EDS 240 - Enhancing visualizations (part I)

A fuzzy monster in a beret and scarf, critiquing their own column graph on a canvas in front of them while other assistant monsters (also in berets) carry over boxes full of elements that can be used to customize a graph (like themes and geometric shapes). In the background is a wall with framed data visualizations. Stylized text reads 'ggplot2: build a data masterpiece.'

Pre-class Prep

Please be sure to complete the following before class:

Install required packages

install.packages("paletteer") # a comprehensive collection of color palettes in R using a common interface
install.packages("viridis") # Colorblind-Friendly Color Maps for R
install.packages("RColorBrewer") # ColorBrewer Palettes
install.packages("tigris") # for downloading and using Census TIGER/Line shapefiles in R

Download data

County-level precipitation data (Jan 2019 - Dec 2023) for the contiguous U.S, made available by NOAA National Centers for Environmental Information (NCEI) (the download buttons are located just beneath the rendered map – choose the CSV option)
- rename the data file as county-jan19-dec23-precip.csv and save it to your class repo at the file path: EDS-240-class-examples/week5/data/county-jan19-dec23-precip.csv

Install Google Chrome extensions (optional, but recommended)

I’ll be using both of these (really wonderful and easy-to-use) tools during lecture and encourage you to install them!

Let’s get color blind: simulates different color deficiencies in the browser
Grayscale the Web: turn specific sites or tabs grayscale
ColorPick Eyedropper: a browser-based color chooser tool (I recommended that you install this for week 3 discussion, so you may already have it!)

Lecture Materials

Week 5 instruction is broken down into three lessons:

What makes a good viz?

lecture 5.1 slides

Colors

lecture 5.2 slides

Colors & Choropleths

lecture 5.3 slides

Discussion Materials

This week, you’ll be prepping a data visualization using the data you found / wrangled as part of your final project (HW #4). This does not need to be a polished viz, but should focus on clarity of message. You’ll be discussing each others’ visualizations and commenting on what the main takeaways are (ideally, you’ll walk away with the same message as intended by the plot-creator!). Please complete the following ahead of section:

choose a well-thought out question that you’d like to answer with your selected data set(s)
hand-draw a plot that you want to create (this can be an important first step before even touching any code)
turn your hand-drawn plot into a ggplot in R!
send both your hand-drawn plot and your resulting ggplot to Sevan via DM (Slack) by Tuesday (2/6) evening

Assignment Reminders

Assignment Type	Assignment Title	Date Assigned	Date Due
EOC	EOC (week 5)	Mon 02/05/2024	Mon 02/05/2024, 11:55pm PT
SR	Mid-course reflection (SR #2)	Mon 02/05/2024	Sat 02/10/2024, 11:59pm PT