Getting and Cleaning Data

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Description

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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.

Created by:  Johns Hopkins University
  • Taught by:  Jeff Leek, PhD…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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.

Created by:  Johns Hopkins University
  • Taught by:  Jeff Leek, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health
  • Taught by:  Roger D. Peng, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health
  • Taught by:  Brian Caffo, PhD, Professor, Biostatistics

    Bloomberg School of Public Health
Basic Info Course 3 of 10 in the Data Science Specialization Language English, Subtitles: Russian, French, Chinese (Simplified) How To Pass Pass all graded assignments to complete the course. User Ratings 4.5 stars Average User Rating 4.5See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Johns Hopkins University 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.

Syllabus


WEEK 1


Week 1
In this first week of the course, we look at finding data and reading different file types.


9 videos, 4 readings expand


  1. Reading: Welcome to Week 1
  2. Reading: Syllabus
  3. Reading: Pre-Course Survey
  4. Video: Obtaining Data Motivation
  5. Video: Raw and Processed Data
  6. Video: Components of Tidy Data
  7. Video: Downloading Files
  8. Video: Reading Local Files
  9. Video: Reading Excel Files
  10. Video: Reading XML
  11. Video: Reading JSON
  12. Video: The data.table Package
  13. Reading: Practical R Exercises in swirl Part 1

Graded: Week 1 Quiz

WEEK 2


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.


5 videos expand


  1. Video: Reading from MySQL
  2. Video: Reading from HDF5
  3. Video: Reading from The Web
  4. Video: Reading From APIs
  5. Video: Reading From Other Sources

Graded: Week 2 Quiz

WEEK 3


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.


7 videos, 1 reading expand


  1. Video: Subsetting and Sorting
  2. Video: Summarizing Data
  3. Video: Creating New Variables
  4. Video: Reshaping Data
  5. Video: Managing Data Frames with dplyr - Introduction
  6. Video: Managing Data Frames with dplyr - Basic Tools
  7. Video: Merging Data
  8. Reading: Practical R Exercises in swirl Part 2
  9. Ungraded Programming: swirl Lesson 1: Manipulating Data with dplyr
  10. Ungraded Programming: swirl Lesson 2: Grouping and Chaining with dplyr
  11. Ungraded Programming: swirl Lesson 3: Tidying Data with tidyr

Graded: Week 3 Quiz

WEEK 4


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.


5 videos, 2 readings expand


  1. Video: Editing Text Variables
  2. Video: Regular Expressions I
  3. Video: Regular Expressions II
  4. Video: Working with Dates
  5. Video: Data Resources
  6. Reading: Practical R Exercises in swirl Part 4
  7. Ungraded Programming: swirl Lesson 1: Dates and Times with lubridate
  8. Reading: Post-Course Survey

Graded: Week 4 Quiz
Graded: Getting and Cleaning Data Course Project
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