Week 4

Transforming data with {dplyr}

weeks
Published

February 18, 2026

ImportantReminder! Schedule adjustment deadline is February 13.

Friday, February 13 is the last day to make changes to your schedule, to change grade method, or to drop a course without a W grade.

Overview

This week includes a review of data visualization and mapping with {ggplot} review, an introduction to data transformation with {dplyr}, and an initial discussion of using {dplyr} with sf objects.

Key Objectives

  • Review the concept of “tidy”, analysis-friendly data
  • Introduce the “verbs” of data wrangling with {dplyr}
  • Practice subsetting rows with dplyr::filter() or dplyr::slice()
  • Practice subsetting columns with dplyr::select()
  • Practice using {tidyselect} helpers including where(), all_of(), any_of(), and starts_with()
  • Practice creating new variables with dplyr::mutate() or dplyr::summarise()

Prepare

Required readings

Optional readings

Participate

🖥️ Transforming data with {dplyr} and {tidyr}

Practice

🛠️️ Exercise 03