图、箱线图、散点图、折线图和直方图。学员将能够熟练绘制图表并进行有意义的解读。 **第三部分：使用dplyr进行数据操作** 利用2013年纽约航班数据库，深入学习`dplyr`包的功能，包括数据过滤、排序、重命名、创建新变量、选择列以及数据集合并。课程将通过实践练习检验学习效果。 **第四部分：使用tidyr进行数据整理** 学习如何整理“脏”数据集，包括将数据转换为更长或更宽的格式，以及如何分离或合并列。 **第五部分：导入数据** 介绍现代化的数据框`tibbles`，并学习如何在R中导入CSV和XLSX等多种结构化数据格式。 **第六部分：案例研究：Adventure Works数据库** 综合运用课程中学到的知识，将`tidyverse`包应用于`Adventure Works`数据库，并了解数据分析师的工作流程。 **第七部分：考试** 包含20道选择题，涵盖课程所有内容，旨在评估学员的学习成果并颁发课程证书。
The tidyverse is a collection of R packages designed for Data Science. The scope of this course is restricted to:ggplot2 packagedplyr packagetidyr packagereadr packagereadxl packagetibbles packageThis course is going to teach how you can use some of these packages for data analysis covering 7 sections as follows.Section 1: IntroductionIn this section, you are going to know what the course is all about and also get a glimpse of some of the tools we will be using throughout the course.Section 2: Data visualization with ggplot2In this section, you will learn how to use the ggpot2 package for data visualization, using the diamonds dataset as a case study.This section will cover major data visualizations such as:BarplotsBoxplotsScatterplotsLine plotsHistogramAt the end of this section, should be able to know how to plot various visualizations and also give meaningful interpretations of them.Section 3: Data manipulation with dplyrIn this section, you will learn all about the dplyr package and how you can manipulate your data with the available functions in the dplyr package using the New York flights database of 2013.At the end of this package, you should be able to perform tasks on the dataset such as filteringarrangingrenamingvariable creationselectionTable/Dataset joining The Practical Quiz at the end of this section will test your understanding of the various concepts treated in the section.Section 4: Data tidying with tidyrThis section is aimed at showing you how you can tidy a dirty dataset when you come across one. You are going to learn how to make datasets longer or wider.You will also be learning how you can separate or unite columns together.Section 5: Importing dataIn this section, you will learn about modernized data frame called tibbles.This section will also show you how you can import various structured data formats in R such as CSV and XLSX files.Section 6: Case Study: Adventure Works DatabaseIn this section, you will learn how you can combine various concepts you have learnt in this course and apply them to the Adventure Works database, and also what a data analyst's workflow process looks like.Section 7: EXAMThis section consists of 20 multiple choice questions which you are expected to answer to get your final course certificate. It covers everything covered in this course.
