Lecture 10
Next Steps
December 9, 2025
Slides & Code
Suggested Reading (from R for Data Science (2e)1)
Chapter 28: A field guide to base R
1 Hadley Wickham, Mine Çetinkaya-Rundel & Garrett Grolemund
Useful Resources
Cheatsheets
Package Websites
tidymodels • ggmap • sf • tidycensus • usethis • Shiny
Other Readings
Feature Engineering and Selection: A Practical Approach for Predictive Models 2 •
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse 3 •
Supervised Machine Learning for Text Analysis in R 4 •
Welcome to Text Mining with R 5 •
ggplot2: Elegant Graphics for Data Analysis (3e) 6 •
Spatial Data Science: With Applications in R 7 •
Happy Git and GitHub for the useR 8
2 Max Kuhn and Kjell Johnson
3 Chester Ismay, Albert Y. Kim, and Arturo Valdivia
4 Emil Hvitfeldt and Julia Silge
5 Julia Silge and David Robinson
6 Hadley Wickham, Danielle Navarro, and Thomas Lin Pedersen
7 Edzer Pebesma and Roger Bivand
8 Jennifer Bryan
Other Resources
Top 50 ggplot Visualizations “Master List” 9 • ggplot2 Extension Packages
awesome ggplot2 10 • Software Carpentry Class: Version Control with Git
9 Good for ideas and sample code!
10 A curated list of awesome ggplot2 tutorials, packages etc.
Crowdsource Help
CS&SS 508 Slack Workspace • Posit community • Stackoverflow
CSSCR @ UW 11
11 Drop by, say hello, get help!