Week 1 Notes - Course Introduction

Key Concepts Learned

Git - tracks changes, collaboration tool for teams

• repo - folder containing your project files

• push - sends changes to GitHub

• pull - get the latest changes fro GitHub

GitHub - cloud hosting for Git repos, creates deployable websites to share projects

GitHub Classroom- creates individual repos for students

Why Quarto:

• reproducible research:

  • code + explanation in one place

  • others can run your analysis

• career relevance:

  • industry standard

Why R:

• free & open source

• reproducible research

• industry standard

Tidyverse - uses “tibbles” (enhanced data frames)

Coding Techniques

Convert data frame to tibble:

#Traditional Data Frame

class(data)

# Convert to tibble

car_data <- as_tibble(data)

class(car_data)

Commonly used:

• select() - choose columns
• filter() - choose rows
  
• mutate() - create new variables
• summarize() - calculate statistics
• group_by() - operate on groups

Questions & Challenges

• Need to practice using pipelines!

Connections to Policy

This semester we’ll use these skills for:

• Census data analysis

• Neighborhood change studies

• Predictive modeling for resource allocation

• Housing market analysis

• Transportation equity assessment

Reflection

I am excited to learn how to use these things that we have learned on a project. I am interested in what a pipeline will look like for me.