Key Concepts Learned
- Main concepts from lecture
- Basic functionalities of GitHub
- Introduction to Quarto as a presentation tool
- Use cases of R for Public Policy Analytics
- Technical skills covered
- Committing, Pushing changes to, and Pulling changes from a repository in GitHub
- Introductory data manipulation functions in R
Coding Techniques
- New R functions or approaches
- filter → subset rows
- select → subset columns
- mutate → create new variable columns
- summarize → perform operations on a grouped dataframe
- group_by → create a grouped dataframe based on a column
- rename → rename columns (use `newname`)
- %>% (Piping) → tidyverse method of passing function outputs to another function
- Quarto features learned
- Various markdown style shortcuts:
- Bold = **
- Italic = *
- Bold/Italic = ***
- Code Text = `
- Lists = -
- Headers = # (x2 or x3)
- Links = [Link text] (link.com)
- Rendering the webpage as we make edits
- Changing Global Options in RStudio to render on save
- Using the “Render” button to force rendering updates
Questions & Challenges
- What I didn’t fully understand
- The nuances of GitHub, but I think I’m getting most of it
- Areas needing more practice
Connections to Policy
- How this week’s content applies to real policy work
- Data manipulation in R will be useful for taking in data from web pages and restructuring it into a format that’ll be useful for modeling
Reflection
- What was most interesting
- Learning how to use GitHub and publish our pages
- How I’ll apply this knowledge
- Using GitHub for collaborative projects in the future