Neighborhood Analysis
  • Home
  • Syllabus
  • Schedule
  • Assignments
  • How To
  • Resources
  • Discussion
  1. Course Introduction
  2. 6. Describing Places
  • 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
  • In Class
  • Reflect
  • Slides
  • Resources for Further Exploration

Sharing Your Work

Session Description

This session builds upon the work on your last lab. In that lab, you worked on developing several workflows that will support your work over the course of the semester. Coming into this lab, you should have a formatted Quarto markdown document. In this session, we’ll talk about strategies for sharing that work, will configure your computer to communicate with GitHub, and will create your first publicly facing websites.

Before Class

  1. Read through the entire lab background description before approaching lab tasks.

  2. Be prepared to access the formatted Quarto notebook you worked on in the last lab that contains your analysis of Chicago community areas.

  3. Be prepared to access your Lab 1 reflection.

In Class

Ouafa Zoom Link

Hello everyone - live from class!

Reflect

  1. How can planners and others engaging directly in public policy discourse and debate leverage emotion in their analysis in ways that generate meaning and connection without manipulating or leading towards particular conclusions?

  2. Is there such thing a “neutral” data analysis?

  3. Can you think of classification systems that may have unintended consequences or biases in data that you’ve used for urban analysis in the past?

Slides

Resources for Further Exploration

Gitcreds Package

Content Andrew J. Greenlee
 
Made with and Quarto
Website Code on Github