Assignment 1: Getting Started
Objectives
This assignment will strengthen your ability to:
Build reproducible workflows using Quarto and version control.
Import, inspect, and critically evaluate real-world data.
Apply
tidyverse
tools to transform and summarize data.Write reusable functions and iteration to create streamlined, readable analyses.
Reflect on reproducibility, data ethics, and workflow choices as a practicing researcher.
Instructions
Join the assignment repository. In the
docs
folder, you’ll find the instructions and questions for the assignment (assignment01.qmd).Change the
yaml
header of the document to include your name and the course number as your affiliationComplete the tasks in the assignment making at least 3 commits
Render the document and push your final html and quarto documents to your repository.
Submission:
Submit a single Quarto document (.qmd) with integrated code, outputs, and written responses. Your document should be written as if it were a lab notebook entry: clear enough that another researcher could reproduce your work without asking you questions. Your assignment will be considered complete if the following are true:
You have at least 3 commits in your version history (which I can access in GitHub classroom)
You have pushed your final Quarto document
You have pushed a rendered
.html
version of your document.
About the Data
PurpleAir manufactures air quality sensors that can be deployed by individuals, communities, and government agencies to provide real-time, hyper-local information on the concentration of various air pollutants surrounding the sensors. These sensors are particularly good at detecting concentrations of pm2.5. These ultra-fine particles are a big part of wildfire smoke and air pollution and have been associated with a variety of respiratory health-risks. In addition, these are the primary contributors to the haze that settles in the Treasure Valley during fires and winter inversions.
PurpleAir makes the data from these sensors available via an API that we can access in R
. I’ve already done that for you and gathered the monthly average pm2.5 values for 34 sensors in ID, MT, OR, and WA beginning in 2020. We’ll use this data as the foundation for demonstrating some of the data wrangling skills you’ve learned so far.
Solutions are here