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.
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Getting and Cleaning Data
This course is part of multiple programs.
Instructors: Jeff Leek, PhD
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(8,062 reviews)
What you'll learn
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
Skills you'll gain
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There are 4 modules in this course
In this first week of the course, we look at finding data and reading different file types.
What's included
9 videos4 readings1 assignment
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.
What's included
5 videos1 assignment
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.
What's included
7 videos1 reading1 assignment3 programming assignments
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.
What's included
5 videos2 readings1 assignment1 programming assignment1 peer review
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Recommended if you're interested in Data Analysis
DeepLearning.AI
Google
Duke University
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Frequently asked questions
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