Code notebooks provide a convenient way to document and organize a data science project from beginning to end; in otherwords, they can form the basis of a workflow.
Working on a workflow
Working on a workflow
Working on a workflow
Working on a workflow
Viewer Tab
Rather than render HTML directly to your browser, you can preview the rendered version in the Viewer tab.
What about files?
When we write code that reads from files, these need to be in places where the Quarto document can find them.
# load tidyverselibrary(tidyverse)# read in abalone dataabalone<-read_csv("data/abalone.csv")# plot abalone rings by diameterggplot(abalone,aes(x=diameter,y=rings)) +geom_hex()
Sharing your file system
The zip function provides a convenient way to turn your entire working directory into a .zip file
#zip up all of my project fileszip("myProject.zip",list.files())
Coursekeeping
Assignment
Due Date
Lab Assignment 5
Tuesday, October 10
Coding Assignment 2
Thursday, October 12
Lab Assignment 6
Tuesday, October 17
Project Proposal
Thursday, October 19
Project proposal
What is the topic?
What is the background to this topic? (2-3 citations)
What datasets are you intending to use?
How would data analysis/visualization to help you understand the topic?
Suggest two visualizations
Activity: Brainstorming with Quarto
Put the Quarto workflow to work in brainstorming ideas for your final project!
Create a file system for your final project
Start a new Quarto document and save it to your working directory
Use headers to outline a data analysis process from a project you’d like to do.
Begin filling out the sections with some preliminary ideas about what kinds of data you’d useand
