Neighborhood Analysis
  • Home
  • Syllabus
  • Schedule
  • Assignments
  • How To
  • Resources
  • Discussion
  1. Course Introduction
  2. 4. Working with Tidy Data
  • Schedule Overview
    • Course Schedule
  • Course Introduction
    • 1. Course Introduction
    • 2. What is a Neighborhood?
    • 3. Building a Data Pipeline
    • 4. Working with Tidy Data
    • 5. Working with Tidy Data
    • 6. Describing Places
    • 7. Communicating Complex Information
  • Strategies for Analysis
    • 8. Describing Places
    • 9. Describing Places
    • 10. Population and the Census
    • 11. Population and the Census
    • 12. Segregation
    • 13. Segregation
    • 14. Neighborhood Change
    • 15. Neighborhood Change
    • 16. Place Opportunity
    • 17. Place Opportunity
    • 18. Transit Equity
    • 19. Transit Equity
    • 20. Health Equity
    • 21. Health Equity
    • 22. Final Project Check-In
    • 23. Final Project Check-In
  • Course Wrap-Up
    • 24. Field Observation
    • 25. Field Observation
    • 26. Final Presentations
    • 27. Independent Work and Advising
    • 28. Final Presentations
    • 29. Final Presentations

On this page

  • Session Description
  • Before Class
  • Reflect
  • Slides
  • Resources for Further Exploration

Introduction to Tidy Data - Session 1

Session Description

Our work this semester blends building capacity for data analysis and storytelling with basic data science skills. Throughout the course of the semester, we will frequently work to structure data in a tidy format - one in which we have one variable per column, and for which each row represents a unique observation. Some of you with a prior background or experience working in R will already be familiar with these principles, but some of you are not. This week, we’ll spend time reviewing the basics of what tidy data are, and will review common manipulation strategies.

Before Class

Review the How To Lesson 1 and Lesson 2. If you are comfortable with these principles and strategies, please take a look at Lesson 3

Reflect

Slides

Resources for Further Exploration

Content Andrew J. Greenlee
 
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