Link to Content:
Getting and Cleaning Data
Johns Hopkins University
Roger D. Peng
Content Found Via:
Free? Partially: Some Free Content, Some Paid
Tags: data cleaning / data extraction / databases / MySQL / R
This is course 3 of 10 in the Coursera Data Science Specialization.
“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.
- In this first week of the course, we look at finding data and reading different file types.
- 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.
- Welcome to Week 3 of Getting and Cleaning Data! This week lectures will focus on organizing, merging and managing the data you have collected using the lectures from Weeks 1 and 2.
- 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.”
Recommended Prerequisites: Some programming experience
Go to Content: Getting and Cleaning Data