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.
课程信息
4.6
5,679 个评分
您将学到的内容有
Apply data cleaning basics to make data "tidy"
Obtain usable data from the web, APIs, and databases
Understand common data storage systems
Use R for text and date manipulation
您将获得的技能
Data ManipulationRegular Expression (REGEX)R ProgrammingData Cleansing
教学大纲 - 您将从这门课程中学到什么
周
1Week 1
In this first week of the course, we look at finding data and reading different file types.
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 Quiz10分钟
周
2Week 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.
5 个视频 （总计 41 分钟）, 1 个测验
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 Quiz10分钟
周
3Week 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.
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 Quiz10分钟
周
4Week 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.
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 Quiz10分钟
4.6
898 个审阅40%
完成这些课程后已开始新的职业生涯
35%
通过此课程获得实实在在的工作福利
热门审阅
创建者 DH•Feb 2nd 2016
Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well.\n\nSee the videos for general presentation, but use the energy on the excersizes.
创建者 BE•Oct 26th 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.
讲师
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Brian Caffo, PhD
Professor, BiostatisticsBloomberg School of Public Health
关于 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.
关于 数据科学 专项课程
Ask the right questions, manipulate data sets, and create visualizations to communicate results.
This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.
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