Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.
约翰霍普金斯大学课程信息
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学生职业成果
37%
完成这些课程后已开始新的职业生涯
37%
通过此课程获得实实在在的工作福利
13%
加薪或升职
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
完成时间大约为20 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 中文（简体）, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）
您将学到的内容有
Understand common data storage systems
Apply data cleaning basics to make data "tidy"
Use R for text and date manipulation
Obtain usable data from the web, APIs, and databases
您将获得的技能
Data ManipulationRegular Expression (REGEX)R ProgrammingData Cleansing
学生职业成果
37%
完成这些课程后已开始新的职业生涯
37%
通过此课程获得实实在在的工作福利
13%
加薪或升职
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
完成时间大约为20 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 中文（简体）, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）
提供方
约翰霍普金斯大学
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
教学大纲 - 您将从这门课程中学到什么
完成时间为 2 小时
Week 1
In this first week of the course, we look at finding data and reading different file types.
完成时间为 2 小时
9 个视频 （总计 67 分钟）, 4 个阅读材料, 1 个测验
9 个视频
Raw and Processed Data7分钟
Components of Tidy Data9分钟
Downloading Files7分钟
Reading Local Files4分钟
Reading Excel Files3分钟
Reading XML12分钟
Reading JSON5分钟
The data.table Package11分钟
4 个阅读材料
Welcome to Week 110分钟
Syllabus10分钟
Pre-Course Survey10分钟
Practical R Exercises in swirl Part 110分钟
1 个练习
Week 1 Quiz30分钟
完成时间为 1 小时
Week 2
Welcome to Week 2 of Getting and Cleaning Data! The primary goal is to introduce you to the most common data storage systems and the appropriate tools to extract data from web or from databases like MySQL.
完成时间为 1 小时
5 个视频 （总计 41 分钟）
5 个视频
Reading from HDF56分钟
Reading from The Web6分钟
Reading From APIs7分钟
Reading From Other Sources4分钟
1 个练习
Week 2 Quiz30分钟
完成时间为 11 小时
Week 3
Welcome to Week 3 of Getting and Cleaning Data! This week the lectures will focus on organizing, merging and managing the data you have collected using the lectures from Weeks 1 and 2.
完成时间为 11 小时
7 个视频 （总计 60 分钟）, 1 个阅读材料, 4 个测验
7 个视频
Summarizing Data11分钟
Creating New Variables10分钟
Reshaping Data9分钟
Managing Data Frames with dplyr - Introduction3分钟
Managing Data Frames with dplyr - Basic Tools12分钟
Merging Data6分钟
1 个阅读材料
Practical R Exercises in swirl Part 210分钟
1 个练习
Week 3 Quiz30分钟
完成时间为 5 小时
Week 4
Welcome to Week 4 of Getting and Cleaning Data! This week we finish up with lectures on text and date manipulation in R. In this final week we will also focus on peer grading of Course Projects.
完成时间为 5 小时
5 个视频 （总计 34 分钟）, 2 个阅读材料, 3 个测验
5 个视频
Regular Expressions I5分钟
Regular Expressions II8分钟
Working with Dates6分钟
Data Resources3分钟
2 个阅读材料
Practical R Exercises in swirl Part 410分钟
Post-Course Survey10分钟
1 个练习
Week 4 Quiz30分钟
审阅
来自获取和整理数据的热门评论
由 HS 提供May 2, 2020
This course provides an introduction of some important concepts and tools on a very important aspect of data science: cleaning and organizing data before any analysis. A must for any data scientist.
由 CW 提供Aug 6, 2020
I think that the level of difficulty of the exercises and final assignment does not match with the depth of the lectures; without a textbook, I feel lost, don't have a reference, and have to guess.
由 BE 提供Oct 25, 2016
This course is really a challenging and compulsory for any one who wants to be a data scientist or working in any sort of data. It teaches you how to make very palatable data-set fro ma messy data.
由 AT 提供Nov 19, 2017
Very interesting and enjoyed doing the Assignment. but the assignment instructions are not clear.A lot of time was wasted trying to figure out what data is what are what are we interested in.
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