Build confidence working with messy, real-world data. In this course, you’ll learn how to import, clean, and organize data in R so that it’s ready for analysis, visualization, or modeling.
Data Tidying and Importing with R
Data Tidying and Importing with R
本课程是 Data Science with R 专项课程 的一部分
位教师：Dr. Elijah Meyer
访问权限由 New York State Department of Labor 提供
您将学到什么
Apply tidy data principles to manipulate and restructure data (e.g., subsetting, adding columns, and transforming data between wide and long formats)
Develop and implement code to join data sets and perform basic web scraping to collect data
Apply data structures such as wide and long formats, using code to convert between these formats as part of data preparation and analysis
您将获得的技能
- Information Privacy
- R Programming
- Data Integrity
- Data Manipulation
- Data Pipelines
- Exploratory Data Analysis
- Data Preprocessing
- Data Wrangling
- Web Scraping
- Data Collection
- Statistical Programming
- Data Ethics
- Personally Identifiable Information
- Data Cleansing
- Data Transformation
- Tidyverse (R Package)
- 技能部分已折叠。显示 10 项技能，共 16 项。
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作业
3 项作业
授课语言：英语（English）
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本课程是 Data Science with R 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
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该课程共有3个模块
Tidy datasets have a specific structure: each variable is a column, and each observation is a row. In this module, we use functional verbs from the dplyr package in R to transform data into a ready-to-use tidy data format. Additionally, we use functional verbs to manipulate data frames.
涵盖的内容
6个视频12篇阅读材料1个作业2个讨论话题1个插件
A column in our data set can be stored as many different types, such as numbers or characters. These different data types inform how R treats the data, and whether certain functions are compatible to use with certain types of data. In this module, we discuss more in detail, the different data types classified by R, data classes, as well as how to recode variables in a data set to be different types, classes, or take on different values.
涵盖的内容
6个视频13篇阅读材料1个作业1个讨论话题1个插件
Web scraping is the process of extracting this information automatically and transforming it into a structured dataset. In this module, we go over how to perform basic web scraping in R to make an abundance of data online more easily accessible.
涵盖的内容
4个视频6篇阅读材料1个作业2个讨论话题1个插件
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